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.

scholarly journals Comparison of three commercial decision support platforms for matching of next-generation sequencing results with therapies in patients with cancer

ESMO Open ◽  
2020 ◽  
Vol 5 (5) ◽  
pp. e000872
Author(s):  
Samantha O Perakis ◽  
Sabrina Weber ◽  
Qing Zhou ◽  
Ricarda Graf ◽  
Sabine Hojas ◽  
...  
Keyword(s):  
Decision Support ◽  
Next Generation Sequencing ◽  
Metastatic Breast ◽  
Clinical Decision ◽  
Molecular Data ◽  
Current Status ◽  
Precision Oncology ◽  
Next Generation ◽  
Generation Sequencing ◽  
Tier I

ObjectivePrecision oncology depends on translating molecular data into therapy recommendations. However, with the growing complexity of next-generation sequencing-based tests, clinical interpretation of somatic genomic mutations has evolved into a formidable task. Here, we compared the performance of three commercial clinical decision support tools, that is, NAVIFY Mutation Profiler (NAVIFY; Roche), QIAGEN Clinical Insight (QCI) Interpret (QIAGEN) and CureMatch Bionov (CureMatch).MethodsIn order to obtain the current status of the respective tumour genome, we analysed cell-free DNA from patients with metastatic breast, colorectal or non-small cell lung cancer. We evaluated somatic copy number alterations and in parallel applied a 77-gene panel (AVENIO ctDNA Expanded Panel). We then assessed the concordance of tier classification approaches between NAVIFY and QCI and compared the strategies to determine actionability among all three platforms. Finally, we quantified the alignment of treatment suggestions across all decision tools.ResultsEach platform varied in its mode of variant classification and strategy for identifying druggable targets and clinical trials, which resulted in major discrepancies. Even the frequency of concordant actionable events for tier I-A or tier I-B classifications was only 4.3%, 9.5% and 28.4% when comparing NAVIFY with QCI, NAVIFY with CureMatch and CureMatch with QCI, respectively, and the obtained treatment recommendations differed drastically.ConclusionsTreatment decisions based on molecular markers appear at present to be arbitrary and dependent on the chosen strategy. As a consequence, tumours with identical molecular profiles would be differently treated, which challenges the promising concepts of genome-informed medicine.

scholarly journals Precision Oncology in Sarcomas: Divide and Conquer

2019 ◽  
pp. 1-16 ◽  
Author(s):  
Roberto Carmagnani Pestana ◽  
Roman Groisberg ◽  
Jason Roszik ◽  
Vivek Subbiah
Keyword(s):  
Next Generation Sequencing ◽  
Soft Tissue Sarcomas ◽  
Genetic Alterations ◽  
Divide And Conquer ◽  
Precision Oncology ◽  
Next Generation ◽  
Mesenchymal Tumors ◽  
Next Generation Sequencing Technology ◽  
Molecular Abnormalities ◽  
Generation Sequencing

Sarcomas are a heterogeneous group of rare malignancies that exhibit remarkable heterogeneity, with more than 50 subtypes recognized. Advances in next-generation sequencing technology have resulted in the discovery of genetic events in these mesenchymal tumors, which in addition to enhancing understanding of the biology, have opened up avenues for molecularly targeted therapy and immunotherapy. This review focuses on how incorporation of next-generation sequencing has affected drug development in sarcomas and strategies for optimizing precision oncology for these rare cancers. In a significant percentage of soft tissue sarcomas, which represent up to 40% of all sarcomas, specific driver molecular abnormalities have been identified. The challenge to evaluate these mutations across rare cancer subtypes requires the careful characterization of these genetic alterations to further define compelling drivers with therapeutic implications. Novel models of clinical trial design also are needed. This shift would entail sustained efforts by the sarcoma community to move from one-size-fits-all trials, in which all sarcomas are treated similarly, to divide-and-conquer subtype-specific strategies.

Enabling Precision Oncology Through Precision Diagnostics

2020 ◽  
Vol 15 (1) ◽  
pp. 97-121 ◽  
Author(s):  
Noah A. Brown ◽  
Kojo S.J. Elenitoba-Johnson
Keyword(s):  
Next Generation Sequencing ◽  
Cancer Patients ◽  
Cancer Genomics ◽  
Cost Effective ◽  
Routine Clinical Practice ◽  
Precision Oncology ◽  
Next Generation ◽  
Sequencing Data ◽  
Molecular Alterations ◽  
Generation Sequencing

Genomic testing enables clinical management to be tailored to individual cancer patients based on the molecular alterations present within cancer cells. Genomic sequencing results can be applied to detect and classify cancer, predict prognosis, and target therapies. Next-generation sequencing has revolutionized the field of cancer genomics by enabling rapid and cost-effective sequencing of large portions of the genome. With this technology, precision oncology is quickly becoming a realized paradigm for managing the treatment of cancer patients. However, many challenges must be overcome to efficiently implement the transition of next-generation sequencing from research applications to routine clinical practice, including using specimens commonly available in the clinical setting; determining how to process, store, and manage large amounts of sequencing data; determining how to interpret and prioritize molecular findings; and coordinating health professionals from multiple disciplines.

scholarly journals GeneMed: An Informatics Hub for the Coordination of Next-Generation Sequencing Studies that Support Precision Oncology Clinical Trials

2015 ◽  
Vol 14s2 ◽  
pp. CIN.S17282 ◽  
Author(s):  
Yingdong Zhao ◽  
Eric C. Polley ◽  
Ming-Chung Li ◽  
Chih-Jian Lih ◽  
Alida Palmisano ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Next Generation Sequencing ◽  
Treatment Selection ◽  
Control Treatment ◽  
Precision Oncology ◽  
Next Generation ◽  
Multiple Cancer ◽  
Randomized Design ◽  
Sequencing Studies ◽  
Generation Sequencing

We have developed an informatics system, GeneMed, for the National Cancer Institute (NCI) molecular profiling-based assignment of cancer therapy (MPACT) clinical trial (NCT01827384) being conducted in the National Institutes of Health (NIH) Clinical Center. This trial is one of the first to use a randomized design to examine whether assigning treatment based on genomic tumor screening can improve the rate and duration of response in patients with advanced solid tumors. An analytically validated next-generation sequencing (NGS) assay is applied to DNA from patients’ tumors to identify mutations in a panel of genes that are thought likely to affect the utility of targeted therapies available for use in the clinical trial. The patients are randomized to a treatment selected to target a somatic mutation in the tumor or with a control treatment. The GeneMed system streamlines the workflow of the clinical trial and serves as a communications hub among the sequencing lab, the treatment selection team, and clinical personnel. It automates the annotation of the genomic variants identified by sequencing, predicts the functional impact of mutations, identifies the actionable mutations, and facilitates quality control by the molecular characterization lab in the review of variants. The GeneMed system collects baseline information about the patients from the clinic team to determine eligibility for the panel of drugs available. The system performs randomized treatment assignments under the oversight of a supervising treatment selection team and generates a patient report containing detected genomic alterations. NCI is planning to expand the MPACT trial to multiple cancer centers soon. In summary, the GeneMed system has been proven to be an efficient and successful informatics hub for coordinating the reliable application of NGS to precision medicine studies.

No-cost next generation sequencing of advanced cancer patients within the Strata Precision Oncology Network supports clinical trial enrollment.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. 3073-3073
Author(s):  
Marc Ryan Matrana ◽  
Scott A. Tomlins ◽  
Kat Kwiatkowski ◽  
Khalis Mitchell ◽  
Jennifer Marie Suga ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Next Generation Sequencing ◽  
Clinical Samples ◽  
Precision Oncology ◽  
Cancer Type ◽  
Next Generation ◽  
Match Trial ◽  
The Impact ◽  
Generation Sequencing

3073 Background: Widespread integration of systematized next generation sequencing (NGS)-based precision oncology is hindered by numerous barriers. Hence, we developed the Strata trial (NCT03061305), a screening protocol to determine the impact of scaled precision oncology. Methods: We implemented no-cost NGS on formalin fixed paraffin embedded (FFPE) clinical samples for all patients with advanced tumors, a common portfolio of partnered therapeutic clinical trials, and robust infrastructure development across the Strata Precision Oncology Network. Results: Across the network of 17 centers, specimens from 8673/9222 (94%) patients were successfully tested in the Strata CLIA/CAP/NCI-MATCH accredited laboratory using comprehensive amplicon-based DNA and RNA NGS. Patients were tested with one of three StrataNGS test versions; the most recent panel assesses all classes of actionable alterations (mutations, copy number alterations, gene fusions, microsatellite instability, tumor mutation burden and PD-L1 expression). Median surface area of received FFPE tumor samples was 25mm2 (interquartile range 9-95mm2), and the median turnaround time from sample receipt to report was 6 business days. 2577 (27.9%) patients had highly actionable alterations, defined as alterations associated with within-cancer type FDA approved or NCCN guideline recommended therapies (1072 patients), NCI-MATCH trial arms (1467 patients), Strata-partnered therapeutic trials (327 patients), or specific alteration-matched FDA approved therapies in patients with cancers of unknown primary (71 patients). Of the 1467 patients matched to an NCI-MATCH trial arm, 15 enrolled. Of the 327 patients matched to one of nine Strata-partnered clinical trials, 77 (24%) were screen failures, while 250 (76%) have either enrolled or are being actively followed for enrollment upon progression. Conclusions: Through streamlined consent methods, electronic medical record queries, and high throughput laboratory testing at no cost to patients, we demonstrate that scaled precision oncology is feasible across a diverse network of healthcare systems when paired with access to relevant clinical trials. Clinical trial information: NCT03061305.

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