Biomarkers for checkpoint inhibition in hematologic malignancies

Publication date: Available online 18 June 2018
Source:Seminars in Cancer Biology
Author(s): Djordje Atanackovic, Tim Luetkens
In the past few years we have seen remarkable paradigm shifts in the treatment of many solid tumors due to the introduction of inhibitors targeting immune checkpoints such as PD-1/PD-L1 and CTLA-4. Recent results indicate that checkpoint inhibition also represents a very promising approach for certain types of hematologic malignancies. Unfortunately, treatment with checkpoint inhibitors is also associated with substantial toxicities and high costs and only a subset of patients appears to derive clinical benefit from these treatments. This demonstrates the urgent need for biomarkers for the identification of patient populations that are likely to respond to this type of therapy and/or have fewer side effects. Here, we have reviewed available information on the prognostic and predictive value of biomarkers for anti-CTLA-4 and anti-PD-1/PD-L1 as the most commonly used checkpoint inhibitors. There are currently no reliable biomarkers capable of predicting responses to anti-CTLA-4 agents, such as ipilimumab, in hematologic malignancies. Certain polymorphisms in the CTLA-4 gene, however, seem to have an impact on the patients' outcome, especially in the case of chronic lymphocytic leukemia (CLL). There is now sufficient data supporting PD-L1 expression levels in the tumor tissue as an independent prognostic factor in B cell lymphomas such as diffuse large B-cell lymphoma (DLBCL). Overexpression of PD-L1 in the tumor tissue and elevated serum levels of soluble PD-L1 may also represent adverse prognostic factors in certain subtypes of T cell lymphomas. Finally, expression levels of PD-L1 also seem to predict responses to anti-PD-1/PD-L1 approaches in patients with Hodgkin lymphoma. Future studies will have to further delineate the prognostic/predictive role of PD-L1 expression as a biomarker in hematologic malignancies and may be able to identify confounding variables, which will hopefully to some extent be generalizable to other types of anti-tumor immunotherapies.



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