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4. Weakly supervised segmentation with point annotations for histopathology images via contrast-based variational model

Author

Zhang, Hongrun, Burrows, Liam, Meng, Yanda, Sculthorpe, Declan, Mukherjee, Abhik, Coupland, Sarah E, Chen, Ke, and Zheng, Yalin

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning
Abstract

Image segmentation is a fundamental task in the field of imaging and vision. Supervised deep learning for segmentation has achieved unparalleled success when sufficient training data with annotated labels are available. However, annotation is known to be expensive to obtain, especially for histopathology images where the target regions are usually with high morphology variations and irregular shapes. Thus, weakly supervised learning with sparse annotations of points is promising to reduce the annotation workload. In this work, we propose a contrast-based variational model to generate segmentation results, which serve as reliable complementary supervision to train a deep segmentation model for histopathology images. The proposed method considers the common characteristics of target regions in histopathology images and can be trained in an end-to-end manner. It can generate more regionally consistent and smoother boundary segmentation, and is more robust to unlabeled `novel' regions. Experiments on two different histology datasets demonstrate its effectiveness and efficiency in comparison to previous models., Comment: Accepted to CVPR2023

Published
2023

7. DTFD-MIL: Double-Tier Feature Distillation Multiple Instance Learning for Histopathology Whole Slide Image Classification

Author

Zhang, Hongrun, Meng, Yanda, Zhao, Yitian, Qiao, Yihong, Yang, Xiaoyun, Coupland, Sarah E., and Zheng, Yalin

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Artificial Intelligence, Computer Science - Machine Learning
Abstract

Multiple instance learning (MIL) has been increasingly used in the classification of histopathology whole slide images (WSIs). However, MIL approaches for this specific classification problem still face unique challenges, particularly those related to small sample cohorts. In these, there are limited number of WSI slides (bags), while the resolution of a single WSI is huge, which leads to a large number of patches (instances) cropped from this slide. To address this issue, we propose to virtually enlarge the number of bags by introducing the concept of pseudo-bags, on which a double-tier MIL framework is built to effectively use the intrinsic features. Besides, we also contribute to deriving the instance probability under the framework of attention-based MIL, and utilize the derivation to help construct and analyze the proposed framework. The proposed method outperforms other latest methods on the CAMELYON-16 by substantially large margins, and is also better in performance on the TCGA lung cancer dataset. The proposed framework is ready to be extended for wider MIL applications. The code is available at: https://github.com/hrzhang1123/DTFD-MIL, Comment: Accepted to CVPR2022

Published
2022

9. The 5th edition of the World Health Organization Classification of Haematolymphoid Tumours: Lymphoid Neoplasms

Author

Alaggio, Rita, Amador, Catalina, Anagnostopoulos, Ioannis, Attygalle, Ayoma D, Araujo, Iguaracyra Barreto de Oliveira, Berti, Emilio, Bhagat, Govind, Borges, Anita Maria, Boyer, Daniel, Calaminici, Mariarita, Chadburn, Amy, Chan, John KC, Cheuk, Wah, Chng, Wee-Joo, Choi, John K, Chuang, Shih-Sung, Coupland, Sarah E, Czader, Magdalena, Dave, Sandeep S, de Jong, Daphne, Du, Ming-Qing, Elenitoba-Johnson, Kojo S, Ferry, Judith, Geyer, Julia, Gratzinger, Dita, Guitart, Joan, Gujral, Sumeet, Harris, Marian, Harrison, Christine J, Hartmann, Sylvia, Hochhaus, Andreas, Jansen, Patty M, Karube, Kennosuke, Kempf, Werner, Khoury, Joseph, Kimura, Hiroshi, Klapper, Wolfram, Kovach, Alexandra E, Kumar, Shaji, Lazar, Alexander J, Lazzi, Stefano, Leoncini, Lorenzo, Leung, Nelson, Leventaki, Vasiliki, Li, Xiao-Qiu, Lim, Megan S, Liu, Wei-Ping, Louissaint, Abner, Marcogliese, Andrea, Medeiros, L Jeffrey, Michal, Michael, Miranda, Roberto N, Mitteldorf, Christina, Montes-Moreno, Santiago, Morice, William, Nardi, Valentina, Naresh, Kikkeri N, Natkunam, Yasodha, Ng, Siok-Bian, Oschlies, Ilske, Ott, German, Parrens, Marie, Pulitzer, Melissa, Rajkumar, S Vincent, Rawstron, Andrew C, Rech, Karen, Rosenwald, Andreas, Said, Jonathan, Sarkozy, Clémentine, Sayed, Shahin, Saygin, Caner, Schuh, Anna, Sewell, William, Siebert, Reiner, Sohani, Aliyah R, Tooze, Reuben, Traverse-Glehen, Alexandra, Vega, Francisco, Vergier, Beatrice, Wechalekar, Ashutosh D, Wood, Brent, Xerri, Luc, and Xiao, Wenbin

Subjects
Cancer, Hematologic Neoplasms, Humans, Lymphoma, World Health Organization, Clinical Sciences, Oncology and Carcinogenesis, Immunology
Abstract

We herein present an overview of the upcoming 5th edition of the World Health Organization Classification of Haematolymphoid Tumours focussing on lymphoid neoplasms. Myeloid and histiocytic neoplasms will be presented in a separate accompanying article. Besides listing the entities of the classification, we highlight and explain changes from the revised 4th edition. These include reorganization of entities by a hierarchical system as is adopted throughout the 5th edition of the WHO classification of tumours of all organ systems, modification of nomenclature for some entities, revision of diagnostic criteria or subtypes, deletion of certain entities, and introduction of new entities, as well as inclusion of tumour-like lesions, mesenchymal lesions specific to lymph node and spleen, and germline predisposition syndromes associated with the lymphoid neoplasms.

Published
2022

10. The 5th edition of the World Health Organization Classification of Haematolymphoid Tumours: Myeloid and Histiocytic/Dendritic Neoplasms

Author

Khoury, Joseph D, Solary, Eric, Abla, Oussama, Akkari, Yassmine, Alaggio, Rita, Apperley, Jane F, Bejar, Rafael, Berti, Emilio, Busque, Lambert, Chan, John KC, Chen, Weina, Chen, Xueyan, Chng, Wee-Joo, Choi, John K, Colmenero, Isabel, Coupland, Sarah E, Cross, Nicholas CP, De Jong, Daphne, Elghetany, M Tarek, Takahashi, Emiko, Emile, Jean-Francois, Ferry, Judith, Fogelstrand, Linda, Fontenay, Michaela, Germing, Ulrich, Gujral, Sumeet, Haferlach, Torsten, Harrison, Claire, Hodge, Jennelle C, Hu, Shimin, Jansen, Joop H, Kanagal-Shamanna, Rashmi, Kantarjian, Hagop M, Kratz, Christian P, Li, Xiao-Qiu, Lim, Megan S, Loeb, Keith, Loghavi, Sanam, Marcogliese, Andrea, Meshinchi, Soheil, Michaels, Phillip, Naresh, Kikkeri N, Natkunam, Yasodha, Nejati, Reza, Ott, German, Padron, Eric, Patel, Keyur P, Patkar, Nikhil, Picarsic, Jennifer, Platzbecker, Uwe, Roberts, Irene, Schuh, Anna, Sewell, William, Siebert, Reiner, Tembhare, Prashant, Tyner, Jeffrey, Verstovsek, Srdan, Wang, Wei, Wood, Brent, Xiao, Wenbin, Yeung, Cecilia, and Hochhaus, Andreas

Subjects
Genetics, Human Genome, 4.1 Discovery and preclinical testing of markers and technologies, Detection, screening and diagnosis, Hematologic Neoplasms, Histiocytosis, Humans, World Health Organization, Clinical Sciences, Oncology and Carcinogenesis, Immunology
Abstract

The upcoming 5th edition of the World Health Organization (WHO) Classification of Haematolymphoid Tumours is part of an effort to hierarchically catalogue human cancers arising in various organ systems within a single relational database. This paper summarizes the new WHO classification scheme for myeloid and histiocytic/dendritic neoplasms and provides an overview of the principles and rationale underpinning changes from the prior edition. The definition and diagnosis of disease types continues to be based on multiple clinicopathologic parameters, but with refinement of diagnostic criteria and emphasis on therapeutically and/or prognostically actionable biomarkers. While a genetic basis for defining diseases is sought where possible, the classification strives to keep practical worldwide applicability in perspective. The result is an enhanced, contemporary, evidence-based classification of myeloid and histiocytic/dendritic neoplasms, rooted in molecular biology and an organizational structure that permits future scalability as new discoveries continue to inexorably inform future editions.

Published
2022

12. Correction: “The 5th edition of The World Health Organization Classification of Haematolymphoid Tumours: Lymphoid Neoplasms” Leukemia. 2022 Jul;36(7):1720–1748

Author

Alaggio, Rita, Amador, Catalina, Anagnostopoulos, Ioannis, Attygalle, Ayoma D., de Oliveira Araujo, Iguaracyra Barreto, Berti, Emilio, Bhagat, Govind, Borges, Anita Maria, Boyer, Daniel, Calaminici, Mariarita, Chadburn, Amy, Chan, John K. C., Cheuk, Wah, Chng, Wee-Joo, Choi, John K., Chuang, Shih-Sung, Coupland, Sarah E., Czader, Magdalena, Dave, Sandeep S., de Jong, Daphne, Di Napoli, Arianna, Du, Ming-Qing, Elenitoba-Johnson, Kojo S., Ferry, Judith, Geyer, Julia, Gratzinger, Dita, Guitart, Joan, Gujral, Sumeet, Harris, Marian, Harrison, Christine J., Hartmann, Sylvia, Hochhaus, Andreas, Jansen, Patty M., Karube, Kennosuke, Kempf, Werner, Khoury, Joseph, Kimura, Hiroshi, Klapper, Wolfram, Kovach, Alexandra E., Kumar, Shaji, Lazar, Alexander J., Lazzi, Stefano, Leoncini, Lorenzo, Leung, Nelson, Leventaki, Vasiliki, Li, Xiao-Qiu, Lim, Megan S., Liu, Wei-Ping, Louissaint, Jr, Abner, Marcogliese, Andrea, Medeiros, L. Jeffrey, Michal, Michael, Miranda, Roberto N., Mitteldorf, Christina, Montes-Moreno, Santiago, Morice, William, Nardi, Valentina, Naresh, Kikkeri N., Natkunam, Yasodha, Ng, Siok-Bian, Oschlies, Ilske, Ott, German, Parrens, Marie, Pulitzer, Melissa, Rajkumar, S. Vincent, Rawstron, Andrew C., Rech, Karen, Rosenwald, Andreas, Said, Jonathan, Sarkozy, Clémentine, Sayed, Shahin, Saygin, Caner, Schuh, Anna, Sewell, William, Siebert, Reiner, Sohani, Aliyah R., Suzuki, Ritsuro, Tooze, Reuben, Traverse-Glehen, Alexandra, Vega, Francisco, Vergier, Beatrice, Wechalekar, Ashutosh D., Wood, Brent, Xerri, Luc, and Xiao, Wenbin

Published
2023
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13. SF3B1 hotspot mutations confer sensitivity to PARP inhibition by eliciting a defective replication stress response

Author

Bland, Philip, Saville, Harry, Wai, Patty T., Curnow, Lucinda, Muirhead, Gareth, Nieminuszczy, Jadwiga, Ravindran, Nivedita, John, Marie Beatrix, Hedayat, Somaieh, Barker, Holly E., Wright, James, Yu, Lu, Mavrommati, Ioanna, Read, Abigail, Peck, Barrie, Allen, Mark, Gazinska, Patrycja, Pemberton, Helen N., Gulati, Aditi, Nash, Sarah, Noor, Farzana, Guppy, Naomi, Roxanis, Ioannis, Pratt, Guy, Oldreive, Ceri, Stankovic, Tatjana, Barlow, Samantha, Kalirai, Helen, Coupland, Sarah E., Broderick, Ronan, Alsafadi, Samar, Houy, Alexandre, Stern, Marc-Henri, Pettit, Stephen, Choudhary, Jyoti S., Haider, Syed, Niedzwiedz, Wojciech, Lord, Christopher J., and Natrajan, Rachael

Published
2023
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15. A Multicenter Study Validates the WHO 2022 Classification for Conjunctival Melanocytic Intraepithelial Lesions With Clinical and Prognostic Relevance

Author

Mudhar, Hardeep Singh, Krishna, Yamini, Cross, Simon, Auw-Haedrich, Claudia, Barnhill, Raymond, Cherepanoff, Svetlana, Eagle, Ralph, Farmer, James, Folberg, Robert, Grossniklaus, Hans, Herwig-Carl, Martina C., Hyrcza, Martin, Lassalle, Sandra, Loeffler, Karin U., Moulin, Alexandre, Milman, Tatyana, Verdijk, Robert M., Heegaard, Steffen, and Coupland, Sarah E.

Published
2024
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24. Integrative Analysis Identifies Four Molecular and Clinical Subsets in Uveal Melanoma

Author

Robertson, A Gordon, Shih, Juliann, Yau, Christina, Gibb, Ewan A, Oba, Junna, Mungall, Karen L, Hess, Julian M, Uzunangelov, Vladislav, Walter, Vonn, Danilova, Ludmila, Lichtenberg, Tara M, Kucherlapati, Melanie, Kimes, Patrick K, Tang, Ming, Penson, Alexander, Babur, Ozgun, Akbani, Rehan, Bristow, Christopher A, Hoadley, Katherine A, Iype, Lisa, Chang, Matthew T, Network, TCGA Research, Abdel-Rahman, Mohamed H, Ally, Adrian, Auman, J Todd, Balasundaram, Miruna, Balu, Saianand, Benz, Christopher, Beroukhim, Rameen, Birol, Inanc, Bodenheimer, Tom, Bowen, Jay, Bowlby, Reanne, Brooks, Denise, Carlsen, Rebecca, Cebulla, Colleen M, Cherniack, Andrew D, Chin, Lynda, Cho, Juok, Chuah, Eric, Chudamani, Sudha, Cibulskis, Carrie, Cibulskis, Kristian, Cope, Leslie, Coupland, Sarah E, Defreitas, Timothy, Demchok, John A, Desjardins, Laurence, Dhalla, Noreen, Esmaeli, Bita, Felau, Ina, Ferguson, Martin L, Frazer, Scott, Gabriel, Stacey B, Gastier-Foster, Julie M, Gehlenborg, Nils, Gerken, Mark, Gershenwald, Jeffrey E, Getz, Gad, Griewank, Klaus G, Grimm, Elizabeth A, Hayes, D Neil, Hegde, Apurva M, Heiman, David I, Helsel, Carmen, Hobensack, Shital, Holt, Robert A, Hoyle, Alan P, Hu, Xin, Hutter, Carolyn M, Jager, Martine J, Jefferys, Stuart R, Jones, Corbin D, Jones, Steven JM, Kandoth, Cyriac, Kasaian, Katayoon, Kim, Jaegil, Kucherlapati, Raju, Lander, Eric, Lawrence, Michael S, Lazar, Alexander J, Lee, Semin, Leraas, Kristen M, Lin, Pei, Liu, Jia, Liu, Wenbin, Lolla, Laxmi, and Lu, Yiling

Subjects
Biological Sciences, Biomedical and Clinical Sciences, Genetics, Human Genome, Rare Diseases, Eye Disease and Disorders of Vision, Cancer, Biomarkers, Tumor, DNA Copy Number Variations, DNA Methylation, Eukaryotic Initiation Factor-1, Gene Expression Regulation, Neoplastic, Humans, Melanoma, Monosomy, Mutation, Phosphoproteins, Prognosis, RNA Splicing Factors, Serine-Arginine Splicing Factors, Tumor Suppressor Proteins, Ubiquitin Thiolesterase, Uveal Neoplasms, TCGA Research Network, EIF1AX, GNA11, GNAQ, SF3B1, SRSF2, TCGA, molecular subtypes, monosomy 3, noncoding RNA, uveal melanoma, Neurosciences, Oncology and Carcinogenesis, Oncology & Carcinogenesis, Biochemistry and cell biology, Oncology and carcinogenesis
Abstract

Comprehensive multiplatform analysis of 80 uveal melanomas (UM) identifies four molecularly distinct, clinically relevant subtypes: two associated with poor-prognosis monosomy 3 (M3) and two with better-prognosis disomy 3 (D3). We show that BAP1 loss follows M3 occurrence and correlates with a global DNA methylation state that is distinct from D3-UM. Poor-prognosis M3-UM divide into subsets with divergent genomic aberrations, transcriptional features, and clinical outcomes. We report change-of-function SRSF2 mutations. Within D3-UM, EIF1AX- and SRSF2/SF3B1-mutant tumors have distinct somatic copy number alterations and DNA methylation profiles, providing insight into the biology of these low- versus intermediate-risk clinical mutation subtypes.

Published
2017

25. RasGRP3 Mediates MAPK Pathway Activation in GNAQ Mutant Uveal Melanoma

Author

Chen, Xu, Wu, Qiuxia, Depeille, Philippe, Chen, Peirong, Thornton, Sophie, Kalirai, Helen, Coupland, Sarah E, Roose, Jeroen P, and Bastian, Boris C

Subjects
Biochemistry and Cell Biology, Biological Sciences, Eye Disease and Disorders of Vision, Cancer, Rare Diseases, 2.1 Biological and endogenous factors, Animals, Cell Line, Tumor, Cell Proliferation, Diglycerides, Enzyme Activation, Extracellular Signal-Regulated MAP Kinases, GTP-Binding Protein alpha Subunits, GTP-Binding Protein alpha Subunits, Gq-G11, Guanine Nucleotide Exchange Factors, Humans, MAP Kinase Signaling System, Melanoma, Mice, Nude, Mutation, Phosphorylation, Protein Kinase C-delta, Protein Kinase C-epsilon, Protein Kinase Inhibitors, RNA Interference, Time Factors, Transfection, Tumor Burden, Uveal Neoplasms, ras Guanine Nucleotide Exchange Factors, DAG, GNA11, GNAQ, MAPK, PKC, RasGEF, RasGRP3, melanoma, uveal melanoma, Neurosciences, Oncology and Carcinogenesis, Oncology & Carcinogenesis, Biochemistry and cell biology, Oncology and carcinogenesis
Abstract

Constitutive activation of Gαq signaling by mutations in GNAQ or GNA11 occurs in over 80% of uveal melanomas (UMs) and activates MAPK. Protein kinase C (PKC) has been implicated as a link, but the mechanistic details remained unclear. We identified PKC δ and ɛ as required and sufficient to activate MAPK in GNAQ mutant melanomas. MAPK activation depends on Ras and is caused by RasGRP3, which is significantly and selectively overexpressed in response to GNAQ/11 mutation in UM. RasGRP3 activation occurs via PKC δ- and ɛ-dependent phosphorylation and PKC-independent, DAG-mediated membrane recruitment, possibly explaining the limited effect of PKC inhibitors to durably suppress MAPK in UM. The findings nominate RasGRP3 as a therapeutic target for cancers driven by oncogenic GNAQ/11.

Published
2017

27. Validation of the Newly Proposed World Health Organization Classification System for Conjunctival Melanocytic Intraepithelial Lesions: A Comparison with the C-MIN and PAM Classification Schemes

Author

Milman, Tatyana, Eiger-Moscovich, Maya, Henry, Roger K., Folberg, Robert, Coupland, Sarah E., Grossniklaus, Hans E., Mudhar, Hardeep Singh, Eberhart, Charles G., Heegaard, Steffen, Auw-Hädrich, Claudia, Herwig-Carl, Martina C., Löffler, Karin U., Cherepanoff, Svetlana, Zhang, Qiang, Sharpe, James E., See, Thonnie Rose O., Shields, Carol L., and Eagle, Ralph C., Jr.

Published
2021
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32. Conjunctival Melanoma: A Clinical Review and Update.

Author

Butt, Karam, Hussain, Rumana, Coupland, Sarah E., and Krishna, Yamini

Subjects
OCULAR tumors, IMMUNOTHERAPY, DIAGNOSTIC errors, EYE diseases, BIOTHERAPY, QUALITY of life, DELAYED diagnosis, BLINDNESS, INDIVIDUALIZED medicine, DISEASE progression, DISEASE incidence
Abstract

Simple Summary: Conjunctival melanoma (Co-M) is a rare and aggressive eye surface cancer. It is often misdiagnosed or overlooked, leading to late diagnosis. Co-M can cause sight loss and even eye loss, impacting quality-of-life. The numbers of new cases globally are rising at alarming rates. There is no standard treatment for Co-M and management varies between eye cancer centres. In ~25% of cases the cancer spreads elsewhere in the body, which can lead to death. The aim of this review is to concisely present what is currently known about Co-M presentation, its development and progression, clinical management and outcomes, and finally summarise future directions for research into novel therapies. Conjunctival melanoma (Co-M) is an aggressive, invasive eye and eyelid cancer. Its global incidence of ~1 in a million is increasing at a rate ratio of ~1.4, but this rises sharply in over 65-year-olds. Although rare, Co-M has a devastating impact on the lives of those who develop it. Co-M is often misdiagnosed or overlooked, leading to vision loss either from the destructive effects of the tumour or side effects of therapy, facial disfigurement from radical surgery, and death from metastases. Due to its rarity, there is limited evidence for diagnosis and management; hence, there is no standardised treatment and not all cases are referred to a specialised ocular oncology centre. Recent progress in cancer immunology and genetics have revolutionised the treatment of cutaneous melanomas, which share some similarities to Co-M. Importantly, a better understanding of Co-M and its precursor lesions is urgently needed to lead to the development of novel targeted and immunotherapies both for local tumour control and disseminated disease. This review aims to provide a comprehensive clinical overview of the current knowledge regarding Co-M, its epidemiology, pathogenesis, presentation, diagnosis and recent changes in the classification of its precursor lesions, management, and recent advances in novel biological therapies for personalised treatment of this disease. [ABSTRACT FROM AUTHOR]

Published
2024
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33. Lymphoma of the Lacrimal Gland — An International Multicenter Retrospective Study

Author

Vest, Stine Dahl, Mikkelsen, Lauge Hjorth, Holm, Frederik, Rasmussen, Peter Kristian, Hindso, Tine Gadegaard, Knudsen, Marina K.H., Coupland, Sarah E., Esmaeli, Bita, Finger, Paul T., Graue, Gerardo F., Grossniklaus, Hans E., Honavar, Santosh G., Mulay, Kaustubh, Sjö, Lene D., Sniegowski, Matthew C., Vemuganti, Geeta K., Thuro, Bradley A., and Heegaard, Steffen

Published
2020
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34. Ano-uro-genital mucosal melanoma UK national guidelines

Author

Smith, Henry G., Bagwan, Izhar, Board, Ruth E., Capper, Sharon, Coupland, Sarah E., Glen, Jessica, Lalondrelle, Susan, Mayberry, Antonia, Muneer, Asif, Nugent, Karen, Pathiraja, Pubudu, Payne, Miranda, Peach, Howard, Smith, Jonathan, Westwell, Sarah, Wilson, Ewan, Rodwell, Simon, Gore, Martin, Turnbull, Nancy, and Smith, Myles J.F.

Published
2020
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43. Orbital Lymphoma—An International Multicenter Retrospective Study

Author

Olsen, Tine Gadegaard, Holm, Frederik, Mikkelsen, Lauge Hjorth, Rasmussen, Peter Kristian, Coupland, Sarah E., Esmaeli, Bita, Finger, Paul T., Graue, Gerardo F., Grossniklaus, Hans E., Honavar, Santosh G., Khong, Jwu Jin, McKelvie, Penelope A., Mulay, Kaustubh, Sjö, Lene Dissing, Vemuganti, Geeta K., Thuro, Bradley A., and Heegaard, Steffen

Published
2019
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44. Cluster analysis of multiplex ligation-dependent probe amplification data in choroidal melanoma.

Author

Caines, Rhydian, Eleuteri, Antonio, Kalirai, Helen, Fisher, Anthony C, Heimann, Heinrich, Damato, Bertil E, Coupland, Sarah E, and Taktak, Azzam FG

Subjects
Chromosomes, Human, Pair 3, Chromosomes, Human, Pair 8, Humans, Melanoma, Choroid Neoplasms, Tumor Burden, Cluster Analysis, Survival Analysis, Retrospective Studies, Nucleic Acid Amplification Techniques, Sequence Deletion, Base Sequence, Principal Component Analysis, Molecular Sequence Data, Adolescent, Adult, Aged, Aged, 80 and over, Middle Aged, Female, Male, Genetic Loci, Ophthalmology & Optometry, Opthalmology and Optometry
Abstract

PurposeTo determine underlying correlations in multiplex ligation-dependent probe amplification (MLPA) data and their significance regarding survival following treatment of choroidal melanoma (CM).MethodsMLPA data were available for 31 loci across four chromosomes (1p, 3, 6, and 8) in tumor material obtained from 602 patients with CM treated at the Liverpool Ocular Oncology Center (LOOC) between 1993 and 2012. Data representing chromosomes 3 and 8q were analyzed in depth since their association with CM patient survival is well-known. Unsupervised k-means cluster analysis was performed to detect latent structure in the data set. Principal component analysis (PCA) was also performed to determine the intrinsic dimensionality of the data. Survival analyses of the identified clusters were performed using Kaplan-Meier (KM) and log-rank statistical tests. Correlation with largest basal tumor diameter (LTD) was investigated.ResultsChromosome 3: A two-cluster (bimodal) solution was found in chromosome 3, characterized by centroids at unilaterally normal probe values and unilateral deletion. There was a large, significant difference in the survival characteristics of the two clusters (log-rank, p

Published
2015

45. The 5th edition of the World Health Organization Classification of mature lymphoid and stromal tumors – an overview and update

Author

Attygalle, Ayoma D., primary, Chan, John K. C., additional, Coupland, Sarah E., additional, Du, Ming-Qing, additional, Ferry, Judith A., additional, Jong, Daphne de, additional, Gratzinger, Dita, additional, Lim, Megan S., additional, Naresh, Kikkeri N., additional, Nicolae, Alina, additional, Ott, German, additional, Rosenwald, Andreas, additional, Schuh, Anna, additional, and Siebert, Reiner, additional

Published
2024
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46. Novel Transcriptional and DNA Methylation Abnormalities of SORT1 Gene in Non-Small Cell Lung Cancer.

Author

Acha-Sagredo, Amelia, Wilson, Cornelia M., Garcia Bediaga, Naiara, Kalirai, Helen, Davies, Michael P. A., Coupland, Sarah E., Field, John K., and Liloglou, Triantafillos

Subjects
PEARSON correlation (Statistics), RESEARCH funding, POLYMERASE chain reaction, CHI-squared test, MANN Whitney U Test, TUMOR suppressor genes, GENE expression, DNA methylation, GENETIC variation, CELL lines, LOG-rank test, LUNG cancer, GENETIC mutation, SEQUENCE analysis
Abstract

Simple Summary: Sortilin is a protein with tumour-suppressor activity. Among other functions, sortilin moves around other proteins in the cell and also out of it by leading them to small vesicles termed exosomes. The aim of this study was to establish the degree of abnormal expression of the gene in non-small cell lung cancer. We show here that the alternative forms of the gene are affected both qualitatively and quantitatively. In addition, the ratio of their expression changes. We demonstrate that expression changes of the SORT1 form are due to DNA methylation of its regulatory region. As sortilin is involved in trafficking EGFR, a known target of current drugs, it is possible that these alterations, beyond their involvement in cancer development, may be predictive of the response to these therapies. Sortilin is an important regulator with potential tumour-suppressor function by limiting EGFR signalling. In this study, we undertook a comprehensive expression analysis of sortilin transcript variants and the DNA methylation status of their corresponding promoters in human non-small cell carcinomas (NSCLCs). RNA/DNA was extracted from 81 NSCLC samples and paired normal tissue. mRNA expression was measured by qPCR and DNA methylation determined by pyrosequencing. BigDye-terminator sequencing was used to confirm exon-8 alternative splicing. Results demonstrated that both SORT1A and SORT1B variants were downregulated in lung tumours. The SORT1A/SORT1B expression ratio was higher in tumours compared to normal tissue. SORT1B promoter hypermethylation was detected in lung tumours compared to normal lung (median difference 14%, Mann–Whitney test p = 10−6). Interestingly, SORT1B is hypermethylated in white blood cells, but a small and very consistent drop in methylation (6%, p = 10−15) was observed in the lung cancer cases compared to control subjects. We demonstrate that the SORT1B exon-8 splice variation, reported in sequence databases, is also a feature of SORT1A. The significantly altered quantitative and qualitative characteristics of sortilin mRNA in NSCLC indicate a significant involvement in tumour pathogenesis and may have significant impact for its utility as a predictive marker in lung cancer management. [ABSTRACT FROM AUTHOR]

Published
2024
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50. Supplementary Figure S2 from Associations between AI-Assisted Tumor Amphiregulin and Epiregulin IHC and Outcomes from Anti-EGFR Therapy in the Routine Management of Metastatic Colorectal Cancer

Author

Williams, Christopher J.M., primary, Elliott, Faye, primary, Sapanara, Nancy, primary, Aghaei, Faranak, primary, Zhang, Liping, primary, Muranyi, Andrea, primary, Yan, Dongyao, primary, Bai, Isaac, primary, Zhao, Zuo, primary, Shires, Michael, primary, Wood, Henry M., primary, Richman, Susan D., primary, Hemmings, Gemma, primary, Hale, Michael, primary, Bottomley, Daniel, primary, Galvin, Leanne, primary, Cartlidge, Caroline, primary, Dance, Sarah, primary, Bacon, Chris M., primary, Mansfield, Laura, primary, Young-Zvandasara, Kathe, primary, Sudan, Ajay, primary, Lambert, Katy, primary, Bibby, Irena, primary, Coupland, Sarah E., primary, Montazeri, Amir, primary, Kipling, Natalie, primary, Hughes, Kathryn, primary, Cross, Simon S., primary, Dewdney, Alice, primary, Pheasey, Leanne, primary, Leng, Cathryn, primary, Gochera, Tatenda, primary, Mangham, D. Chas, primary, Saunders, Mark, primary, Pritchard, Martin, primary, Stott, Helen, primary, Mukherjee, Abhik, primary, Ilyas, Mohammad, primary, Silverman, Rafael, primary, Hyland, Georgina, primary, Sculthorpe, Declan, primary, Thornton, Kirsty, primary, Gould, Imogen, primary, O'Callaghan, Ann, primary, Brown, Nicholas, primary, Turnbull, Samantha, primary, Shaw, Lisa, primary, Seymour, Matthew T., primary, West, Nicholas P., primary, Seligmann, Jenny F., primary, Singh, Shalini, primary, Shanmugam, Kandavel, primary, and Quirke, Philip, primary

Published
2023
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