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Dive into the research topics where Gregory Gydush is active.

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Featured researches published by Gregory Gydush.


Nature Communications | 2017

Scalable whole-exome sequencing of cell-free DNA reveals high concordance with metastatic tumors

Viktor A. Adalsteinsson; Gavin Ha; Samuel S. Freeman; Atish D. Choudhury; Daniel G. Stover; Heather A. Parsons; Gregory Gydush; Sarah C. Reed; Denisse Rotem; Justin Rhoades; Denis Loginov; Dimitri Livitz; Daniel Rosebrock; Ignaty Leshchiner; Jaegil Kim; Chip Stewart; Mara Rosenberg; Joshua M. Francis; Cheng-Zhong Zhang; Ofir Cohen; Coyin Oh; Huiming Ding; Paz Polak; Max Lloyd; Sairah Mahmud; Karla Helvie; Margaret S. Merrill; Rebecca A. Santiago; Edward P. O’Connor; Seong Ho Jeong

Whole-exome sequencing of cell-free DNA (cfDNA) could enable comprehensive profiling of tumors from blood but the genome-wide concordance between cfDNA and tumor biopsies is uncertain. Here we report ichorCNA, software that quantifies tumor content in cfDNA from 0.1× coverage whole-genome sequencing data without prior knowledge of tumor mutations. We apply ichorCNA to 1439 blood samples from 520 patients with metastatic prostate or breast cancers. In the earliest tested sample for each patient, 34% of patients have ≥10% tumor-derived cfDNA, sufficient for standard coverage whole-exome sequencing. Using whole-exome sequencing, we validate the concordance of clonal somatic mutations (88%), copy number alterations (80%), mutational signatures, and neoantigens between cfDNA and matched tumor biopsies from 41 patients with ≥10% cfDNA tumor content. In summary, we provide methods to identify patients eligible for comprehensive cfDNA profiling, revealing its applicability to many patients, and demonstrate high concordance of cfDNA and metastatic tumor whole-exome sequencing.Identifying the mutational landscape of tumours from cell-free DNA in the blood could help diagnostics in cancer. Here, the authors present ichorCNA, software that quantifies tumour content in cell free DNA, and they demonstrate that cell-free DNA whole-exome sequencing is concordant with metastatic tumour whole-exome sequencing.


Cell | 2018

Structural Alterations Driving Castration-Resistant Prostate Cancer Revealed by Linked-Read Genome Sequencing

Srinivas R. Viswanathan; Gavin Ha; Andreas M. Hoff; Jeremiah Wala; Jian Carrot-Zhang; Christopher W. Whelan; Nicholas J. Haradhvala; Samuel S. Freeman; Sarah C. Reed; Justin Rhoades; Paz Polak; Michelle Cipicchio; Stephanie A. Wankowicz; Alicia Wong; Tushar Kamath; Zhenwei Zhang; Gregory Gydush; Denisse Rotem; J. Christopher Love; Gad Getz; Stacey Gabriel; Cheng-Zhong Zhang; Scott M. Dehm; Peter S. Nelson; Eliezer M. Van Allen; Atish D. Choudhury; Viktor A. Adalsteinsson; Rameen Beroukhim; Mary-Ellen Taplin; Matthew Meyerson

Nearly all prostate cancer deaths are from metastatic castration-resistant prostate cancer (mCRPC), but there have been few whole-genome sequencing (WGS) studies of this disease state. We performed linked-read WGS on 23 mCRPC biopsy specimens and analyzed cell-free DNA sequencing data from 86 patients with mCRPC. In addition to frequent rearrangements affecting known prostate cancer genes, we observed complex rearrangements of the AR locus in most cases. Unexpectedly, these rearrangements include highly recurrent tandem duplications involving an upstream enhancer of AR in 70%-87% of cases compared with <2% of primary prostate cancers. A subset of cases displayed AR or MYC enhancer duplication in the context of a genome-wide tandem duplicator phenotype associated with CDK12 inactivation. Our findings highlight the complex genomic structure of mCRPC, nominate alterations that may inform prostate cancer treatment, and suggest that additional recurrent events in the non-coding mCRPC genome remain to be discovered.


Nature Communications | 2018

Whole-exome sequencing of cell-free DNA and circulating tumor cells in multiple myeloma

Salomon Manier; Jang-Ung Park; Marzia Capelletti; Mark Bustoros; Sam Freeman; Gavin Ha; Justin Rhoades; Chia-Jen Liu; Daisy Huynh; Sarah C. Reed; Gregory Gydush; Karma Salem; Denisse Rotem; C. Freymond; Amir Yosef; Adriana Perilla-Glen; Laurent Garderet; E. Van Allen; Shaji Kumar; J. C. Love; Gad Getz; Viktor A. Adalsteinsson; Irene M. Ghobrial

Liquid biopsies including circulating tumor cells (CTCs) and cell-free DNA (cfDNA) have enabled minimally invasive characterization of many cancers, but are rarely analyzed together. Understanding the detectability and genomic concordance of CTCs and cfDNA may inform their use in guiding cancer precision medicine. Here, we report the detectability of cfDNA and CTCs in blood samples from 107 and 56 patients with multiple myeloma (MM), respectively. Using ultra-low pass whole-genome sequencing, we find both tumor fractions correlate with disease progression. Applying whole-exome sequencing (WES) to cfDNA, CTCs, and matched tumor biopsies, we find concordance in clonal somatic mutations (~99%) and copy number alterations (~81%) between liquid and tumor biopsies. Importantly, analyzing CTCs and cfDNA together enables cross-validation of mutations, uncovers mutations exclusive to either CTCs or cfDNA, and allows blood-based tumor profiling in a greater fraction of patients. Our study demonstrates the utility of analyzing both CTCs and cfDNA in MM.Circulating tumor cells (CTCs) and cell-free DNA (cfDNA) enables characterization of a patient’s cancer. Here, the authors analyse CTCs, cfDNA, and tumor biopsies from multiple myeloma patients to show these approaches are complementary for mutation detection, together enabling a greater fraction of patient tumors to be profiled.


Cancer Research | 2017

Abstract 5689: Identify tissue-of-origin in cancer cfDNA by whole genome sequencing

Yaping Liu; Sarah C. Reed; Atish D. Choudhury; Heather A. Parsons; Daniel G. Stover; Gavin Ha; Gregory Gydush; Justin Rhoades; Denisse Rotem; Samuel S. Freeman; Viktor A. Adalsteinsson; Manolis Kellis

Cell free DNA (cfDNA) has been shown to be an emerging non-invasive biomarker to monitor tumor progression in cancer patients. Elevated cfDNA has been found not only from tumors, but also from normal tissues. Thus, the identification of cfDNA’s tissue-of-origin is critical to understand the mechanism of cfDNA release and tumor progression. Recent efforts to identify cfDNA’s tissue-of-origin begin to utilize cfDNA’s epigenomic status, such as DNA methylation and nucleosome spacing. However, both of these methods have limitations: (1) For nucleosome positioning, lack of reference nucleosome maps in different tumor and normal tissues has limited its application to tissue-of-origin deconvolution; (2) For DNA methylation, large DNA degradation during whole genome bisulfite sequencing (WGBS) library preparation, even with current low-input DNA technology, is still the major hurdle for its clinical application, although extensive DNA methylation studies by WGBS in tumor and normal tissues during the last decade have provided many reference maps. Very recently, a pioneer study showed significant differences between DNA fragment lengths of methylated and unmethylated cfDNA. Taking advantage of this experimental observation, we developed a machine learning approach to infer the base pair resolution DNA methylation level from fragment size information in whole genome sequencing (WGS). The predicted DNA methylation, from not only high coverage but also dozens of ultra-low-pass WGS (ULP-WGS), showed high concordance with the ground truth DNA methylation level from WGBS in the same cancer patients. Furthermore, by using hundreds of WGBS datasets from different tumor and normal tissues/cells as the reference map, we deconvoluted cfDNA’s tissue-of-origin status by inferred DNA methylation level at ULP-WGS from thousands of breast/prostate cancer samples and healthy individuals. The cfDNA’s tissue-of-origin status in cancer patients showed high concordance with confirmed metastasis tissues from physicians. Interestingly, some clinical information, such as cancer grades/stages, seemed to be correlated with cfDNA’s tissue-of-origin status. Overall, our methods here pave the road for cfDNA’s application in clinical diagnosis and monitoring. Citation Format: Yaping Liu, Sarah Reed, Atish D. Choudhury, Heather A. Parsons, Daniel G. Stover, Gavin Ha, Gregory Gydush, Justin Rhoades, Denisse Rotem, Samuel Freeman, Viktor Adalsteinsson, Manolis Kellis. Identify tissue-of-origin in cancer cfDNA by whole genome sequencing [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 5689. doi:10.1158/1538-7445.AM2017-5689


Cancer Research | 2016

Abstract LB-136: High concordance of whole-exome sequencing of cell-free DNA and matched biopsies enables genomic discovery in metastatic cancer

Viktor A. Adalsteinsson; Gavin Ha; Sam Freeman; Atish D. Choudhury; Daniel G. Stover; Heather A. Parsons; Gregory Gydush; Sarah C. Reed; Denis Loginov; Dimitri Livitz; Daniel Rosebrock; Ignat Leshchiner; Ofir Cohen; Coyin Oh; Jaegil Kim; Chip Stewart; Mara Rosenberg; Huiming Ding; M Lloyd; Sairah Mahmud; Karla Helvie; Margaret S. Merrill; Rebecca A. Santiago; Edward P. O’Connor; Seong Ho Jeong; Joseph F. Kramkowski; Jens Lohr; Laura Polacek; Nelly Oliver; Lori Marini

Background: Circulating cell-free DNA (cfDNA) has largely been used to monitor blood for specific tumor mutations, but genome-wide discovery from cfDNA has not been well established. Here, we establish a scalable approach for whole-exome sequencing (WES) of cfDNA, making it possible to perform comprehensive genomic characterization of metastatic cancer in a routine and minimally-invasive manner. Comprehensive genomic characterization of metastatic cancer stands to uncover novel alterations of clinical significance. A major challenge is that metastatic tumors are infrequently biopsied. Cell-free DNA is shed abundantly into the bloodstream from metastatic tumors, presenting an opportunity for genomic discovery in advanced cancers that are rarely biopsied in routine clinical care. We report an efficient process to qualify and sequence whole-exomes from cfDNA at scale and systematically compare the somatic mutations, indels, and copy number alterations detected in WES of cfDNA to WES of matched tumor biopsies. Methods: We consented 86 patients with metastatic breast or prostate cancers for blood collection. We isolated cfDNA and germline DNA from blood and performed low coverage sequencing to estimate tumor content based on genome-wide copy number. We screened patient blood samples and prioritized those with higher tumor fractions for WES. In parallel, we analyzed cfDNA and germline DNA from healthy donors to calibrate our methods and assess false positive rate for genomic alterations. Results: We found the vast majority of patients with metastatic prostate or breast cancer to have detectable tumor-derived cfDNA. WES of cfDNA from healthy donors revealed very low false positive rates for somatic mutations, indels and copy number alterations (SCNAs). By analyzing WES of cfDNA and tumor biopsies from dozens of patients with metastatic breast or prostate cancers, we established guidelines for the coverage and tumor fraction required for mutation discovery in WES of cfDNA. We found WES of cfDNA to uncover 91% of the clonal mutations, 59% of the subclonal mutations, and 75% of the SCNAs detected in WES of matched tumor biopsies. In several cases, we observed mutations exclusive to cfDNA that were confirmed in later blood draws, suggesting that cfDNA-exclusive mutations may be derived from unsampled metastases. In some cases, cfDNA revealed clinically actionable mutations that were not detected in matched tumor biopsies. Conclusions: WES of cfDNA uncovers the majority of somatic mutations, indels, and SCNAs found in matched tumor biopsies of metastatic cancer. The high degree of concordance suggests that comprehensive sequencing of cfDNA can be leveraged for genomic discovery in settings where conventional biopsies are difficult to access. Furthermore, the detection of mutations in cfDNA that are not detected in concurrent biopsies suggests that cfDNA may be complementary to tumor biopsies for both translational studies and precision cancer medicine. Citation Format: Viktor A. Adalsteinsson, Gavin Ha, Sam Freeman, Atish D. Choudhury, Daniel G. Stover, Heather A. Parsons, Gregory Gydush, Sarah Reed, Denis Loginov, Dimitri Livitz, Daniel Rosebrock, Ignat Leshchiner, Ofir Cohen, Coyin Oh, Jaegil Kim, Chip Stewart, Mara Rosenberg, Huiming Ding, Maxwell R. Lloyd, Sairah Mahmud, Karla E. Helvie, Margaret S. Merrill, Rebecca A. Santiago, Edward P. O’Connor, Seong H. Jeong, Joseph F. Kramkowski, Jens G. Lohr, Laura Polacek, Nelly Oliver, Lori Marini, Joshua Francis, Lauren C. Harshman, Eliezer M. Van Allen, Eric P. Winer, Nancy U. Lin, Mari Nakabayashi, Mary-Ellen Taplin, Levi A. Garraway, Todd R. Golub, Jesse S. Boehm, Nikhil Wagle, Gad Getz, Matthew Meyerson, Christopher J. Love. High concordance of whole-exome sequencing of cell-free DNA and matched biopsies enables genomic discovery in metastatic cancer. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr LB-136.


Journal of Clinical Oncology | 2018

Association of Cell-Free DNA Tumor Fraction and Somatic Copy Number Alterations With Survival in Metastatic Triple-Negative Breast Cancer

Daniel G. Stover; Heather A. Parsons; Gavin Ha; Samuel S. Freeman; William T. Barry; Hao Guo; Atish D. Choudhury; Gregory Gydush; Sarah C. Reed; Justin Rhoades; Denisse Rotem; Melissa E. Hughes; Deborah A. Dillon; Ann H. Partridge; Nikhil Wagle; Ian E. Krop; Gad Getz; Todd R. Golub; J. Christopher Love; Sara M. Tolaney; Nan Lin; Viktor A. Adalsteinsson


Blood | 2016

Whole-Exome Sequencing and Targeted Deep Sequencing of cfDNA Enables a Comprehensive Mutational Profiling of Multiple Myeloma

Salomon Manier; Jihye Park; Samuel S. Freeman; Gavin Ha; Marzia Capelletti; Sarah C. Reed; Gregory Gydush; Denisse Rotem; Justin Rhoades; Karma Salem; Claudia Freymond; Daisy Huynh; Antonio Sacco; Houry Leblebjian; Adriana Perilla Glen; Amir Yosef; Antonio Palumbo; Laurent Garderet; Shaji Kumar; Aldo M. Roccaro; Thierry Facon; Eliezer M. Van Allen; J. Christopher Love; Gad Getz; Viktor A. Adalsteinsson; Irene M. Ghobrial


Neuro-oncology | 2018

TBIO-18. LIQUID BIOPSY DETECTION OF GENOMIC ALTERATIONS IN PEDIATRIC BRAIN TUMORS FROM CELL FREE DNA IN PERIPHERAL BLOOD, CSF, AND URINE

Melanie Pages; Denisse Rotem; Gregory Gydush; Sarah C. Reed; Justin Rhoades; Gavin Ha; Christopher Lo; Adam Tracy; Roger Jones; Sarah Becker; Michaela Haller; Susan N. Chi; Mark W. Kieran; Liliana Goumnerova; J. Christopher Love; Keith L. Ligon; Pratiti Bandopadhayay; Karen Wright; Viktor A. Adalsteinsson; Rameen Beroukhim


Cancer Research | 2018

Abstract LB-225: Liquid biopsies identify trunk mutations and reflect multiple tumors in a patient

Samuel S. Freeman; Ziao Lin; Gavin Ha; Ignaty Leshchiner; Justin Rhoades; Dimitri Livitz; Daniel Rosebrock; Sarah C. Reed; Gregory Gydush; Christopher Lo; Denisse Rotem; Atish D. Choudhury; Daniel G. Stover; Heather A. Parsons; Jesse S. Boehm; J. Christopher Love; Matthew Meyerson; Paul M. Grandgenett; Michael A. Hollingsworth; Viktor A. Adalsteinsson; Gad Getz


Cancer Research | 2018

Abstract 3001: Broad/IBM Project: Discovery of treatment resistance mechanisms through use of liquid biopsy genomics services

Gad Getz; Carrie Cibulskis; Ignaty Leshchiner; Megan Hanna; Dimitri Livitz; Kara Slowik; Chaya Levovitz; Filippo Utro; Kahn Rhrissorrakrai; Denisse Rotem; Gregory Gydush; Sarah C. Reed; Justin Rhoades; Gavin Ha; Samuel S. Freeman; Christopher Lo; Mark Fleharty; Justin Abreu; Katie Larkin; Michelle Cipicchio; Brendan Blumenstiel; Matt DeFelice; Jonna Grimsby; Susanna Hamilton; Niall J. Lennon; Viktor A. Adalsteinsson; Laxmi Parida

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Heather A. Parsons

Johns Hopkins University School of Medicine

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