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Discovering the Possibilities of I-O Biomarkers

With a focus on precision medicine, our research and development program aims to rapidly translate research into novel regimens to accelerate delivery of the right treatment, for the right patient, at the right time.

To accelerate our ability to identify precision medicine solutions for individual patients, BMS is pursuing a unique multifaceted approach to translational medicine. Based upon our comprehensive analysis of the tumor microenvironment, including tumor-intrinsic signaling and immune biology, BMS aims to identify clinical characteristics and Immuno-Oncology (I-O) biomarkers to determine the patient populations most likely to benefit from I-O therapy.

I-O biomarkers may be used to determine the immune potential of the tumor microenvironment

  • Research in the field of I-O biomarkers seeks to characterize the relationship between the immune system, the tumor and its microenvironment, and the host
  • Unique interactions among these factors contribute to the balance between activation and suppression of the antitumor immune response1-3
  • Tumors can be characterized based on their degree of immune-cell infiltration, ranging from noninflamed to inflamed4

I-O biomarkers that can identify inflamed tumors may help predict a pre-existing antitumor immune response.3,5

To identify I-O biomarkers that clarify this unique interplay between the immune system and the tumor, BMS biomarker research is focused on four key areas:

I-O biomarkers may be used to advance precision medicine, enabling tailored therapeutic solutions for individualized patients

  • For each patient, the interaction of the immune system, cancer, and therapy is complex and unique
  • Therefore, the goal of I-O biomarker development is to enable a more personalized approach to treatment by identifying patients who are likely to respond to specific immunotherapies3,5,8

BMS is committed to the exploration of biomarkers in I-O research. This includes the evaluation of multiple biomarkers, as a composite biomarker approach may provide a more accurate and comprehensive assessment of the tumor and tumor microenvironment.

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I-O Biomarkers: Under investigation for their role in immuno-therapy

See how several biomarkers are under investigation for their potential to predict response to immunotherapy

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REFERENCES–Discovering the possibilities of I-O biomarkers

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PD-L1 expression in human cancers and its association with clinical outcomes. Onco Targets Ther. 2016;9:5023-5039. 24. Patel SP, Kurzrock R. PD-L1 expression as a predictive biomarker in cancer immunotherapy. Mol Cancer Ther. 2015;14(4):847-856. 25. Van Allen EM, Wagle N, Levy MA. Clinical analysis and interpretation of cancer genome data. J Clin Oncol. 2013;31(15):1825-1833. 26. Davies H, Bignell GR, Cox C, et al. Mutations of the BRAF gene in human cancer. Nature. 2002;417(6892):949-954. 27. Mok TS. Personalized medicine in lung cancer: what we need to know. Nat Rev Clin Oncol. 2011;8(11):661-668. 28. Jakobsen JN, Santoni-Rugiu E, Ravn J, Sørensen JB. Intratumour variation of biomarker expression by immunohistochemistry in resectable non-small cell lung cancer. Eur J Cancer. 2013;49(11):2494-2503. 29. Henry NL, Hayes DF. Cancer biomarkers. Mol Oncol. 2012;6(2):140-146. 30. Strimbu K, Tavel JA. What are biomarkers? Curr Opin HIV AIDS. 2010;5(6):463-466. 31. Yu SL, Xu LT, Qi Q, et al. 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Radich JP, Gooley T, Bryant E, et al. The significance of bcr-abl molecular detection in chronic myeloid leukemia patients “late,” 18 months or more after transplantation. Blood. 2001;98(6):1701-1707. 39. Yuda J, Miyamoto T, Odawara J, et al. Persistent detection of alternatively spliced BCR-ABL variant results in a failure to achieve deep molecular response. Cancer Sci. 2017;108(11):2204-2212. 40. Ren R. Mechanisms of BCR-ABL in the pathogenesis of chronic myelogenous leukaemia. Nat Rev Cancer. 2005;5(3):172-183. 41. An X, Tiwari AK, Sun Y, Ding PR, Ashby CR, Chen ZS. BCR-ABL tyrosine kinase inhibitors in the treatment of Philadelphia chromosome positive chronic myeloid leukemia: a review. Leuk Res. 2010;34(10):1255-1268. 42. Long EO, Kim HS, Liu D, Peterson ME, Rajagopalan S. Controlling natural killer cell responses: integration of signals for activation and inhibition. Annu Rev Immunol. 2013;31:227-258. 43. Pardoll DM. The blockade of immune checkpoints in cancer immunotherapy. 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