From Clinical Standards to Translating Next-Generation Sequencing Research into Patient Care Improvement for Hepatobiliary and Pancreatic Cancers

AbstractBackground:Molecular technologies have allowed laboratories to detect and establish the profiles of human cancers by identifying a variety of somatic variants. In order to improve personalized patient care, we have established a next-generation sequencing (NGS) test to screen for somatic variants in primary or advanced cancers. In this study, we describe the laboratory quality management program for NGS testing, and also provide an overview of the somatic variants identified in over 1000 patient samples as well as their implications in clinical practice.Methods:Over the past one-and-a-half years, our laboratory received a total of 1028 formalin-fixed, paraffin-embedded (FFPE) tumor tissues, which consisted of non-small-cell lung carcinomas (NSCLCs), colon adenocarcinomas, glioma/glioblastomas, melanomas, breast carcinomas, and other tumor types. During this time period, we implemented a series of quality control (QC) checks that included (1) pre-DNA extraction, (2) DNA quantification, (3) DNA quality, (4) library quantification, (5) post-emulsification PCR, and (6) post-sequencing metrics. At least 10 ng of genomic DNA (gDNA) were used to prepare barcoded libraries using the AmpliSeq CHPv2. Samples were multiplexed and sequenced on Ion Torrent 318 chips using the Ion PGM System. Variants were identified using the Variant Caller Plugin, and annotation and functional predictions were performed using the Golden Helix SVS.Results:A total of 1005 samples passed QC1–3, and following additional library preparation QC checkpoints, 877 samples were sequenced. Samples were classified into two categories: wild-type (127) and positive for somatic variants (750). Somatic variants were classified into clinically actionable (60%) and non-actionable (40%).Conclusions:The use of NGS in routine clinical laboratory practice allowed for the detection of tumor profiles that are essential for the selection of targeted therapies and identification of applicable clinical trials, contributing to the improvement of personalized patient care in oncology.

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Standards for Clinical Grade Genomic Databases

Archives of Pathology & Laboratory Medicine ◽

10.5858/arpa.2014-0568-cp ◽

2015 ◽

Vol 139 (11) ◽

pp. 1400-1412 ◽

Cited By ~ 12

Author(s):

Sophia L. Yohe ◽

Alexis B. Carter ◽

John D. Pfeifer ◽

James M. Crawford ◽

Allison Cushman-Vokoun ◽

...

Keyword(s):

Next Generation Sequencing ◽

Patient Care ◽

Genomic Medicine ◽

Sequence Variant ◽

Clinical Grade ◽

Next Generation ◽

Data Repositories ◽

Genomic Databases ◽

Clinical Patient ◽

Generation Sequencing

Context Next-generation sequencing performed in a clinical environment must meet clinical standards, which requires reproducibility of all aspects of the testing. Clinical-grade genomic databases (CGGDs) are required to classify a variant and to assist in the professional interpretation of clinical next-generation sequencing. Applying quality laboratory standards to the reference databases used for sequence-variant interpretation presents a new challenge for validation and curation. Objectives To define CGGD and the categories of information contained in CGGDs and to frame recommendations for the structure and use of these databases in clinical patient care. Design Members of the College of American Pathologists Personalized Health Care Committee reviewed the literature and existing state of genomic databases and developed a framework for guiding CGGD development in the future. Results Clinical-grade genomic databases may provide different types of information. This work group defined 3 layers of information in CGGDs: clinical genomic variant repositories, genomic medical data repositories, and genomic medicine evidence databases. The layers are differentiated by the types of genomic and medical information contained and the utility in assisting with clinical interpretation of genomic variants. Clinical-grade genomic databases must meet specific standards regarding submission, curation, and retrieval of data, as well as the maintenance of privacy and security. Conclusion These organizing principles for CGGDs should serve as a foundation for future development of specific standards that support the use of such databases for patient care.

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Chromosomal Microarray in the Era of Next Generation Sequencing: Still Going Strong and Making a Difference in Patient Care. Cases from Medical University of South Carolina

Cancer Genetics ◽

10.1016/j.cancergen.2016.04.040 ◽

2016 ◽

Vol 209 (6) ◽

pp. 296

Author(s):

Iya Znoyko ◽

Cynthia Schandl ◽

Daynna J. Wolff

Keyword(s):

South Carolina ◽

Next Generation Sequencing ◽

Patient Care ◽

Chromosomal Microarray ◽

Next Generation ◽

University Of South Carolina ◽

Making A Difference ◽

Medical University ◽

Generation Sequencing

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Next-generation sequencing and histological response assessment in peritoneal metastasis from pancreatic cancer treated with PIPAC

Journal of Clinical Pathology ◽

10.1136/jclinpath-2020-206607 ◽

2020 ◽

Vol 74 (1) ◽

pp. 19-24 ◽

Cited By ~ 1

Author(s):

Malene Nielsen ◽

Martin Graversen ◽

Signe Bremholm Ellebæk ◽

Thomas Kielsgaard Kristensen ◽

Claus Fristrup ◽

...

Keyword(s):

Pancreatic Cancer ◽

Next Generation Sequencing ◽

Peritoneal Metastasis ◽

Response Assessment ◽

Histological Response ◽

Next Generation ◽

Pancreatic Cancers ◽

Before And After ◽

Next Generation Sequencing Ngs ◽

Generation Sequencing

BackgroundPeritoneal metastasis from pancreatic cancer (PM-PC) may be treated with repeated pressurised intraperitoneal aerosol chemotherapy (PIPAC). Utility of next-generation sequencing (NGS) to detect cancer-related mutations in peritoneal quadrant biopsies (QBs) and peritoneal fluid (PF) after systemic and PIPAC treatment has not been evaluated. Around 90% of pancreatic cancers (PCs) harbour a KRAS mutation, making PC ideal for the evaluation of this aspect.AimsEvaluation of PM-PC in terms of (1) histological response to PIPAC using Peritoneal Regression Grading Score (PRGS), (2) clinical characteristics and (3) frequency of mutations in QBs and PF before and after PIPAC.MethodsPeritoneal QBs and PF were obtained prior to each PIPAC. NGS for 22 cancer-related genes was performed on primary tumours, QBs and PFs. Response was assessed by the four-tiered PRGS.ResultsSixteen patients treated with a median of three PIPAC procedures were included. The mean PRGS was reduced from 1.91 to 1.58 (p=0.02). Fifty-seven specimens (13 primary tumours, 2 metastatic lymph nodes, 16 PFs and 26 QB sets) were analysed with NGS. KRAS mutation was found in 14/16 patients (87.50%) and in QBs, primary tumours and PF in 8/12 (66.67%), 8/13 (61.53%) and 6/9 (66.67%). The median overall survival was 9.9 months (SE 1.5, 95% CI 4.9 to 13.9).ConclusionPIPAC induces histological response in the majority of patients with PM-PC. KRAS mutation can be found in PM-PC after PIPAC at a frequency similar to the primaries. NGS may be used to detect predictive mutations in PM-PC of various origins, also when only post-PIPAC QBs or PFs are available.

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Integrating Somatic and Germline Next-Generation Sequencing Into Routine Clinical Oncology Practice

JCO Precision Oncology ◽

10.1200/po.20.00513 ◽

2021 ◽

pp. 884-895

Author(s):

J. Kevin Hicks ◽

Rachel Howard ◽

Phillip Reisman ◽

Jacob J. Adashek ◽

Karen K. Fields ◽

...

Keyword(s):

Next Generation Sequencing ◽

Electronic Health Record ◽

Patient Care ◽

Treatment Strategies ◽

Health Record ◽

Next Generation ◽

Electronic Health ◽

Oncology Practice ◽

Test Ordering ◽

Generation Sequencing

Next-generation sequencing (NGS) is rapidly expanding into routine oncology practice. Genetic variations in both the cancer and inherited genomes are informative for hereditary cancer risk, prognosis, and treatment strategies. Herein, we focus on the clinical perspective of integrating NGS results into patient care to assist with therapeutic decision making. Five key considerations are addressed for operationalization of NGS testing and application of results to patient care as follows: (1) NGS test ordering and workflow design; (2) result reporting, curation, and storage; (3) clinical consultation services that provide test interpretations and identify opportunities for molecularly guided therapy; (4) presentation of genetic information within the electronic health record; and (5) education of providers and patients. Several of these key considerations center on informatics tools that support NGS test ordering and referencing back to the results for therapeutic purposes. Clinical decision support tools embedded within the electronic health record can assist with NGS test utilization and identifying opportunities for targeted therapy including clinical trial eligibility. Challenges for project and change management in operationalizing NGS-supported, evidence-based patient care in the context of current information technology systems with appropriate clinical data standards are discussed, and solutions for overcoming barriers are provided.

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