Zgura Anca, Chipuc Stefania, Bacalbasa Nicolae, Haineala Bogdan, Rodica Anghel, Sebastian Vâlcea
Department of Oncology-Radiotherapy, Prof. Dr. Alexandru Trestioreanu Institute of Oncology, "Carol Davila" University of Medicine and Pharmacy, 020021 Bucharest, Romania.
Prof. Dr. Alexandru Trestioreanu Institute of Oncology, 022328 Bucharest, Romania.
Cancers (Basel). 2025 Feb 1;17(3):480. doi: 10.3390/cancers17030480.
BACKGROUND: Tumour mutational burden (TMB) is an emerging biomarker for predicting the efficacy of immune checkpoint inhibitors (ICIs) in cancer therapy. While its role is well established in lung cancer and melanoma, its predictive value for breast and prostate cancers remains unclear. OBJECTIVE: This systematic review aimed to assess the predictive value of TMB for ICI therapy across four major cancer types-lung, melanoma, breast, and prostate-and to explore factors contributing to the variability in its effectiveness as a biomarker. METHODS: A systematic search and a review of the literature were conducted in accordance with PRISMA guidelines. Studies examining the relationship between TMB levels and clinical outcomes following ICI therapy in the specified cancers were analyzed. The data were synthesized to evaluate TMB's predictive value and identify gaps in the current research. RESULTS: High TMB consistently correlated with improved outcomes in lung cancer and melanoma, confirming its predictive utility in these cancers. Conversely, the findings for breast and prostate cancers were inconclusive. The variability in TMB's predictive value for these cancers suggests the need for complementary biomarkers or refined criteria to enhance its reliability. Methodological inconsistencies in TMB evaluation were also noted as a significant limitation. CONCLUSIONS: TMB serves as a robust biomarker for predicting ICI response in lung cancer and melanoma, but demonstrates limited predictive utility in breast and prostate cancers. Future research should prioritize standardizing TMB assessment protocols and investigating additional biomarkers to improve treatment personalization for these cancer types.
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