Fariha, Luluel MaknunMuntasir, Md2026-08-232026-08-2320262026-05ID 19346072https://hdl.handle.net/10361/29449This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Pharmacy, 2026.Cataloged from PDF version of thesis.Includes bibliographical references (pages 19-28).Tumor Mutation Burden (TMB) has become one of the most popular predictive biomarkers to determine the application of immune checkpoint inhibitors (ICIs) in cancer treatment, on the grounds that a higher somatic mutation burden has a higher neoantigen load and, as such, is more easily recognized by the immune system. TMB has become a solid part of tumor-agnostic clinical decision-making, with the tumor-agnostic approval of pembrolizumab on solid tumors with TMB of ten or more mutations per megabase by the United States Food and Drug Administration, but its predictive capabilities across cancer types, sequencing systems, and pipelines can vary significantly. This study discusses TMB's biological nature, estimation methods, and clinical results in diverse cancers using peer-reviewed literature, breakthrough clinical studies, and regulatory data. The results reveal that TMB is a context-specific but significant biomarker. Its predictive capacity in classifications with mutational load as the leading driver of immunogenicity such as melanoma, non-small cell lung cancer, and microsatellite instability-high tumors, but is diluted in histologies with low mutational loads or in tumors that contain immunosuppressive microenvironment, intra-tumoral heterogeneity, and other immune-evasion strategies. The lack of a universally validated cut-off, variability based on platforms and inequities in access to genomic testing are the main obstacles to wider adoption. TMB is always better predicted with complementary biomarkers including PD-L1, microsatellite instability, and tumor-infiltrating lymphocyte signals. It concludes that TMB is part of a multi-biomarker system to select immunotherapy patients and that future developments will rely on harmonized measurement standards, histology-specific thresholds, prospective real-world validation, artificial intelligence, and liquid-biopsy systems.40 pagesen-USAttribution-NonCommercial-NoDerivatives 4.0 InternationalBRAC University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission.http://creativecommons.org/licenses/by-nc-nd/4.0/Tumor mutation burdenCancer treatmentImmune checkpoint inhibitorsPredictive biomarkersImmunotherapyPD-L1 inhibitorsPrecision oncologyNext-generation sequencingMicrosatellite instabilityCancer--Immunotherapy.Cancer--Research.Cancer--Immunological aspects.Tumor markers--Diagnostic use.Thesis