Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2020 Oct;11(5):1054-1064.
doi: 10.21037/jgo-20-377.

An alternative splicing signature model for predicting hepatocellular carcinoma-specific survival

Sheng Dong  1 , Li-Jun Lu  1
Affiliations

An alternative splicing signature model for predicting hepatocellular carcinoma-specific survival

Sheng Dong et al. J Gastrointest Oncol. 2020 Oct.

Abstract

Background: Alternative splicing (AS) is a transcriptional regulation mechanism, which can expand the coding ability of genome and contribute to the occurrence and development of cancer. A systematic analysis of AS in hepatocellular carcinoma (HCC) is lacking and urgently needed.

Methods: Univariate and multivariate Cox regression analyses were used to distinguish survival-related AS events and to calculate the risk score. Kaplan-Meier analysis and receiver operating characteristic (ROC) curves were used to evaluate the AS events' clinical significance to build a risk model in HCC.

Results: Data of AS events was obtained from the Splice-Seq database. The corresponding clinical information of HCC was downloaded from The Cancer Genome Atlas (TCGA) data portal. We analyzed 78,878 AS events from 13,045 genes in HCC patients. A total of 2,440 and 2,888 AS events were significantly related to HCC patients' disease-free survival (DFS) and overall survival (OS). The two prognostic models (DFS and OS) were constructed based on a total of seven AS types from survival-related AS events above. The area under the curve (AUC) of the ROC curves was 0.769 in the DFS cohort and 0.886 in the OS cohort.

Conclusions: The prognostic model constructed by AS events can be used to predict the prognosis of HCC patients and provide potential therapeutic targets for further validation.

Keywords: Hepatocellular carcinoma (HCC); alternative splicing (AS); gene analysis; prognosis.

PubMed Disclaimer

Conflict of interest statement

Conflicts of Interest: Both authors have completed the ICMJE uniform disclosure form (available at http://dx.doi.org/10.21037/jgo-20-377). The authors have no conflicts of interest to declare.

Figures

Figure 1
Figure 1
Overview of AS event profiling in HCC. (A) Illustrations for seven types of AS events, including AA, AD, AP, AT, ES, ME, and RI. (B) A number of AS events and involved genes from the HCC patients are shown according to the AS types. The blue bars represent the preliminarily detected AS events. The pink bars represent the involved genes. (C) UpSet plot of interactions between the seven types of detected AS events in HCC. One gene may have up to seven types of AS events related to patient survival. AA, alternate acceptor site; AD, alternate donor site; AP, alternate promoter; AS, alternative splicing; AT, alternate terminator; ES, exon skip; HCC, hepatocellular carcinoma; ME, mutually exclusive exons; RI, retained intron.
Figure 2
Figure 2
The circle maps for seven subgroup analyses of survival-related AS events in the HCC DFS cohort. Hazard ratios of the top 15 genes with survival-related AS events in HCC. The color scale of the circles represents P values by the side; radian length represents 95% CI. AS, alternative splicing; CI, confidence interval; HCC, hepatocellular carcinoma; DFS, disease-free survival.
Figure 3
Figure 3
The circle maps for seven subgroup analyses of survival-related AS events in the HCC OS cohort. Hazard ratios of the top 15 genes with survival-related AS events in HCC. The color scale of the circles represents P values by the side; radian length represents 95% CI. AS, alternative splicing; CI, confidence interval; HCC, hepatocellular carcinoma; OS, overall survival.
Figure 4
Figure 4
Kaplan-Meier and ROC curves of prognostic predictors in the HCC DFS cohort. Kaplan-Meier plot depicting the survival probability over time for prognostic predictors built by one type or all seven types of AS events with a high (red) and low (green) risk group. ROC analysis for all prognostic predictors. The color lines of ROC curves represent the different types of AS events. AS, alternative splicing; DFS, disease-free survival; HCC, hepatocellular carcinoma; ROC, receiver operating characteristic.
Figure 5
Figure 5
Kaplan-Meier and ROC curves of prognostic predictors in the HCC OS cohort. Kaplan-Meier plot depicting the survival probability over time for prognostic predictors built by one type or all seven types of AS events with a high (red) and low (green) risk group. ROC analysis for all prognostic predictors. The color lines of ROC curves represent different types of AS events. AS, alternative splicing; HCC, hepatocellular carcinoma; OS, overall survival; ROC, receiver operating characteristic.
See this image and copyright information in PMC

Similar articles

See all similar articles

Cited by

References

    1. Jemal A, Bray F, Center MM, et al. Global cancer statistics. CA Cancer J Clin 2011;61:69-90. 10.3322/caac.20107 - DOI - PubMed
    1. Morise Z. Laparoscopic liver resection for the patients with hepatocellular carcinoma and chronic liver disease. Transl Gastroenterol Hepatol 2018;3:41. 10.21037/tgh.2018.07.01 - DOI - PMC - PubMed
    1. Du ZG, Wei YG, Chen KF, et al. Risk factors associated with early and late recurrence after curative resection of hepatocellular carcinoma: a single institution's experience with 398 consecutive patients. Hepatobiliary Pancreat Dis Int 2014;13:153-61. 10.1016/S1499-3872(14)60025-4 - DOI - PubMed
    1. Akateh C, Pawlik TM, Cloyd JM. Adjuvant antiviral therapy for the prevention of hepatocellular carcinoma recurrence after liver resection: indicated for all patients with chronic hepatitis B? Ann Transl Med 2018;6:397. 10.21037/atm.2018.08.20 - DOI - PMC - PubMed
    1. Cancer Genome Atlas Research Network Comprehensive and Integrative Genomic Characterization of Hepatocellular Carcinoma. Cell 2017;169:1327-41.e23. 10.1016/j.cell.2017.05.046 - DOI - PMC - PubMed