Wedding of Molecular Alterations and Immune Checkpoint Blockade

Genomics as a Matchmaker

Elena Fountzilas, MD, PhD; Razelle Kurzrock, MD; Henry Hiep Vo, PhD; Apostolia-Maria Tsimberidou MD, PhD


J Natl Cancer Inst. 2021;113(12):1634-1647. 

In This Article

Other Immune-related Biomarkers

Biomarkers beyond genomics predicting response and resistance to immune checkpoint inhibitors are included in Table 2. High PD-L1 expression, defined using various cutoff points ranging from more than 1% to more than 50%, is associated with clinical benefit in patients with various tumor types, but not in all clinical settings. Other emerging predictive biomarkers include gene expression signatures,[153,154] oral and gut microbiome,[155,156] neo-antigen load,[157,158] PD-1 expression on immune cells,[159] and TCR repertoire.[140,142] Biomarkers predicting susceptibility to immune-related adverse events include circulating pro-inflammatory cytokines[160] and gut microbiota.[155]

Tumor microenvironment typically comprises infiltrating immune cells, such as cytotoxic T cells, helper T-cell subsets, regulatory T cells, tumor-associated macrophages, and dendritic cells. The clinical relevance of the density and location of tumor-infiltrating lymphocytes (TILs) in patients with cancer is currently being investigated. Previous studies have demonstrated that increased TIL concentration is associated with improved prognosis in patients with various tumor types.[162] Whether high TIL concentration is predictive of response to immune checkpoint inhibitors is currently under extensive evaluation.[163] Investigators have shown that higher TIL concentrations are associated with higher response rates and improved clinical outcomes in patients who receive immunotherapy in different clinical settings.[140,164] The presence of a high number of TILs has also been associated with high PD-L1 expression[165,166] and/or MSI-H and dMMR.[167,168] Ongoing and future investigations will address the limitations involving the methodology, interpretation (invasive margin or central infiltration), and cutoff values for TILs and will optimize the standardization of TIL assessment to enable comparisons of various clinical trials.[169]