Articles by Shrey Sukhadia in JoVE
Next Generation Sequencing for the Detection of Actionable Mutations in Solid and Liquid Tumors Alan J. Fox1, Matthew C. Hiemenz1, David B. Lieberman1, Shrey Sukhadia1, Barnett Li1, Joseph Grubb1, Patrick Candrea1, Karthik Ganapathy1, Jianhua Zhao1, David Roth1, Evan Alley2,3, Alison Loren2,3, Jennifer J. D. Morrissette1 1Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, 2Division of Hematology/Oncology, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, 3Abramson Cancer Center This manuscript describes clinical protocols for two next-generation sequencing panels. One panel interrogates hematologic malignancies while the other panel targets genes commonly mutated in solid tumors. Molecular classification of driver mutations in human malignancies offers valuable prognostic and predictive information.
Other articles by Shrey Sukhadia on PubMed
Understanding the Limitations of Next Generation Sequencing Informatics, an Approach to Clinical Pipeline Validation Using Artificial Data Sets Cancer Genetics. Dec, 2013 | Pubmed ID: 24528889 The advantages of massively parallel sequencing are quickly being realized through the adoption of comprehensive genomic panels across the spectrum of genetic testing. Despite such widespread utilization of next generation sequencing (NGS), a major bottleneck in the implementation and capitalization of this technology remains in the data processing steps, or bioinformatics. Here we describe our approach to defining the limitations of each step in the data processing pipeline by utilizing artificial amplicon data sets to simulate a wide spectrum of genomic alterations. Through this process, we identified limitations of insertion, deletion (indel), and single nucleotide variant (SNV) detection using standard approaches and described novel strategies to improve overall somatic mutation detection. Using these artificial data sets, we were able to demonstrate that NGS assays can have robust mutation detection if the data can be processed in a way that does not lead to large genomic alterations landing in the unmapped data (i.e., trash). By using these pipeline modifications and a new variant caller, AbsoluteVar, we have been able to validate SNV mutation detection to 100% sensitivity and specificity with an allele frequency as low 4% and detection of indels as large as 90 bp. Clinical validation of NGS relies on the ability for mutation detection across a wide array of genetic anomalies, and the utility of artificial data sets demonstrates a mechanism to intelligently test a vast array of mutation types.
A Novel Approach for Next-generation Sequencing of Circulating Tumor Cells Molecular Genetics & Genomic Medicine. Jul, 2016 | Pubmed ID: 27468416 Next-generation sequencing (NGS) of surgically resected solid tumor samples has become integral to personalized medicine approaches for cancer treatment and monitoring. Liquid biopsies, or the enrichment and characterization of circulating tumor cells (CTCs) from blood, can provide noninvasive detection of evolving tumor mutations to improve cancer patient care. However, the application of solid tumor NGS approaches to circulating tumor samples has been hampered by the low-input DNA available from rare CTCs. Moreover, whole genome amplification (WGA) approaches used to generate sufficient input DNA are often incompatible with blood collection tube preservatives used to facilitate clinical sample batching.