A novel tp53-associated nomogram to predict the overall survival in patients with pancreatic cancer
Abstract Background Gene mutations play critical roles in tumorigenesis and cancer development. Our study aimed to screen survival-related mutations and explore a novel gene signature to predict the overall survival in pancreatic cancer. Methods Somatic mutation data from three cohorts were used to...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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BMC
2021-03-01
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| Series: | BMC Cancer |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12885-021-08066-2 |
| _version_ | 1819117878511665152 |
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| author | Xun Liu Bobo Chen Jiahui Chen Shaolong Sun |
| author_facet | Xun Liu Bobo Chen Jiahui Chen Shaolong Sun |
| author_sort | Xun Liu |
| collection | DOAJ |
| description | Abstract Background Gene mutations play critical roles in tumorigenesis and cancer development. Our study aimed to screen survival-related mutations and explore a novel gene signature to predict the overall survival in pancreatic cancer. Methods Somatic mutation data from three cohorts were used to identify the common survival-related gene mutation with Kaplan-Meier curves. RNA-sequencing data were used to explore the signature for survival prediction. First, Weighted Gene Co-expression Network Analysis was conducted to identify candidate genes. Then, the ICGC-PACA-CA cohort was applied as the training set and the TCGA-PAAD cohort was used as the external validation set. A TP53-associated signature calculating the risk score of every patient was developed with univariate Cox, least absolute shrinkage and selection operator, and stepwise regression analysis. Kaplan-Meier and receiver operating characteristic curves were plotted to verify the accuracy. The independence of the signature was confirmed by the multivariate Cox regression analysis. Finally, a prognostic nomogram including 359 patients was constructed based on the combined expression data and the risk scores. Results TP53 mutation was screened to be the robust and survival-related mutation type, and was associated with immune cell infiltration. Two thousand, four hundred fifty-five genes included in the six modules generated in the WGCNA were screened as candidate survival related TP53-associated genes. A seven-gene signature was constructed: Risk score = (0.1254 × ERRFI1) - (0.1365 × IL6R) - (0.4400 × PPP1R10) - (0.3397 × PTOV1-AS2) + (0.1544 × SCEL) - (0.4412 × SSX2IP) – (0.2231 × TXNL4A). Area Under Curves of 1-, 3-, and 5-year ROC curves were 0.731, 0.808, and 0.873 in the training set and 0.703, 0.677, and 0.737 in the validation set. A prognostic nomogram including 359 patients was constructed and well-calibrated, with the Area Under Curves of 1-, 3-, and 5-year ROC curves as 0.713, 0.753, and 0.823. Conclusions The TP53-associated signature exhibited good prognostic efficacy in predicting the overall survival of PC patients. |
| first_indexed | 2024-12-22T05:39:59Z |
| format | Article |
| id | doaj.art-c633449092c84bfdb242602ed512c5e7 |
| institution | Directory Open Access Journal |
| issn | 1471-2407 |
| language | English |
| last_indexed | 2024-12-22T05:39:59Z |
| publishDate | 2021-03-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Cancer |
| spelling | doaj.art-c633449092c84bfdb242602ed512c5e72022-12-21T18:37:13ZengBMCBMC Cancer1471-24072021-03-0121111510.1186/s12885-021-08066-2A novel tp53-associated nomogram to predict the overall survival in patients with pancreatic cancerXun Liu0Bobo Chen1Jiahui Chen2Shaolong Sun3Department of Pancreas and Endocrine Surgery, Shengjing Hospital of China Medical UniversityDepartment of Pancreas and Endocrine Surgery, Shengjing Hospital of China Medical UniversityDepartment of Pancreas and Endocrine Surgery, Shengjing Hospital of China Medical UniversityDepartment of Pancreas and Endocrine Surgery, Shengjing Hospital of China Medical UniversityAbstract Background Gene mutations play critical roles in tumorigenesis and cancer development. Our study aimed to screen survival-related mutations and explore a novel gene signature to predict the overall survival in pancreatic cancer. Methods Somatic mutation data from three cohorts were used to identify the common survival-related gene mutation with Kaplan-Meier curves. RNA-sequencing data were used to explore the signature for survival prediction. First, Weighted Gene Co-expression Network Analysis was conducted to identify candidate genes. Then, the ICGC-PACA-CA cohort was applied as the training set and the TCGA-PAAD cohort was used as the external validation set. A TP53-associated signature calculating the risk score of every patient was developed with univariate Cox, least absolute shrinkage and selection operator, and stepwise regression analysis. Kaplan-Meier and receiver operating characteristic curves were plotted to verify the accuracy. The independence of the signature was confirmed by the multivariate Cox regression analysis. Finally, a prognostic nomogram including 359 patients was constructed based on the combined expression data and the risk scores. Results TP53 mutation was screened to be the robust and survival-related mutation type, and was associated with immune cell infiltration. Two thousand, four hundred fifty-five genes included in the six modules generated in the WGCNA were screened as candidate survival related TP53-associated genes. A seven-gene signature was constructed: Risk score = (0.1254 × ERRFI1) - (0.1365 × IL6R) - (0.4400 × PPP1R10) - (0.3397 × PTOV1-AS2) + (0.1544 × SCEL) - (0.4412 × SSX2IP) – (0.2231 × TXNL4A). Area Under Curves of 1-, 3-, and 5-year ROC curves were 0.731, 0.808, and 0.873 in the training set and 0.703, 0.677, and 0.737 in the validation set. A prognostic nomogram including 359 patients was constructed and well-calibrated, with the Area Under Curves of 1-, 3-, and 5-year ROC curves as 0.713, 0.753, and 0.823. Conclusions The TP53-associated signature exhibited good prognostic efficacy in predicting the overall survival of PC patients.https://doi.org/10.1186/s12885-021-08066-2TP53 mutationSurvival predictionWGCNANomogramPancreatic Cancer |
| spellingShingle | Xun Liu Bobo Chen Jiahui Chen Shaolong Sun A novel tp53-associated nomogram to predict the overall survival in patients with pancreatic cancer BMC Cancer TP53 mutation Survival prediction WGCNA Nomogram Pancreatic Cancer |
| title | A novel tp53-associated nomogram to predict the overall survival in patients with pancreatic cancer |
| title_full | A novel tp53-associated nomogram to predict the overall survival in patients with pancreatic cancer |
| title_fullStr | A novel tp53-associated nomogram to predict the overall survival in patients with pancreatic cancer |
| title_full_unstemmed | A novel tp53-associated nomogram to predict the overall survival in patients with pancreatic cancer |
| title_short | A novel tp53-associated nomogram to predict the overall survival in patients with pancreatic cancer |
| title_sort | novel tp53 associated nomogram to predict the overall survival in patients with pancreatic cancer |
| topic | TP53 mutation Survival prediction WGCNA Nomogram Pancreatic Cancer |
| url | https://doi.org/10.1186/s12885-021-08066-2 |
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