Novel Biomarkers for Personalized Cancer Immunotherapy

Abstract

Cancer immunotherapy has emerged as a novel and effective treatment strategy for several types of cancer. Immune checkpoint inhibitors (ICIs) have recently demonstrated impressive clinical benefit in some advanced cancers. Nonetheless, in the majority of patients, the successful use of ICIs is limited by a low response rate, high treatment cost, and treatment-related toxicity. Therefore, it is necessary to identify predictive and prognostic biomarkers to select the patients who are most likely to benefit from, and respond well to, these therapies. In this review, we summarize the evidence for candidate biomarkers of response to cancer immunotherapy.

Keywords: Ki-67 expression; biomarkers; cancer immunotherapy; immune checkpoint inhibitors; microbiome; neoantigen; programmed cell death ligand 1; tumor microenvironment; tumor mutation burden.

Figure 1

Cancer immunotherapy treatment outcomes based on predictive biomarkers. Conventional immunotherapies were performed without a predictive biomarker, hence the benefit was low. Patients with a high tumor mutation burden (TMB) or deficient mismatch repair gene (MMR) will respond well to the immune check point inhibitor (ICI) alone. Patients with a high amount of regulatory T cells (Treg) and/or myeloid-derived suppressor cells (MDSC) will require combination immunotherapy of ICI and agents that resolve suppressive immunity. Patients with cold tumors and/or low Ki-67 expression in peripheral blood mononuclear cells (PBMC) will require a combination therapy of ICI and immune adjuvants as well as vaccination against the neoantigens. Patients with a low percentage of peripheral lymphocytes might be regarded as unsuitable candidates for immunotherapy.