Dataset Information

Development and validation of a risk prediction model and nomogram for colon adenocarcinoma based on methylation-driven genes.

ABSTRACT: Evidence suggests that abnormal DNA methylation patterns play a crucial role in the etiology and pathogenesis of colon adenocarcinoma (COAD). In this study, we identified a total of 97 methylation-driven genes (MDGs) through a comprehensive analysis of the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Univariate Cox regression analysis identified four MDGs (CBLN2, RBM47, SLCO4C1, and TMEM220) associated with overall survival (OS) in COAD patients. A risk prediction model was then developed based on these four MDGs to predict the prognosis of COAD patients. We also created a nomogram that incorporated risk scores, age, and TNM stage to promote a personalized prediction of OS in COAD patients. Compared with the traditional TNM staging system, our new nomogram was better at predicting the OS of COAD patients. In cell experiments, we confirmed that the mRNA expression levels of CLBN2 and TMEM220 were regulated by the methylation of their promoter regions. Moreover, immunohistochemistry showed that CBLN2 and TMEM220 were potential prognostic biomarkers for COAD patients. In summary, we have established a risk prediction model and nomogram that might be effectively utilized to promote the prediction of OS in COAD patients.

SUBMITTER: Zhu L

PROVIDER: S-EPMC8266312 | biostudies-literature | 2021 Jun

REPOSITORIES: biostudies-literature

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Development and validation of a risk prediction model and nomogram for colon adenocarcinoma based on methylation-driven genes.

Zhu Liangyu L Sun Hongyu H Tian Guo G Wang Juan J Zhou Qian Q Liu Pu P Tang Xuejiao X Shi Xinrui X Yang Lei L Liu Guangjie G

Aging 20210628 12

Evidence suggests that abnormal DNA methylation patterns play a crucial role in the etiology and pathogenesis of colon adenocarcinoma (COAD). In this study, we identified a total of 97 methylation-driven genes (MDGs) through a comprehensive analysis of the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Univariate Cox regression analysis identified four MDGs (CBLN2, RBM47, SLCO4C1, and TMEM220) associated with overall survival (OS) in COAD pati ...[more]

PMID: 34182539

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Project description:Background/Aims: The incidence of gastric cancer (GC) ranks fifth among common tumors and GC is the third leading cause of cancer-related death worldwide. The aim of this study was to develop and validate a nomogram for predicting the overall survival (OS) of patients with GC. Methods: DNA methylation (DNAm)-driven genes were identified by integrating DNAm and gene expression profiling analyses from The Cancer Genome Atlas (TCGA) GC cohort. Then, a risk score model was built based on Kaplan-Meier (K-M), least absolute shrinkage and selector operation (LASSO), and multivariate Cox regression analyses. After analyzing the clinical parameters, a nomogram was constructed and assessed. Another cohort (GSE62254) was used for external validation. Results: Thirteen differentially expressed DNAm-driven genes were narrowed down to a six-gene signature (PODN, NPY, MICU3, TUBB6 and RHOJ were hypermethylated, and MYO1A was hypomethylated), which was associated with OS (P < 0.05) after survival and LASSO regression analyses. These differentially expressed genes (DEGs) with altered DNAm statuses were included in the prognostic risk score model. The univariate Cox regression analysis indicated that risk score, age, and number of positive lymph nodes were significantly associated with survival time in GC patients. The multivariate Cox regression analysis also indicated that these variables were significant prognostic factors for GC. A nomogram including these variables was constructed, and its performance in predicting the 1-, 3- and 5-year survival outcomes of GC patients was estimated through time-dependent receiver operating characteristic (ROC) curves. In addition, the clinical benefit of this model was revealed by decision curve analysis (DCA). Pathway enrichment analysis suggested that these DNAm-driven genes might impact tumor progression by affecting signaling pathways such as the "ECM RECEPTOR INTERACTION" and "DNA REPLICATION" pathways. Conclusions: The altered status of the DNAm-driven gene signature (PODN, MYO1A, NPY, MICU3, TUBB6 and RHOJ) was significantly associated with the OS of GC patients. A nomogram incorporating risk score, age and number of positive lymph nodes can be conveniently used to facilitate the individualized prediction of OS in patients with GC.

Project description:Background: Pancreatic adenocarcinoma (PAAD) is one of the most aggressive tumors of the digestive tract, with low surgical resection rate and insensitivity to radiotherapy and chemotherapy. Existing evidence suggests that regulation of ferroptosis can induce PAAD cell death, inhibit tumor growth, and may synergistically improve the sensitivity of other antitumor drugs. However, there is little of systematic research on iron metabolism-related genes in PAAD. In this study, a risk-score system of PAAD iron metabolism-related genes was designed and tested, and verified to be robust. Materials and Methods: The TCGA database was used to download 177 PAAD patients' message RNA (mRNA) expression profiles and clinical characteristics. By identifying dysregulated iron metabolism-related genes between PAAD related tissues and adjacent normal tissues, univariate Cox proportional hazards regression and LASSO regression algorithm were used to establish prognostic risk-score system and construct nomogram to estimate the 1-, 2-, 3-year survival in PAAD patients. Finally, selected genes were validated by quantitative PCR (q-PCR). Results: A 9-gene related to iron metabolism risk-score system of PAAD was constructed and validated. The clinicopathological characteristics of age, histologic grade, pathologic stage, T stage, residual tumor, and primary therapy outcome were all worse in patients with a higher risk-score. Further, immunohistochemistry results of SLC2A1, MBOAT2, XDH, CTSE, MOCOS, and ATP6V0A4 confirmed that patients with higher expression are more malignant. Then, a nomogram with 9-gene risk score system as a separate clinical factor was utilized to foretell the 1-, 2-, 3-year overall survival rate of PAAD patients. Results of q-PCR showed that 8 of the 9 genes screened were significantly up-regulated in at least one PAAD cell line, and one gene was significantly down-regulated in three PAAD cell lines. Conclusion: To conclude, we generated a nine-gene system linked to iron metabolism as an independent indicator for predicting PAAD prognosis, therefore presenting a possible prognostic biomarker and potential treatment targets for PAAD.

Project description:BackgroundGallbladder papillary adenocarcinoma (GBPA) is an uncharacteristically gallbladder cancer subtype. Although some studies have shown that the prognosis of GBPA patients is significantly better than that of gallbladder adenocarcinoma (GBA) and gallbladder mucinous adenocarcinoma (GBMA) due to its rarity, there is a lack of large sample studies necessary to confirm the clinical characteristics and survival rate of GBPA. Therefore, this study aimed to describe the clinicopathological characteristics affecting survival in GBPA. This data was then used to establish a prognostic nomogram for GBPA.MethodsThe data of patients diagnosed with gallbladder cancer between 2004 to 2015 were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. The clinical features and survival of patients with GBPA were compared with those of GBA and GBMA after balancing the baseline characteristics using propensity score matching (PSM). Univariate and multivariate Cox analyses were used to identify the prognostic factors for GBPA. Subsequently, the overall survival (OS) and cancer-specific survival (CSS) nomograms were established to predict GBPA prognosis. The performance and discrimination of the nomogram were measured using concordance index (C-index), calibration curves, receptor operating characteristic curves(ROC), and decision curve analysis (DCA) was applied to examine the net benefit of tients with GBPA, 5798 patients with GBA, and 223 patients with GBMA. The mean 1-, 3- and 5-year OS rates for GBPA were 81.3%, 58.8%, and 49.1%, respectively, while the mean 1-, 3- and 5-year CSS rates were 85.0%, 68.1%, and 61.0%, respectively. The median OS rates was 58 months (95% CI: 43-88), while the median CSS was not reached. The PSM analysis showed a differ statistically significantly in the OS between GBPA and GBA. However, there has no statistically difference in CSS. Conversely, the OS and CSS between GBPA and GBMA have statistically significant differences. Age, marital, T stage, and M stage were strongly linked to the prognosis for OS, while T-stage, M-stage, and surgery were significantly associated with the prognosis for CSS in GBPA patients. The AUC for the 1-, 3-, and 5-year OS were 0.722 (95%CI: 0.630-0.813), 0.728 (95%CI: 0.665-0.790), and 0.706 (95%CI: 0.641-0.771), respectively. The AUC for the 1-, 3-, and 5-year CSS were 0.749 (95%CI: 0.659-0.840), 0.698 (95%CI: 0.627-0.770), and 0.665 (95%CI: 0.594-0.735), respectively. The C-indices for the OS and CSS nomograms were 0.701 (95% CI: 0.634-0.744) and 0.651 (95% CI: 0.598-0.703), respectively. The calibration curves showed that the nomograms were well consistency. The DCA showed that compared with the TNM system, the nomogram models had a significant positive net benefit in survival prediction.ConclusionGBPA has distinct clinicopathological characteristics and survival compared to other gallbladder carcinomas. The established nomogram provided a better prediction of survival for GBPA patients than the traditional TNM models.

Dataset Information

Development and validation of a risk prediction model and nomogram for colon adenocarcinoma based on methylation-driven genes.

Publications

Development and validation of a risk prediction model and nomogram for colon adenocarcinoma based on methylation-driven genes.

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