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5 results on '"Mario Solís López"'

1. A verified genomic reference sample for assessing performance of cancer panels detecting small variants of low allele frequency

Author

Wendell Jones, Binsheng Gong, Natalia Novoradovskaya, Dan Li, Rebecca Kusko, Todd A. Richmond, Donald J. Johann, Halil Bisgin, Sayed Mohammad Ebrahim Sahraeian, Pierre R. Bushel, Mehdi Pirooznia, Katherine Wilkins, Marco Chierici, Wenjun Bao, Lee Scott Basehore, Anne Bergstrom Lucas, Daniel Burgess, Daniel J. Butler, Simon Cawley, Chia-Jung Chang, Guangchun Chen, Tao Chen, Yun-Ching Chen, Daniel J. Craig, Angela del Pozo, Jonathan Foox, Margherita Francescatto, Yutao Fu, Cesare Furlanello, Kristina Giorda, Kira P. Grist, Meijian Guan, Yingyi Hao, Scott Happe, Gunjan Hariani, Nathan Haseley, Jeff Jasper, Giuseppe Jurman, David Philip Kreil, Paweł Łabaj, Kevin Lai, Jianying Li, Quan-Zhen Li, Yulong Li, Zhiguang Li, Zhichao Liu, Mario Solís López, Kelci Miclaus, Raymond Miller, Vinay K. Mittal, Marghoob Mohiyuddin, Carlos Pabón-Peña, Barbara L. Parsons, Fujun Qiu, Andreas Scherer, Tieliu Shi, Suzy Stiegelmeyer, Chen Suo, Nikola Tom, Dong Wang, Zhining Wen, Leihong Wu, Wenzhong Xiao, Chang Xu, Ying Yu, Jiyang Zhang, Yifan Zhang, Zhihong Zhang, Yuanting Zheng, Christopher E. Mason, James C. Willey, Weida Tong, Leming Shi, and Joshua Xu

Subjects
Biology (General), QH301-705.5, Genetics, QH426-470
Abstract

Abstract Background Oncopanel genomic testing, which identifies important somatic variants, is increasingly common in medical practice and especially in clinical trials. Currently, there is a paucity of reliable genomic reference samples having a suitably large number of pre-identified variants for properly assessing oncopanel assay analytical quality and performance. The FDA-led Sequencing and Quality Control Phase 2 (SEQC2) consortium analyze ten diverse cancer cell lines individually and their pool, termed Sample A, to develop a reference sample with suitably large numbers of coding positions with known (variant) positives and negatives for properly evaluating oncopanel analytical performance. Results In reference Sample A, we identify more than 40,000 variants down to 1% allele frequency with more than 25,000 variants having less than 20% allele frequency with 1653 variants in COSMIC-related genes. This is 5–100× more than existing commercially available samples. We also identify an unprecedented number of negative positions in coding regions, allowing statistical rigor in assessing limit-of-detection, sensitivity, and precision. Over 300 loci are randomly selected and independently verified via droplet digital PCR with 100% concordance. Agilent normal reference Sample B can be admixed with Sample A to create new samples with a similar number of known variants at much lower allele frequency than what exists in Sample A natively, including known variants having allele frequency of 0.02%, a range suitable for assessing liquid biopsy panels. Conclusion These new reference samples and their admixtures provide superior capability for performing oncopanel quality control, analytical accuracy, and validation for small to large oncopanels and liquid biopsy assays.

Published
2021
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2. Cross-oncopanel study reveals high sensitivity and accuracy with overall analytical performance depending on genomic regions

Author

Binsheng Gong, Dan Li, Rebecca Kusko, Natalia Novoradovskaya, Yifan Zhang, Shangzi Wang, Carlos Pabón-Peña, Zhihong Zhang, Kevin Lai, Wanshi Cai, Jennifer S. LoCoco, Eric Lader, Todd A. Richmond, Vinay K. Mittal, Liang-Chun Liu, Donald J. Johann, James C. Willey, Pierre R. Bushel, Ying Yu, Chang Xu, Guangchun Chen, Daniel Burgess, Simon Cawley, Kristina Giorda, Nathan Haseley, Fujun Qiu, Katherine Wilkins, Hanane Arib, Claire Attwooll, Kevin Babson, Longlong Bao, Wenjun Bao, Anne Bergstrom Lucas, Hunter Best, Ambica Bhandari, Halil Bisgin, James Blackburn, Thomas M. Blomquist, Lisa Boardman, Blake Burgher, Daniel J. Butler, Chia-Jung Chang, Alka Chaubey, Tao Chen, Marco Chierici, Christopher R. Chin, Devin Close, Jeffrey Conroy, Jessica Cooley Coleman, Daniel J. Craig, Erin Crawford, Angela del Pozo, Ira W. Deveson, Daniel Duncan, Agda Karina Eterovic, Xiaohui Fan, Jonathan Foox, Cesare Furlanello, Abhisek Ghosal, Sean Glenn, Meijian Guan, Christine Haag, Xinyi Hang, Scott Happe, Brittany Hennigan, Jennifer Hipp, Huixiao Hong, Kyle Horvath, Jianhong Hu, Li-Yuan Hung, Mirna Jarosz, Jennifer Kerkhof, Benjamin Kipp, David Philip Kreil, Paweł Łabaj, Pablo Lapunzina, Peng Li, Quan-Zhen Li, Weihua Li, Zhiguang Li, Yu Liang, Shaoqing Liu, Zhichao Liu, Charles Ma, Narasimha Marella, Rubén Martín-Arenas, Dalila B. Megherbi, Qingchang Meng, Piotr A. Mieczkowski, Tom Morrison, Donna Muzny, Baitang Ning, Barbara L. Parsons, Cloud P. Paweletz, Mehdi Pirooznia, Wubin Qu, Amelia Raymond, Paul Rindler, Rebecca Ringler, Bekim Sadikovic, Andreas Scherer, Egbert Schulze, Robert Sebra, Rita Shaknovich, Qiang Shi, Tieliu Shi, Juan Carlos Silla-Castro, Melissa Smith, Mario Solís López, Ping Song, Daniel Stetson, Maya Strahl, Alan Stuart, Julianna Supplee, Philippe Szankasi, Haowen Tan, Lin-ya Tang, Yonghui Tao, Shraddha Thakkar, Danielle Thierry-Mieg, Jean Thierry-Mieg, Venkat J. Thodima, David Thomas, Boris Tichý, Nikola Tom, Elena Vallespin Garcia, Suman Verma, Kimbley Walker, Charles Wang, Junwen Wang, Yexun Wang, Zhining Wen, Valtteri Wirta, Leihong Wu, Chunlin Xiao, Wenzhong Xiao, Shibei Xu, Mary Yang, Jianming Ying, Shun H. Yip, Guangliang Zhang, Sa Zhang, Meiru Zhao, Yuanting Zheng, Xiaoyan Zhou, Christopher E. Mason, Timothy Mercer, Weida Tong, Leming Shi, Wendell Jones, and Joshua Xu

Subjects
Oncopanel sequencing, Target enrichment, Molecular diagnostics, Reproducibility, Analytical performance, Precision medicine, Biology (General), QH301-705.5, Genetics, QH426-470
Abstract

Abstract Background Targeted sequencing using oncopanels requires comprehensive assessments of accuracy and detection sensitivity to ensure analytical validity. By employing reference materials characterized by the U.S. Food and Drug Administration-led SEquence Quality Control project phase2 (SEQC2) effort, we perform a cross-platform multi-lab evaluation of eight Pan-Cancer panels to assess best practices for oncopanel sequencing. Results All panels demonstrate high sensitivity across targeted high-confidence coding regions and variant types for the variants previously verified to have variant allele frequency (VAF) in the 5–20% range. Sensitivity is reduced by utilizing VAF thresholds due to inherent variability in VAF measurements. Enforcing a VAF threshold for reporting has a positive impact on reducing false positive calls. Importantly, the false positive rate is found to be significantly higher outside the high-confidence coding regions, resulting in lower reproducibility. Thus, region restriction and VAF thresholds lead to low relative technical variability in estimating promising biomarkers and tumor mutational burden. Conclusion This comprehensive study provides actionable guidelines for oncopanel sequencing and clear evidence that supports a simplified approach to assess the analytical performance of oncopanels. It will facilitate the rapid implementation, validation, and quality control of oncopanels in clinical use.

Published
2021
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4. A verified genomic reference sample for assessing performance of cancer panels detecting small variants of low allele frequency

Author

Margherita Francescatto, Fujun Qiu, Jonathan Foox, Cesare Furlanello, Halil Bisgin, Daniel J. Craig, Chia Jung Chang, Kristina Giorda, Tao Chen, Sayed Mohammad Ebrahim Sahraeian, Yulong Li, Simon Cawley, Ying Yu, Zhihong Zhang, Yun-Ching Chen, Zhiguang Li, Dan Li, Vinay K. Mittal, Raymond Miller, Wendell D. Jones, Jianying Li, Marghoob Mohiyuddin, Zhining Wen, Rebecca Kusko, Gunjan Hariani, Yuanting Zheng, James C. Willey, Chen Suo, Todd Richmond, Wenzhong Xiao, Lee Scott Basehore, David P. Kreil, Dong Wang, Yutao Fu, Nikola Tom, Yifan Zhang, Zhichao Liu, Andreas Scherer, Carlos Pabón-Peña, Kira P. Grist, Meijian Guan, Giuseppe Jurman, Leihong Wu, Chang Xu, Katherine Wilkins, Jiyang Zhang, Anne Bergstrom Lucas, Barbara L. Parsons, Mehdi Pirooznia, Daniel Butler, Paweł P. Łabaj, Scott Happe, Marco Chierici, K. Miclaus, Suzy M. Stiegelmeyer, Daniel Burgess, Nathan Haseley, Kevin Lai, Weida Tong, Quan Zhen Li, Pierre R. Bushel, Donald J. Johann, Angela del Pozo, Yingyi Hao, Binsheng Gong, Guangchun Chen, Christopher E. Mason, Natalia Novoradovskaya, Joshua Xu, Tieliu Shi, Mario Solís López, Wenjun Bao, Leming Shi, J. Jasper, and Institute for Molecular Medicine Finland

Subjects
DNA Copy Number Variations, QH301-705.5, DATABASE, Concordance, 3122 Cancers, EXOME, Sample (statistics), Computational biology, Biology, QH426-470, Workflow, 03 medical and health sciences, Genetic Heterogeneity, 0302 clinical medicine, Gene Frequency, QUALITY-CONTROL, Cell Line, Tumor, Neoplasms, COPY NUMBER VARIATIONS, INDEL DETECTION, Genetics, Biomarkers, Tumor, Humans, Digital polymerase chain reaction, Copy-number variation, Genetic Testing, Liquid biopsy, Biology (General), Allele frequency, Exome, Alleles, 030304 developmental biology, 0303 health sciences, business.industry, Research, 1184 Genetics, developmental biology, physiology, Genetic Variation, Genomics, SOMATIC MUTATIONS, FRAMEWORK, 3. Good health, READ ALIGNMENT, 030220 oncology & carcinogenesis, DISCOVERY, Personalized medicine, ACCURATE, 3111 Biomedicine, business
Abstract

Background Oncopanel genomic testing, which identifies important somatic variants, is increasingly common in medical practice and especially in clinical trials. Currently, there is a paucity of reliable genomic reference samples having a suitably large number of pre-identified variants for properly assessing oncopanel assay analytical quality and performance. The FDA-led Sequencing and Quality Control Phase 2 (SEQC2) consortium analyze ten diverse cancer cell lines individually and their pool, termed Sample A, to develop a reference sample with suitably large numbers of coding positions with known (variant) positives and negatives for properly evaluating oncopanel analytical performance. Results In reference Sample A, we identify more than 40,000 variants down to 1% allele frequency with more than 25,000 variants having less than 20% allele frequency with 1653 variants in COSMIC-related genes. This is 5–100× more than existing commercially available samples. We also identify an unprecedented number of negative positions in coding regions, allowing statistical rigor in assessing limit-of-detection, sensitivity, and precision. Over 300 loci are randomly selected and independently verified via droplet digital PCR with 100% concordance. Agilent normal reference Sample B can be admixed with Sample A to create new samples with a similar number of known variants at much lower allele frequency than what exists in Sample A natively, including known variants having allele frequency of 0.02%, a range suitable for assessing liquid biopsy panels. Conclusion These new reference samples and their admixtures provide superior capability for performing oncopanel quality control, analytical accuracy, and validation for small to large oncopanels and liquid biopsy assays.

Published
2021

5. Loss of function BMP4 mutation supports the implication of the BMP/TGF-β pathway in the etiology of combined pituitary hormone deficiency

Author

Angel Campos-Barros, Angela del Pozo, Elena Vallespín, María Fernández-Elvira, Francisco J Rodríguez-Contreras, Karen E. Heath, Mercedes Marban-Calzon, Mario Solís-López, María Del Valle Rex-Romero, Nerea Lobato-Vidal, and Isabel González-Casado

Subjects
Male, Heterozygote, Hypopituitarism, Bone Morphogenetic Protein 4, Biology, Growth hormone deficiency, Loss of Function Mutation, Transforming Growth Factor beta, Genetics, Central hypothyroidism, medicine, Humans, Genetic Predisposition to Disease, Genetic Testing, Growth Charts, Child, E2F4, Genetics (clinical), Loss function, Genetic Association Studies, Psychomotor retardation, medicine.disease, Phenotype, Ectopic Posterior Pituitary, Cancer research, medicine.symptom, Biomarkers, Signal Transduction
Abstract

Despite BMP4 signaling being critical to Rathke's pouch induction and maintenance during early stages of pituitary development, its implication in the etiology of combined pituitary hormone deficiency (CPHD) and other clinical presentations of congenital hypopituitarism has not yet been definitely demonstrated. We report here the first CPHD patient with a de novo pathogenic loss-of-function variant in BMP4. A 6-year-old boy, with macrocephaly, myopia/astigmatism, mild psychomotor retardation, anterior pituitary hypoplasia and ectopic posterior pituitary, clinically diagnosed with growth hormone deficiency, and central hypothyroidism, was referred for genetic analysis of CPHD. Targeted NGS analysis with a custom panel (n = 310 genes) identified a novel heterozygous de novo nonsense variant, NM_001202.5:c.794G > A, p.(Trp265*) in BMP4, which introduces a premature stop codon in the BMP4 pro-domain, impairing the transcription of the TGF-β mature peptide domain. Additional relevant variants in other genes implicated in pituitary development signaling pathways such as SMAD4 and E2F4 (BMP/TGF-pathway), ALMS1 (NOTCH-pathway), and TSHZ1 (Prokineticin-pathway), were also identified. Our results support the implication of the BMP/TGF-β signaling pathway in the etiology of CPHD and suggest that oligogenic contribution of additional inherited variants may modify the phenotypic expressivity of BMP4 pathogenic variants.

Published
2018

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