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Circulating biomarkers predictive of tumor response to cancer immunotherapy

Lee, Ernest Y. and Kulkarni, Rajan P. (2019) Circulating biomarkers predictive of tumor response to cancer immunotherapy. Expert Review of Molecular Diagnostics, 19 (10). pp. 895-904. ISSN 1473-7159. PMCID PMC6773262. https://resolver.caltech.edu/CaltechAUTHORS:20191004-091120980

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Abstract

Introduction: The advent of checkpoint blockade immunotherapy has revolutionized cancer treatment, but clinical response to immunotherapies is highly heterogeneous among individual patients and between cancer types. This represents a challenge to oncologists when choosing specific immunotherapies for personalized medicine. Thus, biomarkers that can predict tumor responsiveness to immunotherapies before and during treatment are invaluable. Areas covered: We review the latest advances in 'liquid biopsy' biomarkers for noninvasive prediction and in-treatment monitoring of tumor response to immunotherapy, focusing primarily on melanoma and non-small cell lung cancer. We concentrate on high-quality studies published within the last five years on checkpoint blockade immunotherapies, and highlight significant breakthroughs, identify key areas for improvement, and provide recommendations for how these diagnostic tools can be translated into clinical practice. Expert opinion: The first biomarkers proposed to predict tumor response to immunotherapy were based on PD1/PDL1 expression, but their predictive value is limited to specific cancers or patient populations. Recent advances in single-cell molecular profiling of circulating tumor cells and host cells using next-generation sequencing has dramatically expanded the pool of potentially useful predictive biomarkers. As immunotherapy moves toward personalized medicine, a composite panel of both genomic and proteomic biomarkers will have enormous utility in therapeutic decision-making.


Item Type:Article
Related URLs:
URLURL TypeDescription
https://doi.org/10.1080/14737159.2019.1659728DOIArticle
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6773262PubMed CentralArticle
ORCID:
AuthorORCID
Lee, Ernest Y.0000-0001-5144-2552
Additional Information:© 2019 Taylor & Francis. Received 09 Jun 2019, Accepted 21 Aug 2019, Accepted author version posted online: 30 Aug 2019, Published online: 10 Sep 2019. This paper was not funded. E.Y.L. acknowledges support from the UCLA-Caltech Medical Scientist Training Program (T32GM008042), the Dermatology Scientist Training Program (T32AR071307) at UCLA, and an Early Career Research Grant from the National Psoriasis Foundation. R.P.K. acknowledges support from the OHSU Physician-Scientist Award, the Department of Defense (W81XWH-17-1-0098 and W81XWH-17-1-0514), Cancer Research Institute, LUNGevity, and Melanoma Research Alliance. The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties. Peer reviewers on this manuscript have no relevant financial relationships or otherwise to disclose.
Funders:
Funding AgencyGrant Number
UCLA-Caltech Medical Scientist Training ProgramUNSPECIFIED
NIH Predoctoral FellowshipT32GM008042
NIH Predoctoral FellowshipT32AR071307
National Psoriasis FoundationUNSPECIFIED
Oregon Health and Science UniversityUNSPECIFIED
Department of DefenseW81XWH-17-1-0098
Department of DefenseW81XWH-17-1-0514
Cancer Research InstituteUNSPECIFIED
LUNGevityUNSPECIFIED
Melanoma Research AllianceUNSPECIFIED
Subject Keywords:Checkpoint blockade immunotherapy, liquid biopsy, noninvasive diagnostics, circulating tumor cells, personalized medicine
Issue or Number:10
PubMed Central ID:PMC6773262
Record Number:CaltechAUTHORS:20191004-091120980
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20191004-091120980
Official Citation:Ernest Y. Lee & Rajan P. Kulkarni (2019) Circulating biomarkers predictive of tumor response to cancer immunotherapy, Expert Review of Molecular Diagnostics, 19:10, 895-904, DOI: 10.1080/14737159.2019.1659728
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:99069
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:04 Oct 2019 16:24
Last Modified:04 Oct 2019 16:24

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