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Presence of Concurrent TP53 Mutations Is Necessary to Predict Poor Outcomes within the SMAD4 Mutated Subgroup of Metastatic Colorectal Cancer.


ABSTRACT: Prior studies have resulted in conflicting conclusions on the value of SMAD4 mutations as a prognostic biomarker in metastatic colorectal cancer. In this study, the impact of coexisting mutations with SMAD4 on overall survival was evaluated retrospectively in 433 patients with metastatic colorectal cancer. SMAD4 mutation was found in 16.2% (70/433) of tumors. A systemic univariate and multivariate survival analysis model including age, gender, sidedness of primary tumor, RAS, BRAFV600E, APC, TP53 and SMAD4 status showed that SMAD4 mutations were not associated with worse prognosis (multivariate HR = 1.25, 95% CI 0.90-1.73, p = 0.18). However, coexisting mutations in SMAD4 and TP53 were significantly associated with worse overall survival (multivariate HR = 2.5, 95% CI 1.44-4.36, p = 0.001). The median overall survival of patients with coexisting SMAD4 and TP53 mutation was 24.2 months, compared to 42.2 months for the rest of the population (p = 0.002). Concurrent SMAD4 and TP53 defines a new subgroup of patients of metastatic colorectal cancer with poor clinical outcomes.

SUBMITTER: Wang C 

PROVIDER: S-EPMC9332822 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature

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Presence of Concurrent <i>TP53</i> Mutations Is Necessary to Predict Poor Outcomes within the <i>SMAD4</i> Mutated Subgroup of Metastatic Colorectal Cancer.

Wang Chongkai C   Sandhu Jaideep J   Tsao Amber A   Fakih Marwan M  

Cancers 20220727 15


Prior studies have resulted in conflicting conclusions on the value of <i>SMAD4</i> mutations as a prognostic biomarker in metastatic colorectal cancer. In this study, the impact of coexisting mutations with <i>SMAD4</i> on overall survival was evaluated retrospectively in 433 patients with metastatic colorectal cancer. <i>SMAD4</i> mutation was found in 16.2% (70/433) of tumors. A systemic univariate and multivariate survival analysis model including age, gender, sidedness of primary tumor, <i>  ...[more]

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