Abstract
Over the past decade, immune checkpoint blockade (ICB) therapy has revolutionized the outlook for oncology with significant and sustained improvement in the overall patient survival. Unlike traditional cancer therapies, which target the cancer cells directly, ICB acts on the immune system to enhance anti-tumoral immunity. However, the response rate is still far from satisfactory and most patients are refractory to such treatment. Unfortunately, the mechanisms underlying such heterogeneous responses between patients to ICB therapy remain unclear. In addition, escalating costs of cancer care and unnecessary immune-related adverse events also are pertinent considerations with applications of ICB. Given these issues, identifying explicit predictive biomarkers for patient selection is an urgent unmet need to increase the efficacy of ICB therapy. The markers can be classified as tumor related and non-tumor-related biomarkers. Although substantial efforts have been put into investigating various biomarkers, none of them has been found to be sufficient for effectively stratifying patients who may benefit from immunotherapy. The present write up is an attempt to review the various emerging clinically relevant biomarkers affecting the efficacy of immune checkpoint inhibitors, as well as the limitations associated with their clinical application.
Highlights
Conventional oncological treatments such as surgery, chemotherapy, radiotherapy, as well as targeted therapy remained the cornerstones for cancer treatment
The results suggested that the occurrence of more somatic mutations can lead to an increased neoantigen production and trigger a stronger immune response to eradicate tumor [27, 28], and tumor mutation burden (TMB) may be predictive of responsiveness to immune checkpoint blockade (ICB) therapy [29]
The results showed that Beta2 microglobulin (B2M) aberrations including point mutations, deletions or a loss of heterozygosity (LOH) were closely associated with tumor evasion of CD8+ Tcell responses, disease progression and resistance to ICB
Summary
Conventional oncological treatments such as surgery, chemotherapy, radiotherapy, as well as targeted therapy remained the cornerstones for cancer treatment. In patients with advanced HCC (Hepatocellular Carcinoma), the predictive value of PD-L1 expression on tumor cells did not directly correlate with the patient response to anti-PD1 therapy according to the data from CheckMate 040 clinical trial [14]. Gene expression profiling (GEP) of tumor cells could serve as a predictive biomarker to monitor the efficacy of ICB.
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