FDA-approved Next-Generation sequencing system could expand clinical genomic testing

2014 ◽  
Vol 164 (3) ◽  
pp. x-xi ◽  
Keyword(s):  
Next Generation Sequencing ◽  
Genomic Testing ◽  
Next Generation ◽  
Clinical Genomic ◽  
Generation Sequencing

Assessing real-world outcomes in precision oncology by linking clinical genomic testing to electronic medical records.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. e18091-e18091
Author(s):  
Debajyoti Datta ◽  
Theodore Goldstein ◽  
Atul Butte
Keyword(s):  
Next Generation Sequencing ◽  
Cancer Patients ◽  
Relational Database ◽  
Real World ◽  
Molecular Profiling ◽  
Genomic Testing ◽  
Precision Oncology ◽  
Clinical Sequencing ◽  
Clinical Genomic ◽  
Generation Sequencing

e18091 Background: With an ever-widening array of targeted therapies for cancer patients, clinical genomic testing has expanded rapidly in recent years. Tumor molecular profiling by next-generation sequencing is now considered a cornerstone of precision oncology, with the potential to offer patients with advanced cancers new therapeutic options. However, the overall impact of this testing remains unclear, and evidence demonstrating improvement in patient outcomes is lacking. The objective of this study is to assess the utility of clinical sequencing on the management of cancer patients. Methods: We present the development of a database that combines results of tumor mutation profiling using various next-generation sequencing panels (both external commercial tests and our institution’s internal sequencing panel), with a variety of data points from a de-identified representation of our institution’s electronic medical record (EMR). Assembling this data from different sources into a common relational database permits efficient retrospective analysis of real-world outcomes in patients with advanced cancers. Results: This study included over 3000 patients seen at UCSF Comprehensive Cancer Center since 2013. With this linked data set we analyzed the rate at which tumor molecular profiling affected clinical decision making, identified barriers to the efficient use of testing, and assessed for disparities in utilization. For example, by measuring patient survival relative to the clinical intervention of genomic testing for the subset of patients with a date of death recorded in our EMR, we found that a small fraction of patients died before results returned and any action could be taken, especially in cases of pancreatic cancer. Conclusions: We demonstrate that a common relational database combining clinical sequencing results with real-world EMR data provides insights into the optimal clinical use of tumor molecular profiling. This provides new opportunities for advancing precision oncology initiatives and improving patient care, such as identifying which cancer patients should get genomic testing and efficiently matching patients to clinical trials.

scholarly journals An Integrated Approach for Analyzing Clinical Genomic Variant Data from Next-Generation Sequencing

2015 ◽  
Vol 26 (1) ◽  
pp. 19-28 ◽  
Author(s):  
Erin L. Crowgey ◽  
Deborah L. Stabley ◽  
Chuming Chen ◽  
Hongzhan Huang ◽  
Katherine M. Robbins ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
Integrated Approach ◽  
Next Generation ◽  
Genomic Variant ◽  
Clinical Genomic ◽  
Generation Sequencing

Genomic testing and counseling: The contribution of next‐generation sequencing to epilepsy genetics

2020 ◽  
Vol 84 (6) ◽  
pp. 431-436
Author(s):  
Lamia Alsubaie ◽  
Taghrid Aloraini ◽  
Manal Amoudi ◽  
Abdulrahman Swaid ◽  
Wafaa Eyiad ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
Genomic Testing ◽  
Next Generation ◽  
Generation Sequencing ◽  
Testing And Counseling

Academic (AO) and community (CO) oncologists’ knowledge, understanding, and preparedness for clinical next-generation sequencing genomic testing (NGSGT).

2014 ◽  
Vol 32 (15_suppl) ◽  
pp. e17635-e17635 ◽  
Author(s):  
Julie Innocent ◽  
Karen Ruth ◽  
Patrick McKay Boland ◽  
Kim Rainey ◽  
Carolyn Y Fang ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
Genomic Testing ◽  
Next Generation ◽  
Generation Sequencing

scholarly journals Clinical utility of reflex testing using focused next-generation sequencing for management of patients with advanced lung adenocarcinoma

2018 ◽  
Vol 71 (12) ◽  
pp. 1108-1115 ◽  
Author(s):  
Tyler E Miller ◽  
Michael Yang ◽  
David Bajor ◽  
Judah D Friedman ◽  
Richard Y C Chang ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
Lung Adenocarcinoma ◽  
Targeted Therapies ◽  
Medical Center ◽  
Single Gene ◽  
Cancer Center ◽  
Genomic Testing ◽  
Next Generation ◽  
Reflex Testing ◽  
Generation Sequencing

AimsThe growing number of genomically targeted therapies has made genomic testing an important part of the care for patients with non-small cell lung cancer. However, limited tissue availability, cost and long turnaround times can create barriers to efficient genomic testing and subsequent treatment. Effective approaches to reduce these barriers are needed.Methods302 advanced lung adenocarcinomas from consecutive patients seen at University Hospitals Cleveland Medical Center (UHCMC) were tested inhouse using a hybrid DNA/RNA next-generation sequencing (NGS) panel. Sample testing was reflexed from pathology for all stage III or IV tumours. Genomic alterations were tiered according to their clinical relevance and reported with guideline-recommended therapies. Clinical implications of genomic testing results were assessed by manual chart review.ResultsWith a sample cohort consisting of 64% biopsies, 16% excisions/resections and 20% fine needle aspirations, the assay was reliable with a 95% success rate. The average turnaround time from receipt of unstained formalin-fixed paraffin embedded slides to reporting was 4.8±2.1 days, half of the recommended 10 days and similar to single-gene testing. Alterations with Food and Drug Administration-approved or the National Cancer Center Network guideline-recommended targeted therapies were found in 18% of cases. Within this group, 60% of patients went on genomically driven therapies.ConclusionsWe found our reflexed inhouse NGS assay to be reliable, cost-effective and efficient. Incorporation of reflex testing with our NGS assay led to an expansion of successful genomic profiling for all guideline-recommended alterations, and by including an expanded number of alterations within our panel we obtained clinically useful information outside the guidelines without changing cost or efficiency. This approach has enabled UHCMC clinicians to efficiently initiate genomically driven therapies for patients with lung adenocarcinoma.

scholarly journals From Information Overload to Actionable Insights: Digital Solutions for Interpreting Cancer Variants from Genomic Testing

2021 ◽  
Vol 2 (4) ◽  
pp. 312-318
Author(s):  
Stephanie J. Yaung ◽  
Adeline Pek
Keyword(s):  
Decision Support ◽  
Next Generation Sequencing ◽  
Information Overload ◽  
Genomic Testing ◽  
Precision Oncology ◽  
Next Generation ◽  
Medical Oncologists ◽  
Management Plans ◽  
Support Software ◽  
Generation Sequencing

Given the increase in genomic testing in routine clinical use, there is a growing need for digital technology solutions to assist pathologists, oncologists, and researchers in translating variant calls into actionable knowledge to personalize patient management plans. In this article, we discuss the challenges facing molecular geneticists and medical oncologists in working with test results from next-generation sequencing for somatic oncology, and propose key considerations for implementing a decision support software to aid the interpretation of clinically important variants. In addition, we review results from an example decision support software, NAVIFY Mutation Profiler. NAVIFY Mutation Profiler is a cloud-based software that provides curation, annotation, interpretation, and reporting of somatic variants identified by next-generation sequencing. The software reports a tiered classification based on consensus recommendations from AMP, ASCO, CAP, and ACMG. Studies with NAVIFY Mutation Profiler demonstrated that the software provided timely updates and accurate curation, as well as interpretation of variant combinations, demonstrating that decision support tools can help advance implementation of precision oncology.

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