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Mechanism-driven biomarkers to guide immune checkpoint blockade in cancer therapy

Nature Reviews Cancer volume 16, pages 275–287 (2016)Cite this article

Subjects

Key Points

  • Exploration for biomarkers for drugs that block immune checkpoints should be rationally conducted based on knowledge of the mechanism of action of the targeted pathway. The programmed cell death protein 1 (PD1) and cytotoxic T lymphocyte associated antigen 4 (CTLA4) pathways are unique, and there are special considerations based on mechanisms of action for developing biomarkers for drugs blocking each of these pathways.

  • Biomarkers for immune checkpoint-blocking drugs currently fall into three major categories: immunological, genetic and virological. Future work may reveal additional markers related to metabolism and the microbiome.

  • Immunological biomarkers offer the advantage of applicability across multiple tumour types amenable to immune checkpoint blockade. In the case of anti-PD1 drugs, tumour PD1 ligand 1 (PDL1) expression is a pretreatment biomarker that predicts a greater likelihood of response to therapy. Despite technical pitfalls that make clinical application challenging, two PDL1 immunohistochemistry tests are currently approved by the US Food and Drug Administration for guiding treatment decisions in patients with non-small-cell lung cancer and melanoma.

  • Although no specific oncogene or driver mutation has yet been correlated with clinical response to immune checkpoint blockade, overall tumour mutational burden reflecting neoantigenic diversity may have predictive value. This is exemplified by the high anti-PD1 response rate in DNA mismatch repair deficient colorectal cancers (which have a large mutational burden and which account for ∼15% of all colon cancers), whereas mismatch repair proficient colon cancers are unlikely to respond.

  • Virus-associated cancers, which account for more than 20% of cancers worldwide, express viral neoantigens that are strongly immunogenic. Early evidence demonstrates expression of PD1–PDL1 in these cancers, and suggests responsiveness to anti-PD1 therapies.

  • Combination treatment regimens based on immune checkpoint-blocking drugs are emerging as the next step in clinical development to improve efficacy and response durability. Biomarker considerations for these regimens are complex and are likely to involve multifactorial assessments.

Abstract

With recent approvals for multiple therapeutic antibodies that block cytotoxic T lymphocyte associated antigen 4 (CTLA4) and programmed cell death protein 1 (PD1) in melanoma, non-small-cell lung cancer and kidney cancer, and additional immune checkpoints being targeted clinically, many questions still remain regarding the optimal use of drugs that block these checkpoint pathways. Defining biomarkers that predict therapeutic effects and adverse events is a crucial mandate, highlighted by recent approvals for two PDL1 diagnostic tests. Here, we discuss biomarkers for anti-PD1 therapy based on immunological, genetic and virological criteria. The unique biology of the CTLA4 immune checkpoint, compared with PD1, requires a different approach to biomarker development. Mechanism-based insights from such studies may guide the design of synergistic treatment combinations based on immune checkpoint blockade.

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Figure 1: Opportunities for biomarker development based on mechanistic nodes in immune checkpoint pathways.
Figure 2: Mechanisms for intratumoural PDL1 expression.
Figure 3: PDL1 expression patterns in different types of cancer.
Figure 4: Multifactorial biomarkers of clinical response to PD1 pathway blockade.

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Acknowledgements

The authors are grateful to M. Hellmann (Memorial Sloan-Kettering Cancer Center, New York, USA), E. Garon (University of California Los Angeles, USA) and J. Brahmer (Johns Hopkins University, Baltimore, Maryland, USA) for helpful discussions. This work was supported by research funding from Bristol-Myers Squibb (S.L.T., J.M.T., R.A.A. and D.M.P.), the Melanoma Research Alliance (S.L.T., J.M.T. and D.M.P.), the US National Cancer Institute NIH (R01 CA142779; S.L.T., J.M.T. and D.M.P.), the Barney Family Foundation (S.L.T. and J.M.T.), the Dermatology Foundation (J.M.T.), the Laverna Hahn Charitable Trust (S.L.T.), the Commonwealth Foundation (D.M.P.), the W.W. Smith Charitable Trust (J.M.T.) and Moving for Melanoma Delaware (S.L.T., J.M.T. and D.M.P.). All authors were also supported by a Stand Up To Cancer—Cancer Research Institute Cancer Immunology Translational Research Grant (SU2C-AACR-DT1012). Stand Up To Cancer is a programme of the Entertainment Industry Foundation administered by the American Association for Cancer Research.

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Authors and Affiliations

  1. Department of Surgery, Johns Hopkins University School of Medicine, Sidney Kimmel Comprehensive Cancer Center and Bloomberg–Kimmel Institute for Cancer Immunotherapy, 1550 Orleans Street, CRB2 Room 508, Baltimore, 21287, Maryland, USA

    Suzanne L. Topalian

  2. Department of Dermatology, Johns Hopkins University School of Medicine, Sidney Kimmel Comprehensive Cancer Center and Bloomberg–Kimmel Institute for Cancer Immunotherapy, 1550 Orleans Street, CRB2 Room 508, Baltimore, 21287, Maryland, USA

    Janis M. Taube

  3. Department of Oncology, Johns Hopkins University School of Medicine, Sidney Kimmel Comprehensive Cancer Center and Bloomberg–Kimmel Institute for Cancer Immunotherapy, 1550 Orleans Street, CRB2 Room 508, Baltimore, 21287, Maryland, USA

    Janis M. Taube & Drew M. Pardoll

  4. Department of Pathology, Johns Hopkins University School of Medicine, Sidney Kimmel Comprehensive Cancer Center and Bloomberg–Kimmel Institute for Cancer Immunotherapy, 1550 Orleans Street, CRB2 Room 508, Baltimore, 21287, Maryland, USA

    Janis M. Taube & Robert A. Anders

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  1. Suzanne L. Topalian
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Correspondence to Suzanne L. Topalian.

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Competing interests

S.L.T., research grants from Bristol-Myers Squibb, and consulting for Five Prime Therapeutics, GlaxoSmithKline and Jounce Therapeutics. J.M.T., research support from Bristol-Myers Squibb, and consulting for Bristol-Myers Squibb, Merck and AstraZeneca. R.A.A., research support from Five Prime Therapeutics and Bristol-Myers Squibb, and consulting for Adaptive Biotechnologies. D.M.P., research grants from Bristol-Myers Squibb and Potenza Therapeutics; consulting for Amgen, Five Prime Therapeutics, GlaxoSmithKline, Jounce Therapeutics, MedImmune, Merck, Pfizer, Potenza Therapeutics, Sanofi and Tizona; stock options in Jounce, Potenza and Tizona; and patent royalties through his institution, from AstraZeneca, Bristol-Myers Squibb and Potenza.

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Glossary

Tolerance

An immunological phenomenon in which antigen-specific T and/or B cells are absent or unresponsive to antigen-bearing cells, as opposed to rejection, in which antigen-specific immune cells eliminate their targets.

Mixed tumour regression

A therapeutic response pattern in which different metastatic lesions in an individual patient show different responses to therapy, some regressing whereas others progress.

Regulatory T cells

(Treg cells). A subset of CD4+ T cells characterized by expression of the forkhead box transcription factor FOXP3, which interacts with other immune cells to inhibit immune responses.

Adaptive immune system

Comprises T and B lymphocytes with unique antigen receptors generated by somatic DNA recombination events, as compared with the innate immune system, which comprises cells with invariant antigen receptors (for example, natural killer cells and macrophages).

Tertiary lymphoid structure

Ectopic lymphoid tissue that recapitulates some of the structural organization of a lymph node (including T cells, B cells, antigen presenting cells and high endothelial venules) and can support the generation of an adaptive immune response.

Adaptive immune resistance

A phenomenon in which tumour and stromal cells adapt to attack from infiltrating T cells by expressing the immune inhibitory ligand programmed cell death 1 ligand 1 (PDL1). In this scenario, PDL1 expression is driven by inflammatory cytokines such as interferon-γ secreted by tumour antigen-specific T cells.

Objective response rate

The rate of significant tumour regressions in patients undergoing cancer therapy, including complete and partial regressions as defined by standard oncological criteria (for example, Response Evaluation Criteria In Solid Tumours (RECIST), or World Health Organization (WHO) criteria).

Neoantigens

Newly expressed tumour antigens that arise from genetic alterations in tumour cells and are therefore not present in normal cells, such as antigens generated by somatic (non-heritable) mutations or oncoviruses.

Self-antigen

In the context of tumour antigens, a non-mutated component of tumour cells that is also expressed by some normal cells and can be recognized by the immune system.

Anergy

A functional state of T cells in which they are hyporesponsive to T cell receptor engagement by cognate antigen, relative to naive or memory T cells.

DNA mismatch repair complex

(MMR complex). A complex of enzymes that recognizes DNA base mismatches introduced during DNA replication, excises them and replaces them with correctly matched bases.

Microsatellite instability

(MSI). A hallmark of defects in DNA mismatch repair, characterized by alterations in the frequency of repeated DNA sequences (microsatellites).

TH1 phenotype

Differentiation state of CD4+ T cells characterized by production of interferon-γ (in addition to other cytokines) upon encountering cognate antigen.

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Topalian, S., Taube, J., Anders, R. et al. Mechanism-driven biomarkers to guide immune checkpoint blockade in cancer therapy. Nat Rev Cancer 16, 275–287 (2016). https://doi.org/10.1038/nrc.2016.36

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