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Cited by 2,286Cancer Immunotherapy and BiomarkersImmunotherapy and Immune ResponsesT-cell and B-cell Immunology

The evolving landscape of biomarkers for checkpoint inhibitor immunotherapy

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Havel, Jonathan J., Chowell, Diego, Chan, Timothy A.·2019·Nature Reviews Cancer
DOI 10.1038/s41568-019-0116-xPMC PMC6705396
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Abstract

Checkpoint inhibitor-based immunotherapies that target cytotoxic T lymphocyte antigen 4 (CTLA4) or the programmed cell death 1 (PD1) pathway have achieved impressive success in the treatment of different cancer types. Yet, only a subset of patients derive clinical benefit. It is thus critical to understand the determinants driving response, resistance and adverse effects. In this Review, we discuss recent work demonstrating that immune checkpoint inhibitor efficacy is affected by a combination of factors involving tumour genomics, host germline genetics, PD1 ligand 1 (PDL1) levels and other features of the tumour microenvironment, as well as the gut microbiome. We focus on recently identified molecular and cellular determinants of response. A better understanding of how these variables cooperate to affect tumour-host interactions is needed to optimize the implementation of precision immunotherapy.

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  • Reliable prognostic biomarkers for patients with metastatic NSCLC receiving nivolumab remain an unmet need.

    “Nivolumab has significantly improved outcomes in patients with metastatic non-small cell lung cancer (NSCLC); however, reliable prognostic biomarkers remain an unmet need.”

    From SUVmax-IPI as a New Prognostic Index in Metastatic Non-Small Cell Lung Cancer Patients Receiving Nivolumab (2025) · cites this paper as [4]

    The Abstract (page not available) says effective biomarkers for selecting patients for checkpoint immunotherapy are needed and discusses inconsistent first-line NSCLC trial results with nivolumab. It supports the broad unmet-need point, but calls for predictive biomarkers of treatment response rather than specifically prognostic biomarkers for patients with metastatic NSCLC receiving nivolumab. (LLM, conf=0.84)

    Experimental — accuracy not yet measured

  • The clinical utility of PD-L1 expression and tumor mutational burden is limited by spatial heterogeneity, assay variability, and dynamic changes during therapy.

    “While programmed death ligand 1 (PD-L1) expression and tumor mutational burden are established predictive markers, their clinical utility is limited by spatial heterogeneity, assay variability, and dynamic changes during therapy [4].”

    From SUVmax-IPI as a New Prognostic Index in Metastatic Non-Small Cell Lung Cancer Patients Receiving Nivolumab (2025) · cites this paper as [4]

    The ‘PDL1 expression’ section identifies different detection assays, temporal changes and intratumoural heterogeneity as potential reasons for inconsistent PD-L1 biomarker findings. The ‘Tumour antigens and mutation burden’ section says pre-therapy TMB has limited predictive accuracy and that on-therapy TMB changes can be informative. The cited passages do not establish that spatial heterogeneity and assay variability also limit TMB’s clinical utility, as the sentence implies. (LLM, conf=0.84)

    Experimental — accuracy not yet measured

  • Existing predictive biomarkers (PD-L1 expression, TMB, microsatellite instability, and mismatch repair deficiency) have clinical utility in specific contexts, but their predictive accuracy varies considerably across tumor histologies and patient populations.

    “While these markers have clinical utility in specific contexts, their predictive accuracy varies considerably across tumor histologies and patient populations.”

    From PathTIGR: A pathway topology-informed graph representation learning framework for immunotherapy response prediction (2026) · cites this paper as [12]

  • PD-L1 expression and tumor mutational burden are established predictive markers in NSCLC.

    “While programmed death ligand 1 (PD-L1) expression and tumor mutational burden are established predictive markers, their clinical utility is limited by spatial heterogeneity, assay variability, and dynamic changes during therapy [4].”

    From SUVmax-IPI as a New Prognostic Index in Metastatic Non-Small Cell Lung Cancer Patients Receiving Nivolumab (2025) · cites this paper as [4]

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Cited by

Sorted by citations

Authors
Havel, J. J., Chowell, D., & Chan, T. A.
Affiliations
Memorial Sloan Kettering Cancer Center (US)
Corresponding author
Chan, Timothy A.
ORCID
Venue
Nature Reviews Cancer
Publisher
Springer Science and Business Media LLC
Published
2019-02-12
Volume
19
Issue
3
Pages
133-150
ISSN
  • 1474-175X (ISSN-L)
  • 1474-1768
DOI
10.1038/s41568-019-0116-x
PMC
PMC6705396
OpenAlex
W2914335731
Cited by
2,286
References
67
Citations by year
2026: 140 · 2025: 208 · 2024: 278 · 2023: 310 · 2022: 360 · 2021: 439 · 2020: 407 · 2019: 140
FWCI
32.31
Type
journal article
Language
en
Open access
Licence
www.springer.com/tdm (tdm)
Locations
  • Nature reviews. Cancer (publishedVersion)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion)
Funders
  • National Institutes of Health
  • National Cancer Institute (T32CA160001, R01CA205426, P30CA008748)
Topics
  • Health Sciences › Medicine › Oncology › Cancer Immunotherapy and Biomarkers
  • Life Sciences › Immunology and Microbiology › Immunology › Immunotherapy and Immune Responses
  • Life Sciences › Immunology and Microbiology › Immunology › T-cell and B-cell Immunology
Keywords
immune checkpoint inhibitors, biomarkers, CTLA-4, PD-1 pathway, PD-L1 expression, cancer genomics, tumor microenvironment, gut microbiota, immunotherapy response, immunotherapy resistance, precision oncology, tumor-host interaction
MeSH terms
Animals, Humans, Immunologic Factors, Immunotherapy, Neoplasms, Tumor Microenvironment, B7-H1 Antigen, CTLA-4 Antigen

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