812 results on '"Broom, A"'
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2. A Pan-Cancer Analysis Reveals High-Frequency Genetic Alterations in Mediators of Signaling by the TGF-β Superfamily
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Korkut, Anil, Zaidi, Sobia, Kanchi, Rupa S, Rao, Shuyun, Gough, Nancy R, Schultz, Andre, Li, Xubin, Lorenzi, Philip L, Berger, Ashton C, Robertson, Gordon, Kwong, Lawrence N, Datto, Mike, Roszik, Jason, Ling, Shiyun, Ravikumar, Visweswaran, Manyam, Ganiraju, Rao, Arvind, Shelley, Simon, Liu, Yuexin, Ju, Zhenlin, Hansel, Donna, de Velasco, Guillermo, Pennathur, Arjun, Andersen, Jesper B, O'Rourke, Colm J, Ohshiro, Kazufumi, Jogunoori, Wilma, Nguyen, Bao-Ngoc, Li, Shulin, Osmanbeyoglu, Hatice U, Ajani, Jaffer A, Mani, Sendurai A, Houseman, Andres, Wiznerowicz, Maciej, Chen, Jian, Gu, Shoujun, Ma, Wencai, Zhang, Jiexin, Tong, Pan, Cherniack, Andrew D, Deng, Chuxia, Resar, Linda, Network, The Cancer Genome Atlas Research, Caesar-Johnson, Samantha J, Demchok, John A, Felau, Ina, Kasapi, Melpomeni, Ferguson, Martin L, Hutter, Carolyn M, Sofia, Heidi J, Tarnuzzer, Roy, Wang, Zhining, Yang, Liming, Zenklusen, Jean C, Zhang, Jiashan, Chudamani, Sudha, Liu, Jia, Lolla, Laxmi, Naresh, Rashi, Pihl, Todd, Sun, Qiang, Wan, Yunhu, Wu, Ye, Cho, Juok, DeFreitas, Timothy, Frazer, Scott, Gehlenborg, Nils, Getz, Gad, Heiman, David I, Kim, Jaegil, Lawrence, Michael S, Lin, Pei, Meier, Sam, Noble, Michael S, Saksena, Gordon, Voet, Doug, Zhang, Hailei, Bernard, Brady, Chambwe, Nyasha, Dhankani, Varsha, Knijnenburg, Theo, Kramer, Roger, Leinonen, Kalle, Miller, Michael, Reynolds, Sheila, Shmulevich, Ilya, Thorsson, Vesteinn, Zhang, Wei, Akbani, Rehan, Broom, Bradley M, Hegde, Apurva M, Li, Jun, Liang, Han, Liu, Wenbin, and Lu, Yiling
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Biological Sciences ,Genetics ,Cancer ,Human Genome ,Biotechnology ,Cancer Genomics ,2.1 Biological and endogenous factors ,Bone Morphogenetic Protein 5 ,DNA Methylation ,Humans ,MicroRNAs ,Mutation Rate ,Neoplasms ,Receptor ,Transforming Growth Factor-beta Type I ,Signal Transduction ,Smad Proteins ,Transforming Growth Factor beta ,Cancer Genome Atlas Research Network ,DNA methylation ,Pan-Cancer ,TCGA ,TGF-β ,TGF-β pathway ,The Cancer Genome Atlas ,cancer ,microRNA ,mutation hotspot ,transcription ,Biochemistry and Cell Biology ,Biochemistry and cell biology - Abstract
We present an integromic analysis of gene alterations that modulate transforming growth factor β (TGF-β)-Smad-mediated signaling in 9,125 tumor samples across 33 cancer types in The Cancer Genome Atlas (TCGA). Focusing on genes that encode mediators and regulators of TGF-β signaling, we found at least one genomic alteration (mutation, homozygous deletion, or amplification) in 39% of samples, with highest frequencies in gastrointestinal cancers. We identified mutation hotspots in genes that encode TGF-β ligands (BMP5), receptors (TGFBR2, AVCR2A, and BMPR2), and Smads (SMAD2 and SMAD4). Alterations in the TGF-β superfamily correlated positively with expression of metastasis-associated genes and with decreased survival. Correlation analyses showed the contributions of mutation, amplification, deletion, DNA methylation, and miRNA expression to transcriptional activity of TGF-β signaling in each cancer type. This study provides a broad molecular perspective relevant for future functional and therapeutic studies of the diverse cancer pathways mediated by the TGF-β superfamily.
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- 2018
3. Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context
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Chiu, Hua-Sheng, Somvanshi, Sonal, Patel, Ektaben, Chen, Ting-Wen, Singh, Vivek P, Zorman, Barry, Patil, Sagar L, Pan, Yinghong, Chatterjee, Sujash S, Network, The Cancer Genome Atlas Research, Caesar-Johnson, Samantha J, Demchok, John A, Felau, Ina, Kasapi, Melpomeni, Ferguson, Martin L, Hutter, Carolyn M, Sofia, Heidi J, Tarnuzzer, Roy, Wang, Zhining, Yang, Liming, Zenklusen, Jean C, Zhang, Jiashan, Chudamani, Sudha, Liu, Jia, Lolla, Laxmi, Naresh, Rashi, Pihl, Todd, Sun, Qiang, Wan, Yunhu, Wu, Ye, Cho, Juok, DeFreitas, Timothy, Frazer, Scott, Gehlenborg, Nils, Getz, Gad, Heiman, David I, Kim, Jaegil, Lawrence, Michael S, Lin, Pei, Meier, Sam, Noble, Michael S, Saksena, Gordon, Voet, Doug, Zhang, Hailei, Bernard, Brady, Chambwe, Nyasha, Dhankani, Varsha, Knijnenburg, Theo, Kramer, Roger, Leinonen, Kalle, Liu, Yuexin, Miller, Michael, Reynolds, Sheila, Shmulevich, Ilya, Thorsson, Vesteinn, Zhang, Wei, Akbani, Rehan, Broom, Bradley M, Hegde, Apurva M, Ju, Zhenlin, Kanchi, Rupa S, Korkut, Anil, Li, Jun, Liang, Han, Ling, Shiyun, Liu, Wenbin, Lu, Yiling, Mills, Gordon B, Ng, Kwok-Shing, Rao, Arvind, Ryan, Michael, Wang, Jing, Weinstein, John N, Zhang, Jiexin, Abeshouse, Adam, Armenia, Joshua, Chakravarty, Debyani, Chatila, Walid K, de Bruijn, Ino, Gao, Jianjiong, Gross, Benjamin E, Heins, Zachary J, Kundra, Ritika, La, Konnor, Ladanyi, Marc, Luna, Augustin, Nissan, Moriah G, Ochoa, Angelica, Phillips, Sarah M, Reznik, Ed, Sanchez-Vega, Francisco, Sander, Chris, Schultz, Nikolaus, Sheridan, Robert, Sumer, S Onur, Sun, Yichao, Taylor, Barry S, Wang, Jioajiao, Zhang, Hongxin, and Anur, Pavana
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Biological Sciences ,Bioinformatics and Computational Biology ,Women's Health ,Cancer ,Cancer Genomics ,Genetics ,Human Genome ,Breast Cancer ,Biotechnology ,2.1 Biological and endogenous factors ,Cell Line ,Cell Line ,Tumor ,Gene Expression Regulation ,Neoplastic ,Gene Regulatory Networks ,Genes ,Tumor Suppressor ,Humans ,Neoplasms ,Oncogenes ,RNA ,Long Noncoding ,Cancer Genome Atlas Research Network ,RNA-binding proteins ,cancer gene ,interactome ,lncRNA ,microRNA ,modulation ,noncoding RNA ,pan-cancer ,regulation ,Biochemistry and Cell Biology ,Medical Physiology ,Biological sciences - Abstract
Long noncoding RNAs (lncRNAs) are commonly dysregulated in tumors, but only a handful are known to play pathophysiological roles in cancer. We inferred lncRNAs that dysregulate cancer pathways, oncogenes, and tumor suppressors (cancer genes) by modeling their effects on the activity of transcription factors, RNA-binding proteins, and microRNAs in 5,185 TCGA tumors and 1,019 ENCODE assays. Our predictions included hundreds of candidate onco- and tumor-suppressor lncRNAs (cancer lncRNAs) whose somatic alterations account for the dysregulation of dozens of cancer genes and pathways in each of 14 tumor contexts. To demonstrate proof of concept, we showed that perturbations targeting OIP5-AS1 (an inferred tumor suppressor) and TUG1 and WT1-AS (inferred onco-lncRNAs) dysregulated cancer genes and altered proliferation of breast and gynecologic cancer cells. Our analysis indicates that, although most lncRNAs are dysregulated in a tumor-specific manner, some, including OIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergistically dysregulate cancer pathways in multiple tumor contexts.
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- 2018
4. Somatic Mutational Landscape of Splicing Factor Genes and Their Functional Consequences across 33 Cancer Types
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Seiler, Michael, Peng, Shouyong, Agrawal, Anant A, Palacino, James, Teng, Teng, Zhu, Ping, Smith, Peter G, Network, The Cancer Genome Atlas Research, Caesar-Johnson, Samantha J, Demchok, John A, Felau, Ina, Kasapi, Melpomeni, Ferguson, Martin L, Hutter, Carolyn M, Sofia, Heidi J, Tarnuzzer, Roy, Wang, Zhining, Yang, Liming, Zenklusen, Jean C, Zhang, Jiashan, Chudamani, Sudha, Liu, Jia, Lolla, Laxmi, Naresh, Rashi, Pihl, Todd, Sun, Qiang, Wan, Yunhu, Wu, Ye, Cho, Juok, DeFreitas, Timothy, Frazer, Scott, Gehlenborg, Nils, Getz, Gad, Heiman, David I, Kim, Jaegil, Lawrence, Michael S, Lin, Pei, Meier, Sam, Noble, Michael S, Saksena, Gordon, Voet, Doug, Zhang, Hailei, Bernard, Brady, Chambwe, Nyasha, Dhankani, Varsha, Knijnenburg, Theo, Kramer, Roger, Leinonen, Kalle, Liu, Yuexin, Miller, Michael, Reynolds, Sheila, Shmulevich, Ilya, Thorsson, Vesteinn, Zhang, Wei, Akbani, Rehan, Broom, Bradley M, Hegde, Apurva M, Ju, Zhenlin, Kanchi, Rupa S, Korkut, Anil, Li, Jun, Liang, Han, Ling, Shiyun, Liu, Wenbin, Lu, Yiling, Mills, Gordon B, Ng, Kwok-Shing, Rao, Arvind, Ryan, Michael, Wang, Jing, Weinstein, John N, Zhang, Jiexin, Abeshouse, Adam, Armenia, Joshua, Chakravarty, Debyani, Chatila, Walid K, de Bruijn, Ino, Gao, Jianjiong, Gross, Benjamin E, Heins, Zachary J, Kundra, Ritika, La, Konnor, Ladanyi, Marc, Luna, Augustin, Nissan, Moriah G, Ochoa, Angelica, Phillips, Sarah M, Reznik, Ed, Sanchez-Vega, Francisco, Sander, Chris, Schultz, Nikolaus, Sheridan, Robert, Sumer, S Onur, Sun, Yichao, Taylor, Barry S, Wang, Jioajiao, Zhang, Hongxin, Anur, Pavana, Peto, Myron, and Spellman, Paul
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Biological Sciences ,Bioinformatics and Computational Biology ,Genetics ,Cancer ,Human Genome ,Cancer Genomics ,2.1 Biological and endogenous factors ,Cell Line ,Tumor ,Genes ,Tumor Suppressor ,Humans ,Loss of Function Mutation ,Mutation Rate ,Neoplasms ,Oncogenes ,RNA Splicing ,RNA Splicing Factors ,Cancer Genome Atlas Research Network ,FUBP1 ,RBM10 ,SF3B1 ,SRSF2 ,U2AF1 ,cancer ,mutation ,splicing ,Biochemistry and Cell Biology ,Medical Physiology ,Biological sciences - Abstract
Hotspot mutations in splicing factor genes have been recently reported at high frequency in hematological malignancies, suggesting the importance of RNA splicing in cancer. We analyzed whole-exome sequencing data across 33 tumor types in The Cancer Genome Atlas (TCGA), and we identified 119 splicing factor genes with significant non-silent mutation patterns, including mutation over-representation, recurrent loss of function (tumor suppressor-like), or hotspot mutation profile (oncogene-like). Furthermore, RNA sequencing analysis revealed altered splicing events associated with selected splicing factor mutations. In addition, we were able to identify common gene pathway profiles associated with the presence of these mutations. Our analysis suggests that somatic alteration of genes involved in the RNA-splicing process is common in cancer and may represent an underappreciated hallmark of tumorigenesis.
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- 2018
5. Integrated Genomic Analysis of the Ubiquitin Pathway across Cancer Types
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Ge, Zhongqi, Leighton, Jake S, Wang, Yumeng, Peng, Xinxin, Chen, Zhongyuan, Chen, Hu, Sun, Yutong, Yao, Fan, Li, Jun, Zhang, Huiwen, Liu, Jianfang, Shriver, Craig D, Hu, Hai, Network, The Cancer Genome Atlas Research, Caesar-Johnson, Samantha J, Demchok, John A, Felau, Ina, Kasapi, Melpomeni, Ferguson, Martin L, Hutter, Carolyn M, Sofia, Heidi J, Tarnuzzer, Roy, Wang, Zhining, Yang, Liming, Zenklusen, Jean C, Zhang, Jiashan, Chudamani, Sudha, Liu, Jia, Lolla, Laxmi, Naresh, Rashi, Pihl, Todd, Sun, Qiang, Wan, Yunhu, Wu, Ye, Cho, Juok, DeFreitas, Timothy, Frazer, Scott, Gehlenborg, Nils, Getz, Gad, Heiman, David I, Kim, Jaegil, Lawrence, Michael S, Lin, Pei, Meier, Sam, Noble, Michael S, Saksena, Gordon, Voet, Doug, Zhang, Hailei, Bernard, Brady, Chambwe, Nyasha, Dhankani, Varsha, Knijnenburg, Theo, Kramer, Roger, Leinonen, Kalle, Liu, Yuexin, Miller, Michael, Reynolds, Sheila, Shmulevich, Ilya, Thorsson, Vesteinn, Zhang, Wei, Akbani, Rehan, Broom, Bradley M, Hegde, Apurva M, Ju, Zhenlin, Kanchi, Rupa S, Korkut, Anil, Liang, Han, Ling, Shiyun, Liu, Wenbin, Lu, Yiling, Mills, Gordon B, Ng, Kwok-Shing, Rao, Arvind, Ryan, Michael, Wang, Jing, Weinstein, John N, Zhang, Jiexin, Abeshouse, Adam, Armenia, Joshua, Chakravarty, Debyani, Chatila, Walid K, de Bruijn, Ino, Gao, Jianjiong, Gross, Benjamin E, Heins, Zachary J, Kundra, Ritika, La, Konnor, Ladanyi, Marc, Luna, Augustin, Nissan, Moriah G, Ochoa, Angelica, Phillips, Sarah M, Reznik, Ed, Sanchez-Vega, Francisco, Sander, Chris, Schultz, Nikolaus, Sheridan, Robert, Sumer, S Onur, and Sun, Yichao
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Biological Sciences ,Bioinformatics and Computational Biology ,Cancer ,Cancer Genomics ,Genetics ,Human Genome ,Biotechnology ,Good Health and Well Being ,Cell Line ,Tumor ,Gene Expression Regulation ,Neoplastic ,Genome ,Human ,Genomics ,Humans ,Metabolic Networks and Pathways ,Neoplasms ,Oncogene Proteins ,Ubiquitination ,Cancer Genome Atlas Research Network ,FBXW7 ,The Cancer Genome Atlas ,biomarker ,cancer prognosis ,pan-cancer analysis ,therapeutic targets ,tumor subtype ,ubiquitin pathway ,Biochemistry and Cell Biology ,Medical Physiology ,Biological sciences - Abstract
Protein ubiquitination is a dynamic and reversible process of adding single ubiquitin molecules or various ubiquitin chains to target proteins. Here, using multidimensional omic data of 9,125 tumor samples across 33 cancer types from The Cancer Genome Atlas, we perform comprehensive molecular characterization of 929 ubiquitin-related genes and 95 deubiquitinase genes. Among them, we systematically identify top somatic driver candidates, including mutated FBXW7 with cancer-type-specific patterns and amplified MDM2 showing a mutually exclusive pattern with BRAF mutations. Ubiquitin pathway genes tend to be upregulated in cancer mediated by diverse mechanisms. By integrating pan-cancer multiomic data, we identify a group of tumor samples that exhibit worse prognosis. These samples are consistently associated with the upregulation of cell-cycle and DNA repair pathways, characterized by mutated TP53, MYC/TERT amplification, and APC/PTEN deletion. Our analysis highlights the importance of the ubiquitin pathway in cancer development and lays a foundation for developing relevant therapeutic strategies.
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- 2018
6. lncRNA Epigenetic Landscape Analysis Identifies EPIC1 as an Oncogenic lncRNA that Interacts with MYC and Promotes Cell-Cycle Progression in Cancer
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Wang, Zehua, Yang, Bo, Zhang, Min, Guo, Weiwei, Wu, Zhiyuan, Wang, Yue, Jia, Lin, Li, Song, Network, The Cancer Genome Atlas Research, Caesar-Johnson, Samantha J, Demchok, John A, Felau, Ina, Kasapi, Melpomeni, Ferguson, Martin L, Hutter, Carolyn M, Sofia, Heidi J, Tarnuzzer, Roy, Wang, Zhining, Yang, Liming, Zenklusen, Jean C, Zhang, Jiashan, Chudamani, Sudha, Liu, Jia, Lolla, Laxmi, Naresh, Rashi, Pihl, Todd, Sun, Qiang, Wan, Yunhu, Wu, Ye, Cho, Juok, DeFreitas, Timothy, Frazer, Scott, Gehlenborg, Nils, Getz, Gad, Heiman, David I, Kim, Jaegil, Lawrence, Michael S, Lin, Pei, Meier, Sam, Noble, Michael S, Saksena, Gordon, Voet, Doug, Zhang, Hailei, Bernard, Brady, Chambwe, Nyasha, Dhankani, Varsha, Knijnenburg, Theo, Kramer, Roger, Leinonen, Kalle, Liu, Yuexin, Miller, Michael, Reynolds, Sheila, Shmulevich, Ilya, Thorsson, Vesteinn, Zhang, Wei, Akbani, Rehan, Broom, Bradley M, Hegde, Apurva M, Ju, Zhenlin, Kanchi, Rupa S, Korkut, Anil, Li, Jun, Liang, Han, Ling, Shiyun, Liu, Wenbin, Lu, Yiling, Mills, Gordon B, Ng, Kwok-Shing, Rao, Arvind, Ryan, Michael, Wang, Jing, Weinstein, John N, Zhang, Jiexin, Abeshouse, Adam, Armenia, Joshua, Chakravarty, Debyani, Chatila, Walid K, Bruijn, Inode, Gao, Jianjiong, Gross, Benjamin E, Heins, Zachary J, Kundra, Ritika, La, Konnor, Ladanyi, Marc, Luna, Augustin, Nissan, Moriah G, Ochoa, Angelica, Phillips, Sarah M, Reznik, Ed, Sanchez-Vega, Francisco, Sander, Chris, Schultz, Nikolaus, Sheridan, Robert, Sumer, S Onur, Sun, Yichao, Taylor, Barry S, Wang, Jioajiao, Zhang, Hongxin, Anur, Pavana, and Peto, Myron
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Biochemistry and Cell Biology ,Biomedical and Clinical Sciences ,Oncology and Carcinogenesis ,Biological Sciences ,Women's Health ,Cancer ,Cancer Genomics ,Genetics ,Human Genome ,Breast Cancer ,Animals ,Binding Sites ,Breast Neoplasms ,Cell Cycle ,Cell Line ,Tumor ,CpG Islands ,DNA Methylation ,Epigenesis ,Genetic ,Female ,Gene Expression Regulation ,Neoplastic ,Humans ,Mice ,Neoplasm Transplantation ,Prognosis ,Promoter Regions ,Genetic ,Proto-Oncogene Proteins c-myc ,RNA ,Long Noncoding ,Up-Regulation ,Cancer Genome Atlas Research Network ,CIMP ,ENSG00000224271 ,EPIC1 ,LOC284930 ,MYC ,P21 ,TCGA pan-cancer ,breast cancer ,long noncoding RNA ,Neurosciences ,Oncology & Carcinogenesis ,Biochemistry and cell biology ,Oncology and carcinogenesis - Abstract
We characterized the epigenetic landscape of genes encoding long noncoding RNAs (lncRNAs) across 6,475 tumors and 455 cancer cell lines. In stark contrast to the CpG island hypermethylation phenotype in cancer, we observed a recurrent hypomethylation of 1,006 lncRNA genes in cancer, including EPIC1 (epigenetically-induced lncRNA1). Overexpression of EPIC1 is associated with poor prognosis in luminal B breast cancer patients and enhances tumor growth in vitro and in vivo. Mechanistically, EPIC1 promotes cell-cycle progression by interacting with MYC through EPIC1's 129-283 nt region. EPIC1 knockdown reduces the occupancy of MYC to its target genes (e.g., CDKN1A, CCNA2, CDC20, and CDC45). MYC depletion abolishes EPIC1's regulation of MYC target and luminal breast cancer tumorigenesis in vitro and in vivo.
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- 2018
7. Comparative Molecular Analysis of Gastrointestinal Adenocarcinomas
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Liu, Yang, Sethi, Nilay S, Hinoue, Toshinori, Schneider, Barbara G, Cherniack, Andrew D, Sanchez-Vega, Francisco, Seoane, Jose A, Farshidfar, Farshad, Bowlby, Reanne, Islam, Mirazul, Kim, Jaegil, Chatila, Walid, Akbani, Rehan, Kanchi, Rupa S, Rabkin, Charles S, Willis, Joseph E, Wang, Kenneth K, McCall, Shannon J, Mishra, Lopa, Ojesina, Akinyemi I, Bullman, Susan, Pedamallu, Chandra Sekhar, Lazar, Alexander J, Sakai, Ryo, Network, The Cancer Genome Atlas Research, Caesar-Johnson, Samantha J, Demchok, John A, Felau, Ina, Kasapi, Melpomeni, Ferguson, Martin L, Hutter, Carolyn M, Sofia, Heidi J, Tarnuzzer, Roy, Wang, Zhining, Yang, Liming, Zenklusen, Jean C, Zhang, Jiashan, Chudamani, Sudha, Liu, Jia, Lolla, Laxmi, Naresh, Rashi, Pihl, Todd, Sun, Qiang, Wan, Yunhu, Wu, Ye, Cho, Juok, DeFreitas, Timothy, Frazer, Scott, Gehlenborg, Nils, Getz, Gad, Heiman, David I, Lawrence, Michael S, Lin, Pei, Meier, Sam, Noble, Michael S, Saksena, Gordon, Voet, Doug, Zhang, Hailei, Bernard, Brady, Chambwe, Nyasha, Dhankani, Varsha, Knijnenburg, Theo, Kramer, Roger, Leinonen, Kalle, Liu, Yuexin, Miller, Michael, Reynolds, Sheila, Shmulevich, Ilya, Thorsson, Vesteinn, Zhang, Wei, Broom, Bradley M, Hegde, Apurva M, Ju, Zhenlin, Korkut, Anil, Li, Jun, Liang, Han, Ling, Shiyun, Liu, Wenbin, Lu, Yiling, Mills, Gordon B, Ng, Kwok-Shing, Rao, Arvind, Ryan, Michael, Wang, Jing, Weinstein, John N, Zhang, Jiexin, Abeshouse, Adam, Armenia, Joshua, Chakravarty, Debyani, Chatila, Walid K, Bruijn, Inode, Gao, Jianjiong, Gross, Benjamin E, Heins, Zachary J, Kundra, Ritika, La, Konnor, and Ladanyi, Marc
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Biological Sciences ,Genetics ,Genetic Testing ,Colo-Rectal Cancer ,Cancer ,Rare Diseases ,Cancer Genomics ,Digestive Diseases ,Human Genome ,Biotechnology ,Adenocarcinoma ,Aneuploidy ,Chromosomal Instability ,DNA Methylation ,DNA Polymerase II ,DNA-Binding Proteins ,Epigenesis ,Genetic ,Female ,Gastrointestinal Neoplasms ,Gene Regulatory Networks ,Heterogeneous-Nuclear Ribonucleoproteins ,Humans ,Male ,Microsatellite Instability ,MutL Protein Homolog 1 ,Mutation ,Poly-ADP-Ribose Binding Proteins ,Polymorphism ,Single Nucleotide ,Proto-Oncogene Proteins p21(ras) ,RNA-Binding Proteins ,SOX9 Transcription Factor ,Cancer Genome Atlas Research Network ,cancer ,colon ,colorectal ,epigenetic ,esophagus ,genomic ,methylation ,rectum ,stomach ,tumor ,Neurosciences ,Oncology and Carcinogenesis ,Oncology & Carcinogenesis ,Biochemistry and cell biology ,Oncology and carcinogenesis - Abstract
We analyzed 921 adenocarcinomas of the esophagus, stomach, colon, and rectum to examine shared and distinguishing molecular characteristics of gastrointestinal tract adenocarcinomas (GIACs). Hypermutated tumors were distinct regardless of cancer type and comprised those enriched for insertions/deletions, representing microsatellite instability cases with epigenetic silencing of MLH1 in the context of CpG island methylator phenotype, plus tumors with elevated single-nucleotide variants associated with mutations in POLE. Tumors with chromosomal instability were diverse, with gastroesophageal adenocarcinomas harboring fragmented genomes associated with genomic doubling and distinct mutational signatures. We identified a group of tumors in the colon and rectum lacking hypermutation and aneuploidy termed genome stable and enriched in DNA hypermethylation and mutations in KRAS, SOX9, and PCBP1.
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- 2018
8. A Pan-Cancer Analysis of Enhancer Expression in Nearly 9000 Patient Samples
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Chen, Han, Li, Chunyan, Peng, Xinxin, Zhou, Zhicheng, Weinstein, John N, Network, The Cancer Genome Atlas Research, Caesar-Johnson, Samantha J, Demchok, John A, Felau, Ina, Kasapi, Melpomeni, Ferguson, Martin L, Hutter, Carolyn M, Sofia, Heidi J, Tarnuzzer, Roy, Wang, Zhining, Yang, Liming, Zenklusen, Jean C, Zhang, Jiashan, Chudamani, Sudha, Liu, Jia, Lolla, Laxmi, Naresh, Rashi, Pihl, Todd, Sun, Qiang, Wan, Yunhu, Wu, Ye, Cho, Juok, DeFreitas, Timothy, Frazer, Scott, Gehlenborg, Nils, Getz, Gad, Heiman, David I, Kim, Jaegil, Lawrence, Michael S, Lin, Pei, Meier, Sam, Noble, Michael S, Saksena, Gordon, Voet, Doug, Zhang, Hailei, Bernard, Brady, Chambwe, Nyasha, Dhankani, Varsha, Knijnenburg, Theo, Kramer, Roger, Leinonen, Kalle, Liu, Yuexin, Miller, Michael, Reynolds, Sheila, Shmulevich, Ilya, Thorsson, Vesteinn, Zhang, Wei, Akbani, Rehan, Broom, Bradley M, Hegde, Apurva M, Ju, Zhenlin, Kanchi, Rupa S, Korkut, Anil, Li, Jun, Liang, Han, Ling, Shiyun, Liu, Wenbin, Lu, Yiling, Mills, Gordon B, Ng, Kwok-Shing, Rao, Arvind, Ryan, Michael, Wang, Jing, Zhang, Jiexin, Abeshouse, Adam, Armenia, Joshua, Chakravarty, Debyani, Chatila, Walid K, de Bruijn, Ino, Gao, Jianjiong, Gross, Benjamin E, Heins, Zachary J, Kundra, Ritika, La, Konnor, Ladanyi, Marc, Luna, Augustin, Nissan, Moriah G, Ochoa, Angelica, Phillips, Sarah M, Reznik, Ed, Sanchez-Vega, Francisco, Sander, Chris, Schultz, Nikolaus, Sheridan, Robert, Sumer, S Onur, Sun, Yichao, Taylor, Barry S, Wang, Jioajiao, Zhang, Hongxin, Anur, Pavana, Peto, Myron, Spellman, Paul, Benz, Christopher, and Stuart, Joshua M
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Genetics ,Cancer ,Human Genome ,2.1 Biological and endogenous factors ,Aetiology ,Aneuploidy ,B7-H1 Antigen ,Chromatin ,Databases ,Genetic ,Enhancer Elements ,Genetic ,Gene Expression Regulation ,Neoplastic ,Humans ,Immunotherapy ,Neoplasms ,Sequence Analysis ,RNA ,Survival Rate ,Cancer Genome Atlas Research Network ,PD-L1 expression ,The Cancer Genome Atlas ,aneuploidy ,chromatin state ,enhancer expression ,mutation burden ,pan-cancer analysis ,prognostic markers ,Biological Sciences ,Medical and Health Sciences ,Developmental Biology - Abstract
The role of enhancers, a key class of non-coding regulatory DNA elements, in cancer development has increasingly been appreciated. Here, we present the detection and characterization of a large number of expressed enhancers in a genome-wide analysis of 8928 tumor samples across 33 cancer types using TCGA RNA-seq data. Compared with matched normal tissues, global enhancer activation was observed in most cancers. Across cancer types, global enhancer activity was positively associated with aneuploidy, but not mutation load, suggesting a hypothesis centered on "chromatin-state" to explain their interplay. Integrating eQTL, mRNA co-expression, and Hi-C data analysis, we developed a computational method to infer causal enhancer-gene interactions, revealing enhancers of clinically actionable genes. Having identified an enhancer ∼140 kb downstream of PD-L1, a major immunotherapy target, we validated it experimentally. This study provides a systematic view of enhancer activity in diverse tumor contexts and suggests the clinical implications of enhancers.
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- 2018
9. Genomic and Functional Approaches to Understanding Cancer Aneuploidy
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Taylor, Alison M, Shih, Juliann, Ha, Gavin, Gao, Galen F, Zhang, Xiaoyang, Berger, Ashton C, Schumacher, Steven E, Wang, Chen, Hu, Hai, Liu, Jianfang, Lazar, Alexander J, Network, The Cancer Genome Atlas Research, Caesar-Johnson, Samantha J, Demchok, John A, Felau, Ina, Kasapi, Melpomeni, Ferguson, Martin L, Hutter, Carolyn M, Sofia, Heidi J, Tarnuzzer, Roy, Wang, Zhining, Yang, Liming, Zenklusen, Jean C, Zhang, Jiashan, Chudamani, Sudha, Liu, Jia, Lolla, Laxmi, Naresh, Rashi, Pihl, Todd, Sun, Qiang, Wan, Yunhu, Wu, Ye, Cho, Juok, DeFreitas, Timothy, Frazer, Scott, Gehlenborg, Nils, Getz, Gad, Heiman, David I, Kim, Jaegil, Lawrence, Michael S, Lin, Pei, Meier, Sam, Noble, Michael S, Saksena, Gordon, Voet, Doug, Zhang, Hailei, Bernard, Brady, Chambwe, Nyasha, Dhankani, Varsha, Knijnenburg, Theo, Kramer, Roger, Leinonen, Kalle, Liu, Yuexin, Miller, Michael, Reynolds, Sheila, Shmulevich, Ilya, Thorsson, Vesteinn, Zhang, Wei, Akbani, Rehan, Broom, Bradley M, Hegde, Apurva M, Ju, Zhenlin, Kanchi, Rupa S, Korkut, Anil, Li, Jun, Liang, Han, Ling, Shiyun, Liu, Wenbin, Lu, Yiling, Mills, Gordon B, Ng, Kwok-Shing, Rao, Arvind, Ryan, Michael, Wang, Jing, Weinstein, John N, Zhang, Jiexin, Abeshouse, Adam, Armenia, Joshua, Chakravarty, Debyani, Chatila, Walid K, de Bruijn, Ino, Gao, Jianjiong, Gross, Benjamin E, Heins, Zachary J, Kundra, Ritika, La, Konnor, Ladanyi, Marc, Luna, Augustin, Nissan, Moriah G, Ochoa, Angelica, Phillips, Sarah M, Reznik, Ed, Sanchez-Vega, Francisco, Sander, Chris, Schultz, Nikolaus, Sheridan, Robert, Sumer, S Onur, Sun, Yichao, Taylor, Barry S, and Wang, Jioajiao
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Biological Sciences ,Biomedical and Clinical Sciences ,Bioinformatics and Computational Biology ,Genetics ,Oncology and Carcinogenesis ,Cancer ,Cancer Genomics ,Lung ,Human Genome ,Lung Cancer ,2.1 Biological and endogenous factors ,Aneuploidy ,Carcinoma ,Squamous Cell ,Cell Cycle ,Cell Proliferation ,Chromosome Aberrations ,Chromosome Deletion ,Chromosomes ,Human ,Pair 3 ,Databases ,Genetic ,Genomics ,Humans ,Mutation Rate ,Tumor Suppressor Protein p53 ,Cancer Genome Atlas Research Network ,aneuploidy ,cancer genomics ,genome engineering ,lung squamous cell carcinoma ,Neurosciences ,Oncology & Carcinogenesis ,Biochemistry and cell biology ,Oncology and carcinogenesis - Abstract
Aneuploidy, whole chromosome or chromosome arm imbalance, is a near-universal characteristic of human cancers. In 10,522 cancer genomes from The Cancer Genome Atlas, aneuploidy was correlated with TP53 mutation, somatic mutation rate, and expression of proliferation genes. Aneuploidy was anti-correlated with expression of immune signaling genes, due to decreased leukocyte infiltrates in high-aneuploidy samples. Chromosome arm-level alterations show cancer-specific patterns, including loss of chromosome arm 3p in squamous cancers. We applied genome engineering to delete 3p in lung cells, causing decreased proliferation rescued in part by chromosome 3 duplication. This study defines genomic and phenotypic correlates of cancer aneuploidy and provides an experimental approach to study chromosome arm aneuploidy.
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- 2018
10. Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images
- Author
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Saltz, Joel, Gupta, Rajarsi, Hou, Le, Kurc, Tahsin, Singh, Pankaj, Nguyen, Vu, Samaras, Dimitris, Shroyer, Kenneth R, Zhao, Tianhao, Batiste, Rebecca, Van Arnam, John, Network, The Cancer Genome Atlas Research, Caesar-Johnson, Samantha J, Demchok, John A, Felau, Ina, Kasapi, Melpomeni, Ferguson, Martin L, Hutter, Carolyn M, Sofia, Heidi J, Tarnuzzer, Roy, Wang, Zhining, Yang, Liming, Zenklusen, Jean C, Zhang, Jiashan, Chudamani, Sudha, Liu, Jia, Lolla, Laxmi, Naresh, Rashi, Pihl, Todd, Sun, Qiang, Wan, Yunhu, Wu, Ye, Cho, Juok, DeFreitas, Timothy, Frazer, Scott, Gehlenborg, Nils, Getz, Gad, Heiman, David I, Kim, Jaegil, Lawrence, Michael S, Lin, Pei, Meier, Sam, Noble, Michael S, Saksena, Gordon, Voet, Doug, Zhang, Hailei, Bernard, Brady, Chambwe, Nyasha, Dhankani, Varsha, Knijnenburg, Theo, Kramer, Roger, Leinonen, Kalle, Liu, Yuexin, Miller, Michael, Reynolds, Sheila, Shmulevich, Ilya, Thorsson, Vesteinn, Zhang, Wei, Akbani, Rehan, Broom, Bradley M, Hegde, Apurva M, Ju, Zhenlin, Kanchi, Rupa S, Korkut, Anil, Li, Jun, Liang, Han, Ling, Shiyun, Liu, Wenbin, Lu, Yiling, Mills, Gordon B, Ng, Kwok-Shing, Rao, Arvind, Ryan, Michael, Wang, Jing, Weinstein, John N, Zhang, Jiexin, Abeshouse, Adam, Armenia, Joshua, Chakravarty, Debyani, Chatila, Walid K, de Bruijn, Ino, Gao, Jianjiong, Gross, Benjamin E, Heins, Zachary J, Kundra, Ritika, La, Konnor, Ladanyi, Marc, Luna, Augustin, Nissan, Moriah G, Ochoa, Angelica, Phillips, Sarah M, Reznik, Ed, Sanchez-Vega, Francisco, Sander, Chris, Schultz, Nikolaus, Sheridan, Robert, Sumer, S Onur, Sun, Yichao, Taylor, Barry S, and Wang, Jioajiao
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Biological Sciences ,Cancer ,Machine Learning and Artificial Intelligence ,Genetics ,Human Genome ,Networking and Information Technology R&D (NITRD) ,Good Health and Well Being ,Deep Learning ,Humans ,Image Interpretation ,Computer-Assisted ,Lymphocytes ,Tumor-Infiltrating ,Neoplasms ,Cancer Genome Atlas Research Network ,artificial intelligence ,bioinformatics ,computer vision ,deep learning ,digital pathology ,immuno-oncology ,lymphocytes ,machine learning ,tumor microenvironment ,tumor-infiltrating lymphocytes ,Biochemistry and Cell Biology ,Medical Physiology ,Biological sciences - Abstract
Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumor-infiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment.
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- 2018
11. Oncogenic Signaling Pathways in The Cancer Genome Atlas
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Sanchez-Vega, Francisco, Mina, Marco, Armenia, Joshua, Chatila, Walid K, Luna, Augustin, La, Konnor C, Dimitriadoy, Sofia, Liu, David L, Kantheti, Havish S, Saghafinia, Sadegh, Chakravarty, Debyani, Daian, Foysal, Gao, Qingsong, Bailey, Matthew H, Liang, Wen-Wei, Foltz, Steven M, Shmulevich, Ilya, Ding, Li, Heins, Zachary, Ochoa, Angelica, Gross, Benjamin, Gao, Jianjiong, Zhang, Hongxin, Kundra, Ritika, Kandoth, Cyriac, Bahceci, Istemi, Dervishi, Leonard, Dogrusoz, Ugur, Zhou, Wanding, Shen, Hui, Laird, Peter W, Way, Gregory P, Greene, Casey S, Liang, Han, Xiao, Yonghong, Wang, Chen, Iavarone, Antonio, Berger, Alice H, Bivona, Trever G, Lazar, Alexander J, Hammer, Gary D, Giordano, Thomas, Kwong, Lawrence N, McArthur, Grant, Huang, Chenfei, Tward, Aaron D, Frederick, Mitchell J, McCormick, Frank, Meyerson, Matthew, Network, The Cancer Genome Atlas Research, Caesar-Johnson, Samantha J, Demchok, John A, Felau, Ina, Kasapi, Melpomeni, Ferguson, Martin L, Hutter, Carolyn M, Sofia, Heidi J, Tarnuzzer, Roy, Wang, Zhining, Yang, Liming, Zenklusen, Jean C, Zhang, Jiashan, Chudamani, Sudha, Liu, Jia, Lolla, Laxmi, Naresh, Rashi, Pihl, Todd, Sun, Qiang, Wan, Yunhu, Wu, Ye, Cho, Juok, DeFreitas, Timothy, Frazer, Scott, Gehlenborg, Nils, Getz, Gad, Heiman, David I, Kim, Jaegil, Lawrence, Michael S, Lin, Pei, Meier, Sam, Noble, Michael S, Saksena, Gordon, Voet, Doug, Zhang, Hailei, Bernard, Brady, Chambwe, Nyasha, Dhankani, Varsha, Knijnenburg, Theo, Kramer, Roger, Leinonen, Kalle, Liu, Yuexin, Miller, Michael, Reynolds, Sheila, Thorsson, Vesteinn, Zhang, Wei, Akbani, Rehan, Broom, Bradley M, Hegde, Apurva M, and Ju, Zhenlin
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Biochemistry and Cell Biology ,Bioinformatics and Computational Biology ,Biological Sciences ,Biomedical and Clinical Sciences ,Genetics ,Oncology and Carcinogenesis ,Cancer ,Human Genome ,Cancer Genomics ,2.1 Biological and endogenous factors ,Good Health and Well Being ,Databases ,Genetic ,Genes ,Neoplasm ,Humans ,Neoplasms ,Phosphatidylinositol 3-Kinases ,Signal Transduction ,Transforming Growth Factor beta ,Tumor Suppressor Protein p53 ,Wnt Proteins ,Cancer Genome Atlas Research Network ,PanCanAtlas ,TCGA ,cancer genome atlas ,cancer genomics ,combination therapy ,pan-cancer ,precision oncology ,signaling pathways ,therapeutics ,whole exome sequencing ,Medical and Health Sciences ,Developmental Biology ,Biological sciences ,Biomedical and clinical sciences - Abstract
Genetic alterations in signaling pathways that control cell-cycle progression, apoptosis, and cell growth are common hallmarks of cancer, but the extent, mechanisms, and co-occurrence of alterations in these pathways differ between individual tumors and tumor types. Using mutations, copy-number changes, mRNA expression, gene fusions and DNA methylation in 9,125 tumors profiled by The Cancer Genome Atlas (TCGA), we analyzed the mechanisms and patterns of somatic alterations in ten canonical pathways: cell cycle, Hippo, Myc, Notch, Nrf2, PI-3-Kinase/Akt, RTK-RAS, TGFβ signaling, p53 and β-catenin/Wnt. We charted the detailed landscape of pathway alterations in 33 cancer types, stratified into 64 subtypes, and identified patterns of co-occurrence and mutual exclusivity. Eighty-nine percent of tumors had at least one driver alteration in these pathways, and 57% percent of tumors had at least one alteration potentially targetable by currently available drugs. Thirty percent of tumors had multiple targetable alterations, indicating opportunities for combination therapy.
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- 2018
12. Machine Learning Identifies Stemness Features Associated with Oncogenic Dedifferentiation
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Malta, Tathiane M, Sokolov, Artem, Gentles, Andrew J, Burzykowski, Tomasz, Poisson, Laila, Weinstein, John N, Kamińska, Bożena, Huelsken, Joerg, Omberg, Larsson, Gevaert, Olivier, Colaprico, Antonio, Czerwińska, Patrycja, Mazurek, Sylwia, Mishra, Lopa, Heyn, Holger, Krasnitz, Alex, Godwin, Andrew K, Lazar, Alexander J, Network, The Cancer Genome Atlas Research, Caesar-Johnson, Samantha J, Demchok, John A, Felau, Ina, Kasapi, Melpomeni, Ferguson, Martin L, Hutter, Carolyn M, Sofia, Heidi J, Tarnuzzer, Roy, Wang, Zhining, Yang, Liming, Zenklusen, Jean C, Zhang, Jiashan, Chudamani, Sudha, Liu, Jia, Lolla, Laxmi, Naresh, Rashi, Pihl, Todd, Sun, Qiang, Wan, Yunhu, Wu, Ye, Cho, Juok, DeFreitas, Timothy, Frazer, Scott, Gehlenborg, Nils, Getz, Gad, Heiman, David I, Kim, Jaegil, Lawrence, Michael S, Lin, Pei, Meier, Sam, Noble, Michael S, Saksena, Gordon, Voet, Doug, Zhang, Hailei, Bernard, Brady, Chambwe, Nyasha, Dhankani, Varsha, Knijnenburg, Theo, Kramer, Roger, Leinonen, Kalle, Liu, Yuexin, Miller, Michael, Reynolds, Sheila, Shmulevich, Ilya, Thorsson, Vesteinn, Zhang, Wei, Akbani, Rehan, Broom, Bradley M, Hegde, Apurva M, Ju, Zhenlin, Kanchi, Rupa S, Korkut, Anil, Li, Jun, Liang, Han, Ling, Shiyun, Liu, Wenbin, Lu, Yiling, Mills, Gordon B, Ng, Kwok-Shing, Rao, Arvind, Ryan, Michael, Wang, Jing, Zhang, Jiexin, Abeshouse, Adam, Armenia, Joshua, Chakravarty, Debyani, Chatila, Walid K, de Bruijn, Ino, Gao, Jianjiong, Gross, Benjamin E, Heins, Zachary J, Kundra, Ritika, La, Konnor, Ladanyi, Marc, Luna, Augustin, Nissan, Moriah G, Ochoa, Angelica, Phillips, Sarah M, Reznik, Ed, and Sanchez-Vega, Francisco
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Biomedical and Clinical Sciences ,Oncology and Carcinogenesis ,Immunology ,Stem Cell Research - Induced Pluripotent Stem Cell ,Stem Cell Research - Nonembryonic - Non-Human ,Stem Cell Research ,Human Genome ,Cancer ,Rare Diseases ,Cancer Genomics ,Genetics ,Stem Cell Research - Nonembryonic - Human ,Machine Learning and Artificial Intelligence ,Good Health and Well Being ,Carcinogenesis ,Cell Dedifferentiation ,DNA Methylation ,Databases ,Genetic ,Epigenesis ,Genetic ,Humans ,Machine Learning ,MicroRNAs ,Neoplasm Metastasis ,Neoplasms ,Stem Cells ,Transcriptome ,Tumor Microenvironment ,Cancer Genome Atlas Research Network ,The Cancer Genome Atlas ,cancer stem cells ,dedifferentiation ,epigenomic ,genomic ,machine learning ,pan-cancer ,stemness ,Biological Sciences ,Medical and Health Sciences ,Developmental Biology ,Biological sciences ,Biomedical and clinical sciences - Abstract
Cancer progression involves the gradual loss of a differentiated phenotype and acquisition of progenitor and stem-cell-like features. Here, we provide novel stemness indices for assessing the degree of oncogenic dedifferentiation. We used an innovative one-class logistic regression (OCLR) machine-learning algorithm to extract transcriptomic and epigenetic feature sets derived from non-transformed pluripotent stem cells and their differentiated progeny. Using OCLR, we were able to identify previously undiscovered biological mechanisms associated with the dedifferentiated oncogenic state. Analyses of the tumor microenvironment revealed unanticipated correlation of cancer stemness with immune checkpoint expression and infiltrating immune cells. We found that the dedifferentiated oncogenic phenotype was generally most prominent in metastatic tumors. Application of our stemness indices to single-cell data revealed patterns of intra-tumor molecular heterogeneity. Finally, the indices allowed for the identification of novel targets and possible targeted therapies aimed at tumor differentiation.
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- 2018
13. Perspective on Oncogenic Processes at the End of the Beginning of Cancer Genomics
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Ding, Li, Bailey, Matthew H, Porta-Pardo, Eduard, Thorsson, Vesteinn, Colaprico, Antonio, Bertrand, Denis, Gibbs, David L, Weerasinghe, Amila, Huang, Kuan-lin, Tokheim, Collin, Cortés-Ciriano, Isidro, Jayasinghe, Reyka, Chen, Feng, Yu, Lihua, Sun, Sam, Olsen, Catharina, Kim, Jaegil, Taylor, Alison M, Cherniack, Andrew D, Akbani, Rehan, Suphavilai, Chayaporn, Nagarajan, Niranjan, Stuart, Joshua M, Mills, Gordon B, Wyczalkowski, Matthew A, Vincent, Benjamin G, Hutter, Carolyn M, Zenklusen, Jean Claude, Hoadley, Katherine A, Wendl, Michael C, Shmulevich, llya, Lazar, Alexander J, Wheeler, David A, Getz, Gad, Network, The Cancer Genome Atlas Research, Caesar-Johnson, Samantha J, Demchok, John A, Felau, Ina, Kasapi, Melpomeni, Ferguson, Martin L, Sofia, Heidi J, Tarnuzzer, Roy, Wang, Zhining, Yang, Liming, Zenklusen, Jean C, Zhang, Jiashan, Chudamani, Sudha, Liu, Jia, Lolla, Laxmi, Naresh, Rashi, Pihl, Todd, Sun, Qiang, Wan, Yunhu, Wu, Ye, Cho, Juok, DeFreitas, Timothy, Frazer, Scott, Gehlenborg, Nils, Heiman, David I, Lawrence, Michael S, Lin, Pei, Meier, Sam, Noble, Michael S, Saksena, Gordon, Voet, Doug, Zhang, Hailei, Bernard, Brady, Chambwe, Nyasha, Dhankani, Varsha, Knijnenburg, Theo, Kramer, Roger, Leinonen, Kalle, Liu, Yuexin, Miller, Michael, Reynolds, Sheila, Shmulevich, Ilya, Zhang, Wei, Broom, Bradley M, Hegde, Apurva M, Ju, Zhenlin, Kanchi, Rupa S, Korkut, Anil, Li, Jun, Liang, Han, Ling, Shiyun, Liu, Wenbin, Lu, Yiling, Ng, Kwok-Shing, Rao, Arvind, Ryan, Michael, Wang, Jing, Weinstein, John N, Zhang, Jiexin, and Abeshouse, Adam
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Biological Sciences ,Biomedical and Clinical Sciences ,Bioinformatics and Computational Biology ,Genetics ,Oncology and Carcinogenesis ,Cancer ,Cancer Genomics ,Human Genome ,Biotechnology ,2.1 Biological and endogenous factors ,Good Health and Well Being ,Carcinogenesis ,DNA Repair ,Databases ,Genetic ,Genes ,Neoplasm ,Genomics ,Humans ,Metabolic Networks and Pathways ,Microsatellite Instability ,Mutation ,Neoplasms ,Transcriptome ,Tumor Microenvironment ,Cancer Genome Atlas Research Network ,TCGA ,cancer ,cancer genomics ,omics ,oncogenic process ,Medical and Health Sciences ,Developmental Biology ,Biological sciences ,Biomedical and clinical sciences - Abstract
The Cancer Genome Atlas (TCGA) has catalyzed systematic characterization of diverse genomic alterations underlying human cancers. At this historic junction marking the completion of genomic characterization of over 11,000 tumors from 33 cancer types, we present our current understanding of the molecular processes governing oncogenesis. We illustrate our insights into cancer through synthesis of the findings of the TCGA PanCancer Atlas project on three facets of oncogenesis: (1) somatic driver mutations, germline pathogenic variants, and their interactions in the tumor; (2) the influence of the tumor genome and epigenome on transcriptome and proteome; and (3) the relationship between tumor and the microenvironment, including implications for drugs targeting driver events and immunotherapies. These results will anchor future characterization of rare and common tumor types, primary and relapsed tumors, and cancers across ancestry groups and will guide the deployment of clinical genomic sequencing.
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- 2018
14. Comprehensive Characterization of Cancer Driver Genes and Mutations
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Bailey, Matthew H, Tokheim, Collin, Porta-Pardo, Eduard, Sengupta, Sohini, Bertrand, Denis, Weerasinghe, Amila, Colaprico, Antonio, Wendl, Michael C, Kim, Jaegil, Reardon, Brendan, Ng, Patrick Kwok-Shing, Jeong, Kang Jin, Cao, Song, Wang, Zixing, Gao, Jianjiong, Gao, Qingsong, Wang, Fang, Liu, Eric Minwei, Mularoni, Loris, Rubio-Perez, Carlota, Nagarajan, Niranjan, Cortés-Ciriano, Isidro, Zhou, Daniel Cui, Liang, Wen-Wei, Hess, Julian M, Yellapantula, Venkata D, Tamborero, David, Gonzalez-Perez, Abel, Suphavilai, Chayaporn, Ko, Jia Yu, Khurana, Ekta, Park, Peter J, Van Allen, Eliezer M, Liang, Han, Group, The MC3 Working, Network, The Cancer Genome Atlas Research, Caesar-Johnson, Samantha J, Demchok, John A, Felau, Ina, Kasapi, Melpomeni, Ferguson, Martin L, Hutter, Carolyn M, Sofia, Heidi J, Tarnuzzer, Roy, Wang, Zhining, Yang, Liming, Zenklusen, Jean C, Zhang, Jiashan, Chudamani, Sudha, Liu, Jia, Lolla, Laxmi, Naresh, Rashi, Pihl, Todd, Sun, Qiang, Wan, Yunhu, Wu, Ye, Cho, Juok, DeFreitas, Timothy, Frazer, Scott, Gehlenborg, Nils, Getz, Gad, Heiman, David I, Lawrence, Michael S, Lin, Pei, Meier, Sam, Noble, Michael S, Saksena, Gordon, Voet, Doug, Zhang, Hailei, Bernard, Brady, Chambwe, Nyasha, Dhankani, Varsha, Knijnenburg, Theo, Kramer, Roger, Leinonen, Kalle, Liu, Yuexin, Miller, Michael, Reynolds, Sheila, Shmulevich, Ilya, Thorsson, Vesteinn, Zhang, Wei, Akbani, Rehan, Broom, Bradley M, Hegde, Apurva M, Ju, Zhenlin, Kanchi, Rupa S, Korkut, Anil, Li, Jun, Ling, Shiyun, Liu, Wenbin, Lu, Yiling, Mills, Gordon B, Ng, Kwok-Shing, Rao, Arvind, Ryan, Michael, Wang, Jing, Weinstein, John N, and Zhang, Jiexin
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Biological Sciences ,Bioinformatics and Computational Biology ,Biomedical and Clinical Sciences ,Oncology and Carcinogenesis ,Genetic Testing ,Cancer ,Cancer Genomics ,Precision Medicine ,Genetics ,Human Genome ,Networking and Information Technology R&D (NITRD) ,2.1 Biological and endogenous factors ,Good Health and Well Being ,Algorithms ,B7-H1 Antigen ,Computational Biology ,Databases ,Genetic ,Entropy ,Humans ,Microsatellite Instability ,Mutation ,Neoplasms ,Principal Component Analysis ,Programmed Cell Death 1 Receptor ,MC3 Working Group ,Cancer Genome Atlas Research Network ,driver gene discovery ,mutations of clinical relevance ,oncology ,structure analysis ,Medical and Health Sciences ,Developmental Biology ,Biological sciences ,Biomedical and clinical sciences - Abstract
Identifying molecular cancer drivers is critical for precision oncology. Multiple advanced algorithms to identify drivers now exist, but systematic attempts to combine and optimize them on large datasets are few. We report a PanCancer and PanSoftware analysis spanning 9,423 tumor exomes (comprising all 33 of The Cancer Genome Atlas projects) and using 26 computational tools to catalog driver genes and mutations. We identify 299 driver genes with implications regarding their anatomical sites and cancer/cell types. Sequence- and structure-based analyses identified >3,400 putative missense driver mutations supported by multiple lines of evidence. Experimental validation confirmed 60%-85% of predicted mutations as likely drivers. We found that >300 MSI tumors are associated with high PD-1/PD-L1, and 57% of tumors analyzed harbor putative clinically actionable events. Our study represents the most comprehensive discovery of cancer genes and mutations to date and will serve as a blueprint for future biological and clinical endeavors.
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- 2018
15. A Comprehensive Pan-Cancer Molecular Study of Gynecologic and Breast Cancers
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Berger, Ashton C, Korkut, Anil, Kanchi, Rupa S, Hegde, Apurva M, Lenoir, Walter, Liu, Wenbin, Liu, Yuexin, Fan, Huihui, Shen, Hui, Ravikumar, Visweswaran, Rao, Arvind, Schultz, Andre, Li, Xubin, Sumazin, Pavel, Williams, Cecilia, Mestdagh, Pieter, Gunaratne, Preethi H, Yau, Christina, Bowlby, Reanne, Robertson, A Gordon, Tiezzi, Daniel G, Wang, Chen, Cherniack, Andrew D, Godwin, Andrew K, Kuderer, Nicole M, Rader, Janet S, Zuna, Rosemary E, Sood, Anil K, Lazar, Alexander J, Ojesina, Akinyemi I, Adebamowo, Clement, Adebamowo, Sally N, Baggerly, Keith A, Chen, Ting-Wen, Chiu, Hua-Sheng, Lefever, Steve, Liu, Liang, MacKenzie, Karen, Orsulic, Sandra, Roszik, Jason, Shelley, Carl Simon, Song, Qianqian, Vellano, Christopher P, Wentzensen, Nicolas, Network, The Cancer Genome Atlas Research, Caesar-Johnson, Samantha J, Demchok, John A, Felau, Ina, Kasapi, Melpomeni, Ferguson, Martin L, Hutter, Carolyn M, Sofia, Heidi J, Tarnuzzer, Roy, Wang, Zhining, Yang, Liming, Zenklusen, Jean C, Zhang, Jiashan, Chudamani, Sudha, Liu, Jia, Lolla, Laxmi, Naresh, Rashi, Pihl, Todd, Sun, Qiang, Wan, Yunhu, Wu, Ye, Cho, Juok, DeFreitas, Timothy, Frazer, Scott, Gehlenborg, Nils, Getz, Gad, Heiman, David I, Kim, Jaegil, Lawrence, Michael S, Lin, Pei, Meier, Sam, Noble, Michael S, Saksena, Gordon, Voet, Doug, Zhang, Hailei, Bernard, Brady, Chambwe, Nyasha, Dhankani, Varsha, Knijnenburg, Theo, Kramer, Roger, Leinonen, Kalle, Miller, Michael, Reynolds, Sheila, Shmulevich, Ilya, Thorsson, Vesteinn, Zhang, Wei, Akbani, Rehan, Broom, Bradley M, Ju, Zhenlin, Li, Jun, Liang, Han, and Ling, Shiyun
- Subjects
Biological Sciences ,Bioinformatics and Computational Biology ,Biomedical and Clinical Sciences ,Oncology and Carcinogenesis ,Women's Health ,Cancer ,Cancer Genomics ,Precision Medicine ,Genetics ,Human Genome ,Breast Cancer ,4.1 Discovery and preclinical testing of markers and technologies ,Breast Neoplasms ,DNA Copy Number Variations ,Databases ,Genetic ,Female ,Gene Expression Profiling ,Gene Expression Regulation ,Neoplastic ,Gene Regulatory Networks ,Genetic Predisposition to Disease ,Genital Neoplasms ,Female ,Humans ,Mutation ,Organ Specificity ,Prognosis ,RNA ,Long Noncoding ,Receptors ,Estrogen ,Cancer Genome Atlas Research Network ,TCGA ,The Cancer Genome Atlas ,breast cancer ,cervical cancer ,gynecologic cancer ,omics ,ovarian cancer ,pan-gynecologic ,uterine cancer ,uterine carcinosarcoma ,Neurosciences ,Oncology & Carcinogenesis ,Biochemistry and cell biology ,Oncology and carcinogenesis - Abstract
We analyzed molecular data on 2,579 tumors from The Cancer Genome Atlas (TCGA) of four gynecological types plus breast. Our aims were to identify shared and unique molecular features, clinically significant subtypes, and potential therapeutic targets. We found 61 somatic copy-number alterations (SCNAs) and 46 significantly mutated genes (SMGs). Eleven SCNAs and 11 SMGs had not been identified in previous TCGA studies of the individual tumor types. We found functionally significant estrogen receptor-regulated long non-coding RNAs (lncRNAs) and gene/lncRNA interaction networks. Pathway analysis identified subtypes with high leukocyte infiltration, raising potential implications for immunotherapy. Using 16 key molecular features, we identified five prognostic subtypes and developed a decision tree that classified patients into the subtypes based on just six features that are assessable in clinical laboratories.
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- 2018
16. Cell-of-Origin Patterns Dominate the Molecular Classification of 10,000 Tumors from 33 Types of Cancer
- Author
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Hoadley, Katherine A, Yau, Christina, Hinoue, Toshinori, Wolf, Denise M, Lazar, Alexander J, Drill, Esther, Shen, Ronglai, Taylor, Alison M, Cherniack, Andrew D, Thorsson, Vésteinn, Akbani, Rehan, Bowlby, Reanne, Wong, Christopher K, Wiznerowicz, Maciej, Sanchez-Vega, Francisco, Robertson, A Gordon, Schneider, Barbara G, Lawrence, Michael S, Noushmehr, Houtan, Malta, Tathiane M, Network, The Cancer Genome Atlas, Caesar-Johnson, Samantha J, Demchok, John A, Felau, Ina, Kasapi, Melpomeni, Ferguson, Martin L, Hutter, Carolyn M, Sofia, Heidi J, Tarnuzzer, Roy, Wang, Zhining, Yang, Liming, Zenklusen, Jean C, Zhang, Jiashan, Chudamani, Sudha, Liu, Jia, Lolla, Laxmi, Naresh, Rashi, Pihl, Todd, Sun, Qiang, Wan, Yunhu, Wu, Ye, Cho, Juok, DeFreitas, Timothy, Frazer, Scott, Gehlenborg, Nils, Getz, Gad, Heiman, David I, Kim, Jaegil, Lin, Pei, Meier, Sam, Noble, Michael S, Saksena, Gordon, Voet, Doug, Zhang, Hailei, Bernard, Brady, Chambwe, Nyasha, Dhankani, Varsha, Knijnenburg, Theo, Kramer, Roger, Leinonen, Kalle, Liu, Yuexin, Miller, Michael, Reynolds, Sheila, Shmulevich, Ilya, Thorsson, Vesteinn, Zhang, Wei, Broom, Bradley M, Hegde, Apurva M, Ju, Zhenlin, Kanchi, Rupa S, Korkut, Anil, Li, Jun, Liang, Han, Ling, Shiyun, Liu, Wenbin, Lu, Yiling, Mills, Gordon B, Ng, Kwok-Shing, Rao, Arvind, Ryan, Michael, Wang, Jing, Weinstein, John N, Zhang, Jiexin, Abeshouse, Adam, Armenia, Joshua, Chakravarty, Debyani, Chatila, Walid K, de Bruijn, Ino, Gao, Jianjiong, Gross, Benjamin E, Heins, Zachary J, Kundra, Ritika, La, Konnor, Ladanyi, Marc, Luna, Augustin, Nissan, Moriah G, Ochoa, Angelica, and Phillips, Sarah M
- Subjects
Biological Sciences ,Bioinformatics and Computational Biology ,Genetics ,Cancer ,Biotechnology ,Cancer Genomics ,Human Genome ,Networking and Information Technology R&D (NITRD) ,2.1 Biological and endogenous factors ,Aneuploidy ,Chromosomes ,Cluster Analysis ,CpG Islands ,DNA Methylation ,Databases ,Factual ,Humans ,MicroRNAs ,Mutation ,Neoplasm Proteins ,Neoplasms ,RNA ,Messenger ,Cancer Genome Atlas Network ,TCGA ,cancer ,cell-of-origin ,genome ,methylome ,organs ,proteome ,subtypes ,tissues ,transcriptome ,Medical and Health Sciences ,Developmental Biology ,Biological sciences ,Biomedical and clinical sciences - Abstract
We conducted comprehensive integrative molecular analyses of the complete set of tumors in The Cancer Genome Atlas (TCGA), consisting of approximately 10,000 specimens and representing 33 types of cancer. We performed molecular clustering using data on chromosome-arm-level aneuploidy, DNA hypermethylation, mRNA, and miRNA expression levels and reverse-phase protein arrays, of which all, except for aneuploidy, revealed clustering primarily organized by histology, tissue type, or anatomic origin. The influence of cell type was evident in DNA-methylation-based clustering, even after excluding sites with known preexisting tissue-type-specific methylation. Integrative clustering further emphasized the dominant role of cell-of-origin patterns. Molecular similarities among histologically or anatomically related cancer types provide a basis for focused pan-cancer analyses, such as pan-gastrointestinal, pan-gynecological, pan-kidney, and pan-squamous cancers, and those related by stemness features, which in turn may inform strategies for future therapeutic development.
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- 2018
17. Pathogenic Germline Variants in 10,389 Adult Cancers
- Author
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Huang, Kuan-lin, Mashl, R Jay, Wu, Yige, Ritter, Deborah I, Wang, Jiayin, Oh, Clara, Paczkowska, Marta, Reynolds, Sheila, Wyczalkowski, Matthew A, Oak, Ninad, Scott, Adam D, Krassowski, Michal, Cherniack, Andrew D, Houlahan, Kathleen E, Jayasinghe, Reyka, Wang, Liang-Bo, Zhou, Daniel Cui, Liu, Di, Cao, Song, Kim, Young Won, Koire, Amanda, McMichael, Joshua F, Hucthagowder, Vishwanathan, Kim, Tae-Beom, Hahn, Abigail, Wang, Chen, McLellan, Michael D, Al-Mulla, Fahd, Johnson, Kimberly J, Network, The Cancer Genome Atlas Research, Caesar-Johnson, Samantha J, Demchok, John A, Felau, Ina, Kasapi, Melpomeni, Ferguson, Martin L, Hutter, Carolyn M, Sofia, Heidi J, Tarnuzzer, Roy, Wang, Zhining, Yang, Liming, Zenklusen, Jean C, Zhang, Jiashan, Chudamani, Sudha, Liu, Jia, Lolla, Laxmi, Naresh, Rashi, Pihl, Todd, Sun, Qiang, Wan, Yunhu, Wu, Ye, Cho, Juok, DeFreitas, Timothy, Frazer, Scott, Gehlenborg, Nils, Getz, Gad, Heiman, David I, Kim, Jaegil, Lawrence, Michael S, Lin, Pei, Meier, Sam, Noble, Michael S, Saksena, Gordon, Voet, Doug, Zhang, Hailei, Bernard, Brady, Chambwe, Nyasha, Dhankani, Varsha, Knijnenburg, Theo, Kramer, Roger, Leinonen, Kalle, Liu, Yuexin, Miller, Michael, Shmulevich, Ilya, Thorsson, Vesteinn, Zhang, Wei, Akbani, Rehan, Broom, Bradley M, Hegde, Apurva M, Ju, Zhenlin, Kanchi, Rupa S, Korkut, Anil, Li, Jun, Liang, Han, Ling, Shiyun, Liu, Wenbin, Lu, Yiling, Mills, Gordon B, Ng, Kwok-Shing, Rao, Arvind, Ryan, Michael, Wang, Jing, Weinstein, John N, Zhang, Jiexin, Abeshouse, Adam, Armenia, Joshua, Chakravarty, Debyani, Chatila, Walid K, de Bruijn, Ino, and Gao, Jianjiong
- Subjects
Biological Sciences ,Biomedical and Clinical Sciences ,Genetics ,Oncology and Carcinogenesis ,Cancer ,Rare Diseases ,Cancer Genomics ,Prevention ,Human Genome ,2.1 Biological and endogenous factors ,DNA Copy Number Variations ,Databases ,Genetic ,Gene Deletion ,Gene Frequency ,Genetic Predisposition to Disease ,Genotype ,Germ Cells ,Germ-Line Mutation ,Humans ,Loss of Heterozygosity ,Mutation ,Missense ,Neoplasms ,Polymorphism ,Single Nucleotide ,Proto-Oncogene Proteins c-met ,Proto-Oncogene Proteins c-ret ,Tumor Suppressor Proteins ,Cancer Genome Atlas Research Network ,LOH ,cancer predisposition ,germline and somatic genomes ,variant pathogenicity ,Medical and Health Sciences ,Developmental Biology ,Biological sciences ,Biomedical and clinical sciences - Abstract
We conducted the largest investigation of predisposition variants in cancer to date, discovering 853 pathogenic or likely pathogenic variants in 8% of 10,389 cases from 33 cancer types. Twenty-one genes showed single or cross-cancer associations, including novel associations of SDHA in melanoma and PALB2 in stomach adenocarcinoma. The 659 predisposition variants and 18 additional large deletions in tumor suppressors, including ATM, BRCA1, and NF1, showed low gene expression and frequent (43%) loss of heterozygosity or biallelic two-hit events. We also discovered 33 such variants in oncogenes, including missenses in MET, RET, and PTPN11 associated with high gene expression. We nominated 47 additional predisposition variants from prioritized VUSs supported by multiple evidences involving case-control frequency, loss of heterozygosity, expression effect, and co-localization with mutations and modified residues. Our integrative approach links rare predisposition variants to functional consequences, informing future guidelines of variant classification and germline genetic testing in cancer.
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- 2018
18. The Cancer Genome Atlas Comprehensive Molecular Characterization of Renal Cell Carcinoma
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Ricketts, Christopher J, De Cubas, Aguirre A, Fan, Huihui, Smith, Christof C, Lang, Martin, Reznik, Ed, Bowlby, Reanne, Gibb, Ewan A, Akbani, Rehan, Beroukhim, Rameen, Bottaro, Donald P, Choueiri, Toni K, Gibbs, Richard A, Godwin, Andrew K, Haake, Scott, Hakimi, A Ari, Henske, Elizabeth P, Hsieh, James J, Ho, Thai H, Kanchi, Rupa S, Krishnan, Bhavani, Kwiatkowski, David J, Lui, Wembin, Merino, Maria J, Mills, Gordon B, Myers, Jerome, Nickerson, Michael L, Reuter, Victor E, Schmidt, Laura S, Shelley, C Simon, Shen, Hui, Shuch, Brian, Signoretti, Sabina, Srinivasan, Ramaprasad, Tamboli, Pheroze, Thomas, George, Vincent, Benjamin G, Vocke, Cathy D, Wheeler, David A, Yang, Lixing, Kim, William Y, Robertson, A Gordon, Network, The Cancer Genome Atlas Research, Caesar-Johnson, Samantha J, Demchok, John A, Felau, Ina, Kasapi, Melpomeni, Ferguson, Martin L, Hutter, Carolyn M, Sofia, Heidi J, Tarnuzzer, Roy, Wang, Zhining, Yang, Liming, Zenklusen, Jean C, Zhang, Jiashan, Chudamani, Sudha, Liu, Jia, Lolla, Laxmi, Naresh, Rashi, Pihl, Todd, Sun, Qiang, Wan, Yunhu, Wu, Ye, Cho, Juok, DeFreitas, Timothy, Frazer, Scott, Gehlenborg, Nils, Getz, Gad, Heiman, David I, Kim, Jaegil, Lawrence, Michael S, Lin, Pei, Meier, Sam, Noble, Michael S, Saksena, Gordon, Voet, Doug, Zhang, Hailei, Bernard, Brady, Chambwe, Nyasha, Dhankani, Varsha, Knijnenburg, Theo, Kramer, Roger, Leinonen, Kalle, Liu, Yuexin, Miller, Michael, Reynolds, Sheila, Shmulevich, Ilya, Thorsson, Vesteinn, Zhang, Wei, Broom, Bradley M, Hegde, Apurva M, Ju, Zhenlin, Korkut, Anil, Li, Jun, Liang, Han, Ling, Shiyun, Liu, Wenbin, and Lu, Yiling
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Biological Sciences ,Cancer ,Rare Diseases ,Cancer Genomics ,Orphan Drug ,Genetics ,Human Genome ,Kidney Disease ,Biotechnology ,4.1 Discovery and preclinical testing of markers and technologies ,2.1 Biological and endogenous factors ,Good Health and Well Being ,Biomarkers ,Tumor ,Carcinoma ,Renal Cell ,Cyclin-Dependent Kinase Inhibitor p16 ,DNA-Binding Proteins ,Genome ,Human ,Humans ,Kidney Neoplasms ,Metabolic Networks and Pathways ,Nuclear Proteins ,PTEN Phosphohydrolase ,Phenotype ,Survival Analysis ,Transcription Factors ,Tumor Suppressor Proteins ,Ubiquitin Thiolesterase ,Cancer Genome Atlas Research Network ,CDKN2A ,DNA hypermethylation ,PanCanAtlas ,TCGA ,chromatin remodeling ,chromophobe renal cell carcinoma ,clear cell renal cell carcinoma ,immune signature ,papillary renal cell carcinoma ,Biochemistry and Cell Biology ,Medical Physiology ,Biological sciences - Abstract
Renal cell carcinoma (RCC) is not a single disease, but several histologically defined cancers with different genetic drivers, clinical courses, and therapeutic responses. The current study evaluated 843 RCC from the three major histologic subtypes, including 488 clear cell RCC, 274 papillary RCC, and 81 chromophobe RCC. Comprehensive genomic and phenotypic analysis of the RCC subtypes reveals distinctive features of each subtype that provide the foundation for the development of subtype-specific therapeutic and management strategies for patients affected with these cancers. Somatic alteration of BAP1, PBRM1, and PTEN and altered metabolic pathways correlated with subtype-specific decreased survival, while CDKN2A alteration, increased DNA hypermethylation, and increases in the immune-related Th2 gene expression signature correlated with decreased survival within all major histologic subtypes. CIMP-RCC demonstrated an increased immune signature, and a uniform and distinct metabolic expression pattern identified a subset of metabolically divergent (MD) ChRCC that associated with extremely poor survival.
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- 2018
19. Systematic Analysis of Splice-Site-Creating Mutations in Cancer
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Jayasinghe, Reyka G, Cao, Song, Gao, Qingsong, Wendl, Michael C, Vo, Nam Sy, Reynolds, Sheila M, Zhao, Yanyan, Climente-González, Héctor, Chai, Shengjie, Wang, Fang, Varghese, Rajees, Huang, Mo, Liang, Wen-Wei, Wyczalkowski, Matthew A, Sengupta, Sohini, Li, Zhi, Payne, Samuel H, Fenyö, David, Miner, Jeffrey H, Walter, Matthew J, Network, The Cancer Genome Atlas Research, Caesar-Johnson, Samantha J, Demchok, John A, Felau, Ina, Kasapi, Melpomeni, Ferguson, Martin L, Hutter, Carolyn M, Sofia, Heidi J, Tarnuzzer, Roy, Wang, Zhining, Yang, Liming, Zenklusen, Jean C, Zhang, Jiashan, Chudamani, Sudha, Liu, Jia, Lolla, Laxmi, Naresh, Rashi, Pihl, Todd, Sun, Qiang, Wan, Yunhu, Wu, Ye, Cho, Juok, DeFreitas, Timothy, Frazer, Scott, Gehlenborg, Nils, Getz, Gad, Heiman, David I, Kim, Jaegil, Lawrence, Michael S, Lin, Pei, Meier, Sam, Noble, Michael S, Saksena, Gordon, Voet, Doug, Zhang, Hailei, Bernard, Brady, Chambwe, Nyasha, Dhankani, Varsha, Knijnenburg, Theo, Kramer, Roger, Leinonen, Kalle, Liu, Yuexin, Miller, Michael, Reynolds, Sheila, Shmulevich, Ilya, Thorsson, Vesteinn, Zhang, Wei, Akbani, Rehan, Broom, Bradley M, Hegde, Apurva M, Ju, Zhenlin, Kanchi, Rupa S, Korkut, Anil, Li, Jun, Liang, Han, Ling, Shiyun, Liu, Wenbin, Lu, Yiling, Mills, Gordon B, Ng, Kwok-Shing, Rao, Arvind, Ryan, Michael, Wang, Jing, Weinstein, John N, Zhang, Jiexin, Abeshouse, Adam, Armenia, Joshua, Chakravarty, Debyani, Chatila, Walid K, de Bruijn, Ino, Gao, Jianjiong, Gross, Benjamin E, Heins, Zachary J, Kundra, Ritika, La, Konnor, Ladanyi, Marc, Luna, Augustin, Nissan, Moriah G, Ochoa, Angelica, and Phillips, Sarah M
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Biological Sciences ,Bioinformatics and Computational Biology ,Cancer ,Rare Diseases ,Immunotherapy ,Cancer Genomics ,Genetics ,Human Genome ,5.1 Pharmaceuticals ,2.1 Biological and endogenous factors ,BRCA1 Protein ,GATA3 Transcription Factor ,HEK293 Cells ,Humans ,Mutation ,Neoplasms ,Poly (ADP-Ribose) Polymerase-1 ,Programmed Cell Death 1 Receptor ,RNA Splice Sites ,Tumor Suppressor Protein p53 ,X-linked Nuclear Protein ,Cancer Genome Atlas Research Network ,RNA ,mutations of clinical relevance ,splicing ,Biochemistry and Cell Biology ,Medical Physiology ,Biological sciences - Abstract
For the past decade, cancer genomic studies have focused on mutations leading to splice-site disruption, overlooking those having splice-creating potential. Here, we applied a bioinformatic tool, MiSplice, for the large-scale discovery of splice-site-creating mutations (SCMs) across 8,656 TCGA tumors. We report 1,964 originally mis-annotated mutations having clear evidence of creating alternative splice junctions. TP53 and GATA3 have 26 and 18 SCMs, respectively, and ATRX has 5 from lower-grade gliomas. Mutations in 11 genes, including PARP1, BRCA1, and BAP1, were experimentally validated for splice-site-creating function. Notably, we found that neoantigens induced by SCMs are likely several folds more immunogenic compared to missense mutations, exemplified by the recurrent GATA3 SCM. Further, high expression of PD-1 and PD-L1 was observed in tumors with SCMs, suggesting candidates for immune blockade therapy. Our work highlights the importance of integrating DNA and RNA data for understanding the functional and the clinical implications of mutations in human diseases.
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- 2018
20. Driver Fusions and Their Implications in the Development and Treatment of Human Cancers
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Gao, Qingsong, Liang, Wen-Wei, Foltz, Steven M, Mutharasu, Gnanavel, Jayasinghe, Reyka G, Cao, Song, Liao, Wen-Wei, Reynolds, Sheila M, Wyczalkowski, Matthew A, Yao, Lijun, Yu, Lihua, Sun, Sam Q, Group, The Fusion Analysis Working, Network, The Cancer Genome Atlas Research, Caesar-Johnson, Samantha J, Demchok, John A, Felau, Ina, Kasapi, Melpomeni, Ferguson, Martin L, Hutter, Carolyn M, Sofia, Heidi J, Tarnuzzer, Roy, Wang, Zhining, Yang, Liming, Zenklusen, Jean C, Zhang, Jiashan, Chudamani, Sudha, Liu, Jia, Lolla, Laxmi, Naresh, Rashi, Pihl, Todd, Sun, Qiang, Wan, Yunhu, Wu, Ye, Cho, Juok, DeFreitas, Timothy, Frazer, Scott, Gehlenborg, Nils, Getz, Gad, Heiman, David I, Kim, Jaegil, Lawrence, Michael S, Lin, Pei, Meier, Sam, Noble, Michael S, Saksena, Gordon, Voet, Doug, Zhang, Hailei, Bernard, Brady, Chambwe, Nyasha, Dhankani, Varsha, Knijnenburg, Theo, Kramer, Roger, Leinonen, Kalle, Liu, Yuexin, Miller, Michael, Reynolds, Sheila, Shmulevich, Ilya, Thorsson, Vesteinn, Zhang, Wei, Akbani, Rehan, Broom, Bradley M, Hegde, Apurva M, Ju, Zhenlin, Kanchi, Rupa S, Korkut, Anil, Li, Jun, Liang, Han, Ling, Shiyun, Liu, Wenbin, Lu, Yiling, Mills, Gordon B, Ng, Kwok-Shing, Rao, Arvind, Ryan, Michael, Wang, Jing, Weinstein, John N, Zhang, Jiexin, Abeshouse, Adam, Armenia, Joshua, Chakravarty, Debyani, Chatila, Walid K, de Bruijn, Ino, Gao, Jianjiong, Gross, Benjamin E, Heins, Zachary J, Kundra, Ritika, La, Konnor, Ladanyi, Marc, Luna, Augustin, Nissan, Moriah G, Ochoa, Angelica, Phillips, Sarah M, Reznik, Ed, Sanchez-Vega, Francisco, Sander, Chris, Schultz, Nikolaus, Sheridan, Robert, Sumer, S Onur, and Sun, Yichao
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Biological Sciences ,Cancer ,Rare Diseases ,Cancer Genomics ,Genetics ,Digestive Diseases ,Human Genome ,Biotechnology ,5.1 Pharmaceuticals ,Good Health and Well Being ,Antineoplastic Agents ,Carcinogenesis ,Cell Line ,Tumor ,Humans ,Molecular Targeted Therapy ,Neoplasms ,Oncogene Fusion ,Oncogene Proteins ,Fusion ,Fusion Analysis Working Group ,Cancer Genome Atlas Research Network ,RNA ,cancer ,fusion ,gene fusions ,translocation ,Biochemistry and Cell Biology ,Medical Physiology ,Biological sciences - Abstract
Gene fusions represent an important class of somatic alterations in cancer. We systematically investigated fusions in 9,624 tumors across 33 cancer types using multiple fusion calling tools. We identified a total of 25,664 fusions, with a 63% validation rate. Integration of gene expression, copy number, and fusion annotation data revealed that fusions involving oncogenes tend to exhibit increased expression, whereas fusions involving tumor suppressors have the opposite effect. For fusions involving kinases, we found 1,275 with an intact kinase domain, the proportion of which varied significantly across cancer types. Our study suggests that fusions drive the development of 16.5% of cancer cases and function as the sole driver in more than 1% of them. Finally, we identified druggable fusions involving genes such as TMPRSS2, RET, FGFR3, ALK, and ESR1 in 6.0% of cases, and we predicted immunogenic peptides, suggesting that fusions may provide leads for targeted drug and immune therapy.
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- 2018
21. Molecular Characterization and Clinical Relevance of Metabolic Expression Subtypes in Human Cancers
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Peng, Xinxin, Chen, Zhongyuan, Farshidfar, Farshad, Xu, Xiaoyan, Lorenzi, Philip L, Wang, Yumeng, Cheng, Feixiong, Tan, Lin, Mojumdar, Kamalika, Du, Di, Ge, Zhongqi, Li, Jun, Thomas, George V, Birsoy, Kivanc, Liu, Lingxiang, Zhang, Huiwen, Zhao, Zhongming, Marchand, Calena, Weinstein, John N, Network, The Cancer Genome Atlas Research, Caesar-Johnson, Samantha J, Demchok, John A, Felau, Ina, Kasapi, Melpomeni, Ferguson, Martin L, Hutter, Carolyn M, Sofia, Heidi J, Tarnuzzer, Roy, Wang, Zhining, Yang, Liming, Zenklusen, Jean C, Zhang, Jiashan, Chudamani, Sudha, Liu, Jia, Lolla, Laxmi, Naresh, Rashi, Pihl, Todd, Sun, Qiang, Wan, Yunhu, Wu, Ye, Cho, Juok, DeFreitas, Timothy, Frazer, Scott, Gehlenborg, Nils, Getz, Gad, Heiman, David I, Kim, Jaegil, Lawrence, Michael S, Lin, Pei, Meier, Sam, Noble, Michael S, Saksena, Gordon, Voet, Doug, Zhang, Hailei, Bernard, Brady, Chambwe, Nyasha, Dhankani, Varsha, Knijnenburg, Theo, Kramer, Roger, Leinonen, Kalle, Liu, Yuexin, Miller, Michael, Reynolds, Sheila, Shmulevich, Ilya, Thorsson, Vesteinn, Zhang, Wei, Akbani, Rehan, Broom, Bradley M, Hegde, Apurva M, Ju, Zhenlin, Kanchi, Rupa S, Korkut, Anil, Liang, Han, Ling, Shiyun, Liu, Wenbin, Lu, Yiling, Mills, Gordon B, Ng, Kwok-Shing, Rao, Arvind, Ryan, Michael, Wang, Jing, Zhang, Jiexin, Abeshouse, Adam, Armenia, Joshua, Chakravarty, Debyani, Chatila, Walid K, de Bruijn, Ino, Gao, Jianjiong, Gross, Benjamin E, Heins, Zachary J, Kundra, Ritika, La, Konnor, Ladanyi, Marc, Luna, Augustin, Nissan, Moriah G, Ochoa, Angelica, Phillips, Sarah M, and Reznik, Ed
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Biological Sciences ,Cancer ,Cancer Genomics ,Genetics ,Nutrition ,Human Genome ,2.1 Biological and endogenous factors ,Cell Line ,Tumor ,Core Binding Factor Alpha 2 Subunit ,Drug Resistance ,Neoplasm ,HEK293 Cells ,Humans ,Metabolic Networks and Pathways ,Neoplasms ,Snail Family Transcription Factors ,Transcriptome ,Cancer Genome Atlas Research Network ,The Cancer Genome Atlas ,carbohydrate metabolism ,drug sensitivity ,master regulator ,prognostic markers ,somatic drivers ,therapeutic targets ,tumor subtypes ,Biochemistry and Cell Biology ,Medical Physiology ,Biological sciences - Abstract
Metabolic reprogramming provides critical information for clinical oncology. Using molecular data of 9,125 patient samples from The Cancer Genome Atlas, we identified tumor subtypes in 33 cancer types based on mRNA expression patterns of seven major metabolic processes and assessed their clinical relevance. Our metabolic expression subtypes correlated extensively with clinical outcome: subtypes with upregulated carbohydrate, nucleotide, and vitamin/cofactor metabolism most consistently correlated with worse prognosis, whereas subtypes with upregulated lipid metabolism showed the opposite. Metabolic subtypes correlated with diverse somatic drivers but exhibited effects convergent on cancer hallmark pathways and were modulated by highly recurrent master regulators across cancer types. As a proof-of-concept example, we demonstrated that knockdown of SNAI1 or RUNX1-master regulators of carbohydrate metabolic subtypes-modulates metabolic activity and drug sensitivity. Our study provides a system-level view of metabolic heterogeneity within and across cancer types and identifies pathway cross-talk, suggesting related prognostic, therapeutic, and predictive utility.
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- 2018
22. Machine Learning Detects Pan-cancer Ras Pathway Activation in The Cancer Genome Atlas
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Way, Gregory P, Sanchez-Vega, Francisco, La, Konnor, Armenia, Joshua, Chatila, Walid K, Luna, Augustin, Sander, Chris, Cherniack, Andrew D, Mina, Marco, Ciriello, Giovanni, Schultz, Nikolaus, Network, The Cancer Genome Atlas Research, Caesar-Johnson, Samantha J, Demchok, John A, Felau, Ina, Kasapi, Melpomeni, Ferguson, Martin L, Hutter, Carolyn M, Sofia, Heidi J, Tarnuzzer, Roy, Wang, Zhining, Yang, Liming, Zenklusen, Jean C, Zhang, Jiashan, Chudamani, Sudha, Liu, Jia, Lolla, Laxmi, Naresh, Rashi, Pihl, Todd, Sun, Qiang, Wan, Yunhu, Wu, Ye, Cho, Juok, DeFreitas, Timothy, Frazer, Scott, Gehlenborg, Nils, Getz, Gad, Heiman, David I, Kim, Jaegil, Lawrence, Michael S, Lin, Pei, Meier, Sam, Noble, Michael S, Saksena, Gordon, Voet, Doug, Zhang, Hailei, Bernard, Brady, Chambwe, Nyasha, Dhankani, Varsha, Knijnenburg, Theo, Kramer, Roger, Leinonen, Kalle, Liu, Yuexin, Miller, Michael, Reynolds, Sheila, Shmulevich, Ilya, Thorsson, Vesteinn, Zhang, Wei, Akbani, Rehan, Broom, Bradley M, Hegde, Apurva M, Ju, Zhenlin, Kanchi, Rupa S, Korkut, Anil, Li, Jun, Liang, Han, Ling, Shiyun, Liu, Wenbin, Lu, Yiling, Mills, Gordon B, Ng, Kwok-Shing, Rao, Arvind, Ryan, Michael, Wang, Jing, Weinstein, John N, Zhang, Jiexin, Abeshouse, Adam, Chakravarty, Debyani, de Bruijn, Ino, Gao, Jianjiong, Gross, Benjamin E, Heins, Zachary J, Kundra, Ritika, Ladanyi, Marc, Nissan, Moriah G, Ochoa, Angelica, Phillips, Sarah M, Reznik, Ed, Sheridan, Robert, Sumer, S Onur, Sun, Yichao, Taylor, Barry S, and Wang, Jioajiao
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Biological Sciences ,Bioinformatics and Computational Biology ,Genetics ,Human Genome ,Cancer ,Precision Medicine ,Cancer Genomics ,Machine Learning and Artificial Intelligence ,Networking and Information Technology R&D (NITRD) ,Good Health and Well Being ,Cell Line ,Tumor ,Gene Expression Regulation ,Neoplastic ,Genome ,Human ,Humans ,Machine Learning ,Neoplasms ,Signal Transduction ,ras Proteins ,Cancer Genome Atlas Research Network ,Gene expression ,HRAS ,KRAS ,NF1 ,NRAS ,Ras ,TCGA ,drug sensitivity ,machine learning ,pan-cancer ,Biochemistry and Cell Biology ,Medical Physiology ,Biological sciences - Abstract
Precision oncology uses genomic evidence to match patients with treatment but often fails to identify all patients who may respond. The transcriptome of these "hidden responders" may reveal responsive molecular states. We describe and evaluate a machine-learning approach to classify aberrant pathway activity in tumors, which may aid in hidden responder identification. The algorithm integrates RNA-seq, copy number, and mutations from 33 different cancer types across The Cancer Genome Atlas (TCGA) PanCanAtlas project to predict aberrant molecular states in tumors. Applied to the Ras pathway, the method detects Ras activation across cancer types and identifies phenocopying variants. The model, trained on human tumors, can predict response to MEK inhibitors in wild-type Ras cell lines. We also present data that suggest that multiple hits in the Ras pathway confer increased Ras activity. The transcriptome is underused in precision oncology and, combined with machine learning, can aid in the identification of hidden responders.
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- 2018
23. An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics
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Liu, Jianfang, Lichtenberg, Tara, Hoadley, Katherine A, Poisson, Laila M, Lazar, Alexander J, Cherniack, Andrew D, Kovatich, Albert J, Benz, Christopher C, Levine, Douglas A, Lee, Adrian V, Omberg, Larsson, Wolf, Denise M, Shriver, Craig D, Thorsson, Vesteinn, Network, The Cancer Genome Atlas Research, Caesar-Johnson, Samantha J, Demchok, John A, Felau, Ina, Kasapi, Melpomeni, Ferguson, Martin L, Hutter, Carolyn M, Sofia, Heidi J, Tarnuzzer, Roy, Wang, Zhining, Yang, Liming, Zenklusen, Jean C, Zhang, Jiashan, Chudamani, Sudha, Liu, Jia, Lolla, Laxmi, Naresh, Rashi, Pihl, Todd, Sun, Qiang, Wan, Yunhu, Wu, Ye, Cho, Juok, DeFreitas, Timothy, Frazer, Scott, Gehlenborg, Nils, Getz, Gad, Heiman, David I, Kim, Jaegil, Lawrence, Michael S, Lin, Pei, Meier, Sam, Noble, Michael S, Saksena, Gordon, Voet, Doug, Zhang, Hailei, Bernard, Brady, Chambwe, Nyasha, Dhankani, Varsha, Knijnenburg, Theo, Kramer, Roger, Leinonen, Kalle, Liu, Yuexin, Miller, Michael, Reynolds, Sheila, Shmulevich, Ilya, Zhang, Wei, Akbani, Rehan, Broom, Bradley M, Hegde, Apurva M, Ju, Zhenlin, Kanchi, Rupa S, Korkut, Anil, Li, Jun, Liang, Han, Ling, Shiyun, Liu, Wenbin, Lu, Yiling, Mills, Gordon B, Ng, Kwok-Shing, Rao, Arvind, Ryan, Michael, Wang, Jing, Weinstein, John N, Zhang, Jiexin, Abeshouse, Adam, Armenia, Joshua, Chakravarty, Debyani, Chatila, Walid K, de Bruijn, Ino, Gao, Jianjiong, Gross, Benjamin E, Heins, Zachary J, Kundra, Ritika, La, Konnor, Ladanyi, Marc, Luna, Augustin, Nissan, Moriah G, Ochoa, Angelica, Phillips, Sarah M, Reznik, Ed, Sanchez-Vega, Francisco, Sander, Chris, Schultz, Nikolaus, Sheridan, Robert, and Sumer, S Onur
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Biological Sciences ,Bioinformatics and Computational Biology ,Biomedical and Clinical Sciences ,Oncology and Carcinogenesis ,Networking and Information Technology R&D (NITRD) ,Women's Health ,Cancer ,Cancer Genomics ,Precision Medicine ,Genetics ,Human Genome ,Biotechnology ,Good Health and Well Being ,Databases ,Genetic ,Genomics ,Humans ,Kaplan-Meier Estimate ,Neoplasms ,Proportional Hazards Models ,Cancer Genome Atlas Research Network ,Cox proportional hazards regression model ,TCGA ,The Cancer Genome Atlas ,clinical data resource ,disease-free interval ,disease-specific survival ,follow-up time ,overall survival ,progression-free interval ,translational research ,Medical and Health Sciences ,Developmental Biology ,Biological sciences ,Biomedical and clinical sciences - Abstract
For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale.
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- 2018
24. Genomic and Molecular Landscape of DNA Damage Repair Deficiency across The Cancer Genome Atlas
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Knijnenburg, Theo A, Wang, Linghua, Zimmermann, Michael T, Chambwe, Nyasha, Gao, Galen F, Cherniack, Andrew D, Fan, Huihui, Shen, Hui, Way, Gregory P, Greene, Casey S, Liu, Yuexin, Akbani, Rehan, Feng, Bin, Donehower, Lawrence A, Miller, Chase, Shen, Yang, Karimi, Mostafa, Chen, Haoran, Kim, Pora, Jia, Peilin, Shinbrot, Eve, Zhang, Shaojun, Liu, Jianfang, Hu, Hai, Bailey, Matthew H, Yau, Christina, Wolf, Denise, Zhao, Zhongming, Weinstein, John N, Li, Lei, Ding, Li, Mills, Gordon B, Laird, Peter W, Wheeler, David A, Shmulevich, Ilya, Network, The Cancer Genome Atlas Research, Caesar-Johnson, Samantha J, Demchok, John A, Felau, Ina, Kasapi, Melpomeni, Ferguson, Martin L, Hutter, Carolyn M, Sofia, Heidi J, Tarnuzzer, Roy, Wang, Zhining, Yang, Liming, Zenklusen, Jean C, Zhang, Jiashan, Chudamani, Sudha, Liu, Jia, Lolla, Laxmi, Naresh, Rashi, Pihl, Todd, Sun, Qiang, Wan, Yunhu, Wu, Ye, Cho, Juok, DeFreitas, Timothy, Frazer, Scott, Gehlenborg, Nils, Getz, Gad, Heiman, David I, Kim, Jaegil, Lawrence, Michael S, Lin, Pei, Meier, Sam, Noble, Michael S, Saksena, Gordon, Voet, Doug, Zhang, Hailei, Bernard, Brady, Dhankani, Varsha, Knijnenburg, Theo, Kramer, Roger, Leinonen, Kalle, Miller, Michael, Reynolds, Sheila, Thorsson, Vesteinn, Zhang, Wei, Broom, Bradley M, Hegde, Apurva M, Ju, Zhenlin, Kanchi, Rupa S, Korkut, Anil, Li, Jun, Liang, Han, Ling, Shiyun, Liu, Wenbin, Lu, Yiling, Ng, Kwok-Shing, Rao, Arvind, Ryan, Michael, Wang, Jing, and Zhang, Jiexin
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Biological Sciences ,Bioinformatics and Computational Biology ,Genetics ,Women's Health ,Cancer ,Rare Diseases ,Cancer Genomics ,Orphan Drug ,Ovarian Cancer ,Human Genome ,2.1 Biological and endogenous factors ,Cell Line ,Tumor ,DNA Damage ,Gene Silencing ,Genome ,Human ,Humans ,Loss of Heterozygosity ,Machine Learning ,Mutation ,Neoplasms ,Recombinational DNA Repair ,Tumor Suppressor Proteins ,Cancer Genome Atlas Research Network ,DNA damage footprints ,DNA damage repair ,The Cancer Genome Atlas PanCanAtlas project ,epigenetic silencing ,integrative statistical analysis ,mutational signatures ,protein structure analysis ,somatic copy-number alterations ,somatic mutations ,Biochemistry and Cell Biology ,Medical Physiology ,Biological sciences - Abstract
DNA damage repair (DDR) pathways modulate cancer risk, progression, and therapeutic response. We systematically analyzed somatic alterations to provide a comprehensive view of DDR deficiency across 33 cancer types. Mutations with accompanying loss of heterozygosity were observed in over 1/3 of DDR genes, including TP53 and BRCA1/2. Other prevalent alterations included epigenetic silencing of the direct repair genes EXO5, MGMT, and ALKBH3 in ∼20% of samples. Homologous recombination deficiency (HRD) was present at varying frequency in many cancer types, most notably ovarian cancer. However, in contrast to ovarian cancer, HRD was associated with worse outcomes in several other cancers. Protein structure-based analyses allowed us to predict functional consequences of rare, recurrent DDR mutations. A new machine-learning-based classifier developed from gene expression data allowed us to identify alterations that phenocopy deleterious TP53 mutations. These frequent DDR gene alterations in many human cancers have functional consequences that may determine cancer progression and guide therapy.
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- 2018
25. Scalable Open Science Approach for Mutation Calling of Tumor Exomes Using Multiple Genomic Pipelines
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Ellrott, Kyle, Bailey, Matthew H, Saksena, Gordon, Covington, Kyle R, Kandoth, Cyriac, Stewart, Chip, Hess, Julian, Ma, Chiotti, Kami E, McLellan, Michael, Sofia, Heidi J, Hutter, Carolyn, Getz, Gad, Wheeler, David, Ding, Li, Group, MC3 Working, Network, The Cancer Genome Atlas Research, Caesar-Johnson, Samantha J, Demchok, John A, Felau, Ina, Kasapi, Melpomeni, Ferguson, Martin L, Hutter, Carolyn M, Tarnuzzer, Roy, Wang, Zhining, Yang, Liming, Zenklusen, Jean C, Zhang, Jiashan, Chudamani, Sudha, Liu, Jia, Lolla, Laxmi, Naresh, Rashi, Pihl, Todd, Sun, Qiang, Wan, Yunhu, Wu, Ye, Cho, Juok, DeFreitas, Timothy, Frazer, Scott, Gehlenborg, Nils, Heiman, David I, Kim, Jaegil, Lawrence, Michael S, Lin, Pei, Meier, Sam, Noble, Michael S, Voet, Doug, Zhang, Hailei, Bernard, Brady, Chambwe, Nyasha, Dhankani, Varsha, Knijnenburg, Theo, Kramer, Roger, Leinonen, Kalle, Liu, Yuexin, Miller, Michael, Reynolds, Sheila, Shmulevich, Ilya, Thorsson, Vesteinn, Zhang, Wei, Akbani, Rehan, Broom, Bradley M, Hegde, Apurva M, Ju, Zhenlin, Kanchi, Rupa S, Korkut, Anil, Li, Jun, Liang, Han, Ling, Shiyun, Liu, Wenbin, Lu, Yiling, Mills, Gordon B, Ng, Kwok-Shing, Rao, Arvind, Ryan, Michael, Wang, Jing, Weinstein, John N, Zhang, Jiexin, Abeshouse, Adam, Armenia, Joshua, Chakravarty, Debyani, Chatila, Walid K, de Bruijn, Ino, Gao, Jianjiong, Gross, Benjamin E, Heins, Zachary J, Kundra, Ritika, La, Konnor, Ladanyi, Marc, Luna, Augustin, Nissan, Moriah G, Ochoa, Angelica, Phillips, Sarah M, Reznik, Ed, Sanchez-Vega, Francisco, Sander, Chris, and Schultz, Nikolaus
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Biological Sciences ,Bioinformatics and Computational Biology ,Genetics ,Genetic Testing ,Cancer ,Rare Diseases ,Cancer Genomics ,Human Genome ,Networking and Information Technology R&D (NITRD) ,2.1 Biological and endogenous factors ,Good Health and Well Being ,Algorithms ,Exome ,Genomics ,High-Throughput Nucleotide Sequencing ,Humans ,Information Dissemination ,Mutation ,Neoplasms ,Sequence Analysis ,DNA ,Software ,Exome Sequencing ,MC3 Working Group ,Cancer Genome Atlas Research Network ,PanCanAtlas project ,TCGA ,large-scale ,open science ,pan-cancer ,reproducible computing ,somatic mutation calling ,Biochemistry and Cell Biology ,Biochemistry and cell biology - Abstract
The Cancer Genome Atlas (TCGA) cancer genomics dataset includes over 10,000 tumor-normal exome pairs across 33 different cancer types, in total >400 TB of raw data files requiring analysis. Here we describe the Multi-Center Mutation Calling in Multiple Cancers project, our effort to generate a comprehensive encyclopedia of somatic mutation calls for the TCGA data to enable robust cross-tumor-type analyses. Our approach accounts for variance and batch effects introduced by the rapid advancement of DNA extraction, hybridization-capture, sequencing, and analysis methods over time. We present best practices for applying an ensemble of seven mutation-calling algorithms with scoring and artifact filtering. The dataset created by this analysis includes 3.5 million somatic variants and forms the basis for PanCan Atlas papers. The results have been made available to the research community along with the methods used to generate them. This project is the result of collaboration from a number of institutes and demonstrates how team science drives extremely large genomics projects.
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- 2018
26. Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas
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Schaub, Franz X, Dhankani, Varsha, Berger, Ashton C, Trivedi, Mihir, Richardson, Anne B, Shaw, Reid, Zhao, Wei, Zhang, Xiaoyang, Ventura, Andrea, Liu, Yuexin, Ayer, Donald E, Hurlin, Peter J, Cherniack, Andrew D, Eisenman, Robert N, Bernard, Brady, Grandori, Carla, Network, The Cancer Genome Atlas, Caesar-Johnson, Samantha J, Demchok, John A, Felau, Ina, Kasapi, Melpomeni, Ferguson, Martin L, Hutter, Carolyn M, Sofia, Heidi J, Tarnuzzer, Roy, Wang, Zhining, Yang, Liming, Zenklusen, Jean C, Zhang, Jiashan, Chudamani, Sudha, Liu, Jia, Lolla, Laxmi, Naresh, Rashi, Pihl, Todd, Sun, Qiang, Wan, Yunhu, Wu, Ye, Cho, Juok, DeFreitas, Timothy, Frazer, Scott, Gehlenborg, Nils, Getz, Gad, Heiman, David I, Kim, Jaegil, Lawrence, Michael S, Lin, Pei, Meier, Sam, Noble, Michael S, Saksena, Gordon, Voet, Doug, Zhang, Hailei, Chambwe, Nyasha, Knijnenburg, Theo, Kramer, Roger, Leinonen, Kalle, Miller, Michael, Reynolds, Sheila, Shmulevich, Ilya, Thorsson, Vesteinn, Zhang, Wei, Akbani, Rehan, Broom, Bradley M, Hegde, Apurva M, Ju, Zhenlin, Kanchi, Rupa S, Korkut, Anil, Li, Jun, Liang, Han, Ling, Shiyun, Liu, Wenbin, Lu, Yiling, Mills, Gordon B, Ng, Kwok-Shing, Rao, Arvind, Ryan, Michael, Wang, Jing, Weinstein, John N, Zhang, Jiexin, Abeshouse, Adam, Armenia, Joshua, Chakravarty, Debyani, Chatila, Walid K, de Bruijn, Ino, Gao, Jianjiong, Gross, Benjamin E, Heins, Zachary J, Kundra, Ritika, La, Konnor, Ladanyi, Marc, Luna, Augustin, Nissan, Moriah G, Ochoa, Angelica, Phillips, Sarah M, Reznik, Ed, Sanchez-Vega, Francisco, Sander, Chris, and Schultz, Nikolaus
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Biological Sciences ,Bioinformatics and Computational Biology ,Cancer ,Cancer Genomics ,Genetics ,Human Genome ,Biotechnology ,2.1 Biological and endogenous factors ,Basic Helix-Loop-Helix Leucine Zipper Transcription Factors ,Basic Helix-Loop-Helix Transcription Factors ,Biomarkers ,Tumor ,Carcinogenesis ,Chromatin ,Computational Biology ,Genes ,myc ,Genomics ,Humans ,Neoplasms ,Oncogenes ,Proteomics ,Proto-Oncogene Proteins c-myc ,Repressor Proteins ,Signal Transduction ,Transcription Factors ,Cancer Genome Atlas Network ,MAX ,MNT ,MYC genomic alterations ,TCGA ,The Cancer Genome Atlas ,Biochemistry and Cell Biology ,Biochemistry and cell biology - Abstract
Although the MYC oncogene has been implicated in cancer, a systematic assessment of alterations of MYC, related transcription factors, and co-regulatory proteins, forming the proximal MYC network (PMN), across human cancers is lacking. Using computational approaches, we define genomic and proteomic features associated with MYC and the PMN across the 33 cancers of The Cancer Genome Atlas. Pan-cancer, 28% of all samples had at least one of the MYC paralogs amplified. In contrast, the MYC antagonists MGA and MNT were the most frequently mutated or deleted members, proposing a role as tumor suppressors. MYC alterations were mutually exclusive with PIK3CA, PTEN, APC, or BRAF alterations, suggesting that MYC is a distinct oncogenic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such as immune response and growth factor signaling; chromatin, translation, and DNA replication/repair were conserved pan-cancer. This analysis reveals insights into MYC biology and is a reference for biomarkers and therapeutics for cancers with alterations of MYC or the PMN.
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- 2018
27. Comprehensive Molecular Characterization of Muscle-Invasive Bladder Cancer
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Robertson, A Gordon, Kim, Jaegil, Al-Ahmadie, Hikmat, Bellmunt, Joaquim, Guo, Guangwu, Cherniack, Andrew D, Hinoue, Toshinori, Laird, Peter W, Hoadley, Katherine A, Akbani, Rehan, Castro, Mauro AA, Gibb, Ewan A, Kanchi, Rupa S, Gordenin, Dmitry A, Shukla, Sachet A, Sanchez-Vega, Francisco, Hansel, Donna E, Czerniak, Bogdan A, Reuter, Victor E, Su, Xiaoping, Carvalho, Benilton de Sa, Chagas, Vinicius S, Mungall, Karen L, Sadeghi, Sara, Pedamallu, Chandra Sekhar, Lu, Yiling, Klimczak, Leszek J, Zhang, Jiexin, Choo, Caleb, Ojesina, Akinyemi I, Bullman, Susan, Leraas, Kristen M, Lichtenberg, Tara M, Wu, Catherine J, Schultz, Nicholaus, Getz, Gad, Meyerson, Matthew, Mills, Gordon B, McConkey, David J, Network, TCGA Research, Albert, Monique, Alexopoulou, Iakovina, Ally, Adrian, Antic, Tatjana, Aron, Manju, Balasundaram, Miruna, Bartlett, John, Baylin, Stephen B, Beaver, Allison, Birol, Inanc, Boice, Lori, Bootwalla, Moiz S, Bowen, Jay, Bowlby, Reanne, Brooks, Denise, Broom, Bradley M, Bshara, Wiam, Burks, Eric, Cárcano, Flavio M, Carlsen, Rebecca, Carvalho, Benilton S, Carvalho, Andre L, Castle, Eric P, Castro, Patricia, Catto, James W, Chesla, David W, Chuah, Eric, Chudamani, Sudha, Cortessis, Victoria K, Cottingham, Sandra L, Crain, Daniel, Curley, Erin, Daneshmand, Siamak, Demchok, John A, Dhalla, Noreen, Djaladat, Hooman, Eckman, John, Egea, Sophie C, Engel, Jay, Felau, Ina, Ferguson, Martin L, Gardner, Johanna, Gastier-Foster, Julie M, Gerken, Mark, Gomez-Fernandez, Carmen R, and Harr, Jodi
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Biomedical and Clinical Sciences ,Oncology and Carcinogenesis ,Cancer ,Genetics ,Cancer Genomics ,Urologic Diseases ,Human Genome ,Biotechnology ,2.1 Biological and endogenous factors ,Aetiology ,Aged ,Cluster Analysis ,DNA Methylation ,Humans ,MicroRNAs ,Middle Aged ,Muscle ,Smooth ,RNA ,Long Noncoding ,Survival Analysis ,Urinary Bladder ,Urinary Bladder Neoplasms ,TCGA Research Network ,APOBEC mutation ,DNA methylation ,basal mRNA subtype ,lncRNA transcriptome ,luminal mRNA subtype ,microRNA ,muscle-invasive bladder cancer ,neoantigen ,neuronal subtype ,regulon ,Biological Sciences ,Medical and Health Sciences ,Developmental Biology ,Biological sciences ,Biomedical and clinical sciences - Abstract
We report a comprehensive analysis of 412 muscle-invasive bladder cancers characterized by multiple TCGA analytical platforms. Fifty-eight genes were significantly mutated, and the overall mutational load was associated with APOBEC-signature mutagenesis. Clustering by mutation signature identified a high-mutation subset with 75% 5-year survival. mRNA expression clustering refined prior clustering analyses and identified a poor-survival "neuronal" subtype in which the majority of tumors lacked small cell or neuroendocrine histology. Clustering by mRNA, long non-coding RNA (lncRNA), and miRNA expression converged to identify subsets with differential epithelial-mesenchymal transition status, carcinoma in situ scores, histologic features, and survival. Our analyses identified 5 expression subtypes that may stratify response to different treatments.
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- 2017
28. The Molecular Taxonomy of Primary Prostate Cancer
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Network, The Cancer Genome Atlas Research, Abeshouse, Adam, Ahn, Jaeil, Akbani, Rehan, Ally, Adrian, Amin, Samirkumar, Andry, Christopher D, Annala, Matti, Aprikian, Armen, Armenia, Joshua, Arora, Arshi, Auman, J Todd, Balasundaram, Miruna, Balu, Saianand, Barbieri, Christopher E, Bauer, Thomas, Benz, Christopher C, Bergeron, Alain, Beroukhim, Rameen, Berrios, Mario, Bivol, Adrian, Bodenheimer, Tom, Boice, Lori, Bootwalla, Moiz S, dos Reis, Rodolfo Borges, Boutros, Paul C, Bowen, Jay, Bowlby, Reanne, Boyd, Jeffrey, Bradley, Robert K, Breggia, Anne, Brimo, Fadi, Bristow, Christopher A, Brooks, Denise, Broom, Bradley M, Bryce, Alan H, Bubley, Glenn, Burks, Eric, Butterfield, Yaron SN, Button, Michael, Canes, David, Carlotti, Carlos G, Carlsen, Rebecca, Carmel, Michel, Carroll, Peter R, Carter, Scott L, Cartun, Richard, Carver, Brett S, Chan, June M, Chang, Matthew T, Chen, Yu, Cherniack, Andrew D, Chevalier, Simone, Chin, Lynda, Cho, Juok, Chu, Andy, Chuah, Eric, Chudamani, Sudha, Cibulskis, Kristian, Ciriello, Giovanni, Clarke, Amanda, Cooperberg, Matthew R, Corcoran, Niall M, Costello, Anthony J, Cowan, Janet, Crain, Daniel, Curley, Erin, David, Kerstin, Demchok, John A, Demichelis, Francesca, Dhalla, Noreen, Dhir, Rajiv, Doueik, Alexandre, Drake, Bettina, Dvinge, Heidi, Dyakova, Natalya, Felau, Ina, Ferguson, Martin L, Frazer, Scott, Freedland, Stephen, Fu, Yao, Gabriel, Stacey B, Gao, Jianjiong, Gardner, Johanna, Gastier-Foster, Julie M, Gehlenborg, Nils, Gerken, Mark, Gerstein, Mark B, Getz, Gad, Godwin, Andrew K, Gopalan, Anuradha, Graefen, Markus, Graim, Kiley, Gribbin, Thomas, Guin, Ranabir, Gupta, Manaswi, Hadjipanayis, Angela, Haider, Syed, Hamel, Lucie, and Hayes, D Neil
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Biomedical and Clinical Sciences ,Clinical Sciences ,Oncology and Carcinogenesis ,Human Genome ,Cancer ,Genetic Testing ,Genetics ,Urologic Diseases ,Prostate Cancer ,Good Health and Well Being ,DNA Repair ,Epigenesis ,Genetic ,Gene Expression Regulation ,Neoplastic ,Gene Fusion ,Humans ,Male ,Mutation ,Neoplasm Metastasis ,Phosphatidylinositol 3-Kinases ,Prostatic Neoplasms ,Receptors ,Androgen ,Signal Transduction ,ras Proteins ,Cancer Genome Atlas Research Network ,Biological Sciences ,Medical and Health Sciences ,Developmental Biology ,Biological sciences ,Biomedical and clinical sciences - Abstract
There is substantial heterogeneity among primary prostate cancers, evident in the spectrum of molecular abnormalities and its variable clinical course. As part of The Cancer Genome Atlas (TCGA), we present a comprehensive molecular analysis of 333 primary prostate carcinomas. Our results revealed a molecular taxonomy in which 74% of these tumors fell into one of seven subtypes defined by specific gene fusions (ERG, ETV1/4, and FLI1) or mutations (SPOP, FOXA1, and IDH1). Epigenetic profiles showed substantial heterogeneity, including an IDH1 mutant subset with a methylator phenotype. Androgen receptor (AR) activity varied widely and in a subtype-specific manner, with SPOP and FOXA1 mutant tumors having the highest levels of AR-induced transcripts. 25% of the prostate cancers had a presumed actionable lesion in the PI3K or MAPK signaling pathways, and DNA repair genes were inactivated in 19%. Our analysis reveals molecular heterogeneity among primary prostate cancers, as well as potentially actionable molecular defects.
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- 2015
29. Higher dose corticosteroids in patients admitted to hospital with COVID-19 who are hypoxic but not requiring ventilatory support (RECOVERY)
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Obbina Abani, Ali Abbas, Fatima Abbas, Joshua Abbas, Kasim Abbas, Mustafa Abbas, Sadia Abbasi, Hakam Abbass, Alfie Abbott, Alison Abbott, Nabeel Abdallah, Ammar Abdelaziz, Ashraf Abdelaziz, Mohamed Abdelfattah, Bushra Abdelqader, Audrey Abdul, Basir Abdul, Siddiqui Abdul, Althaf Abdul Rasheed, Ajibode Abdulakeem, Rezan Abdul-Kadir, Abdullah Abdullah, Abdulfatahi Abdulmumeen, Rasheed Abdul-Raheem, Niyaz Abdulshukkoor, Kula Abdusamad, Yazeed Abed El Khaleq, Mai Abedalla, Abeer Abeer Ul Amna, Lynn Abel, Katrina Abernethy, Movin Abeywickrema, Chandra Abhinaya, Affyarsyah Abidin, Adebanke Aboaba, Abigail Aboagye-Odei, Christopher Aboah, Heba Aboelela, Hani Abo-Leyah, Karim Abouelela, Ahmed Abou-Haggar, Mahmoud Abouibrahim, Ahmed Abousamra, Mona Abouzaid, Miriam Abraham, Tizzy Abraham, Abraheem Abraheem, Judith Abrams, Rebecca Abrams, Hyacinth-John Abu, Ahmed Abu-Arafeh, Syed M Abubacker, Akata Abung, Yousuf Abusamra, Yaa Aceampong, Amaka Achara, Devikumar Acharya, Faustina Acheampong, Prince Acheampong, Sarah Acheampong, Janet Acheson, Shiella Achieng, Andres Acosta, Rebecca Acquah, Catherine Acton, Jacqueline Adabie-Ankrah, Paul Adair, Fiona Adam, Matthew Adam, Huzaifa Adamali, Marta Adamczyk, Carol Adams, Charlotte Adams, Daniel Adams, Kate Adams, Laura Adams, Nikkita Adams, Richard Adams, Tim Adams, Laura Adamu-Ikeme, Krishma Adatia, Kirsty Adcock, Lawrence Addai-Boampong, Afua Addo, Oluwatobi Adeagbo, Ade Adebiyi, Ogunlana Adedeji, Yewande Adegeye, Ken Adegoke, Vicki Adell, Sherna Adenwalla, Femi W Adeoye, Oluwasegun A Adesemoye, Emmanuel O Adewunmi, Adedamola Adeyanju, Joyce Adeyemi, Tenifayo Adeyemo, Binay Adhikari, Shanti A Adhikari, Rina Adhikary, Adhikarla Aditya, Patience Adjepong, Gabrielle Adkins, Adnan Adnan, Marguerite Adriaanse, John Aeron-Thomas, Debbie Affleck, Carmel Afnan, Muhammad Afridi, Patricia Afrim, Felicia Akua Afriyie, Zainab A Aftab, Meenakshi Agarwal, Rachel Agbeko, Chris Agbo, Sunil Aggarwal, Arameh Aghababaie, Laura Aguilar Jimenez, Jacqueline Afrakomah Agyekum, Kwame Agyen, Shafana Ahamed Sadiq, Mohamed H Ahammed Nazeer, Mohammad Ahmad, Syed Ahmad, Afshan Ahmed, Ashar Ahmed, Asim Ahmed, Basheer A R Ahmed, Bilal Ahmed, Forizuddin Ahmed, Hamze Ahmed, Hanad Ahmed, Irshad Ahmed, Khaled Ahmed, Khalil Ahmed, Liban Ahmed, Mahin Ahmed, Maria C Ahmed, Muhammad S Ahmed, Naseer Ahmed, Nausheen Ahmed, Osama Ahmed, Rajia A Ahmed, Rawya Ahmed, Rizwan Ahmed, Saif Ahmed, Sammiya Ahmed, Sana G Ahmed, Syed Ahmed, Syed H Ahmed, Roa Ahmed Ali, Bilal Ahmed Mohamud, Sana Ahmed, Sana Ahmer, Augustine Ahonia, Christine Aiken, Dhiraj Ail, Mark Ainsworth, Myriam Aissa, Lindianne Aitken, Bini Ajay, Abdulakeem Ajibode, Ayesha Ajmi, Nasim Akhtar, Nauman Akhtar, Suha Akili, Bolutito Akinbiyi, Oludoyinsola Akindolie, Yinka Akinfenwa, Olugbenga Akinkugbe, Ibrahim Akinpelu, Mohammad Akram, Olugbenro Aktinade, Uzayr Akudi, Ahmad S A R Al Aaraj, Asma Al Balushi, Majd Al Dakhola, Aladdin Al Swaifi, Eslam Al-Abadi, Adegoke Alabi, Narendra Aladangady, Mohamed Alafifi, Ayaz Alam, Sajid Alam, Abbas Al-Asadi, Kyriaki Alatzoglou, Paul Albert, Albertus Albertus, Lorraine Albon, Angela Alcala, Gemma Alcorn, Stephen Alcorn, Aggie Aldana, David Alderdice, Abdullah Aldesouki, Rayan Aldouri, Jonathan Aldridge, Nicolas Aldridge, Ram Maya Ale, Ana Alegria, Alison Alexander, Courtney Alexander, John Alexander, Peter D G Alexander, Julyan Al-fori, Laith Alghazawi, Osama Alhabsha, Bahij Al-Hakim, Rafil Alhameed, Mohammed Al-Hayali, Shams Al-Hity, Ali Ali, Amanda Ali, Asad Ali, Fawzia R Ali, Jawad Ali, Mariam Ali, Mohamed Ali, Mohammad Ali, Muhammad S Ali, Nayab Ali, Oudai Ali, Ramla Ali, Sakina Ali, Syed Ali, Emilio Aliberti, Jade Alin, Abid Alina, Analyn Alipustain, Bachti Alisjahbana, Fine Aliyuda, Katrin Alizadeh, Maithem Al-Jibury, Saba Al-Juboori, Majid Al-Khalil, Abdullah Alkhudhayri, Moutaz Alkhusheh, Fiona Allan, Nataliya Allan, Alison Allanson, Robert Allcock, Eireann Allen, Jade Allen, Kerry Allen, Louise Allen, Poppy Allen, Rebecca Allen, Sam Allen, Sharon Allen, Simon Allen, Tania Allen, Abiola Alli, Kathryn Allison, Bethan Allman, Helen K Allsop, Lynne Allsop, David Allsup, Amal F T Almahroos, Hassan Al-Moasseb, Magda Al-Obaidi, Lina Alomari, Akram Al-Rabahi, Bahar Al-Ramadhani, Zayneb Al-Saadi, Riyam Al-Sammarraie, Inji Alshaer, Rustam Al-Shahi Salman, Warkaq Al-Shamkhani, Fadia Alsheikh, Bashar Al-Sheklly, Sara Altaf, Amanda Alty, Mary Alvarez, Maria Alvarez Corral, Edward Alveyn, Maysaa Alzetani, Susan Amamou, Noor Amar, Sakkarai Ambalavanan, Robert Ambrogetti, Chris Ambrose, Amir Ameen, Amel Amelia Ganefianty, Katharine Ames, Maria R Amezaga, Allison Amin, Amina Amin, Kanish Amin, Syed Amin, Tara Amin, Badshah Amit, Amjad Amjad, Neelma Amjad, James Amoah-Dankwa, Victoria Amosun, Muhammad Amsal, Khaled Amsha, John Amuasi, Noelia Amutio Martin, Pugh Amy, Ann Anada, Atul Anand, Samantha Anandappa, Satya D Anantapatnaikuni, Ellen Anderson, Julie Anderson, Laura Anderson, Marina Anderson, Michelle Anderson, Nicola Anderson, Rachel Anderson, Rebecca Anderson, Rory Anderson, Samantha Anderson, Wendy Anderson, Prematie Andreou, Angela Andrews, Antonette Andrews, Jill Andrews, Joyann Andrews, Kanayochukwu Aneke, Andrew Ang, Wan Wei Ang, Tammy Angel, Aramburo Angela, Paola Angelini, Lazarus Anguvaa, Oleg Anichtchik, Millicent Anim-Somuah, Krishnan Aniruddhan, Jessica Annett, Louise Anning, Maldwyn Ansah, Patrick J Anstey, Rebekah Anstey, Alpha Anthony, Aaron Anthony-Pillai, Philip Antill, Zhelyazkova Antonina, Varghese Anu, Muhammad Anwar, Elena Apetri, Aristeidis Apostolopoulos, Sarah Appleby, Diane Appleyard, Maia F Aquino, Bianca Araba, Samuel Aransiola, Mariana Araujo, Ann Archer, Denise Archer, Samuel Archer, Simon Archer, Daniele Arcoria, Christian Ardley, Ana-Maria Arias, Oluwatoyin Aribike, Ryoki Arimoto, Charlotte Arkley, Charlotte Armah, Ilianna Armata, Jennifer Armistead, Adam Armitage, Ceri Armstrong, Maureen Armstrong, Sonia Armstrong, Wendy Armstrong, Philippa Armtrong, Heike Arndt, Clare Arnison-Newgass, David Arnold, Rachael Arnold, Andrew Arnott, Dhawal Arora, Kavan Arora, Pardeep Arora, Rishi Arora, Arslam Arter, Armena Arumaithurai, Ayush Arya, Rita Arya, Diptesh Aryal, Denisa Asandei, Adeeba Asghar, Malik Asghar, Arif Ashab, Catherine Ashbrook-Raby, Helen Ashby, Jan Ashcroft, John Ashcroft, Samuel Ashcroft, Georgia Asher, Zakariya Ashfak, Ayesha Ashfaq, Abdul Ashish, Dawn Ashley, Sally Ashman-Flavell, Sundar Ashok, Abd-El-Aziz Ashour, Muhammad Z Ashraf, Saima Ashraf, Mohammad B Ashraq, Deborah Ashton, Susan Ashton, Andrew Ashworth, Fiona J Ashworth, Rebecca Ashworth, Arshia Aslam, I Aslam, Suhail Aslam, Laura Aslett, Harshini Asogan, Atif Asrar, Omar Assaf, Raine Astin-Chamberlain, Deborah Athorne, Billie Atkins, Christopher Atkins, Stacey Atkins, John Atkinson, Vicki Atkinson, Abolaji Atomode, Brygitta Atraskiewicz, Abdul A Attia, Eva Attubato, Marie Attwood, Paula Aubrey, Zoltan Auer, Avinash Aujayeb, Aye Chan Thar Aung, Hnin Aung, Hnin Wint Wint Aung, Ko Ko Aung, Kyaw Thu Aung, Nwe Aung, Yin Aung, Zaw Myo Aung, Emily Austin, Karen Austin, Abdusshakur Auwal, Malcolm Avari, Miriam Avery, Nicholas Aveyard, Joanne Avis, Georgina Aviss, Cristina Avram, Paula Avram, Abuzar Awadelkareem, Gabriel Awadzi, Mahmoud Awaly, Atia Awan, Aszad Aya, Eman Ayaz, John Maximilian Ayerh, Amanda Ayers, Jawwad Azam, Ahmed Azeem, Mohammed Azharuddin, Ammar Aziz, Ghazala Aziz, Imran Aziz, N Aziz, Ali Azkoul, Ashaari Azman Shah, Giada Azzopardi, Hocine Azzoug, Fiyinfoluwa Babatunde, Melvin Babi, Babiker Babiker, Gayna Babington, Matthew Babirecki, Marta Babores, Adetona O Babs-Osibodu, Sammy Bacciarelli, Roudi Bachar, Michel-Elie Bachour, Alisjahbana Bachti, Gina Bacon, Jenny Bacon, Bibi Badal, Aysha Badat, Maryuma Bader, Gurpreet R Badhan, Shreya Badhrinarayanan, Joseph P Bae, Alice Baggaley, Amy Baggott, Graham Bagley, Dinesh Bagmane, Lynsey Bagshaw, Kasra Bahadori, Angela Bailey, James Bailey, Katie Bailey, Lindsey Bailey, Liz Bailey, Lucy Bailey, Maria A Bailey, Morgan Bailey, Pippa Bailey, Sarah Bailey, Hamish Baillie, J Kenneth Baillie, Jennifer Bain, Vikram Bains, David Baird, Eilidh Baird, Kevin Baird, Susan Baird, Tracy Baird, Yolanda Baird, Aiysha Bajandouh, Danielle C Baker, Evelyn Baker, Johanne Baker, Josephine Baker, Kenneth Baker, Mark Baker, Rebecca Baker, Terri-Anne Baker, Victoria Baker, Hugh Bakere, Nawar Bakerly, Michelle Baker-Moffatt, Ameet Bakhai, Nauman Bakhtiar, Panos Bakoulas, Dhanalakshmi Bakthavatsalam, Niranjan Balachandran, Andrea Balan, Prasath Balasingam, Theodosios Balaskas, Madhu Balasubramaniam, Nicola Balatoni, Alison Balcombe, Alexander Baldwin, Ashley Baldwin, Caron Baldwin, Danielle Baldwin, Fiona Baldwin, Rebekah Baldwin-Jones, Nichola Bale, James Balfour, Matthew Ball, Robert Ball, K Ballard, Ismael Balluz, Craig Balmforth, Emese Balogh, Abeir Baltmr, Amir Baluwala, Gabby Bambridge, Alasdair Bamford, Amy Bamford, Peter Bamford, Adefunke Bamgboye, Elizabeth Bancroft, Hollie Bancroft, Joyce Banda, Krishna Bandaru, Srini Bandi, Nageswar Bandla, Somaditya Bandyopadhyam, Amit Banerjee, Ritwik Banerjee, Santosh Baniya, Omar Bani-Saad, Harrison Banks, Luke Banks, Paul Banks, Claudia Bann, Helen Bannister, Oliver Bannister, Laura Banton, Tran Bao, Mariamma Baptist, Tanya Baqai, Ananya M Baral, Sharad Chandra Baral, Desislava Baramova, Russel Barber, Emma Barbon, Monica Barbosa, Jamie Barbour, Alexander Barclay, Amanda Barclay, Claire Barclay, George Bardsley, Stephanie Bareford, Shahedal Bari, Morris Barimbing, Amy Barker, Debbie Barker, Erandi Barker, Helen Barker, Joseph Barker, Leon Barker, Lesley Barker, Oliver Barker, Kerry Barker-Williams, Sinha Barkha, Juliana Barla, Gavin Barlow, Richard Barlow, Valerie Barlow, James Barnacle, Alex Barnard, Debi Barnes, Nicky Barnes, Rory Barnes, Theresa Barnes, Calum Barnetson, Amy Barnett, Ashton Barnett-Vanes, Prince Gyenti Barning, William Barnsley, Andrew Barr, David Barr, James Barr, Charlotte Barr, Nina Barratt, Shaney Barratt, Manuella Barrera, Amy Barrett, Fiona Barrett, Jessica Barrett, Sue Barrett, Esther Barrow, Jazz Bartholomew, Claire Bartlett, Georgina Bartlett, James Bartlett, Louise Bartlett, Shauna Bartley, Sandra Bartolmeu-Pires, Anna Barton, Greg Barton, Jill Barton, Lorna Barton, Rachael Barton, Rosaleen Baruah, Sonia Baryschpolec, Hannah Bashir, Archana Bashyal, Betsy Basker, Sudha Basnet, Buddha Basnyat, Ayten Basoglu, Alexander Basran, John Bassett, G Bassett, Chris Bassford, Bengisu Bassoy, Victoria Bastion, Anup Bastola, Anupam Basumatary, Precious Basvi, Jireh A Batac, Vipula R Bataduwaarachchi, Tristan Bate, Harry J Bateman, Kathryn Bateman, Vhairi Bateman, Eleanor Bates, Hayley Bates, Michelle Bates, Simon Bates, Sally Batham, Ana Batista, Amit Batla, Dushyant Batra, Harry Batty, Thomas Batty, Alice Batty, Miranda Baum, Rachel Baumber, Carina Bautista, Fareha Bawa, Tanveer Bawa, Fatima S Bawani, Simon Bax, Matt Baxter, Nicola Baxter, Zachary Baxter, Hannah Bayes, Lee-Ann Bayo, Farid Bazari, Rohit Bazaz, Ahmad Bazli, Laura Beacham, Wendy Beadles, Kirsten Beadon, Philip Beak, Andy Beale, Kathy Beard, Jack Bearpark, Alanna Beasley, Sandee Beattie, Karen Beaumont, Dawn Beaumont-Jewell, Theresa Beaver, Sarah Beavis, Christy Beazley, Sarah Beck, Virginia Beckett, Rosie Beckitt, Sarah Beckley, Heidi Beddall, Seonaid Beddows, Deborah Beeby, Sophia Beeby, Gail Beech, Michelle Beecroft, Nigel Beer, Sally Beer, Jane Beety, Gabriela Bega, Alison Begg, Susan Begg, Sara Beghini, Ayesha Begum, Salman Begum, Selina Begum, Teresa Behan, Roya Behrouzi, Jon Beishon, Claire Beith, James Belcher, Holly Belfield, Katherine Belfield, Ajay Belgaumkar, Dina Bell, Gareth Bell, Gillian Bell, Jessica Bell, Lauren Bell, Louise Bell, Nicholas Bell, Pippa Bell, Stephanie Bell, Jennifer Bellamu, Mary Bellamy, Tammy Bellamy, Arianna Bellini, Amanda Bellis, Fionn Bellis, Lesley Bendall, Naveena Benesh, Nicola Benetti, Leonie Benham, Guy Benison-Horner, Sarah Benkenstein, Tracey Benn, Ann 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Flanagan, Charles Flanders, Nikolaos Flaris, Gail Fleming, Julie Fleming, Lucy Fleming, Paul Fleming, William Flesher, Alison Fletcher, Anna Fletcher, Jonathan Fletcher, Lucy Fletcher, Simon Fletcher, Sophie Fletcher, Fiona Flett, Karen Flewitt, Sarah Flockhart, Christopher Flood, Ian Floodgate, Jonathan Flor, Vincent Florence, Mary Flowerdew, Sharon Floyd, Margaret J Flynn, Rachel Flynn, Claire Foden, Adama Fofana, Georgina Fogarty, Paul Foley, Linda Folkes, Tracey Fong, Daniela M Font, Aiwyne Foo, Jane Foo, Andrew Foot, Helen R Foot, Jayne Foot, Jane Forbes, Amber Ford, Jamie Ford, Imogen Fordham, Jennifer Foreman, Matthew Forester, Mohammad Forkan, Caroline Fornolles, Adam Forrest, Ellie Forsey, Miranda Forsey, Thomas Forshall, Elliot Forster, Abigail Forsyth, Julian Forton, Conrad Foster, Emily Foster, Joseph Foster, Rachel A Foster, Tracy Foster, Angela Foulds, Ian Foulds, Folakemi Fowe, Natasha Fowkes, Emily Fowler, Robert Fowler, Stephen Fowler, Amy Fox, Claire Fox, Heather Fox, 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Giokanini-Royal, Anna Gipson, Barbie Giri, Joanna Girling, Rhian Gisby, Angelena Gkioni, Aikaterini Gkoritsa, Effrossyni Gkrania-Klotsas, Amy Gladwell, James Glanville, Jessica Glasgow, Susannah Glasgow, Jon Glass, Lynn Glass, Sharon Glaysher, Lisa Gledhill, Eleanor Glenday, Ana Glennon, Jodie Glossop, John Glover, Kyle Glover, Michelle Glover, Jan Glover Bengtsson, Deborah Glowski, Sharon Glynn, Chevanthy Gnanalingam, Julie Goddard, Wendy Goddard, Emily Godden, Jo Godden, Sarah Godlee, Emma Godson, Gillian Godwin, Sukanya Gogoi, Aiky Goh, Manjinder Gohel, Rebeca Goiriz, Sriya Gokaraju, Raphael Goldacre, Arthur Goldsmith, Portia Goldsmith, Darren Gomersall, Lucia Gomez, Raquel Gomez-Marcos, Ali Gondal, Celia Gonzalez, Jack Goodall, Vicky Goodall, Bob Goodenough, Anna Goodfellow, Laura Goodfellow, James Goodlife, Camelia Goodwin, Elizabeth Goodwin, Jayne Goodwin, Paula Goodyear, Rajiv Gooentilleke, Michelle Goonasekara, Sheila Gooseman, Shameer Gopal, Chris Gordon, Sally Gordon, Robin 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Hale, Jennie Hale, Carmel Halevy, Paul Halford, William Halford, Alaina Halim, Alistair Hall, Anthony Hall, Claire Hall, Elizabeth Hall, Fiona Hall, Helen Hall, Jennifer Hall, Kathryn Hall, Laura Hall, Jan Hallas, Kyle Hallas, Charles Hallett, Jackie Halliday, Akmal Hallman, Heather Halls, Maryam Hamdollah-Zadeh, Ifedadepo A Hamed-Adekale, Bilal Hameed, Mohammed Hameed, Raph L Hamers, Imran Hamid, Mohamad Hamie, Raymond Hamill, Bethany Hamilton, Fergus Hamilton, Gus Hamilton, Leigh Hamilton, Melanie Hamilton, Nicola Hamilton, Sara Hamilton, Ruth Hamlin, Eleanor Hamlyn, Beatrice Hammans, Shirley Hammersley, Kate Hammerton, Bev Hammond, Emily Hammond, Leah Hammond, Sally Hammond, Fiona Hammonds, Ibrahim Hamoodi, Karen Hampshire, James A Hampson, Jude Hampson, Lucy Hampson, Lisa Hamzah, Jenny Han, Ozan Hanci, Sadiyah Hand, Lala Handayani, Jasmine Handford, Soran Handrean, Nina K Handzewniak, Sarah Haney, Vu Thi Kim Hang, Sheharyar Hanif, E Hanison, Esther Hanison, Jennifer Hannah, Amy 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Ruth Hartley, Tom Hartley, William Hartrey, Phillipa Hartridge, Stuart Hartshorn, Alice Harvey, Angela Harvey, Anna Harvey, Max Harvey, Catherine Harwood, Helen Harwood, Zoe Harzeli, Brigitte Haselden, Kazi Hashem, Mohammed Hashimm, Tadaaki Hashimoto, Imranullah Hashmi, Jack Haslam, Zena Haslam, Grace Hasnip, Adil Hassan, Ali Hassan, Amro Hassan, Awab Hassan, Zeinab Hassan, Sapna Hassasing, Jane Hassell, Philip Hassell, Alex Hastings, Bethany Hastings, Janice Hastings, Sarah Hathaway-Lees, Jonathan Hatton, Jennifer Hau, May Havinden-Williams, Stefan Havlik, Daniel B Hawcutt, Kadean Hawes, Liz Hawes, Nicola Hawes, Lydia Hawker, Annie Hawkins, Joe Hawkins, Nancy Hawkins, W John Hawkins, Dan Hawley, Ed Hawley-Jones, Edward Haworth, Alasdair W Hay, Cathy Hay, Amna Hayat, Jamal Hayat, Mohamed-Riyal Hayathu, Anne Hayes, Jonas Hayes, Kate Hayes, Melony Hayes, Fiona Hayes, Patrick Hayle, Chloe Haylett, Antara Hayman, Melanie Hayman, Matthew Haynes, Richard Haynes, Rachel Hayre, Carole Hays, Sarah Haysom, James Hayward, Patrick Haywood, Hazel Haywood Hasford, Tracy Hazelton, Phoebe Hazenberg, Zhengmai He, Elizabeth Headon, Carrie Heal, Brendan Healy, Jessica L Healy, Amy Hearn, David Heasman, Angela Heath, Debbie Heath, Rowan Heath, Diane Heaton, Adam Heavens, Kerry Hebbron, Catherine Heckman, Gemma Hector, Sadie Heddon, Andy Hedges, Katrine Hedges, Cheryl Heeley, Elaine Heeney, Richard Heinink, Rajdeep Heire, Ingvild Helgesen, Joanne Hemingway, Ulla Hemmila, Beth Hemmings, Scott Hemphill, Deborah Hemsley, Abigail Henderson, Eilidh Henderson, Jennifer Henderson, Steven Henderson, Joanne Henry, Karol Henry, Lavinia Henry, Margo Henry, Natalie Henry, David Henshall, Gillian Herdman, Rosaleen Herdman-Grant, Morag Herkes, Lucas E Hermans, Fe Marie Hernandez, Emma Heron, Lisa Heron, William Herrington, Emilia Heselden, Peta Heslop, Tracey Heslop, Simon Hester, Emily Hetherington, Joseph Hetherington, Chamila Hettiarachchi, Pramodh Hettiarachchi, Hayley Hewer, John Hewertson, Anna Hewetson, Sue Hewins, Nicola Hewitson, Claire Hewitt, Davina Hewitt, Richard Hewitt, Samuel Hey, Robert S Heyderman, Mathis Heydtmann, Joseph Heys, Jonathan Heywood, Meg Hibbert, John Hickey, Naomi Hickey, Peter Hickey, Nicky Hickman, Alex Hicks, Jenny Hicks, Scott R Hicks, Phan Thi Thu Hien, Daniel Higbee, Lucy Higgins, Andrew Higham, Martin Highcock, Judith Highgate, Mondy Hikmat, Amanda Hill, Helen Hill, Joanne Hill, Lisa Hill, Lucy Hill, Phoebe Hill, Uta Hill, Annette Hilldrith, Catherine Hillman-Cooper, Jon Hilton, Zoe Hilton, Sarah Hinch, Andrew Hindle, Esther Hindley, Alice Hindmarsh, Paul Hine, Kim Hinshaw, Clare Hird, Claire Hirst, Lindsay Hirst, Jemma Hives, Htet M Hlaing, Benson Ho, David K K Ho, Rosemary Ho, Michaela Hoare, David Hobden, Gill Hobden, Maria Hobrok, Simon Hobson, Christopher Hodge, Simon Hodge, Lesley Hodgen, George Hodgetts, Holly Hodgkins, Sally Hodgkinson, David Hodgson, Helen Hodgson, Luke Hodgson, Sheila Hodgson, Gemma Hodkinson, Kenneth Hodson, 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Elizabeth Horsley, Sarah Horton, Jane Hosea, Toby Hoskins, Muhammad S Hossain, Rashed Hossain, Maxine Hough, Sarah Hough, Catherine Houghton, Kathryn Houghton, Rebecca Houlihan, Kay Housely, Hamish Houston, Roseanna Hovvels, Lee How, Laura Howaniec, Joanne Howard, Kate Howard, Laura Howard, Linda Howard, Lucy Howard, Megan Howard, Sarah Howard, Stuart Howard, Richard Howard-Griffin, Louise Howard-Sandy, Serena Howe, Alice Howell, Mark Howells, Lyn Howie, Kerry Howlett, Sophie Howlett, Ruth Howman, Josh Hrycaiczuk, Hein Htet, Naing Z Htoon, Su Htwe, Ying Hu, Chiang O H Huah, Sylvia Huang, Kelly Hubbard, Abby Huckle, Shahzya Huda, Alison Hudak, Lisa Hudig, Heather Hudson, Suzanne Hudson, Oli Hudson, Alison Hufton, Connor Huggins, Alistair Hughes, Caitlin Hughes, Emma Hughes, Gareth Hughes, Heather Hughes, Luke Hughes, Martin Hughes, Rachel Hughes, Rebecca Hughes, Samantha Hughes, Stephen Hughes, Vikki Hughes, Wesley Hughes, Lukas Huhn, Ching Hui, Ruth Hulbert, Diana Hull, Grace Hull, Robert Hull, Amanda Hulme, Peter Hulme, Wendy Hulse, George Hulston, Ryan Hum, Megan Hume, Charlotte Humphrey, Alasdair Humphries, Amy Humphries, Joanne Humphries, Charlotte Hunt, Fiona Hunt, Jane Hunt, Jonquil Hunt, Kristen Hunt, Luke Hunt, Molly Hunt, Sophie Hunt, Alexandra Hunter, Catherine Hunter, Ewan Hunter, Karl Hunter, Neil Hunter, Ross Hunter, Sophie Hunter, George Huntington, Fuad Huq, Elizabeth Hurditch, Judith Hurdman, Cian Hurley, Katrina Hurley, Mohammed A Husain, Syeda Y Husaini, Coralie Huson, Afreen Hussain, Chreif Hussain, Ibraar Hussain, Ifza Hussain, Mohammad Hussain, Mohammed Hussain, Muhammad Hussain, Reda Hussain, Rizwana Hussain, Samia Hussain, Sanniah Hussain, Yasmin Hussain, Mohammed Hussam El-Din, Samahir F E M Hussein, Ziad Hussein, Rebecca Hussey, Adiel Haqiq Hussien, Anja Hutchinson, Camille Hutchinson, Dorothy Hutchinson, Elizabeth Hutchinson, John Hutchinson, Claire Hutsby, Paula Hutton, Nguyen Quang Huy, Thuong Huyen, Tran Bang Huyen, Nguyen Thi Huyen Thuong, Hieu Huynh, Daniella Hydes, Jamie Hyde-Wyatt, Niamh Hynes, Megan Hyslop, Angeliki Iakovou, Katherine Ibison, Mazen Ibraheim, Abdalla Ibrahim, Ahmed Ibrahim, Asil Ibrahim, Javed Ibrahim, Mamoun Ibrahim, Mohamed Ibrahim, Wadah Ibrahim, Becky Icke, Adetokunbo Idowu Idowu, Muhammad Idrees, Nauman Idrees, Hina Iftikhar, Mawara Iftikhar, Chukwuemeka Igwe, Ogechukwu Igwe, Mohammad Ijaz, Amaju Ikomi, Clare Iles, Stamatina Iliodromiti, Mary Ilsley, Lorna Ilves, Fatima Mariam Ilyas, La'ali Imam-Gutierrez, Mohamed Iman, Christopher Imray, Haider Imtiaz, Jack Ingham, Jo Ingham, Julie Ingham, Rory Ingham, Tejas Ingle, Jennifer Inglis, Samantha Inglis-Hawkes, Anne Ingram, Luke Ingram, Tanya Ingram, Nicholas Innes, Peter Inns, Vithusha Inpadhas, Ken Inweregbu, Andreea A Ionescu, Ana Ionita, Ilian Petkov Iordanov, Anil Ipe, Javaid Iqbal, Madiha Iqbal, Mishal Iqbal, Mohammed Iqbal, Faisal Iqbal Sait, Iziegbe Irabor, Jane Ireland, Jamie Irisari, Robert Irons, Mohannad Irshad, Muhammad S Irshad, 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Jennings, Jacqui Jennings, Louise Jennings, Virginia Jennings, Ellen Jerome, Douglas Jerry, Greame Jervis, Ellen Jessup-Dunton, Jorge A Jesus Silva, Champa Jetha, Kishan Jethwa, Roshan Kumar Jha, Shaman Jhanji, Khoo Jian, Zhixin Jiao, Laura Jimenez, Ana Jimenez Gil, Jithin Jith, Teishel Joefield, Navraj Johal, Simran Johal, Karine Johannessen, Aisyah Johari, Annie John, Anu John, Maya John, Navin John, Emma Johns, Margaret Johns, Antoinette Johnson, Emma Johnson, Gillian Johnson, Kathryn Johnson, Katie Johnson, Luke Johnson, Mark Johnson, Nelsonseelan Johnson, Oliver Johnson, Rachel Johnson, Brogan Johnston, Claire Johnston, Janet Johnston, Susan Johnston, Victoria Johnston, Dawn Johnstone, Ed Johnstone, Janet Johnstone, Manohar Joishy, Adam Jones, Alistair Jones, Amy Jones, Angela Jones, Annabel Jones, Ben Jones, Bryony Jones, Carys Jones, Ceri Jones, Charlotte Jones, Christine E Jones, Debra Jones, Emily Jones, Gareth Jones, Geraldine Jones, Jac Jones, James Jones, Jonathon Jones, Julie Jones, Kate E Jones, Kimberly Jones, Laura Jones, Laura M Jones, Louise Jones, Mathew Jones, Nancy Jones, Nicola Jones, Olivia Jones, Paul Jones, Philip H Jones, Rhianna Jones, Ruth E Jones, Samantha Jones, Sophie Jones, Stefanie Jones, Steve Jones, Susan Jones, Taya Jones, Thomas Jones, Tim Jones, Tracey Jones, Ramya Jonnalagadda, Rebecca Jordache, Michele Jordan, Sarah Jordan, Abi Jose, Litty Jose, Louise Jose, Sanal Jose, Anna Joseph, Gigee Joseph, P Aiden Joseph, Rosane Joseph, Sibet Joseph, Dhaara Joshi, Mehul Joshi, Pratichi Joshi, Tushar Joshi, Benz Josiah, Lijo Joy, Tiffany Joyce, Hong Ju, Adriel Ju Wen Kwek, Andrew Judd, Edward Jude, Parminder Judge, Jessica Juhl, Sirisha Jujjavarapu, Mark Juniper, Edmund Juszczak, Deepthi Jyothish, Kasamu Kabiru Dawa, Mark Kacar, Nikhil Kadam, Nicole Kader, Ajai Kailey, Matthew Kain, Gail Kakoullis, Azad Kala Bhushan, Richard J K Kalayi, Roobala Kaliannan Periyasami, Efthymia Kallistrou, Thomas Kalmus Eliasz, Seika Kalsoom, Elisa Kam, 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Chloe Vansomeren, William Van't Hoff, Sejal Vara, Stehen J Vardy, Anu Varghese, Maria Varghese, William Varney, Giulia Varnier, Anna-Nektaria Varouxaki, Resti Varquez, Valeria Vasadi, Olivia Vass, Katherine Vassell, Vimal Vasu, Vasanthi Vasudevan, Manu Vatish, Sue Vaughan, Heloyes Vayalaman, Darini Vayapooree, Christopher Vaz, Niki Veale, Sachuda Veerasamy, Swati Velankar, Luxmi Velauthar, Neyme Veli, Nicola Vella, Aravind Velugupati, Anitha Velusamy, Ian Venables, Mavi Venditti, Ramya Venkataramakrishnan, Richard Venn, Robert Venn, Michelle Venter, Lyn Ventilacion, Joanne Vere, Mark Veres, Stefania Vergnano, Will Verling, Amit Verma, Rachel Vernall, Britney Vernon, Mark Vertue, Liberty Verueco, Jerik Verula, Anna Veterini, Natalie Vethanayagam, Shambavi Vettikumaran, Lucy Veys, Carinna Vickers, Saji Victor, SImpson Victoria, Celine P Vidaillac, Jennifer Vidler, Bavithra Vijayakumar, Vinod W Vijayaraghavan Nalini, Brigita Vilcinskaite, Alicija Vileito, Neringa Vilimiene, Lynn Vinall, 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Wallbutton, Jessica Wallen, Karl Wallendszus, Arabella Waller, Rosemary Waller, Gabiel Wallis, Gabriel Wallis, Louise Wallis, Matthew Wallis, Emma Walmsley, Donna Walsh, Elizabeth Walsh, Livia Walsh, Deborah Walstow, Daniel Walter, Alex Walters, Holt Walters, James Walters, Jocelyn Walters, Eileen Walton, Lucy Walton, Maisie Walton, Michael Walton, Olivia Walton, Sharon Walton, Susan Walton, Mandy Wan, Junita Wanda, Mary Wands, Rachel Wane, Frank Wang, Nick Wang, Ran Wang, Shentong Wang, Deborah Warbrick, Samantha Warburton, Christopher Ward, Deborah Ward, Emma Ward, Hannah Ward, Janice Ward, Joanna Ward, Luke Ward, Nicola Ward, Rachael Ward, Thomas Ward, Tom Ward, Scott A Warden, Gibril Wardere, Steve Wardle, Hassan Wardy, Gareth Waring, Scott Waring, Jenny Warmington, Ben Warner, Christian Warner, Lewis Warnock, Sarah Warran, Jade Warren, Lisa Warren, Rebecca Warren, Yolanda Warren, Davina Warrender, Hannah Warren-Miell, Adilia Warris, Gill Warwick, Helen Wassall, Sean Wasserman, Elizabeth Wasson, Hazel J Watchorn, Holly Waterfall, Abby Waters, Donald Waters, Mark Waterstone, Abigail Watkin, Catherine Watkins, Catrin Watkins, Eleanor Watkins, Karen Watkins, Lynn Watkins, Abigail Watson, Adam J R Watson, Ekaterina Watson, Eleanor Watson, Felicity Watson, J G R Watson, Louisa Watson, Paul Watson, Rebecca Watson, Robert Watson, Kathleen Watson, Malcolm Watters, Donna Watterson, Khairiah Wattimena, Daniel Watts, John Watts, Merlin Watts, Victoria Waugh, Emma Wayman, Matthew Wayman, Akhlaq Wazir, Mark Weatherhead, Nick Weatherly, Chloe Webb, Claire Webb, Hayley Webb, Kathryn Webb, Kylie Webb, Stephen Webb, Cheryl Websdale, Deborah Webster, Ian Webster, Jemma Webster, Tim Webster, Jordan Wedlin, Ling Wee, Rebecca Weerakoon, Thanuja Weerasinghe, Janaka Weeratunga, Maria Weetman, Shuying Wei, Immo Weichert, Emma Welch, Hugh Welch, James Welch, Leanne Welch, Steven Welch, Benjamin Welham, Samantha Weller, Lucy Wellings, Brian Wells, Susan Wellstead, Berni Welsh, Richard Welsh, Ingeborg Welters, Rachael Welton, Victoria Wenn, Lauren Wentworth, Joan Wesonga, Kate Wesseldine, Joe West, Magdelena West, Raha West, Ruth West, Sophie West, Luke Western, Ruth Westhead, Heather Weston, Alice Westwood, Kelly Westwood, Sharon Westwood, Bill Wetherill, Sharon Wheaver, Helen Wheeler, Ben Whelan, Matthew Whelband, Amanda Whileman, Alison Whitcher, Andrew White, Ayesha White, Benjamin White, Catherine White, Christopher White, Duncan White, James White, Jonathan White, Katie White, Marie White, Nick White, Nikki White, Sarah White, Sonia White, Tracey White, Catherine Whitehead, Kelly Whitehorn, Anne Whitehouse, Claire Whitehouse, Tony Whitehouse, Julia Whiteley, Louiza Whiteley, Sophie Whiteley, Rachael Whitham, Gabriel Whitlingum, David Whitmore, Elizabeth Whittaker, Lindsay Whittam, Ashley Whittington, Helen Whittle, Robert Whittle, Eunice Wiafe, Lou Wiblin, Olivia Wickens, John Widdrington, Jason Wieboldt, Hannah Wieringa, Cornelia Wiesender, Laura Wiffen, Andrew Wight, Ashleigh Wignall, Christopher Wignall, Annamaria Wilce, Danielle Wilcock, Emma Wilcock, Louise Wilcox, Ben Wild, Laura Wild, Stephen Wild, Michael Wilde, Laura Wilding, Peter Wilding, Tracey Wildsmith, Joe Wileman, Joy Wiles, Kate Wiles, Elva Wilhelmsen, Thomas Wiliams, Janet Wilkie, David Wilkin, Hannah Wilkins, Joy Wilkins, Suzanne Wilkins, Iain Wilkinson, Lesley Wilkinson, Nicola Wilkinson, Sophia Wilkinson, Susan Wilkinson, Tim Wilkinson, Sylvia Willetts, Aimee Williams, Alexandra Williams, Alison Williams, Angharad Williams, Anna Williams, Ava Williams, Carl Williams, Caroline V Williams, Claire Williams, Dewi Williams, Eleri Williams, Gail Williams, Gemma Williams, Gina Williams, Hannah Williams, Heledd Williams, James Williams, Jennie Williams, Jill Williams, John Williams, Joseph Williams, Karen Williams, Kathryn Williams, Mandy Williams, Marie Williams, Mark Williams, Matthew Williams, Patricia Williams, Penny Williams, Rachel Williams, Robin Williams, Rupert Williams, Samson Williams, Sarah Williams, Sophie Williams, Steffan Williams, Tamanna Williams, Tania Williams, Annie Williamson, Cath Williamson, Catherine Williamson, Dawn Williamson, James D Williamson, Jodie Williamson, Rachel Williamson, Helen Williamson, Elaine Willis, Elizabeth Willis, Emily Willis, Heather Willis, Herika Willis, Joanna Willis, Louise Wills, Lucy Willsher, Catherine Willshire, Francesca Willson, Jayne Willson, Alison Wilson, Andrea Wilson, Anna Wilson, Antoinette Wilson, Billy Wilson, David Wilson, Imogen Wilson, James Wilson, Karen Wilson, Kate Wilson, Kristy-Ann Wilson, Lucinda Wilson, Mark Wilson, Stephen Wilson, Toni Wilson, John Wilson, Khin Lei Yee Win, Marlar Win, Than Win, Tin Tin Win, Wut Yee Win Win, Lucinda Winckworth, Laura Winder, Piers Winder, Stuart Winearl, Helen Winmill, Simon Winn, Carmen Winpenny, Helen Winslow, Helen Winter, Jonathan Winter, Barbara Winter-Goodwin, Joseph Winterton, Hannah Winwood, Jack Wischhusen, Stephen Wisdom, Matthew Wise, Martin Wiselka, Rebecca Wiseman, Sophie Wiseman, Steven Wishart, Tabitha WIshlade, Eric Witele, Nicholas Withers, Janet Wittes, Donna Wixted, Therese Wodehouse, Will Wolf, Nicola Wolff, Kirsten Wolffsohn, Rebecca Wolf-Roberts, Elena Wolodimeroff, Adam Wolstencroft, Alan Wong, Charlotte Wong, Chi-Hung Wong, Chi-Man Wong, Edwin Wong, Jessica S Y Wong, Kit Y Wong, Mei Yin Wong, Nick Wong, Sam Wong, Ting Wong, Aaron B Wongkyezeng, Amanda Wood, Caroline Wood, Dianne Wood, Fiona Wood, Gordon Wood, Hannah Wood, Jennifer Wood, Joe Wood, Lisa Wood, Louise Wood, Madeleine Wood, Stephen Wood, Tracy Wood, Katharine Woodall, Rebecca Woodfield, Christopher Woodford, Elizabeth Woodford, Jill Woodford, Louise Woodhead, Timothy Woodhead, Philip Woodland, Marc Woodman, Myles Woodman, Stephen Woodmansey, Charlotte Woods, Jane Woods, Katherine Woods, Sarah Woods, Zoe Woodward, Megan Woolcock, Gemma Wooldridge, Rebecca Woolf, Chris Woollard, Christopher Woollard, Louisa Woollen, Emma Woolley, Jade Woolley, Daniel Woosey, Dan Wootton, Joanne Wootton, Daniel Worley, Stephy Worton, Jonathan Wraight, Maria Wray, Kim Wren, Lynn Wren, Caroline Wrey Brown, Catherine Wright, Demi Wright, Francesca Wright, Holly Wright, Imogen Wright, Lianne Wright, Rachel Wright, Sarah Wright, Stephanie Wright, Tim Wright, Caroline Wroe, Hannah Wroe, Henry Wu, Peishan Wu, Pensee Wu, Jonathan Wubetu, Fitria Wulandari, Retno Wulandari, Subie Wurie, Craig Wyatt, Frederick Wyn-Griffiths, Inez Wynter, Bindhu Xavier, Arnold Xhikola, Bingru E Xia, Zhongyang Xia, Effua Yacoba, Santosh Yadav, Masseh Yakubi, May Yan, Yuuki Yanagisawa, Freda Yang, Yingjia Yang, Michael Yanney, Woei Lin Yap, Nabil Yaqoob, Salima Yasmin, Bryan Yates, David Yates, Edward Yates, Helen Yates, Thomas Yates, Mark Yates, Jessica Ye, Charlotte Yearwood Martin, Khin Yein, Fiona Yelnoorkar, Lam Minh Yen, Alastair Yeoh, Chun Yu Yeung, Peter Yew, Durgesh Yewatkar, Laura Ylquimiche Melly, Inez Ynter, H Yong, Jemma Yorke, Jasmine Youens, Abdel Younes Ibrahim, Eoin Young, Gail Young, Louise Young, Asfand Yousafzar, Sajeda Youssouf, Ahmed Yousuf, Hartantri Yovita, Chrissie Yu, Jack S J Yuan, Nindya Yufaniaputri, Bernard Yung, Daniel Yusef, Said Yusef, Intekhab Yusuf, Anna-Sophia Zafar, Silvia Zagalo, Su Zaher, Aqsa Zahoor, Mahrukh Zainab, Thornton Zak, Kareem Zaki, Nabhan Zakir, Kasia Zalewska, Ane Zamalloa, Mohsin Zaman, Shakir Zaman, Julie Zamikula, Louise Zammit, Marie Zammit-Mangion, Marcelina Zawadzka, Mohammed Zayed, Esther Zebracki, Daniel Zehnder, Lisa Zeidan, Darius Zeinali, Jing Zhang, Xiaobei Zhao, Dongling Zheng, Doreen Zhu, Madiha Zia, Omar Zibdeh, Rabia Zill-E-Huma, Ei Thankt Zin, Eva Zincone, Garikai Zindoga, Eleanor Zinkin, Vivian Zinyemba, Christos Zipitis, Letizia Zitter, Arkadiusz Zmierczak, Garazi Zubikarai, Azam Zubir, Naz Zuhra, Rasha Zulaikha, Sabrina Zulfikar, Carol Zullo, Ana Zuriaga-Alvaro, University of St Andrews. Infection and Global Health Division, University of St Andrews. School of Medicine, and Group, RECOVERY Collaborative
- Subjects
Adult ,Male ,Hypoxia/etiology ,SARS-CoV-2 ,COVID-19 ,3rd-DAS ,General Medicine ,Adrenal Cortex Hormones/therapeutic use ,AC ,Dexamethasone/therapeutic use ,Hospitals ,Oxygen ,Treatment Outcome ,SDG 3 - Good Health and Well-being ,MCP ,Humans ,Female - Abstract
Background Low-dose corticosteroids have been shown to reduce mortality for patients with COVID-19 requiring oxygen or ventilatory support (non-invasive mechanical ventilation, invasive mechanical ventilation, or extracorporeal membrane oxygenation). We evaluated the use of a higher dose of corticosteroids in this patient group. Methods This randomised, controlled, open-label platform trial (Randomised Evaluation of COVID-19 Therapy [RECOVERY]) is assessing multiple possible treatments in patients hospitalised for COVID-19. Eligible and consenting adult patients with clinical evidence of hypoxia (ie, receiving oxygen or with oxygen saturation Findings Between May 25, 2021, and May 13, 2022, 1272 patients with COVID-19 and hypoxia receiving no oxygen (eight [1%]) or simple oxygen only (1264 [99%]) were randomly allocated to receive usual care plus higher dose corticosteroids (659 patients) versus usual care alone (613 patients, of whom 87% received low-dose corticosteroids during the follow-up period). Of those randomly assigned, 745 (59%) were in Asia, 512 (40%) in the UK, and 15 (1%) in Africa. 248 (19%) had diabetes and 769 (60%) were male. Overall, 123 (19%) of 659 patients allocated to higher dose corticosteroids versus 75 (12%) of 613 patients allocated to usual care died within 28 days (rate ratio 1·59 [95% CI 1·20–2·10]; p=0·0012). There was also an excess of pneumonia reported to be due to non-COVID infection (64 cases [10%] vs 37 cases [6%]; absolute difference 3·7% [95% CI 0·7–6·6]) and an increase in hyperglycaemia requiring increased insulin dose (142 [22%] vs 87 [14%]; absolute difference 7·4% [95% CI 3·2–11·5]). Interpretation In patients hospitalised for COVID-19 with clinical hypoxia who required either no oxygen or simple oxygen only, higher dose corticosteroids significantly increased the risk of death compared with usual care, which included low-dose corticosteroids. The RECOVERY trial continues to assess the effects of higher dose corticosteroids in patients hospitalised with COVID-19 who require non-invasive ventilation, invasive mechanical ventilation, or extracorporeal membrane oxygenation. Funding UK Research and Innovation (Medical Research Council), National Institute of Health and Care Research, and Wellcome Trust.
- Published
- 2023
30. Variants of the elongator protein 3 ( ELP3 ) gene are associated with motor neuron degeneration
- Author
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Simpson, Claire L, Lemmens, Robin, Miskiewicz, Katarzyna, Broom, Wendy J, Hansen, Valerie K, van Vught, Paul WJ, Landers, John E, Sapp, Peter, Van Den Bosch, Ludo, Knight, Joanne, Neale, Benjamin M, Turner, Martin R, Veldink, Jan H, Ophoff, Roel A, Tripathi, Vineeta B, Beleza, Ana, Shah, Meera N, Proitsi, Petroula, Van Hoecke, Annelies, Carmeliet, Peter, Horvitz, H Robert, Leigh, P Nigel, Shaw, Christopher E, van den Berg, Leonard H, Sham, Pak C, Powell, John F, Verstreken, Patrik, Brown, Robert H, Robberecht, Wim, and Al-Chalabi, Ammar
- Subjects
Rare Diseases ,Genetics ,Neurodegenerative ,Biotechnology ,Brain Disorders ,Neurosciences ,ALS ,2.1 Biological and endogenous factors ,Aetiology ,Neurological ,Adult ,Aged ,Aged ,80 and over ,Amyotrophic Lateral Sclerosis ,Animals ,Drosophila ,Female ,Genetic Predisposition to Disease ,Genetic Variation ,Histone Acetyltransferases ,Humans ,Male ,Mice ,Mice ,Transgenic ,Middle Aged ,Motor Neurons ,Mutation ,Nerve Tissue Proteins ,White People ,Zebrafish ,Biological Sciences ,Medical and Health Sciences ,Genetics & Heredity - Abstract
Amyotrophic lateral sclerosis (ALS) is a spontaneous, relentlessly progressive motor neuron disease, usually resulting in death from respiratory failure within 3 years. Variation in the genes SOD1 and TARDBP accounts for a small percentage of cases, and other genes have shown association in both candidate gene and genome-wide studies, but the genetic causes remain largely unknown. We have performed two independent parallel studies, both implicating the RNA polymerase II component, ELP3, in axonal biology and neuronal degeneration. In the first, an association study of 1884 microsatellite markers, allelic variants of ELP3 were associated with ALS in three human populations comprising 1483 people (P=1.96 x 10(-9)). In the second, an independent mutagenesis screen in Drosophila for genes important in neuronal communication and survival identified two different loss of function mutations, both in ELP3 (R475K and R456K). Furthermore, knock down of ELP3 protein levels using antisense morpholinos in zebrafish embryos resulted in dose-dependent motor axonal abnormalities [Pearson correlation: -0.49, P=1.83 x 10(-12) (start codon morpholino) and -0.46, P=4.05 x 10(-9) (splice-site morpholino), and in humans, risk-associated ELP3 genotypes correlated with reduced brain ELP3 expression (P=0.01). These findings add to the growing body of evidence implicating the RNA processing pathway in neurodegeneration and suggest a critical role for ELP3 in neuron biology and of ELP3 variants in ALS.
- Published
- 2009
31. Ursodeoxycholic acid in intrahepatic cholestasis of pregnancy: a systematic review and individual participant data meta-analysis
- Author
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Agata Majewska, Jessica A Marathe, Jenny Chambers, Romana Brun-Furrer, Ugo Indraccolo, Yue Cui, Stefan C. Kane, George Attilakos, Maria C. Estiú, L.F. Audris Wong, Andrew Shennan, Rachel M. Tribe, Michael J. Peek, Richard H. Lee, Keren Zloto, Jim G Thornton, Hanns-Ulrich Marschall, Tharni Vasavan, Yoav Yinon, Yannick Bacq, Caroline Ovadia, Berrin Günaydin, Xiaohua Liu, Yayi Hu, Catherine Williamson, Jūratė Kondrackienė, Ayse Gul Kebapcilar, Martijn A. Oudijk, Qianwen Zhang, Kasia Maksym, Victoria Geenes, William M. Hague, Alexander Juusela, Min Ding, Levent Kebapcilar, Valeria Tripodi, Deniz Oztekin, Kajol Patel, Rocio I.R. Macias, Nicholas A. Williamson, Christian Haslinger, Monika Grymowicz, Linoy Batsry, Fergus W. Gardiner, Naciye Turk Ozterlemez, Riza Madazli, Lucy C Chappell, Peter H. Dixon, Paul T. Seed, Anna Locatelli, Kelsey Broom, Maria P.H. Koster, Laura N. Bull, Jenna Sajous, Adam Morton, Francesco Azzaroli, Katherine Kohari, Ovadia C., Sajous J., Seed P.T., Patel K., Williamson N.J., Attilakos G., Azzaroli F., Bacq Y., Batsry L., Broom K., Brun-Furrer R., Bull L., Chambers J., Cui Y., Ding M., Dixon P.H., Estiu M.C., Gardiner F.W., Geenes V., Grymowicz M., Gunaydin B., Hague W.M., Haslinger C., Hu Y., Indraccolo U., Juusela A., Kane S.C., Kebapcilar A., Kebapcilar L., Kohari K., Kondrackiene J., Koster M.P.H., Lee R.H., Liu X., Locatelli A., Macias R.I.R., Madazli R., Majewska A., Maksym K., Marathe J.A., Morton A., Oudijk M.A., Oztekin D., Peek M.J., Shennan A.H., Tribe R.M., Tripodi V., Turk Ozterlemez N., Vasavan T., Wong L.F.A., Yinon Y., Zhang Q., Zloto K., Marschall H.-U., Thornton J., Chappell L.C., Williamson C., Obstetrics and Gynaecology, ARD - Amsterdam Reproduction and Development, Ovadia, C, Sajous, J, Seed, P, Patel, K, Williamson, N, Attilakos, G, Azzaroli, F, Bacq, Y, Batsry, L, Broom, K, Brun-Furrer, R, Bull, L, Chambers, J, Cui, Y, Ding, M, Dixon, P, Estiu, M, Gardiner, F, Geenes, V, Grymowicz, M, Gunaydin, B, Hague, W, Haslinger, C, Hu, Y, Indraccolo, U, Juusela, A, Kane, S, Kebapcilar, A, Kebapcilar, L, Kohari, K, Kondrackiene, J, Koster, M, Lee, R, Liu, X, Locatelli, A, Macias, R, Madazli, R, Majewska, A, Maksym, K, Marathe, J, Morton, A, Oudijk, M, Oztekin, D, Peek, M, Shennan, A, Tribe, R, Tripodi, V, Turk Ozterlemez, N, Vasavan, T, Wong, L, Yinon, Y, Zhang, Q, Zloto, K, Marschall, H, Thornton, J, Chappell, L, Williamson, C, Obstetrics & Gynecology, and Amsterdam Reproduction & Development (AR&D)
- Subjects
Cholagogues and Choleretics ,medicine.medical_specialty ,medicine.drug_class ,Cholestasis, Intrahepatic ,03 medical and health sciences ,0302 clinical medicine ,Cholestasis ,Pregnancy ,Internal medicine ,Cholestasis of pregnancy ,Humans ,Medicine ,Hepatology ,Bile acid ,business.industry ,Obstetrics ,Individual participant data ,Gastroenterology ,Obstetrics and Gynecology ,General Medicine ,Odds ratio ,medicine.disease ,Ursodeoxycholic acid ,Pregnancy Complications ,030220 oncology & carcinogenesis ,Meta-analysis ,Female ,030211 gastroenterology & hepatology ,stillbirth ,Ursodeoxycholic acid, pregnancy, intrahepatic cholestasis of pregnancy ,business ,medicine.drug ,Cohort study - Abstract
Background: Ursodeoxycholic acid is commonly used to treat intrahepatic cholestasis of pregnancy, yet its largest trial detected minimal benefit for a composite outcome (stillbirth, preterm birth, and neonatal unit admission). We aimed to examine whether ursodeoxycholic acid affects specific adverse perinatal outcomes. Methods: In this systematic review and individual participant data meta-analysis, we searched PubMed, Web of Science, Embase, MEDLINE, CINAHL, Global Health, MIDIRS, and Cochrane without language restrictions for relevant articles published between database inception, and Jan 1, 2020, using search terms referencing intrahepatic cholestasis of pregnancy, ursodeoxycholic acid, and perinatal outcomes. Eligible studies had 30 or more study participants and reported on at least one individual with intrahepatic cholestasis of pregnancy and bile acid concentrations of 40 μmol/L or more. We also included two unpublished cohort studies. Individual participant data were collected from the authors of selected studies. The primary outcome was the prevalence of stillbirth, for which we anticipated there would be insufficient data to achieve statistical power. Therefore, we included a composite of stillbirth and preterm birth as a main secondary outcome. A mixed-effects meta-analysis was done using multi-level modelling and adjusting for bile acid concentration, parity, and multifetal pregnancy. Individual participant data analyses were done for all studies and in different subgroups, which were produced by limiting analyses to randomised controlled trials only, singleton pregnancies only, or two-arm studies only. This study is registered with PROSPERO, CRD42019131495. Findings: The authors of the 85 studies fulfilling our inclusion criteria were contacted. Individual participant data from 6974 women in 34 studies were included in the meta-analysis, of whom 4726 (67·8%) took ursodeoxycholic acid. Stillbirth occurred in 35 (0·7%) of 5097 fetuses among women with intrahepatic cholestasis of pregnancy treated with ursodeoxycholic acid and in 12 (0·6%) of 2038 fetuses among women with intrahepatic cholestasis of pregnancy not treated with ursodeoxycholic acid (adjusted odds ratio [aOR] 1·04, 95% CI 0·35–3·07; p=0·95). Ursodeoxycholic acid treatment also had no effect on the prevalence of stillbirth when considering only randomised controlled trials (aOR 0·29, 95% CI 0·04–2·42; p=0·25). Ursodeoxycholic acid treatment had no effect on the prevalence of the composite outcome in all studies (aOR 1·28, 95% CI 0·86–1·91; p=0·22), but was associated with a reduced composite outcome when considering only randomised controlled trials (0·60, 0·39–0·91; p=0·016). Interpretation: Ursodeoxycholic acid treatment had no significant effect on the prevalence of stillbirth in women with intrahepatic cholestasis of pregnancy, but our analysis was probably limited by the low overall event rate. However, when considering only randomised controlled trials, ursodeoxycholic acid was associated with a reduction in stillbirth in combination with preterm birth, providing evidence for the clinical benefit of antenatal ursodeoxycholic acid treatment. Funding: Tommy's, the Wellcome Trust, ICP Support, and the National Institute for Health Research.
- Published
- 2021
32. Pathway for post-prostatectomy urinary incontinence: impact on patient confidence and satisfaction
- Author
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Ruth, Broom
- Subjects
Male ,Prostatectomy ,Urinary Incontinence ,Patient Satisfaction ,Incontinence Pads ,Humans ,Personal Satisfaction ,General Nursing - Abstract
Background: Between 8% and 87% of prostatectomies result in urinary incontinence, with around half of patients using incontinence pads daily at 6 months. Specialist urology continence nurses at the Norfolk and Norwich University Hospitals NHS Foundation Trust created a pre- and post-surgical care pathway formalising support for these patients, which involves the provision of TENA Men (Essity) male incontinence pads. Aims: This audit aimed to assess patient satisfaction with this pathway and TENA Men pads. Methods: Patients who underwent a radical prostatectomy at NNUH between 27 April and 9 November 2021 and who required continence pads were invited to fill out an online anonymous mixed-method (mainly qualitative) survey. Results: Of 28 respondents, 71% reported incontinence after their surgical catheter was removed. Most (89%) were satisfied with the preoperative advice. Of 19 respondents to questions on confidence and satisfaction, 16 were confident that the pads they had been prescribed were helping them to manage urinary leakage, and 16 were confident or very confident that they could manage their incontinence themselves. Generally, respondents were confident that their overall and mental health had improved, and most were confident or very confident that they had less anxiety. However, less than a quarter of respondents were ‘very confident’ about going out, meeting people or exercising. All but one respondent found TENA Men pads easy to fit, and the most used words in the free-text explanations of what they most included ‘easy’, ‘discreet’, ‘comfortable’ and ‘unobtrusive’. Conclusion: The clinical pathway helped give patients undergoing radical prostatectomy confidence in their ability to manage post-surgery incontinence themselves and could be of value in other hospitals. Easy access to incontinence pads designed for the male anatomy has an important part in this.
- Published
- 2022
33. Parental perceptions on the impact of visiting restrictions during <scp>COVID‐19</scp> in a tertiary neonatal intensive care unit
- Author
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Margaret Broom, Tim Cochrane, Debbora Cruickshank, and Hazel Carlisle
- Subjects
Parents ,Communication ,Intensive Care Units, Neonatal ,Pediatrics, Perinatology and Child Health ,Infant, Newborn ,COVID-19 ,Humans ,Infant ,Child ,Patient Discharge - Abstract
During the first wave of coronavirus disease 2019 (COVID-19), visiting guidelines in neonatal units changed to maintain the health and safety of staff, neonates, and families. In the neonatal intensive care unit/special care nursery (NICU/SCN), restrictions were placed on parental contact and extended family excluded. Our team was interested in evaluating the effect of these restrictions on parental stress and discharge confidence.A prospective descriptive study utilising survey methodology was undertaken. The survey was developed and previously used by the NICU research group to evaluate parental knowledge and understanding, parental role, communication, and parental stress (admission/discharge). We have also included a section regarding COVID19 visiting restrictions (ETH.2020.LRE.00124). The survey used a five-level Likert scale. Statistical analysis was completed using SPSS version 21.Notably, 33 surveys were returned. Results showed visiting restrictions reduced social contact between partners 26/33 (84%), with their other children 14/16 (87.5%) and extended family 28/33 (84.8%). Parents indicated that they had high levels of confidence in understanding their babies' medical needs (78-93%) and gaining hands-on experience caring for their baby (87-100%). However, 11/33 (33%) of parents reported concerns with discharge processes and gaining consistent information as challenges during their baby's admission. Notably, 17/33 (51.5) stated their NICU/SCN experience had been very to extremely stressful. Parents openly described how the restrictions had affected their mental/emotional health identifying the need to treat parents as one unit, and a gap in the psychological support available for families.Support services and consistency of communication with NICU/SCN families need to be enhanced and prioritised during periods of restrictions, especially peri-discharge.
- Published
- 2022
34. Myocarditis and Cardiac Complications Associated With COVID-19 and mRNA Vaccination: A Pragmatic Narrative Review to Guide Clinical Practice
- Author
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David J. Holland, Penni L. Blazak, Joshua Martin, Jennifer Broom, Rohan S. Poulter, and Tony Stanton
- Subjects
Pulmonary and Respiratory Medicine ,Myocarditis ,Heart Diseases ,SARS-CoV-2 ,Vaccination ,COVID-19 ,Humans ,RNA, Messenger ,Cardiology and Cardiovascular Medicine - Abstract
Coronavirus disease 2019 (COVID-19) caused by the SARS-CoV-2 virus is likely to remain endemic globally despite widespread vaccination. There is increasing concern for myocardial involvement and ensuing cardiac complications due to COVID-19, however, the available evidence suggests these risks are low. Pandemic publishing has resulted in rapid manuscript availability though pre-print servers. Subsequent article retractions, a lack of standardised definitions, over-reliance on isolated troponin elevation and the heterogeneity of studied patient groups (i.e. severe vs. symptomatic vs all infections) resulted in early concern for high rates of myocarditis in patients with and recovering from COVID-19. The estimated incidence of myocarditis in COVID-19 infection is 11 cases per 100,000 infections compared with an estimated 2.7 cases per 100,000 persons following mRNA vaccination. For substantiated cases, the clinical course of myocarditis related to COVID-19 or mRNA vaccination appears mild and self-limiting, with reports of severe/fulminant myocarditis being rare. There is limited data available on the management of myocarditis in these settings. Clinical guidance for appropriate use of cardiac investigations and monitoring in COVID-19 is needed for effective risk stratification and efficient use of cardiac resources in Australia. An amalgamation of national and international position statements and guidelines is helpful for guiding clinical practice. This paper reviews the current available evidence and guidelines and provides a summary of the risks and potential use of cardiac investigations and monitoring for patients with COVID-19.
- Published
- 2022
35. Supervised Aerobic Exercise Training and Increased Lifestyle Physical Activity to Reduce Cardiovascular Disease Risk for Women With Polycystic Ovary Syndrome: A Randomized Controlled Feasibility Trial
- Author
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Woodward, Amie, Broom, David, Dalton, Caroline, Metwally, Mostafa, and Klonizakis, Markos
- Subjects
Cardiovascular Diseases ,Feasibility Studies ,Humans ,Female ,Orthopedics and Sports Medicine ,Exercise ,Life Style ,Polycystic Ovary Syndrome - Abstract
Background: Polycystic ovary syndrome (PCOS) is a complex, heterogeneous endocrinopathy. Women with PCOS often present with cardiovascular disease risk factors. Physical activity (PA) interventions reduce cardiovascular disease risk factors in women with PCOS. However, sedentary behaviors have a distinct deleterious effect on cardiometabolic health. Increasing PA and reducing sedentary behaviors may be a worthwhile therapeutic target to improve cardiovascular health in this population. This study investigated the feasibility of 2 PA interventions to decrease cardiovascular disease risk in women with PCOS. Methods: This was a feasibility randomized controlled trial of 2 PA interventions in 36 women with PCOS. Participants were randomized to a supervised exercise intervention (n = 12), a lifestyle physical activity group intervention aimed at reducing sedentary behaviors (n = 12), or a control group (n = 12), for 12 weeks. Primary outcomes included the feasibility and acceptability of the interventions and procedures. Results: Recruitment rate was 56%. Adherence rate was 53% and 100% to the exercise intervention and lifestyle PA intervention, respectively. Secondary outcome data indicate a reduction in oxidized low-density lipoprotein concentrations in the exercise group, and weight loss in both intervention groups. Conclusions: The procedures for recruitment, allocation, and outcome measurements were acceptable. However, before progression to a full-scale trial, adherence to the exercise program should be addressed.
- Published
- 2022
36. ‘We're welcomed into people's homes every day’ versus ‘we're the people that come and arrest you’: The relational production of masculinities and vulnerabilities among male first responders
- Author
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Skaiste Linceviciute, Damien Ridge, Chantal Gautier, Alex Broom, John Oliffe, and Coral Dando
- Subjects
Male ,Masculinity ,Health (social science) ,Health Policy ,Emotions ,Emergency Responders ,Public Health, Environmental and Occupational Health ,Humans ,Workplace - Abstract
Encouraging men to open-up about their feelings is a new cultural directive, yet little is known about how this works in practice, including to promote mental health. Ideals of hegemonic masculinity may be increasingly tolerating expressions of vulnerability in some areas of social life. However, the expression of vulnerability in paid work and/or career situations is regulated by organisational ideals and circumstances that may also produce distress. To address uncertainty in the literature, we investigated the experiences of men in traditionally male dominated professions, namely first responders (police, paramedics, and firefighters/rescue). Twenty-one UK based men of diverse ranks and experience currently working within first responder services participated in semi-structured telephone interviews. Distress was positioned as an inevitable part of the work. Yet, striking differences in institutionalised ways of expressing vulnerabilities differentiated the experiences of frontline workers, contributing to a wide spectrum of men's silence right through to relative openness about vulnerability, both in the workplace and domestic spheres. The findings provide importanat insights into how vulnerability is institutionally regulated, illuminating and contrasting how the possibilities for male vulnerabilities are socially produced.
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- 2022
37. Fibroblast Growth Factor Receptor 1 Drives the Metastatic Progression of Prostate Cancer
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Nicolas Anselmino, Peter Shepherd, Michael W. Starbuck, Arul M. Chinnaiyan, Bradley M. Broom, Paul G. Corn, Nora M. Navone, Xinhai Wan, Vikas Kundra, Estefania Labanca, Christopher J Logothethis, Juan Bizzotto, Leah D Guerra, Patricia Troncoso, Jiabin Dong, Jun Yang, Geraldine Gueron, and Murali Ravoori
- Subjects
Male ,Urology ,Bone Neoplasms ,urologic and male genital diseases ,Fibroblast growth factor ,Mice ,Prostate cancer ,In vivo ,Animals ,Humans ,Medicine ,Radiology, Nuclear Medicine and imaging ,Receptor, Fibroblast Growth Factor, Type 1 ,business.industry ,Fibroblast growth factor receptor 1 ,Bone metastasis ,medicine.disease ,In vitro ,Fibroblast Growth Factors ,Prostatic Neoplasms, Castration-Resistant ,stomatognathic diseases ,Oncology ,Fibroblast growth factor receptor ,Cancer research ,Immunohistochemistry ,Surgery ,business - Abstract
No curative therapy is currently available for metastatic prostate cancer (PCa). The diverse mechanisms of progression include fibroblast growth factor (FGF) axis activation.To investigate the molecular and clinical implications of fibroblast growth factor receptor 1 (FGFR1) and its isoforms (α/β) in the pathogenesis of PCa bone metastases.In silico, in vitro, and in vivo preclinical approaches were used. RNA-sequencing and immunohistochemical (IHC) studies in human samples were conducted.In mice, bone metastases (chi-square/Fisher's test) and survival (Mantel-Cox) were assessed. In human samples, FGFR1 and ladinin 1 (LAD1) analysis associated with PCa progression were evaluated (IHC studies, Fisher's test).FGFR1 isoform expression varied among PCa subtypes. Intracardiac injection of mice with FGFR1-expressing PC3 cells reduced mouse survival (α, p 0.0001; β, p = 0.032) and increased the incidence of bone metastases (α, p 0.0001; β, p = 0.02). Accordingly, IHC studies of human castration-resistant PCa (CRPC) bone metastases revealed significant enrichment of FGFR1 expression compared with treatment-naïve, nonmetastatic primary tumors (p = 0.0007). Expression of anchoring filament protein LAD1 increased in FGFR1-expressing PC3 cells and was enriched in human CRPC bone metastases (p = 0.005).FGFR1 expression induces bone metastases experimentally and is significantly enriched in human CRPC bone metastases, supporting its prometastatic effect in PCa. LAD1 expression, found in the prometastatic PCa cells expressing FGFR1, was also enriched in CRPC bone metastases. Our studies support and provide a roadmap for the development of FGFR blockade for advanced PCa.We studied the role of fibroblast growth factor receptor 1 (FGFR1) in prostate cancer (PCa) progression. We found that PCa cells with high FGFR1 expression increase metastases and that FGFR1 expression is increased in human PCa bone metastases, and identified genes that could participate in the metastases induced by FGFR1. These studies will help pinpoint PCa patients who use fibroblast growth factor to progress and will benefit by the inhibition of this pathway.
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- 2022
38. Home-based exercise for adults with overweight or obesity: A rapid review
- Author
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Nikita Rowley, Michael Duncan, Sofie Power, David Broom, and Darren Flynn
- Subjects
Adult ,Nutrition and Dietetics ,Endocrinology, Diabetes and Metabolism ,Communicable Disease Control ,COVID-19 ,Humans ,Obesity ,Overweight ,Exercise ,Pandemics - Abstract
The COVID-19 pandemic has impacted the ability of people globally to consistently engage in their typical physical activity and exercise behaviour, contributing to the rising number of people living with overweight and obesity. The imposed government lockdowns and quarantine periods saw an increase in social media influencers delivering their own home-based exercise programmes, but these are unlikely to be an evidence-based, efficacious, long-term solution to tackle sedentary behaviour and increase physical activity. This rapid review aims to conceptualise home-based exercise and physical activity programmes, by extracting relevant programme characteristics regarding the availability of evidence and effectiveness of home-based exercise programmes. Fifteen studies met the inclusion criteria, of which there were varied reports of significant positive effects of the exercise programme on weight management and related outcomes. The two most common measures were Body Mass Index and body mass, as of which almost all reported a trend of post intervention reduction. Some programmes reported qualitative data, identifying barriers to physical activity and preferred programme components, highlighting a need to consider factors outside of physiological measures. The findings provide guidance and direction for the development of future home-based physical activity and exercise programmes for adults living with overweight and obesity.
- Published
- 2022
39. Experiencing the SARS-CoV-2 Pandemic Whilst Living With Cancer
- Author
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Alexander Page, Alex Broom, Katherine Kenny, Zarnie Lwin, Claire E Wakefield, Malinda Itchins, and Mustafa Khasraw
- Subjects
Coronavirus ,SARS-CoV-2 ,Neoplasms ,Public Health, Environmental and Occupational Health ,COVID-19 ,Humans ,Pandemics ,Telemedicine - Abstract
The SARS-CoV-2 pandemic has resulted in considerable consequences for many cancer patients, exacerbating pre-existing systemic health system limitations as well as creating new challenges. From socially distanced clinics and the widespread introduction of telehealth, to the halting of clinical trials and the reassessment of what constitutes “essential” treatment, care in oncology has abruptly changed. There is currently limited analysis of cancer patients’ experiences of the pandemic and its impacts on illness, wellness, and everyday life. Through semi-structured interviews with 54 people living with cancer during the 2020 phase of the SARS-CoV-2 pandemic in Australia, we explore how patients experience illness and care in reflecting upon a range of pandemic challenges, including delay, distance, and vulnerability. We find that in some cases, these pandemic conditions redefined the meaning of essential cancer care, reconfigured expectations around clinical trials, constructed new affective distances, and amplified dread and fear for people living with cancer.
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- 2022
40. A qualitative study of barriers to antimicrobial stewardship in Indonesian hospitals: governance, competing interests, cost, and structural vulnerability
- Author
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Ralalicia Limato, Alex Broom, Erni J. Nelwan, and Raph L. Hamers
- Subjects
Microbiology (medical) ,Antimicrobial Stewardship ,Infectious Diseases ,Indonesia ,Public Health, Environmental and Occupational Health ,Humans ,Pharmacology (medical) ,Hospitals ,Qualitative Research ,Anti-Bacterial Agents - Abstract
Background Antimicrobial resistance (AMR) is one of the leading global public health threats of the 21st Century. Antimicrobial stewardship (AMS) programmes have been shown to improve antibiotic use and clinical outcomes in high-income settings, but context-specific evidence is lacking on the value and effectiveness of current AMS programmes in low-resource settings. This study sought to explore context-specific underlying barriers to AMS implementation in Indonesian hospitals with a focus on governance practices and structural vulnerabilities. Methods We conducted semi-structured interviews with physicians, surgeons, clinical microbiologists, pharmacists, AMS team leaders, hospital managers, medical students, and national AMR stakeholders, and performed a thematic analysis. Results Based on 51 interviews conducted between January and October 2020, four main barriers to AMS implementation were evident in the participants' experiences: (1) Ineffective resourcing and institutional buy-in regarding mandatory AMS under hospital accreditation; (2) Entangled priorities to generate profits and interprofessional relationships between doctors and hospital managers or AMS leaders; (3) Cost-prohibitive bacterial culture testing and thresholds of national health insurance coverage; (4) Unreliable infrastructures, including microbiology laboratory and surgical facilities, ensuring high antibiotic usage to cover structural vulnerabilities. Conclusions Limited progress will be made with implementing AMS in Indonesian hospitals, and in settings with similar structural features, without addressing concerns around governance, competing interests, cost and structural vulnerabilities.
- Published
- 2023
41. A method for assessing sustainability, with beef production as an example
- Author
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Broom, Donald M, Broom, Donald M [0000-0002-1573-7182], and Apollo - University of Cambridge Repository
- Subjects
0106 biological sciences ,Value (ethics) ,Conservation of Natural Resources ,forage-based systems ,media_common.quotation_subject ,silvopastoral ,Animal Welfare ,010603 evolutionary biology ,01 natural sciences ,General Biochemistry, Genetics and Molecular Biology ,human-edible feed ,03 medical and health sciences ,Animal welfare ,Animals ,Humans ,Production (economics) ,Relevance (information retrieval) ,Quality (business) ,biodiversity ,030304 developmental biology ,media_common ,0303 health sciences ,Environmental economics ,land and water usage ,feedlot ,beef production ,sustainability assessment ,greenhouse gas ,Sustainability ,Land degradation ,Cattle ,Business ,General Agricultural and Biological Sciences ,Diversity (business) - Abstract
A comprehensive approach to decisions about the use of land and other world resources, taking full account of biological and other scientific information, is crucial for good decisions to be made now and in future. The sustainability of systems for producing food and other products is sometimes assessed using too narrow a range of component factors. A production system might be unsustainable because of adverse effects on a wide range of aspects of human welfare, animal welfare, or the environment. All factors should be included in sustainability evaluation, otherwise products or actions might be avoided without adequate consideration of key factors or of the diversity of production systems. A scoring method that is based on scientific information and potentially of general relevance is presented here, using beef production as a example with a review of each of its sustainability components. This includes an overall combined score and specific factors that make the system unacceptable for some consumers. The results show that, in this example, the sustainability of the best systems is very much better than that of the worst systems. By taking account of scores for a wide range of components of sustainability in comparing beef-production systems, better quality policies about beef use can be formulated than when statements referring only to one system are considered. The least sustainable beef-production systems are extensive grazing that causes land degradation and the use of feedlots or indoor housing with grain feeding. Semi-intensive silvopastoral systems are the most sustainable beef-production systems, and well-managed pasture-fed beef from areas where crop production is uneconomic is also sustainable. This simple, scientifically based scoring system could be modified to use positive as well as negative scores and is of value for policy makers, researchers, producers, organisations aiming to improve sustainability, and the general public.
- Published
- 2021
42. Safety of home-based exercise for people with intermittent claudication: A systematic review
- Author
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Alexander Waddell, Sally Seed, David R Broom, Gordon McGregor, Stefan T Birkett, and Amy E Harwood
- Subjects
Heart Diseases ,Humans ,Pain ,Walking ,Intermittent Claudication ,Cardiology and Cardiovascular Medicine ,C600 ,R1 ,Exercise Therapy - Abstract
Intermittent claudication (IC) is a classic symptom of peripheral artery disease, with first line treatment being supervised exercise therapy (SET). Despite this, SET is frequently underutilised, and adherence is often poor. An alternative option are home-based exercise programmes (HBEP). Although HBEPs are well tolerated, to the authors’ knowledge, no research has assessed their safety. The aim of this review was to assess the safety of HBEPs in people living with IC. We performed an electronic search of the MEDLINE, CINAHL, and Cochrane Library databases. The main parameter of interest was complication rate, calculated as the number of related adverse events per patient-hours. Subanalysis was undertaken to determine differences in safety for studies that did and did not include pre-exercise cardiac screening, and for studies with exercise at low, moderate, and high levels of claudication pain. Our search strategy identified 8693 results, of which 27 studies were included for full review. Studies included 1642 participants completing 147,810 patient-hours of home-based exercise. Four related adverse events were reported, three of which were cardiac in origin, giving an all-cause complication rate of one event per 36,953 patient-hours. Three of these events occurred following exercise to high levels of claudication pain, and one occurred with pain-free exercise. One event occured in a study without cardiac screening. Based on the low number of related adverse events, HBEPs appear to be a safe method of exercise prescription for people with IC. Our results strengthen the rationale for providing alternative exercise options for this population. PROSPERO Registration No.: CRD42021254581
- Published
- 2021
43. COVID-19 in patients with CLL: improved survival outcomes and update on management strategies
- Author
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Lindsey E. Roeker, Toby A. Eyre, Meghan C. Thompson, Nicole Lamanna, Alexander R. Coltoff, Matthew S. Davids, Peter O. Baker, Lori Leslie, Kerry A. Rogers, John N. Allan, Raul Cordoba, Alberto Lopez-Garcia, Darko Antic, John M. Pagel, Nicolas Martinez-Calle, José Antonio García-Marco, Jose-Ángel Hernández-Rivas, Fatima Miras, Catherine C. Coombs, Anders Österborg, Lotta Hansson, Amanda N. Seddon, Javier López Jiménez, Matthew R. Wilson, Dima El-Sharkawi, Daniel Wojenski, Shuo Ma, Talha Munir, Susana Valenciano, Erlene Seymour, Paul M. Barr, Jeffrey Pu, Piers E. M. Patten, Guilherme F. Perini, Scott F. Huntington, Helen Parry, Suchitra Sundaram, Alan Skarbnik, Manali Kamdar, Ryan Jacobs, Harriet Walter, Renata Walewska, Angus Broom, Sonia Lebowitz, Krista M. Isaac, Craig A. Portell, Inhye E. Ahn, Chaitra S. Ujjani, Mazyar Shadman, Sigrid S. Skånland, Elise A. Chong, and Anthony R. Mato
- Subjects
Adult ,Male ,medicine.medical_specialty ,2019-20 coronavirus outbreak ,Coronavirus disease 2019 (COVID-19) ,Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) ,Immunology ,MEDLINE ,Improved survival ,Antiviral Agents ,Biochemistry ,Internal medicine ,Antineoplastic Combined Chemotherapy Protocols ,medicine ,Humans ,In patient ,Aged ,Retrospective Studies ,Aged, 80 and over ,Lymphoid Neoplasia ,SARS-CoV-2 ,business.industry ,COVID-19 ,Disease Management ,Cell Biology ,Hematology ,Middle Aged ,Prognosis ,Leukemia, Lymphocytic, Chronic, B-Cell ,United States ,Survival Rate ,Drug Therapy, Combination ,Female ,business ,Follow-Up Studies - Published
- 2021
44. Impact of introducing a lactation consultant into a neonatal unit
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Margaret Broom, Mary-Ellen Youseman, and Alison L. Kent
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medicine.medical_specialty ,Lactation consultant ,Consultants ,Breastfeeding ,Aftercare ,Mothers ,Audit ,law.invention ,law ,Intensive Care Units, Neonatal ,Lactation ,medicine ,Humans ,Milk, Human ,Obstetrics ,business.industry ,Infant, Newborn ,Gestational age ,Patient Discharge ,Breast Feeding ,medicine.anatomical_structure ,Pediatrics, Perinatology and Child Health ,Female ,Chart audit ,Breast pump ,business ,Breast feeding - Abstract
AIM Benefits of mothers' own milk (MOM) for premature and sick neonates are well documented. To increase access, many neonatal units have a lactation consultant (LC) on staff. This study aimed to assess the impact of a permanent LC on (i) maternal access to LC support; (ii) staff confidence in providing Breast Feeding (BF) education and (iii) provision of MOM. METHODS Study included a staff survey and chart audit. Questions provided feedback on access to lactation support and meeting maternal needs. Audit data included: gestational age, birthweight, intention to breastfeed, documentation of LC appointment, provision of MOM at 12 hours, days 3, 7, 28 and discharge. Student's t-tests were used for numerical data and chi-squared tests for categorical variables. RESULTS Ninety-one staff surveys were returned, (pre 35/75 (47%), post 56/85 (66%) with staff reporting organising an LC appointment was significantly easier (P
- Published
- 2021
45. Post COVID‐19: a solution scan of options for preventing future zoonotic epidemics
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David C. Aldridge, Milorad Radakovic, Thomas B. White, Chinedu A Ugwu, Diogo Veríssimo, Maurizio Ferri, Alice C. Hughes, Nasir Uddin, Christian Walzer, Andrew J. Bladon, Steven Broad, George Mayes, Amy Hinsley, Fangyuan Hua, Donald M. Broom, Neil D. Burgess, Silviu O. Petrovan, Kate E. Jones, William J. Sutherland, Andrew A. Cunningham, Sarah Cleaveland, Harriet Bartlett, Moira Kelly, Hollie Booth, James L. N. Wood, Petrovan, Silviu O. [0000-0002-3984-2403], Bartlett, Harriet [0000-0002-7389-8785], Bladon, Andrew J. [0000-0002-2677-1247], Broom, Donald M. [0000-0002-1573-7182], Ferri, Maurizio [0000-0002-6185-7089], Jones, Kate [0000-0001-5231-3293], Apollo - University of Cambridge Repository, Petrovan, Silviu O [0000-0002-3984-2403], Bladon, Andrew J [0000-0002-2677-1247], and Broom, Donald M [0000-0002-1573-7182]
- Subjects
pandemic prevention ,BAT CORONAVIRUSES ,TRANSMISSION ,DATE PALM SAP ,Wildlife ,coronavirus ,Genetics and Molecular Biology ,Animals, Wild ,General Biochemistry, Genetics and Molecular Biology ,DISEASE ,SARS‐CoV‐2 ,EMERGENCE ,Zoonoses ,Pandemic ,Animals ,Humans ,Veterinary Sciences ,Environmental planning ,Pandemics ,RISK ,Transmission (medicine) ,business.industry ,SARS-CoV-2 ,Biology and Life Sciences ,COVID-19 ,zoonotic spillover ,Original Articles ,emerging infectious disease ,zoonotic risk ,WILDLIFE TRADE ,wildlife trade ,NIPAH VIRUS ,Wildlife trade ,Scale (social sciences) ,General Biochemistry ,Emerging infectious disease ,Position (finance) ,Livestock ,BIODIVERSITY ,Original Article ,Business ,General Agricultural and Biological Sciences ,AVIAN INFLUENZA - Abstract
Funder: MAVA Foundation; Id: http://dx.doi.org/10.13039/100013324, The crisis generated by the emergence and pandemic spread of COVID‐19 has thrown into the global spotlight the dangers associated with novel diseases, as well as the key role of animals, especially wild animals, as potential sources of pathogens to humans. There is a widespread demand for a new relationship with wild and domestic animals, including suggested bans on hunting, wildlife trade, wet markets or consumption of wild animals. However, such policies risk ignoring essential elements of the problem as well as alienating and increasing hardship for local communities across the world, and might be unachievable at scale. There is thus a need for a more complex package of policy and practical responses. We undertook a solution scan to identify and collate 161 possible options for reducing the risks of further epidemic disease transmission from animals to humans, including potential further SARS‐CoV‐2 transmission (original or variants). We include all categories of animals in our responses (i.e. wildlife, captive, unmanaged/feral and domestic livestock and pets) and focus on pathogens (especially viruses) that, once transmitted from animals to humans, could acquire epidemic potential through high rates of human‐to‐human transmission. This excludes measures to prevent well‐known zoonotic diseases, such as rabies, that cannot readily transmit between humans. We focused solutions on societal measures, excluding the development of vaccines and other preventive therapeutic medicine and veterinary medicine options that are discussed elsewhere. We derived our solutions through reading the scientific literature, NGO position papers, and industry guidelines, collating our own experiences, and consulting experts in different fields. Herein, we review the major zoonotic transmission pathways and present an extensive list of options. The potential solutions are organised according to the key stages of the trade chain and encompass solutions that can be applied at the local, regional and international scales. This is a set of options targeted at practitioners and policy makers to encourage careful examination of possible courses of action, validating their impact and documenting outcomes.
- Published
- 2021
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46. Role of allogeneic transplantation in chronic myelomonocytic leukemia: an international collaborative analysis
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Marie Robin, Liesbeth C. de Wreede, Eric Padron, Katerina Bakunina, Pierre Fenaux, Linda Koster, Aziz Nazha, Dietrich W. Beelen, Raajit K. Rampal, Katja Sockel, Rami S. Komrokji, Nico Gagelmann, Dirk-Jan Eikema, Aleksandar Radujkovic, Jürgen Finke, Victoria Potter, Sally B. Killick, Faezeh Legrand, Eric Solary, Angus Broom, Guillermo Garcia-Manero, Vittorio Rizzoli, Patrick Hayden, Mrinal M. Patnaik, Francesco Onida, Ibrahim Yakoub-Agha, and Raphael Itzykson
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Adult ,Male ,Adolescent ,Immunology ,Hematopoietic Stem Cell Transplantation ,Leukemia, Myelomonocytic, Chronic ,Cell Biology ,Hematology ,Middle Aged ,Biochemistry ,Young Adult ,Leukemia, Myelomonocytic, Juvenile ,Humans ,Transplantation, Homologous ,Aged ,Retrospective Studies - Abstract
To determine the survival benefit of allogeneic hematopoietic cell transplantation (allo-HCT) in chronic myelomonocytic leukemias (CMML), we assembled a retrospective cohort of CMML patients 18-70 years old diagnosed between 2000 and 2014 from an international CMML dataset (n = 730) and the EBMT registry (n = 384). The prognostic impact of allo-HCT was analyzed through univariable and multivariable time-dependent models and with a multistate model, accounting for age, sex, CMML prognostic scoring system (low or intermediate-1 grouped as lower-risk, intermediate-2 or high as higher-risk) at diagnosis, and AML transformation. In univariable analysis, lower-risk CMMLs had a 5-year overall survival (OS) of 20% with allo-HCT vs 42% without allo-HCT (P < .001). In higher-risk patients, 5-year OS was 27% with allo-HCT vs 15% without allo-HCT (P = .13). With multistate models, performing allo-HCT before AML transformation reduced OS in patients with lower-risk CMML, and a survival benefit was predicted for men with higher-risk CMML. In a multivariable analysis of lower-risk patients, performing allo-HCT before transformation to AML significantly increased the risk of death within 2 years of transplantation (hazard ratio [HR], 3.19; P < .001), with no significant change in long-term survival beyond this time point (HR, 0.98; P = .92). In higher-risk patients, allo-HCT significantly increased the risk of death in the first 2 years after transplant (HR 1.46; P = .01) but not beyond (HR, 0.60; P = .09). Performing allo-HCT before AML transformation decreases life expectancy in lower-risk patients but may be considered in higher-risk patients.
- Published
- 2022
47. Conceptualizing Qualitative Data
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Alex Broom
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Research design ,030504 nursing ,Conceptualization ,Public Health, Environmental and Occupational Health ,Qualitative property ,Development theory ,Data science ,03 medical and health sciences ,Range (mathematics) ,0302 clinical medicine ,Humans ,030212 general & internal medicine ,Sociology ,0305 other medical science ,Qualitative Research ,Qualitative research - Abstract
Qualitative research is practiced across diverse disciplines and contexts, and this produces a wide range of perspectives on the role of conceptualization and theory development. It also results in a hugely varied mix of submissions to qualitative research journals in terms of their level of conceptual elevation. This editorial explores why we conceptualize qualitative data, and some common challenges evident in current qualitative practice.
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- 2021
48. PARP and CDK4/6 Inhibitor Combination Therapy Induces Apoptosis and Suppresses Neuroendocrine Differentiation in Prostate Cancer
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Chuandong Geng, Daoqi Wang, Shan Peng, Patricia Troncoso, Courtney W. Hudgens, Sanghee Park, Carlos A. Torres-Cabala, Patrick G. Pilie, Jonathan L. Curry, Guang Yang, Paul G. Corn, Zhe Tang, Debora A. Ledesma, Cheng Wu, Timothy C. Thompson, Ganiraju C. Manyam, Bradley M. Broom, Shakuntala Kondraganti, Yungang Lu, and Mario L. Marques-Piubelli
- Subjects
Male ,Cancer Research ,Combination therapy ,Pyridines ,Aminopyridines ,Mice, Nude ,Neuroectodermal Tumors ,Apoptosis ,Palbociclib ,Neuroendocrine differentiation ,Piperazines ,Article ,Olaparib ,Mice ,chemistry.chemical_compound ,Prostate cancer ,Antineoplastic Combined Chemotherapy Protocols ,Tumor Cells, Cultured ,medicine ,Animals ,Humans ,E2F1 ,Cell Proliferation ,Cyclin-dependent kinase 1 ,Chemistry ,Cell Cycle ,Cyclin-Dependent Kinase 4 ,Prostatic Neoplasms ,Cell Differentiation ,Cyclin-Dependent Kinase 6 ,medicine.disease ,Xenograft Model Antitumor Assays ,Oncology ,Cancer research ,Phthalazines ,Benzimidazoles ,Poly(ADP-ribose) Polymerases ,biological phenomena, cell phenomena, and immunity ,Growth inhibition ,Signal Transduction - Abstract
We analyzed the efficacy and mechanistic interactions of PARP inhibition (PARPi; olaparib) and CDK4/6 inhibition (CDK4/6i; palbociclib or abemaciclib) combination therapy in castration-resistant prostate cancer (CRPC) and neuroendocrine prostate cancer (NEPC) models. We demonstrated that combined olaparib and palbociblib or abemaciclib treatment resulted in synergistic suppression of the p-Rb1–E2F1 signaling axis at the transcriptional and posttranslational levels, leading to disruption of cell-cycle progression and inhibition of E2F1 gene targets, including genes involved in DDR signaling/damage repair, antiapoptotic BCL-2 family members (BCL-2 and MCL-1), CDK1, and neuroendocrine differentiation (NED) markers in vitro and in vivo. In addition, olaparib + palbociclib or olaparib + abemaciclib combination treatment resulted in significantly greater growth inhibition and apoptosis than either single agent alone. We further showed that PARPi and CDK4/6i combination treatment–induced CDK1 inhibition suppressed p-S70-BCL-2 and increased caspase cleavage, while CDK1 overexpression effectively prevented the downregulation of p-S70-BCL-2 and largely rescued the combination treatment–induced cytotoxicity. Our study defines a novel combination treatment strategy for CRPC and NEPC and demonstrates that combination PARPi and CDK4/6i synergistically promotes suppression of the p-Rb1-E2F1 axis and E2F1 target genes, including CDK1 and NED proteins, leading to growth inhibition and increased apoptosis in vitro and in vivo. Taken together, our results provide a molecular rationale for PARPi and CDK4/6i combination therapy and reveal mechanism-based clinical trial opportunities for men with NEPC.
- Published
- 2021
49. Experiences of the SARS-CoV-2 pandemic amongst Australian Healthcare workers: From stressors to protective factors
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J. Broom, L. Williams Veazey, A. Broom, S. Hor, C. Degeling, P. Burns, M. Wyer, and G.L. Gilbert
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Microbiology (medical) ,Infection Control ,SARS-CoV-2 ,Epidemiology ,Health Personnel ,education ,Australia ,COVID-19 ,General Medicine ,1103 Clinical Sciences, 1117 Public Health and Health Services ,Protective Factors ,Article ,Coronavirus ,Infectious Diseases ,Humans ,Pandemics - Abstract
Background. The SARS-CoV-2 pandemic has critically challenged healthcare systems globally. Examining the experiences of healthcare workers (HCWs) is important for optimising ongoing and future pandemic responses. Objectives. In-depth exploration of Australian HCWs’ experiences of the SARS-CoV-2 pandemic, with a focus on reported stressors vis-à-vis protective factors. Methods. Individual interviews were performed with 63 HCWs in Australia. A range of professional streams and operational staff were included. Thematic analysis was performed. Results. Thematic analysis identified stressors centred on paucity of, or changing, evidence, leading to absence of, or mistrust in, guidelines; unprecedented alterations to the autonomy and sense of control of clinicians; and, deficiencies in communication and support. Key protective factors included: the development of clear guidance from respected clinical leaders or recognised clinical bodies, interpersonal support, and strong teamwork, leadership, and a sense of organisational preparedness. Conclusions. This study provides insights into the key organisational sources of emotional stress for HCWs within pandemic responses and describes experiences of protective factors. HCWs experiencing unprecedented uncertainty, fear, and rapid change, rely on clear communication, strong leadership, guidelines endorsed by recognised expert groups or individuals, and have increased reliance on interpersonal support. Structured strategies for leadership and communication at team, service group and organisational levels, provision of psychological support, and consideration of the potential negative effects of centralising control, would assist in ameliorating the extreme pressures of working within a pandemic environment.
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- 2021
50. 'I Was Having My Midlife Fat Crisis': Exploring the Experiences and Preferences of Home-Based Exercise Programmes for Adults Living with Overweight and Obesity
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David Broom, Nikita Rowley, Michael Duncan, and Sofie Power
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Adult ,Health, Toxicology and Mutagenesis ,home-based exercise ,obesity ,overweight ,semi-structured interviews ,Public Health, Environmental and Occupational Health ,Humans ,Obesity ,Overweight ,Exercise ,Exercise Therapy - Abstract
The involvement of people with lived experience in the design of exercise programmes is more likely to lead to a more needs-sensitive and population-specific intervention. There is limited evidence of the integration of people with lived experience, particularly regarding home-based exercise programmes for adults living with overweight and obesity, despite this being a population that would significantly benefit from a suitably tailored programme. Semi-structured interviews were virtually conducted to explore 20 participants’ experiences of exercising at home and their preferences for the design of future home-based exercise programmes. Codes were generated through thematic analysis, highlighting considerations such as comfort within a home-based environment, a desire for social connection, and the integration of technology. Four corresponding themes were generated, encapsulating participants’ choice reasoning for home-based exercise, difficulties of engaging in home-based exercise, undertaking and adhering to home-based exercise, and factors that constitute the perfect programme. Although the involvement of people with lived experience in research can be time-consuming, this process is fundamental to the design of an effective and efficacious programme. These findings will inform the design and development of a home-based exercise programme for adults living with overweight and obesity.
- Published
- 2022
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