Immune checkpoint inhibitors are a promising strategy in the treatment of cancer, especially advanced types. However, not all patients are responsive to immune checkpoint inhibitors. The response rate depends on the immune microenvironment, tumor mutational burden (TMB), expression level of immune checkpoint proteins, and molecular subtypes of cancers. Along with the Cancer Genome Project, various open access databases, including The Cancer Genome Atlas and Gene Expression Omnibus, provide large volumes of data, which allow researchers to explore responsive or resistant biomarkers of immune checkpoint inhibitors. In this review, we introduced some methodologies on database selection, biomarker screening, current progress of immune checkpoint blockade in solid tumor treatment, possible mechanisms of drug resistance, strategies of overcoming resistance, and indications for immune checkpoint inhibitor therapy.
Keywords: data mining; immune checkpoint blockade; resistance; sensitivity.