A Systematic Review and Meta-Analysis of the Impact of Tumour Mutation Burden on Survival Outcomes in Solid Tumours.
Tumour mutation burden (TMB) is an emerging pan-cancer biomarker with predictive value for immune checkpoint inhibitor (ICI) outcomes, yet evidence is inconsistent due to methodological variability and cut-off thresholds. This systematic review and meta-analysis evaluated the impact of TMB on overall survival (OS) and progression-free survival (PFS) across solid tumours in ICI-treated cohorts and its predictive relevance in non-ICI-treated cohorts.
Following PRISMA 2020 guidelines, we searched PubMed, Scopus, ScienceDirect and Cochrane for studies published between 2010 and 2024 reporting hazard ratios (HRs) and 95% confidence intervals (CIs) for OS and PFS in high- versus low-TMB cohorts. High and low TMB were defined by study-specific cut-offs, and ultra-high TMB was defined as the top 20% of cohort-specific values. Study quality was assessed with the Newcastle-Ottawa Scale; heterogeneity with I2; publication bias with funnel plots/Egger's test; and robustness by leave-one-out analysis.
5278 patients across 28 studies were analysed. High TMB, defined by cohort-specific cut-offs, was significantly associated with improved OS and PFS, particularly in non-small cell lung cancer (OS: HR = 0.56), selected gastrointestinal cancers (OS: HR = 0.36), and advanced/recurrent tumours (OS: HR = 0.52). Benefits were greatest in ICI-treated patients, especially with combined anti-PD-L1/PD-1 and anti-CTLA-4 therapy (OS: HR = 0.47; PFS: HR = 0.50). Chemotherapy-treated cohorts also showed better outcomes, but less consistently (OS: HR = 0.60; PFS: HR = 0.55). Ultra-high TMB had better OS than the universal 10 mut/Mb cut-off (HR = 0.44 vs. 0.58). Non-beneficial associations were observed in glioma and penile squamous cell carcinoma, highlighting disease-specific variability. Sequencing platforms and cut-off definitions remained sources of heterogeneity.
TMB demonstrates prognostic relevance and predictive utility in a histology- and treatment-context-dependent manner, with the most consistent associations in selected ICI-treated tumours. Associations in non-ICI-treated cohorts were weaker and inconsistent, indicating putative predictive value. Standardising TMB assessment and refining relevant thresholds are essential for optimising its role in precision oncology.
PROSPERO Registration Number: CRD42024608809.
Following PRISMA 2020 guidelines, we searched PubMed, Scopus, ScienceDirect and Cochrane for studies published between 2010 and 2024 reporting hazard ratios (HRs) and 95% confidence intervals (CIs) for OS and PFS in high- versus low-TMB cohorts. High and low TMB were defined by study-specific cut-offs, and ultra-high TMB was defined as the top 20% of cohort-specific values. Study quality was assessed with the Newcastle-Ottawa Scale; heterogeneity with I2; publication bias with funnel plots/Egger's test; and robustness by leave-one-out analysis.
5278 patients across 28 studies were analysed. High TMB, defined by cohort-specific cut-offs, was significantly associated with improved OS and PFS, particularly in non-small cell lung cancer (OS: HR = 0.56), selected gastrointestinal cancers (OS: HR = 0.36), and advanced/recurrent tumours (OS: HR = 0.52). Benefits were greatest in ICI-treated patients, especially with combined anti-PD-L1/PD-1 and anti-CTLA-4 therapy (OS: HR = 0.47; PFS: HR = 0.50). Chemotherapy-treated cohorts also showed better outcomes, but less consistently (OS: HR = 0.60; PFS: HR = 0.55). Ultra-high TMB had better OS than the universal 10 mut/Mb cut-off (HR = 0.44 vs. 0.58). Non-beneficial associations were observed in glioma and penile squamous cell carcinoma, highlighting disease-specific variability. Sequencing platforms and cut-off definitions remained sources of heterogeneity.
TMB demonstrates prognostic relevance and predictive utility in a histology- and treatment-context-dependent manner, with the most consistent associations in selected ICI-treated tumours. Associations in non-ICI-treated cohorts were weaker and inconsistent, indicating putative predictive value. Standardising TMB assessment and refining relevant thresholds are essential for optimising its role in precision oncology.
PROSPERO Registration Number: CRD42024608809.
Authors
Meng Meng, Yuile Yuile, Sim Sim, Thavaneswaran Thavaneswaran, Noor Noor, Yeung Yeung, Mehta Mehta, Powell Powell, Zaman Zaman
View on Pubmed