Co-Mutation Landscape of PIK3CA Across Multiple Adenocarcinomas: Insights from TCGA Data
DOI:
https://doi.org/10.37609/srinmed.72Keywords:
PIK3CA, Co-mutation analysis, TCGA, Cancer genomics, Precision oncologyAbstract
Objective: PIK3CA is one of the most frequently mutated oncogenes across multiple cancer types, playing a crucial role in tumorigenesis via the PI3K/AKT/mTOR signaling pathway. Understanding its genuine co-mutation landscape is essential for identifying oncogenic interactions and refining targeted therapeutic strategies. In this study, we analyzed the true functional co-mutation patterns of PIK3CA in colorectal adenocarcinoma (COAD), cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC), stomach adenocarcinoma (STAD), and lung adenocarcinoma (LUAD).
Method: Somatic mutation data were obtained from The Cancer Genome Atlas (TCGA). Co-mutation and mutual exclusivity analyses were performed using R (maftools). To rigorously distinguish genuine biological cooperativity from confounding background mutation rates, multivariate logistic regression models were implemented, incorporating tumor mutational burden (TMB) continuous covariate.
Results: TMB-adjusted analyses revealed distinct, robust co-occurrence and mutual exclusivity relationships across cancer types, filtering out passenger mutations. In COAD, PIK3CA mutations significantly co-occur with KRAS, suggesting a cooperative role in tumorigenesis, while maintaining strict mutual exclusivity with TP53. In STAD, PIK3CA exhibits a strong, true functional co-occurrence with the chromatin remodeling gene ARID1A, while maintaining mutual exclusivity with TP53 and CSMD3. Interestingly, in both LUAD and CESC, PIK3CA demonstrates a highly significant mutual exclusivity with the mucin gene MUC17, pointing to context-specific evolutionary trajectories.
Conclusion: These findings highlight the complex, TMB-independent molecular landscape of PIK3CA-driven tumors, emphasizing the necessity of cancer-type-specific therapeutic approaches. By utilizing robust TMB-adjusted models, this study successfully isolates true genetic interactions, providing valuable insights into potential drug resistance mechanisms and novel combination therapy strategies for PIK3CA-mutant cancers.
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