Abstract
Hepatocellular carcinoma (HCC) is the most common type of liver cancer. Unfortunately, it is frequently diagnosed in advanced stages, limiting the available treatment options. Immune checkpoint inhibitors (ICIs) have shown promise in treating HCC, although their effectiveness varies among patients and can result in undesirable side effects. To enhance treatment outcomes and ensure patient safety, close monitoring and early intervention for side effects are necessary. Consequently, the selection of biomarkers that can predict the response to ICIs in HCC becomes crucial. MicroRNAs, which play a vital role in regulating gene expression in HCC, have emerged as potential biomarkers for predicting treatment response. Some microRNAs have been found to affect ICIs such as CTLA-4 and PD-L1, which are the targets of checkpoint inhibitor therapy. By identifying specific microRNAs that can forecast the response to ICIs, healthcare providers can personalize treatment plans for HCC patients. This tailored approach optimizes resource utilization and minimizes the risk of adverse side effects. Ultimately, this personalized strategy can improve treatment outcomes and enhance the quality of life for individuals with HCC. Thus, the selection of microRNAs capable of predicting the response to ICIs in HCC treatment holds significant importance. It has the potential to enhance patient response rates, decrease adverse effects, and optimize the utilization of healthcare resources.
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