Integrated analysis of methylation-driven genes and pretreatment prognostic factors in patients with hepatocellular carcinoma
| Autor: | Shengyin Liao, Xuehua Xie, Lifang Cai, Mengxing You, Dongsheng He, Weiming Huang |
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| Rok vydání: | 2021 |
| Předmět: |
Oncology
Cancer Research medicine.medical_specialty Carcinoma Hepatocellular Hepatocellular carcinoma Datasets as Topic Kaplan-Meier Estimate Ribosomal Protein S6 Kinases 90-kDa Nomogram Epigenesis Genetic Phosphatidylcholine-Sterol O-Acyltransferase Surgical oncology Internal medicine Biomarkers Tumor Genetics medicine Hepatectomy Humans RC254-282 Neoplasm Staging Framingham Risk Score Sequence Analysis RNA Proportional hazards model business.industry Gene Expression Profiling Liver Neoplasms Neoplasms. Tumors. Oncology. Including cancer and carcinogens Cancer DNA Methylation Prognosis medicine.disease Gene Expression Regulation Neoplastic Nomograms Treatment Outcome Liver ROC Curve Preoperative Period DNA methylation Methylation-driven genes T-stage business Research Article |
| Zdroj: | BMC Cancer, Vol 21, Iss 1, Pp 1-13 (2021) BMC Cancer |
| ISSN: | 1471-2407 |
| Popis: | Background The potential reversibility of aberrant DNA methylation indicates an opportunity for oncotherapy. This study aimed to integrate methylation-driven genes and pretreatment prognostic factors and then construct a new individual prognostic model in hepatocellular carcinoma (HCC) patients. Methods The gene methylation, gene expression dataset and clinical information of HCC patients were downloaded from The Cancer Genome Atlas (TCGA) database. Methylation-driven genes were screened with a Pearson’s correlation coefficient less than − 0.3 and a P value less than 0.05. Univariable and multivariable Cox regression analyses were performed to construct a risk score model and identify independent prognostic factors from the clinical parameters of HCC patients. The least absolute shrinkage and selection operator (LASSO) technique was used to construct a nomogram that might act to predict an individual’s OS, and then C-index, ROC curve and calibration plot were used to test the practicability. The correlation between clinical parameters and core methylation-driven genes of HCC patients was explored with Student’s t-test. Results In this study, 44 methylation-driven genes were discovered, and three prognostic signatures (LCAT, RPS6KA6, and C5orf58) were screened to construct a prognostic risk model of HCC patients. Five clinical factors, including T stage, risk score, cancer status, surgical method and new tumor events, were identified from 13 clinical parameters as pretreatment-independent prognostic factors. To avoid overfitting, LASSO analysis was used to construct a nomogram that could be used to calculate the OS in HCC patients. The C-index was superior to that from previous studies (0.75 vs 0.717, 0.676). Furthermore, LCAT was found to be correlated with T stage and new tumor events, and RPS6KA6 was found to be correlated with T stage. Conclusion We identified novel therapeutic targets and constructed an individual prognostic model that can be used to guide personalized treatment in HCC patients. |
| Databáze: | OpenAIRE |
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