Advances and Prospects of Biomarkers for Immune Checkpoint Inhibitors Immune checkpoint inhibitors (ICIs) enhance anti-cancer immunity by blocking T cell checkpoint molecules such as PD-1 and CTLA-4. Despite their efficacy, ICIs have limitations, including low response rates, severe side effects, and high costs. Biomarkers are essential for selecting patients who will benefit from ICI treatment and improving their efficiency. This review summarizes established and potential biomarkers for ICI therapy, including PD-L1 expression, DNA mismatch repair deficiency, microsatellite instability high, and tumor mutational burden. Potential biomarkers under investigation include tumor-infiltrating and peripheral lymphocytes, gut microbiome, and signaling pathways related to DNA damage and antigen presentation. PD-L1 expression is a key biomarker for anti-PD-1/PD-L1 therapy. Immunohistochemical (IHC) staining is the primary method for assessing PD-L1. FDA-approved antibodies, such as SP142, 22C3, 28-8, and SP263, are used for PD-L1 detection. PD-L1 expression varies among cancer types and influences ICI efficacy. However, PD-L1 glycosylation can lead to false-negative results, complicating detection. A refined protocol involving pre-treatment glycosylation removal before IHC staining has improved PD-L1 detection. Tumor-infiltrating lymphocytes (TILs) are also potential biomarkers for ICIs. TILs are associated with improved clinical outcomes in various cancers. However, PD-L1 expression is heterogeneous within and between tumors, leading to sampling errors. PD-L1 expression can vary over time due to tumor progression and treatment. TILs and other biomarkers, such as TMB and MSI-H, are being evaluated for their predictive value in ICI therapy. The gut microbiome plays a significant role in ICI response. High gut microbiome diversity is associated with better response to anti-PD-1 therapy in melanoma patients. Specific microbial species, such as Bifidobacteriaceae spp., Coriobacteriaceae spp., Ruminococcaceae spp., and Lachnospiraceae spp., are correlated with better ICI response. Strategies to target the microbiome, such as fecal microbiota transplantation, are being studied to enhance ICI efficacy and reduce side effects. Other immune checkpoints, such as LAG-3, TIM-3, and TIGIT, are being explored as potential targets for ICI therapy. LAG-3, TIM-3, and TIGIT interact with their ligands to deliver negative signals and inhibit T cell function, acting as a compensatory mechanism of ICI resistance. Biomarkers for these checkpoints are being investigated to improve patient selection and treatment outcomes. In addition to tumor tissue-based biomarkers, plasma biomarkers such as circulatingAdvances and Prospects of Biomarkers for Immune Checkpoint Inhibitors Immune checkpoint inhibitors (ICIs) enhance anti-cancer immunity by blocking T cell checkpoint molecules such as PD-1 and CTLA-4. Despite their efficacy, ICIs have limitations, including low response rates, severe side effects, and high costs. Biomarkers are essential for selecting patients who will benefit from ICI treatment and improving their efficiency. This review summarizes established and potential biomarkers for ICI therapy, including PD-L1 expression, DNA mismatch repair deficiency, microsatellite instability high, and tumor mutational burden. Potential biomarkers under investigation include tumor-infiltrating and peripheral lymphocytes, gut microbiome, and signaling pathways related to DNA damage and antigen presentation. PD-L1 expression is a key biomarker for anti-PD-1/PD-L1 therapy. Immunohistochemical (IHC) staining is the primary method for assessing PD-L1. FDA-approved antibodies, such as SP142, 22C3, 28-8, and SP263, are used for PD-L1 detection. PD-L1 expression varies among cancer types and influences ICI efficacy. However, PD-L1 glycosylation can lead to false-negative results, complicating detection. A refined protocol involving pre-treatment glycosylation removal before IHC staining has improved PD-L1 detection. Tumor-infiltrating lymphocytes (TILs) are also potential biomarkers for ICIs. TILs are associated with improved clinical outcomes in various cancers. However, PD-L1 expression is heterogeneous within and between tumors, leading to sampling errors. PD-L1 expression can vary over time due to tumor progression and treatment. TILs and other biomarkers, such as TMB and MSI-H, are being evaluated for their predictive value in ICI therapy. The gut microbiome plays a significant role in ICI response. High gut microbiome diversity is associated with better response to anti-PD-1 therapy in melanoma patients. Specific microbial species, such as Bifidobacteriaceae spp., Coriobacteriaceae spp., Ruminococcaceae spp., and Lachnospiraceae spp., are correlated with better ICI response. Strategies to target the microbiome, such as fecal microbiota transplantation, are being studied to enhance ICI efficacy and reduce side effects. Other immune checkpoints, such as LAG-3, TIM-3, and TIGIT, are being explored as potential targets for ICI therapy. LAG-3, TIM-3, and TIGIT interact with their ligands to deliver negative signals and inhibit T cell function, acting as a compensatory mechanism of ICI resistance. Biomarkers for these checkpoints are being investigated to improve patient selection and treatment outcomes. In addition to tumor tissue-based biomarkers, plasma biomarkers such as circulating