Bringing the next Generation of Immuno-Oncology Biomarkers to the Clinic

Abstract

The recent successes in the use of immunotherapy to treat cancer have led to a multiplicity of new compounds in development. Novel clinical-grade biomarkers are needed to guide the choice of these agents to obtain the maximal likelihood of patient benefit. Predictive biomarkers for immunotherapy differ from the traditional biomarkers used for targeted therapies: the complexity of the immune response and tumour biology requires a more holistic approach than the use of a single analyte biomarker. This paper reviews novel biomarker approaches for the effective development of immune-oncology therapies, highlighting the promise of the advances in next-generation gene expression profiling that allow biologic information to be efficiently organized and interpreted for a maximum predictive value at the individual patient level.

Keywords: NanoString; PanCancer IO360; biomarker; gene expression profiling; gene expression signature; immuno-oncology; immunotherapy.

Figure 1

Actionable immune-based classification of cancer. Ag = antigen; BETi = inhibitors of bromodomain and extraterminal proteins; carbo = carboplatin; CSF1 = colony stimulating factor 1; CFM = cyclophosphamide; CTLA-4 = cytotoxic T-lymphocyte–associated antigen 4; HDAC = histone deacetylase; HMA = hypomethylating agents; IDO = indoleamine 2,3-dioxyenase; IO = immune-oncology; LN = lymph nodes; LAG-3 = lymphocyte-activation gene 3; MDSC = myeloid-derived suppressor cells; P13K = phosphoinositide 3-kinase; PD-1 = programmed cell death-1; PD-L1 = programmed cell death-ligand 1; STING = stimulator of interferon genes; TIM3 = T cell immunoglobulin and mucin domain 3; TME = tumor microenvironment; Treg = regulatory T cells; TLR = toll-like receptor; Wnt = wingless, int-1.