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A prognostic predictive model constituted with gene mutations of APC, BRCA2, CDH1, SMO, and TSC2 in colorectal cancer
BACKGROUND: Colorectal cancer (CRC) is a malignant tumor that seriously threatens human health. A CRC predictive model can be used as an effective method to provide an appropriate treatment for CRC patients. METHODS: A total of 34 CRC patients were enrolled in this study. After performing 1000-gene...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
AME Publishing Company
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8106061/ https://www.ncbi.nlm.nih.gov/pubmed/33987378 http://dx.doi.org/10.21037/atm-21-1010 |
Sumario: | BACKGROUND: Colorectal cancer (CRC) is a malignant tumor that seriously threatens human health. A CRC predictive model can be used as an effective method to provide an appropriate treatment for CRC patients. METHODS: A total of 34 CRC patients were enrolled in this study. After performing 1000-gene panel targeted next-generation sequencing (NGS), high-frequency mutation genes were screened, and their functional terms and pathways were enriched. In The Cancer Genome Atlas (TCGA) CRC cases, the risk factors for overall survival (OS) were screened by univariate and multivariate analysis, and a predictive model was constructed and verified. Subsequently, the relationship among mutation status, gene expression, methylation level, and OS was analyzed to explore the molecular mechanism of CRC progression. RESULTS: A total of 26 high-frequency mutation genes were screened, which were mainly enriched in breast cancer and proteoglycans in cancer pathways. The clinical parameters of age, stage, recurrence and metastasis, the mutation status of APC, BRCA2, CDH1, SMO, and TSC2 were identified as risk factors for the construction of the predictive model. The areas under the receiver operating characteristic curve were 0.734, 0.754, 0.774, and 0.74 for 1-, 3-, 5- and 7-year survival in the model group, respectively. CONCLUSIONS: We identified several mutated genes and clinical parameters affecting OS and established a model to better predict the OS of CRC patients. |
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