ESMO 2017: A pool of predictive biomarkers for response to immunotherapy could soon be available to select responsive patients


  • Oncology Conference Roundups
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Where we are

  • The use of immunotherapy in cancer is growing rapidly, with many new indications.
  • Patients response can vary widely even in the presence of similar clinical and genomic biomarkers.
  • In the absence of useful predictive tools for response, the clinical use of immunotherapy can be compromised.
  • Cancer-immune system interactions are based on a number of largely unrelated parameters such as intratumoral inhibition of tumour-specific T cells or the level of “foreignness” of the tumour in order to elicit a clinically relevant T cell response.
  • The effect of these parameters can differ greatly between patients.
  • Because of the multifactorial nature of those interactions, we need validated combinations of biomarker assays.

Take home messages

  • The introduction of an evolving “cancer immunogram” is a useful clinical tool to select patients that are suitable for immunotherapy.
  • New categories of biomarkers will be added in the next months/years. Nonetheless, even an immunogram based on present-day knowledge does make it possible to assess the cancer-immune interactions in individual patients.

New perspectives

  • Prof. Christian Blank from the Netherlands Cancer Institute proposed and discussed a pool of biomarkers (cancer immunogram), to be used in clinic to assess the cancer-immune system interaction in individual patients.

1. Tumour foreignness: data suggest that it may be determined in large part by the expression of neoantigens derived from viral or mutated gene products.

  • The presence of neoantigens is probabilistic: tumour foreignness can be guaranteed only for tumours with very high mutational loads, and can only be inferred for tumours with an intermediate or low mutational load; more sophisticated readouts are required.

2. General immune status: a decrease in lymphocyte counts has been associated with poor outcome upon cytotoxic T lymphocyte antigen 4 blockade in patients with melanoma cohorts.

  • Neutrophil/lymphocyte ratio has been correlated with poor patient outcome after immunotherapy, as myeloid-derived suppressor cell count in circulating blood is a negative predictor.
  • Elevated eosinophil counts may be associated with improved outcome in patients with melanoma treated with anti-cytotoxic T lymphocyte antigen 4 antibody.

3. Immune cell infiltration: absence of T cell infiltration may reflect a defect at the level of T cell priming, a mechanical barrier due to cancer-associated fibrosis.

4. Absence of checkpoints: the expression profile of both T cell checkpoints and their ligands is likely to be a valuable biomarker because it is related to the presence of specific therapeutic targets.

5. Absence of soluble inhibitors: tumour-promoting effects of     inflammation can be mediated through suppression of T cell reactivity.

  • Increase in inflammatory markers (C-reactive protein or erythrocyte sedimentation rate) is associated with poor outcome in anti-cytotoxic T lymphocyte antigen 4 antibody treatment; the presence of an interferon gene signature in tumours was associated with improved outcome upon programmed cell death 1 blockade.

6. Absence of inhibitor tumour metabolism: high serum lactate dehydrogenase concentrations correlate strongly with poor outcome in cytotoxic T lymphocyte antigen 4 and programmed cell death 1 blockade (phase 3 clinical trial data).

  • Lactic acid and low local pH can impair crucial T cell functions, such as cytokine production, proliferation, and lytic activity.
  • Intratumoral hypoxia and glucose depletion also deserve attention as potential biomarkers in this class (mouse model data).

7. Tumour sensitivity to immune effectors: analysis of immunotherapy resistance at the level of tumour cell sensitivity to immune effectors will be useful to identify patients who are less likely to respond to T cell-activating therapies.

8. Microbiome: gut microbiome is an emerging biomarker for immunotherapy response.

  • Faecal transplants from human non-responder patients to responder mice and subsequent resistance to immunotherapy in the animal model demonstrate the immunomodulating properties of microbiome. Further studies are needed.