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- Title
The Impact of Mutational Hotspots on Cancer Survival.
- Authors
Gonzalez-Cárdenas, Melissa; Treviño, Víctor
- Abstract
Simple Summary: In cancer, hotspots are those mutations emerging recurrently in tumors. Hotspots are highly likely to be functional because tumors tend to keep those mutations that provide physiological advantages. However, few hotspots have been studied, mainly because it is costly and time-consuming. Here, we systematically test more than 1400 hotspots for their association with patient survival and provide the results, including more than 300 significant associations, accessible on the web. This would help prioritize hotspots that are likely functional and affect patient survival, accelerating our knowledge of cancer and improving patient care. Background: Cofactors, biomarkers, and the mutational status of genes such as TP53, EGFR, IDH1/2, or PIK3CA have been used for patient stratification. However, many genes exhibit recurrent mutational positions known as hotspots, specifically linked to varying degrees of survival outcomes. Nevertheless, few hotspots have been analyzed (e.g., TP53 and EGFR). Thus, many other genes and hotspots remain unexplored. Methods: We systematically screened over 1400 hotspots across 33 TCGA cancer types. We compared the patients carrying a hotspot against (i) all cases, (ii) gene-mutated cases, (iii) other mutated hotspots, or (iv) specific hotspots. Due to the limited number of samples in hotspots and the inherent group imbalance, besides Cox models and the log-rank test, we employed VALORATE to estimate their association with survival precisely. Results: We screened 1469 hotspots in 6451 comparisons, where 314 were associated with survival. Many are discussed and linked to the current literature. Our findings demonstrate associations between known hotspots and survival while also revealing more potential hotspots. To enhance accessibility and promote further investigation, all the Kaplan–Meier curves, the log-rank tests, Cox statistics, and VALORATE-estimated null distributions are accessible on our website. Conclusions: Our analysis revealed both known and putatively novel hotspots associated with survival, which can be used as biomarkers. Our web resource is a valuable tool for cancer research.
- Subjects
TUMOR risk factors; TUMOR genetics; DISEASE clusters; RISK assessment; CANCER relapse; CANCER patient medical care; TUMOR markers; LOG-rank test; KAPLAN-Meier estimator; GENETIC mutation; SURVIVAL analysis (Biometry); TUMORS; QUALITY assurance; COMPARATIVE studies; PROPORTIONAL hazards models
- Publication
Cancers, 2024, Vol 16, Issue 5, p1072
- ISSN
2072-6694
- Publication type
Article
- DOI
10.3390/cancers16051072