Wenbo Zou1,2,3,4, Zizheng Wang2,3,4, Fei Wang2,3,4, Lincheng Li2,3,4, Rong Liu5,6,7, Minggen Hu8,9,10. 1. Medical School of Chinese PLA, Beijing, China. 2. Faculty of Hepato-Pancreato-Biliary Surgery, Chinese PLA General Hospital, No.28 Fuxing Road, Haidian District, Beijing, 100853, China. 3. Institute of Hepatobiliary Surgery of Chinese PLA, Beijing, China. 4. Key Laboratory of Digital Hepetobiliary Surgery, PLA, Beijing, China. 5. Faculty of Hepato-Pancreato-Biliary Surgery, Chinese PLA General Hospital, No.28 Fuxing Road, Haidian District, Beijing, 100853, China. liurong301@126.com. 6. Institute of Hepatobiliary Surgery of Chinese PLA, Beijing, China. liurong301@126.com. 7. Key Laboratory of Digital Hepetobiliary Surgery, PLA, Beijing, China. liurong301@126.com. 8. Faculty of Hepato-Pancreato-Biliary Surgery, Chinese PLA General Hospital, No.28 Fuxing Road, Haidian District, Beijing, 100853, China. hmg301@126.com. 9. Institute of Hepatobiliary Surgery of Chinese PLA, Beijing, China. hmg301@126.com. 10. Key Laboratory of Digital Hepetobiliary Surgery, PLA, Beijing, China. hmg301@126.com.
Abstract
BACKGROUND: Long non-coding RNA (lncRNA) plays a critical role in the malignant progression of intrahepatic cholangiocarcinoma (iCCA). This study aimed to establish a 4-lncRNA prognostic signature and explore corresponding potential mechanisms in patients with iCCA. METHODS: The original lncRNA-seq and clinical data were collected from the TCGA and GEO databases. Overlapping and differentially expressed lncRNAs (DE-lncRNAs) were further identified from transcriptome data. Univariate regression analysis was performed to screen survival-related DE-lncRNAs, which were further selected to develop an optimal signature to predict prognosis using multivariate regression analysis. The Kaplan-Meier survival curve visualized the discrimination of the signature on overall survival (OS). The area under the curve (AUC) and C-index were used to verify the predictive accuracy of the signature. Combined with clinical data, multivariate survival analysis was used to reveal the independent predictive capability of the signature. In addition, a prognostic nomogram was constructed. Finally, the common target genes of 4 lncRNAs were predicted by the co-expression method, and the corresponding functions were annotated by GO and KEGG enrichment analysis. Gene set enrichment analysis (GSEA) was also performed to explore the potential mechanism of the signature. Quantitative real-time PCR was used to evaluated the expression of 4 lncRNAs in an independent cohort. RESULTS: We identified and constructed a 4-lncRNA (AC138430.1, AGAP2-AS1, AP001783.1, and AP005233.2) prognostic signature using regression analysis, and it had the capability to independently predict prognosis. The AUCs were 0.952, 0.909, and 0.882 at 1, 2, and 3 years, respectively, and the C-index was 0.808, which showed good predictive capability. Subsequently, combined with clinical data, we constructed a nomogram with good clinical application. Finally, 252 target genes of all four lncRNAs were identified by the co-expression method, and functional enrichment analysis showed that the signature was strongly correlated with metabolism-related mechanisms in tumourigenesis. The same results were also validated via GSEA. CONCLUSION: We demonstrated that a metabolism-related 4-lncRNA prognostic signature could be a novel biomarker and deeply explored the target genes and potential mechanism. This study will provide a promising therapeutic strategy for patients with intrahepatic cholangiocarcinoma.
BACKGROUND: Long non-coding RNA (lncRNA) plays a critical role in the malignant progression of intrahepatic cholangiocarcinoma (iCCA). This study aimed to establish a 4-lncRNA prognostic signature and explore corresponding potential mechanisms in patients with iCCA. METHODS: The original lncRNA-seq and clinical data were collected from the TCGA and GEO databases. Overlapping and differentially expressed lncRNAs (DE-lncRNAs) were further identified from transcriptome data. Univariate regression analysis was performed to screen survival-related DE-lncRNAs, which were further selected to develop an optimal signature to predict prognosis using multivariate regression analysis. The Kaplan-Meier survival curve visualized the discrimination of the signature on overall survival (OS). The area under the curve (AUC) and C-index were used to verify the predictive accuracy of the signature. Combined with clinical data, multivariate survival analysis was used to reveal the independent predictive capability of the signature. In addition, a prognostic nomogram was constructed. Finally, the common target genes of 4 lncRNAs were predicted by the co-expression method, and the corresponding functions were annotated by GO and KEGG enrichment analysis. Gene set enrichment analysis (GSEA) was also performed to explore the potential mechanism of the signature. Quantitative real-time PCR was used to evaluated the expression of 4 lncRNAs in an independent cohort. RESULTS: We identified and constructed a 4-lncRNA (AC138430.1, AGAP2-AS1, AP001783.1, and AP005233.2) prognostic signature using regression analysis, and it had the capability to independently predict prognosis. The AUCs were 0.952, 0.909, and 0.882 at 1, 2, and 3 years, respectively, and the C-index was 0.808, which showed good predictive capability. Subsequently, combined with clinical data, we constructed a nomogram with good clinical application. Finally, 252 target genes of all four lncRNAs were identified by the co-expression method, and functional enrichment analysis showed that the signature was strongly correlated with metabolism-related mechanisms in tumourigenesis. The same results were also validated via GSEA. CONCLUSION: We demonstrated that a metabolism-related 4-lncRNA prognostic signature could be a novel biomarker and deeply explored the target genes and potential mechanism. This study will provide a promising therapeutic strategy for patients with intrahepatic cholangiocarcinoma.
Entities:
Keywords:
Intrahepatic cholangiocarcinoma; Long non-coding RNA; Nomogram; Overall survival; Signature
Authors: Jesus M Banales; Jose J G Marin; Angela Lamarca; Pedro M Rodrigues; Shahid A Khan; Lewis R Roberts; Vincenzo Cardinale; Guido Carpino; Jesper B Andersen; Chiara Braconi; Diego F Calvisi; Maria J Perugorria; Luca Fabris; Luke Boulter; Rocio I R Macias; Eugenio Gaudio; Domenico Alvaro; Sergio A Gradilone; Mario Strazzabosco; Marco Marzioni; Cédric Coulouarn; Laura Fouassier; Chiara Raggi; Pietro Invernizzi; Joachim C Mertens; Anja Moncsek; Sumera Rizvi; Julie Heimbach; Bas Groot Koerkamp; Jordi Bruix; Alejandro Forner; John Bridgewater; Juan W Valle; Gregory J Gores Journal: Nat Rev Gastroenterol Hepatol Date: 2020-06-30 Impact factor: 46.802