Literature DB >> 31550176

Operationalization of Next-Generation Sequencing and Decision Support for Precision Oncology.

Jia Zeng1, Amber Johnson1, Md Abu Shufean1, Michael Kahle1, Dong Yang1, Scott E Woodman1, Thuy Vu1, Shhyam Moorthy1, Vijaykumar Holla1, Funda Meric-Bernstam1.   

Abstract

Genomic testing has become a part of routine oncology care and plays critical roles in diagnosis, prognostic assessment, and treatment selection. Thus, in parallel, the variety of genomic testing providers and sequencing platforms has grown exponentially. Selection of the best-fit panel for each case can be daunting, with many factors to consider. Among them is whether alteration interpretation and therapy/clinical trial matching are included and/or sufficient. In this article, we review some common commercially available sequencing platforms for the genes and types of alterations tested, samples needed, and reporting content provided. We review publicly available resources for a do-it-yourself approach to alteration interpretation when it is not provided or when supplemental research is needed, along with resources to identify genomically matched treatment options that are approved and/or investigational. However, with both commercially provided interpretation and publicly available resources, there are still caveats and limitations that can stem from insufficient or ambiguous nomenclature as well as from the presentation of information. Use cases in which clinical decision making was affected are discussed. After treatment options are identified, it is important to assess the level of evidence for use within the patient's tumor type and molecular profile. However, numerous level-of-evidence scales have been published in recent years, so we provide a publicly available tool to facilitate interoperability. The level of evidence, along with other factors, such as allelic frequency and copy number, can be used to prioritize treatment options when multiple are identified.

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Year:  2019        PMID: 31550176      PMCID: PMC6874004          DOI: 10.1200/CCI.19.00089

Source DB:  PubMed          Journal:  JCO Clin Cancer Inform        ISSN: 2473-4276


  37 in total

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Journal:  J Natl Cancer Inst       Date:  2015-04-11       Impact factor: 13.506

5.  Clinical Use of Precision Oncology Decision Support.

Authors:  Amber Johnson; Yekaterina B Khotskaya; Lauren Brusco; Jia Zeng; Vijaykumar Holla; Ann M Bailey; Beate C Litzenburger; Nora Sanchez; Md Abu Shufean; Sarina Piha-Paul; Vivek Subbiah; David Hong; Mark Routbort; Russell Broaddus; Kenna R Mills Shaw; Gordon B Mills; John Mendelsohn; Funda Meric-Bernstam
Journal:  JCO Precis Oncol       Date:  2017-09-13

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10.  Coexistence of sensitive and resistant epidermal growth factor receptor (EGFR) mutations in pretreatment non-small cell lung cancer (NSCLC) patients: First or third generation tyrosine kinase inhibitors (TKIs)?

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Journal:  Lung Cancer       Date:  2018-01-10       Impact factor: 5.705

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Journal:  Oncologist       Date:  2021-03-26

2.  Direct comparison shows that mRNA-based diagnostics incorporate information which cannot be learned directly from genomic mutations.

Authors:  Hersh D Ravkin; Ofer Givton; David B Geffen; Eitan Rubin
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3.  Germline Testing Data Validate Inferences of Mutational Status for Variants Detected From Tumor-Only Sequencing.

Authors:  Nahed Jalloul; Israel Gomy; Samantha Stokes; Alexander Gusev; Bruce E Johnson; Neal I Lindeman; Laura Macconaill; Shridar Ganesan; Judy E Garber; Hossein Khiabanian
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4.  Impact of Precision Medicine on Clinical Outcomes: A Single-Institution Retrospective Study.

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Review 5.  Integrating Somatic and Germline Next-Generation Sequencing Into Routine Clinical Oncology Practice.

Authors:  J Kevin Hicks; Rachel Howard; Phillip Reisman; Jacob J Adashek; Karen K Fields; Jhanelle E Gray; Bryan McIver; Kelly McKee; Mandy F O'Leary; Randa M Perkins; Edmondo Robinson; Ankita Tandon; Jamie K Teer; Joseph Markowitz; Dana E Rollison
Journal:  JCO Precis Oncol       Date:  2021-05-20

Review 6.  A Review of Precision Oncology Knowledgebases for Determining the Clinical Actionability of Genetic Variants.

Authors:  Xuanyi Li; Jeremy L Warner
Journal:  Front Cell Dev Biol       Date:  2020-02-11

Review 7.  UGT1A1 Guided Cancer Therapy: Review of the Evidence and Considerations for Clinical Implementation.

Authors:  Ryan S Nelson; Nathan D Seligson; Sal Bottiglieri; Estrella Carballido; Alex Del Cueto; Iman Imanirad; Richard Levine; Alexander S Parker; Sandra M Swain; Emma M Tillman; J Kevin Hicks
Journal:  Cancers (Basel)       Date:  2021-03-29       Impact factor: 6.639

Review 8.  Molecular-based precision oncology clinical decision making augmented by artificial intelligence.

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