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381 results on '"Cenk Sahinalp"'

1. Clonal Evolution and Heterogeneity of Osimertinib Acquired Resistance Mechanisms in EGFR Mutant Lung Cancer

Author

Nitin Roper, Anna-Leigh Brown, Jun S. Wei, Svetlana Pack, Christopher Trindade, Chul Kim, Olivia Restifo, Shaojian Gao, Sivasish Sindiri, Farid Mehrabadi, Rajaa El Meskini, Zoe Weaver Ohler, Tapan K. Maity, Abhilash Venugopalan, Constance M. Cultraro, Elizabeth Akoth, Emerson Padiernos, Haobin Chen, Aparna Kesarwala, DeeDee K. Smart, Naris Nilubol, Arun Rajan, Zofia Piotrowska, Liqiang Xi, Mark Raffeld, Anna R. Panchenko, Cenk Sahinalp, Stephen Hewitt, Chuong D. Hoang, Javed Khan, and Udayan Guha

Subjects
EGFR mutant lung cancer, non-small cell lung cancer, osimertinib, MET amplification, copy number ampplifications, neuroendocrine differentiation, Medicine (General), R5-920
Abstract

Summary: Clonal evolution of osimertinib-resistance mechanisms in EGFR mutant lung adenocarcinoma is poorly understood. Using multi-region whole-exome and RNA sequencing of prospectively collected pre- and post-osimertinib-resistant tumors, including at rapid autopsies, we identify a likely mechanism driving osimertinib resistance in all patients analyzed. The majority of patients acquire two or more resistance mechanisms either concurrently or in temporal sequence. Focal copy-number amplifications occur subclonally and are spatially and temporally separated from common resistance mutations such as EGFR C797S. MET amplification occurs in 66% (n = 6/9) of first-line osimertinib-treated patients, albeit spatially heterogeneous, often co-occurs with additional acquired focal copy-number amplifications and is associated with early progression. Noteworthy osimertinib-resistance mechanisms discovered include neuroendocrine differentiation without histologic transformation, PD-L1, KRAS amplification, and ESR1-AKAP12, MKRN1-BRAF fusions. The subclonal co-occurrence of acquired genomic alterations upon osimertinib resistance will likely require targeting multiple resistance mechanisms by combination therapies.

Published
2020
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2. PRESAGE: PRivacy-preserving gEnetic testing via SoftwAre Guard Extension

Author

Feng Chen, Chenghong Wang, Wenrui Dai, Xiaoqian Jiang, Noman Mohammed, Md Momin Al Aziz, Md Nazmus Sadat, Cenk Sahinalp, Kristin Lauter, and Shuang Wang

Subjects
SGX, Homomorphic encryption, Data outsourcing, Privacy preserving, Internal medicine, RC31-1245, Genetics, QH426-470
Abstract

Abstract Background Advances in DNA sequencing technologies have prompted a wide range of genomic applications to improve healthcare and facilitate biomedical research. However, privacy and security concerns have emerged as a challenge for utilizing cloud computing to handle sensitive genomic data. Methods We present one of the first implementations of Software Guard Extension (SGX) based securely outsourced genetic testing framework, which leverages multiple cryptographic protocols and minimal perfect hash scheme to enable efficient and secure data storage and computation outsourcing. Results We compared the performance of the proposed PRESAGE framework with the state-of-the-art homomorphic encryption scheme, as well as the plaintext implementation. The experimental results demonstrated significant performance over the homomorphic encryption methods and a small computational overhead in comparison to plaintext implementation. Conclusions The proposed PRESAGE provides an alternative solution for secure and efficient genomic data outsourcing in an untrusted cloud by using a hybrid framework that combines secure hardware and multiple crypto protocols.

Published
2017
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4. Strain level microbial detection and quantification with applications to single cell metagenomics

Author

Kaiyuan Zhu, Alejandro A. Schäffer, Welles Robinson, Junyan Xu, Eytan Ruppin, A. Funda Ergun, Yuzhen Ye, and S. Cenk Sahinalp

Subjects
Science
Abstract

Here the authors develop CAMMiQ, a combinatorial optimization approach that utilizes variable length, “unique” and “doubly-unique” genomic segments, showing improves identification and quantification of distinct microbes in metagenomic sequence data.

Published
2022
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5. Computational pharmacogenotype extraction from clinical next-generation sequencing

Author

Tyler Shugg, Reynold C. Ly, Wilberforce Osei, Elizabeth J. Rowe, Caitlin A. Granfield, Ty C. Lynnes, Elizabeth B. Medeiros, Jennelle C. Hodge, Amy M. Breman, Bryan P. Schneider, S. Cenk Sahinalp, Ibrahim Numanagić, Benjamin A. Salisbury, Steven M. Bray, Ryan Ratcliff, and Todd C. Skaar

Subjects
pharmacogenetic algorithm, next-generating sequencing, whole genome sequencing (WGS), whole exome sequencing (WES), pharmacogenomics (PGx), pharmacogenetics (PGx), Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

BackgroundNext-generation sequencing (NGS), including whole genome sequencing (WGS) and whole exome sequencing (WES), is increasingly being used for clinic care. While NGS data have the potential to be repurposed to support clinical pharmacogenomics (PGx), current computational approaches have not been widely validated using clinical data. In this study, we assessed the accuracy of the Aldy computational method to extract PGx genotypes from WGS and WES data for 14 and 13 major pharmacogenes, respectively.MethodsGermline DNA was isolated from whole blood samples collected for 264 patients seen at our institutional molecular solid tumor board. DNA was used for panel-based genotyping within our institutional Clinical Laboratory Improvement Amendments- (CLIA-) certified PGx laboratory. DNA was also sent to other CLIA-certified commercial laboratories for clinical WGS or WES. Aldy v3.3 and v4.4 were used to extract PGx genotypes from these NGS data, and results were compared to the panel-based genotyping reference standard that contained 45 star allele-defining variants within CYP2B6, CYP2C8, CYP2C9, CYP2C19, CYP2D6, CYP3A4, CYP3A5, CYP4F2, DPYD, G6PD, NUDT15, SLCO1B1, TPMT, and VKORC1.ResultsMean WGS read depth was >30x for all variant regions except for G6PD (average read depth was 29 reads), and mean WES read depth was >30x for all variant regions. For 94 patients with WGS, Aldy v3.3 diplotype calls were concordant with those from the genotyping reference standard in 99.5% of cases when excluding diplotypes with additional major star alleles not tested by targeted genotyping, ambiguous phasing, and CYP2D6 hybrid alleles. Aldy v3.3 identified 15 additional clinically actionable star alleles not covered by genotyping within CYP2B6, CYP2C19, DPYD, SLCO1B1, and NUDT15. Within the WGS cohort, Aldy v4.4 diplotype calls were concordant with those from genotyping in 99.7% of cases. When excluding patients with CYP2D6 copy number variation, all Aldy v4.4 diplotype calls except for one CYP3A4 diplotype call were concordant with genotyping for 161 patients in the WES cohort.ConclusionAldy v3.3 and v4.4 called diplotypes for major pharmacogenes from clinical WES and WGS data with >99% accuracy. These findings support the use of Aldy to repurpose clinical NGS data to inform clinical PGx.

Published
2023
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6. ImmunoTyper-SR: A Novel Computational Approach for Genotyping Immunoglobulin Heavy Chain Variable Genes Using Short Read Data.

Author

Michael Ford, Ananth Hari, Oscar Rodriguez, Junyan Xu, Justin Lack, Cihan Oguz, Yu Zhang, Sarah Weber, Mary Magliocco, Jason Barnett, Sandhya Xirasagar, Smilee Samuel, Luisa Imberti, Paolo Bonfanti, Andrea Biondi, Clifton L. Dalgard, Stephen J. Chanock, Lindsey Rosen, Steven Holland, Helen Su, Luigi Notarangelo, Uzi Vishkin, Corey Watson, and Süleyman Cenk Sahinalp

Published
2022
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15. Analyses of non-coding somatic drivers in 2,658 cancer whole genomes.

Author

Esther Rheinbay, Morten Muhlig Nielsen, Federico Abascal, Jeremiah Wala, Ofer Shapira, Grace Tiao, Henrik Hornshøj, Julian M. Hess, Randi Istrup Juul, Ziao Lin, Lars Feuerbach, Radhakrishnan Sabarinathan, Tobias Madsen, Jaegil Kim, Loris Mularoni, Shimin Shuai, Andrés Lanzós, Carl Herrmann, Yosef E. Maruvka, Ciyue Shen, Samirkumar B. Amin, Pratiti Bandopadhayay, Johanna Bertl, Keith A. Boroevich, John Busanovich, Joana Carlevaro-Fita, Dimple Chakravarty, Calvin Wing Yiu Chan, David Craft, Priyanka Dhingra, Klev Diamanti, Nuno A. Fonseca, Abel Gonzalez-Perez, Qianyun Guo, Mark P. Hamilton, Nicholas J. Haradhvala, Chen Hong, Keren Isaev, Todd A. Johnson, Malene Juul, André Kahles, Abdullah Kahraman, Youngwook Kim, Jan Komorowski, Kiran Kumar, Sushant Kumar, Donghoon Lee 0006, Kjong-Van Lehmann, Yilong Li, Eric Minwei Liu, Lucas Lochovsky, Keunchil Park, Oriol Pich, Nicola D. Roberts, Gordon Saksena, Steven E. Schumacher, Nikos Sidiropoulos, Lina Sieverling, Nasa Sinnott-Armstrong, Chip Stewart, David Tamborero, Jose M. C. Tubio, Husen M. Umer, Liis Uusküla-Reimand, Claes Wadelius, Lina Wadi, Xiaotong Yao, Cheng-Zhong Zhang, Jing Zhang 0062, James E. Haber, Asger Hobolth, Marcin Imielinski, Manolis Kellis, Michael S. Lawrence, Christian von Mering, Hidewaki Nakagawa, Benjamin J. Raphael, Mark A. Rubin, Chris Sander, Lincoln D. Stein, Joshua M. Stuart, Tatsuhiko Tsunoda, David A. Wheeler, Rory Johnson, Jüri Reimand, Mark Gerstein, Ekta Khurana, Peter J. Campbell, Núria López-Bigas, Gary D. Bader, Jonathan Barenboim, Rameen Beroukhim, Søren Brunak, Ken Chen, Jung Kyoon Choi, Jordi Deu-Pons, J. Lynn Fink, Joan Frigola, Carlo Gambacorti Passerini, Dale W. Garsed, Gad Getz, Ivo Glynne Gut, David Haan, Arif Ozgun Harmanci, Mohamed Helmy, Ermin Hodzic, José M. G. Izarzugaza, Jong K. Kim, Jan O. Korbel, Erik Larsson, Shantao Li, Xiaotong Li, Shaoke Lou, Kathleen Marchal, Iñigo Martincorena, Alexander Martínez-Fundichely, Patrick D. McGillivray, William Meyerson, Ferran Muiños, Marta Paczkowska, Kiejung Park, Jakob Skou Pedersen, Tirso Pons, Sergio Pulido-Tamayo, Iker Reyes-Salazar, Matthew A. Reyna, Carlota Rubio-Perez, Süleyman Cenk Sahinalp, Leonidas Salichos, Mark Shackleton, Raunak Shrestha, Alfonso Valencia, Miguel Vazquez, Lieven P. C. Verbeke, Jiayin Wang, Jonathan Warrell, Sebastian M. Waszak, Joachim Weischenfeldt, Guanming Wu, Jun Yu, Xuanping Zhang, Yan Zhang 0032, Zhongming Zhao, Lihua Zou, Kadir C. Akdemir, Eva G. Alvarez, Adrian Baez-Ortega, Paul C. Boutros, David D. L. Bowtell, Benedikt Brors, Kathleen H. Burns, Kin Chan, Isidro Cortés-Ciriano, Ana Dueso-Barroso, Andrew J. Dunford, Paul A. Edwards, Xavier Estivill, Dariush Etemadmoghadam, Milana Frenkel-Morgenstern, Dmitry A. Gordenin, Barbara Hutter, David T. W. Jones, Young Seok Ju, Marat D. Kazanov, Leszek J. Klimczak, Youngil Koh, Eunjung Alice Lee, Jake June-Koo Lee, Andy G. Lynch, Geoff MacIntyre, Florian Markowetz, Matthew Meyerson, Satoru Miyano, Fabio C. P. Navarro, Stephan Ossowski, Peter J. Park, John V. Pearson, Montserrat Puiggròs, Karsten Rippe, Steven A. Roberts, Bernardo Rodriguez-Martin, Ralph Scully, David Torrents, Izar Villasante, Nicola Waddell, Jeremiah A. Wala, Lixing Yang, Sung-Soo Yoon, and Jorge Zamora

Published
2020
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16. The evolutionary history of 2,658 cancers.

Author

Moritz Gerstung, Clemency Jolly, Ignaty Leshchiner, Stefan C. Dentro, Santiago Gonzalez, Thomas J. Mitchell, Yulia Rubanova, Pavana Anur, Kaixian Yu, Maxime Tarabichi, Amit G. Deshwar, Jeff Wintersinger, Kortine Kleinheinz, Ignacio Vázquez-García, Kerstin Haase, Lara Jerman, Subhajit Sengupta, Geoff MacIntyre, Salem Malikic, Nilgun Donmez, Dimitri G. Livitz, Marek Cmero, Jonas Demeulemeester, Steven E. Schumacher, Yu Fan, Xiaotong Yao, Juhee Lee, Matthias Schlesner, Paul C. Boutros, David D. L. Bowtell, Hongtu Zhu, Gad Getz, Marcin Imielinski, Rameen Beroukhim, Süleyman Cenk Sahinalp, Yuan Ji, Martin Peifer, Florian Markowetz, Ville Mustonen, Ke Yuan, Wenyi Wang 0001, Quaid D. Morris, David J. Adams, Peter J. Campbell, Shaolong Cao, Elizabeth L. Christie, Yupeng Cun, Kevin J. Dawson, Ruben M. Drews, Roland Eils, Matthew Fittall, Dale W. Garsed, Gavin Ha, Henry Lee-Six, Iñigo Martincorena, Layla Oesper, Myron Peto, Benjamin J. Raphael, Daniel T. Rosebrock, Adriana Salcedo, Ruian Shi, Seung Jun Shin, Oliver Spiro, Lincoln D. Stein, Shankar Vembu, David A. Wheeler, Tsun-Po Yang, Paul T. Spellman, David C. Wedge, and Peter Van Loo

Published
2020
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17. A multi-labeled tree dissimilarity measure for comparing 'clonal trees' of tumor progression

Author

Nikolai Karpov, Salem Malikic, Md. Khaledur Rahman, and S. Cenk Sahinalp

Subjects
Intra-tumor heterogeneity, Tumor evolution, Multi-labeled tree, Tree edit distance, Dynamic programming, Biology (General), QH301-705.5, Genetics, QH426-470
Abstract

Abstract We introduce a new dissimilarity measure between a pair of “clonal trees”, each representing the progression and mutational heterogeneity of a tumor sample, constructed by the use of single cell or bulk high throughput sequencing data. In a clonal tree, each vertex represents a specific tumor clone, and is labeled with one or more mutations in a way that each mutation is assigned to the oldest clone that harbors it. Given two clonal trees, our multi-labeled tree dissimilarity (MLTD) measure is defined as the minimum number of mutation/label deletions, (empty) leaf deletions, and vertex (clonal) expansions, applied in any order, to convert each of the two trees to the maximum common tree. We show that the MLTD measure can be computed efficiently in polynomial time and it captures the similarity between trees of different clonal granularity well.

Published
2019
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18. Author Correction: Pathway and network analysis of more than 2500 whole cancer genomes

Author

Matthew A. Reyna, David Haan, Marta Paczkowska, Lieven P. C. Verbeke, Miguel Vazquez, Abdullah Kahraman, Sergio Pulido-Tamayo, Jonathan Barenboim, Lina Wadi, Priyanka Dhingra, Raunak Shrestha, Gad Getz, Michael S. Lawrence, Jakob Skou Pedersen, Mark A. Rubin, David A. Wheeler, Søren Brunak, Jose M. G. Izarzugaza, Ekta Khurana, Kathleen Marchal, Christian von Mering, S. Cenk Sahinalp, Alfonso Valencia, PCAWG Drivers and Functional Interpretation Working Group, Jüri Reimand, Joshua M. Stuart, Benjamin J. Raphael, and PCAWG Consortium

Subjects
Science
Published
2022
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24. BAP1 haploinsufficiency predicts a distinct immunogenic class of malignant peritoneal mesothelioma

Author

Raunak Shrestha, Noushin Nabavi, Yen-Yi Lin, Fan Mo, Shawn Anderson, Stanislav Volik, Hans H. Adomat, Dong Lin, Hui Xue, Xin Dong, Robert Shukin, Robert H. Bell, Brian McConeghy, Anne Haegert, Sonal Brahmbhatt, Estelle Li, Htoo Zarni Oo, Antonio Hurtado-Coll, Ladan Fazli, Joshua Zhou, Yarrow McConnell, Andrea McCart, Andrew Lowy, Gregg B. Morin, Tianhui Chen, Mads Daugaard, S. Cenk Sahinalp, Faraz Hach, Stephane Le Bihan, Martin E. Gleave, Yuzhuo Wang, Andrew Churg, and Colin C. Collins

Subjects
Peritoneal mesothelioma, BAP1, Genomics, Tumor immunosurveillance, Precision oncology, Medicine, Genetics, QH426-470
Abstract

Abstract Background Malignant peritoneal mesothelioma (PeM) is a rare and fatal cancer that originates from the peritoneal lining of the abdomen. Standard treatment of PeM is limited to cytoreductive surgery and/or chemotherapy, and no effective targeted therapies for PeM exist. Some immune checkpoint inhibitor studies of mesothelioma have found positivity to be associated with a worse prognosis. Methods To search for novel therapeutic targets for PeM, we performed a comprehensive integrative multi-omics analysis of the genome, transcriptome, and proteome of 19 treatment-naïve PeM, and in particular, we examined BAP1 mutation and copy number status and its relationship to immune checkpoint inhibitor activation. Results We found that PeM could be divided into tumors with an inflammatory tumor microenvironment and those without and that this distinction correlated with haploinsufficiency of BAP1. To further investigate the role of BAP1, we used our recently developed cancer driver gene prioritization algorithm, HIT’nDRIVE, and observed that PeM with BAP1 haploinsufficiency form a distinct molecular subtype characterized by distinct gene expression patterns of chromatin remodeling, DNA repair pathways, and immune checkpoint receptor activation. We demonstrate that this subtype is correlated with an inflammatory tumor microenvironment and thus is a candidate for immune checkpoint blockade therapies. Conclusions Our findings reveal BAP1 to be a potential, easily trackable prognostic and predictive biomarker for PeM immunotherapy that refines PeM disease classification. BAP1 stratification may improve drug response rates in ongoing phases I and II clinical trials exploring the use of immune checkpoint blockade therapies in PeM in which BAP1 status is not considered. This integrated molecular characterization provides a comprehensive foundation for improved management of a subset of PeM patients.

Published
2019
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25. An efficient genotyper and star-allele caller for pharmacogenomics

Author

Ananth Hari, Qinghui Zhou, Nina Gonzaludo, John Harting, Stuart A. Scott, Xiang Qin, Steve Scherer, S. Cenk Sahinalp, and Ibrahim Numanagić

Subjects
Genetics, Genetics (clinical)
Abstract

High-throughput sequencing provides sufficient means for determining genotypes of clinically important pharmacogenes that can be used to tailor medical decisions to individual patients. However, pharmacogene genotyping, also known as star-allele calling, is a challenging problem that requires accurate copy number calling, structural variation identification, variant calling, and phasing within each pharmacogene copy present in the sample. Here we introduce Aldy 4, a fast and efficient tool for genotyping pharmacogenes that uses combinatorial optimization for accurate star-allele calling across different sequencing technologies. Aldy 4 adds support for long reads and uses a novel phasing model and improved copy number and variant calling models. We compare Aldy 4 against the current state-of-the-art star-allele callers on a large and diverse set of samples and genes sequenced by various sequencing technologies, such as whole-genome and targeted Illumina sequencing, barcoded 10x Genomics, and Pacific Biosciences (PacBio) HiFi. We show that Aldy 4 is the most accurate star-allele caller with near-perfect accuracy in all evaluated contexts, and hope that Aldy remains an invaluable tool in the clinical toolbox even with the advent of long-read sequencing technologies.

Published
2023
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31. ReMixT: clone-specific genomic structure estimation in cancer

Author

Andrew W. McPherson, Andrew Roth, Gavin Ha, Cedric Chauve, Adi Steif, Camila P. E. de Souza, Peter Eirew, Alexandre Bouchard-Côté, Sam Aparicio, S. Cenk Sahinalp, and Sohrab P. Shah

Subjects
Cancer genomics, DNA sequencing, Tumour heterogeneity, Genomic rearrangement, Copy number variation, Biology (General), QH301-705.5, Genetics, QH426-470
Abstract

Abstract Somatic evolution of malignant cells produces tumors composed of multiple clonal populations, distinguished in part by rearrangements and copy number changes affecting chromosomal segments. Whole genome sequencing mixes the signals of sampled populations, diluting the signals of clone-specific aberrations, and complicating estimation of clone-specific genotypes. We introduce ReMixT, a method to unmix tumor and contaminating normal signals and jointly predict mixture proportions, clone-specific segment copy number, and clone specificity of breakpoints. ReMixT is free, open-source software and is available at http://bitbucket.org/dranew/remixt .

Published
2017
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35. CYP2C8, CYP2C9, and CYP2C19 Characterization Using Next-Generation Sequencing and Haplotype Analysis

Author

Andrea Gaedigk, Erin C. Boone, Steven E. Scherer, Seung-been Lee, Ibrahim Numanagić, Cenk Sahinalp, Joshua D. Smith, Sean McGee, Aparna Radhakrishnan, Xiang Qin, Wendy Y. Wang, Emily G. Farrow, Nina Gonzaludo, Aaron L. Halpern, Deborah A. Nickerson, Neil A. Miller, Victoria M. Pratt, and Lisa V. Kalman

Subjects
Molecular Medicine, Pathology and Forensic Medicine
Published
2022
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36. Melanoma clonal subline analysis uncovers heterogeneity-driven immunotherapy resistance mechanisms

Author

Charli Gruen, Howard H. Yang, Antonella Sassano, Emily Wu, Vishaka Gopalan, Kerrie L. Marie, Andrea Castro, Farid Rashidi Mehrabadi, Chih Hao Wu, Isabella Church, Gabriel A. Needle, Cari Smith, Sung Chin, Jessica Ebersole, Christina Marcelus, Anyen Fon, Huaitian Liu, Salem Malikic, Cenk Sahinalp, Hanna Carter, Sridhar Hannenhalli, Chi-Ping Day, Maxwell P. Lee, Glenn Merlino, and Eva Pérez-Guijarro

Subjects
Article
Abstract

Intratumoral heterogeneity (ITH) can promote cancer progression and treatment failure, but the complexity of the regulatory programs and contextual factors involved complicates its study. To understand the specific contribution of ITH to immune checkpoint blockade (ICB) response, we generated single cell-derived clonal sublines from an ICB-sensitive and genetically and phenotypically heterogeneous mouse melanoma model, M4. Genomic and single cell transcriptomic analyses uncovered the diversity of the sublines and evidenced their plasticity. Moreover, a wide range of tumor growth kinetics were observedin vivo, in part associated with mutational profiles and dependent on T cell-response. Further inquiry into melanoma differentiation states and tumor microenvironment (TME) subtypes of untreated tumors from the clonal sublines demonstrated correlations between highly inflamed and differentiated phenotypes with the response to anti-CTLA-4 treatment. Our results demonstrate that M4 sublines generate intratumoral heterogeneity at both levels of intrinsic differentiation status and extrinsic TME profiles, thereby impacting tumor evolution during therapeutic treatment. These clonal sublines proved to be a valuable resource to study the complex determinants of response to ICB, and specifically the role of melanoma plasticity in immune evasion mechanisms.

Published
2023
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43. Data from Mutational Analysis of Gene Fusions Predicts Novel MHC Class I–Restricted T-Cell Epitopes and Immune Signatures in a Subset of Prostate Cancer

Author

Julian J. Lum, Faraz Hach, Colin C. Collins, S. Cenk Sahinalp, Emma M.H. Loy, Alexandra P. Comber, Phineas T. Hamilton, Yen-Yi Lin, David S. Neilson, and Jennifer L. Kalina

Abstract

Purpose: Gene fusions are frequently found in prostate cancer and may result in the formation of unique chimeric amino acid sequences (CASQ) that span the breakpoint of two fused gene products. This study evaluated the potential for fusion-derived CASQs to be a source of tumor neoepitopes, and determined their relationship to patterns of immune signatures in prostate cancer patients.Experimental Design: A computational strategy was used to identify CASQs and their corresponding predicted MHC class I epitopes using RNA-Seq data from The Cancer Genome Atlas of prostate tumors. In vitro peptide-specific T-cell expansion was performed to identify CASQ-reactive T cells. A multivariate analysis was used to relate patterns of in silico–predicted tumor-infiltrating immune cells with prostate tumors harboring these mutational events.Results: Eighty-seven percent of tumors contained gene fusions with a mean of 12 per tumor. In total, 41% of fusion-positive tumors were found to encode CASQs. Within these tumors, 87% gave rise to predicted MHC class I–binding epitopes. This observation was more prominent when patients were stratified into low- and intermediate/high-risk categories. One of the identified CASQ from the recurrent TMPRSS2:ERG type VI fusion contained several high-affinity HLA-restricted epitopes. These peptides bound HLA-A*02:01 in vitro and were recognized by CD8+ T cells. Finally, the presence of fusions and CASQs were associated with expression of immune cell infiltration.Conclusions: Mutanome analysis of gene fusion-derived CASQs can give rise to patient-specific predicted neoepitopes. Moreover, these fusions predicted patterns of immune cell infiltration within a subgroup of prostate cancer patients. Clin Cancer Res; 23(24); 7596–607. ©2017 AACR.

Published
2023
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