A novel qualitative signature based on lncRNA pairs for prognosis prediction in hepatocellular carcinoma

Xiaoyun Bu; Luyao Ma; Shuang Liu; Dongsheng Wen; Anna Kan; Yujie Xu; Xuanjia Lin; Ming Shi

doi:10.1186/s12935-022-02507-z

A novel qualitative signature based on lncRNA pairs for prognosis prediction in hepatocellular carcinoma

Cancer Cell Int. 2022 Feb 22;22(1):95. doi: 10.1186/s12935-022-02507-z.

Authors

Xiaoyun Bu^#^{1

2}, Luyao Ma^#^{3

4

5}, Shuang Liu^#^{1

2}, Dongsheng Wen^{1

2}, Anna Kan^{1

2}, Yujie Xu^{1

2}, Xuanjia Lin, Ming Shi^{6

7}

Affiliations

¹ Department of Liver Surgery, Sun Yat-Sen University Cancer Center, Guangzhou, China.
² State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, 651 Dongfeng East Road, Guangzhou, 510060, China.
³ Guizhou Medical University, Guiyang, China.
⁴ Department of Hepatic-Biliary-Pancreatic Surgery, The Affiliated Hospital of Guizhou Medical University, Guiyang, China.
⁵ Key Laboratory of Hepatobiliary and Pancreatic Surgery, Guiyang, China.
⁶ Department of Liver Surgery, Sun Yat-Sen University Cancer Center, Guangzhou, China. shiming@sysu.edu.cn.
⁷ State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, 651 Dongfeng East Road, Guangzhou, 510060, China. shiming@sysu.edu.cn.

^# Contributed equally.

Abstract

Background: Prognostic assessment is imperative for clinical management of patients with hepatocellular carcinoma (HCC). Most reported prognostic signatures are based on risk scores summarized from quantitative expression level of candidate genes, which are vulnerable against experimental batch effects and impractical for clinical application. We aimed to develop a robust qualitative signature to assess individual survival risk for HCC patients.

Methods: Long non-coding RNA (lncRNA) pairs correlated with overall survival (OS) were identified and an optimal combination of lncRNA pairs based on the majority voting rule was selected as a classification signature to predict the overall survival risk in the cancer genome atlas (TCGA). Then, the signature was further validated in two external datasets. Besides, biomolecular characteristics, immune infiltration status, and chemotherapeutics efficacy of different risk groups were further compared. Finally, we performed key lncRNA screening and validated it in vitro.

Results: A signature consisting of 50 lncRNA pairs (50-LPS) was identified in TCGA and successfully validated in external datasets. Patients in the high-risk group, when at least 25 of the 50-LPS voted for high risk, had significantly worse OS than the low-risk group. Multivariate Cox, receiver operating characteristic (ROC) curve and decision curve analyses (DCA) demonstrated that the 50-LPS was an independent prognostic factor and more powerful than other available clinical factors in OS prediction. Comparison analyses indicated that different risk groups had distinct biomolecular characteristics, immune infiltration status, and chemotherapeutics efficacy. TDRKH-AS1 was confirmed as a key lncRNA and associated with cell growth of HCC.

Conclusions: The 50-LPS could not only predict the prognosis of HCC patients robustly and individually, but also provide theoretical basis for therapy. Besides, TDRKH-AS1 was identified as a key lncRNA in the proliferation of HCC. The 50-LPS might guide personalized therapy for HCC patients in clinical practice.

Keywords: Hepatocellular carcinoma; LncRNA pairs; Precision medicine; Risk stratification.

Abstract

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