Prognostic and predictive role of a metabolic rate‐limiting enzyme signature in hepatocellular carcinoma
| Autor: | Xiaoping Zou, Qiang Wang, Anliang Xia, Zhangding Wang, Guifang Xu, Shouyu Wang, Yao Fu, Chen Chen, Jiamu Qu |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Oncology
medicine.medical_specialty Carcinoma Hepatocellular Kaplan-Meier Estimate rate‐limiting enzymes Mice Internal medicine Cell Line Tumor medicine Animals Humans chemistry.chemical_classification Framingham Risk Score Receiver operating characteristic Proportional hazards model business.industry Liver Neoplasms Cell Biology General Medicine Original Articles hepatocellular carcinoma Hep G2 Cells Nomogram medicine.disease Prognosis Gene Expression Regulation Neoplastic Mice Inbred C57BL Nomograms Enzyme chemistry ROC Curve Hepatocellular carcinoma Cohort Original Article Risk assessment business metabolism signature |
| Zdroj: | Cell Proliferation |
| ISSN: | 1365-2184 0960-7722 |
| Popis: | Objectives Abnormal expression of metabolic rate‐limiting enzymes drives the occurrence and progression of hepatocellular carcinoma (HCC). This study aimed to elucidate the comprehensive model of metabolic rate‐limiting enzymes associated with the prognosis of HCC. Materials and Methods HCC animal model and TCGA project were used to screen out differentially expressed metabolic rate‐limiting enzyme. Cox regression, least absolute shrinkage and selection operation (LASSO) and experimentally verification were performed to identify metabolic rate‐limiting enzyme signature. The area under the receiver operating characteristic curve (AUC) and prognostic nomogram were used to assess the efficacy of the signature in the three HCC cohorts (TCGA training cohort, internal cohort and an independent validation cohort). Results A classifier based on three rate‐limiting enzymes (RRM1, UCK2 and G6PD) was conducted and serves as independent prognostic factor. This effect was further confirmed in an independent cohort, which indicated that the AUC at year 5 was 0.715 (95% CI: 0.653‐0.777) for clinical risk score, whereas it was significantly increased to 0.852 (95% CI: 0.798‐0.906) when combination of the clinical with signature risk score. Moreover, a comprehensive nomogram including the signature and clinicopathological aspects resulted in significantly predict the individual outcomes. Conclusions Our results highlighted the prognostic value of rate‐limiting enzymes in HCC, which may be useful for accurate risk assessment in guiding clinical management and treatment decisions. Step1: Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses of differentially expressed genes from HCC animals RNA‐seq data clustered the majority genes in metabolic pathways. Step2: By conjointly analyzing the differentially expressed metabolic rate‐limiting enzymes from RNA‐seq data of HCC animal model and TCGA data, 12 transcripts were overlapped (RRM1, SQLE, PCK1, PYGB, G6PD, PLAT, ACSL1, RRM2, UCK2, ASS1, FBP1 and IMPDH1). Step3: Univariate and LASSO Cox regression were performed to screen out 3 rate‐limiting enzymes with a significant overall prognosis(i), three HCC cohorts (TCGA training cohort, internal cohort and an independent validation cohort) were used to validate the metabolic rate‐limiting enzyme signature by Uni/Multivariate Cox regression, KM survival, ROC analysis and Nomogram model. |
| Databáze: | OpenAIRE |
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