Development and validation of a novel cellular senescence-related prognostic signature for predicting the survival and immune landscape in hepatocellular carcinoma

Rui Sun; Xu Wang; Jiajie Chen; Da Teng; Shixin Chan; Xucan Tu; Zhenglin Wang; Xiaomin Zuo; Xiang Wei; Li Lin; Qing Zhang; Xiaomin Zhang; Kechao Tang; Huabing Zhang; Wei Chen

doi:10.3389/fgene.2022.949110

Development and validation of a novel cellular senescence-related prognostic signature for predicting the survival and immune landscape in hepatocellular carcinoma

Front Genet. 2022 Sep 6:13:949110. doi: 10.3389/fgene.2022.949110. eCollection 2022.

Authors

Rui Sun¹, Xu Wang¹, Jiajie Chen², Da Teng³, Shixin Chan¹, Xucan Tu¹, Zhenglin Wang¹, Xiaomin Zuo¹, Xiang Wei⁴, Li Lin⁴, Qing Zhang⁴, Xiaomin Zhang⁴, Kechao Tang⁴, Huabing Zhang^{4

5}, Wei Chen¹

Affiliations

¹ Department of General Surgery, First Affiliated Hospital of Anhui Medical University, Hefei, China.
² Department of Dermatology, First Affiliated Hospital of Anhui Medical University, Hefei, China.
³ Department of Hepatopancreatobiliary Surgery, Affiliated Chuzhou Hospital of Anhui Medical University, First People's Hospital of Chuzhou, Chuzhou, China.
⁴ Department of Biochemistry and Molecular Biology, Metabolic Disease Research Center, School of Basic Medicine, Anhui Medical University, Hefei, China.
⁵ Affiliated Chuzhou Hospital of Anhui Medical University, First People's Hospital of Chuzhou, Chuzhou, China.

Abstract

Background: Cellular senescence is a typical irreversible form of life stagnation, and recent studies have suggested that long non-coding ribonucleic acids (lncRNA) regulate the occurrence and development of various tumors. In the present study, we attempted to construct a novel signature for predicting the survival of patients with hepatocellular carcinoma (HCC) and the associated immune landscape based on senescence-related (sr) lncRNAs. Method: Expression profiles of srlncRNAs in 424 patients with HCC were retrieved from The Cancer Genome Atlas database. Lasso and Cox regression analyses were performed to identify differentially expressed lncRNAs related to senescence. The prediction efficiency of the signature was checked using a receiver operating characteristic (ROC) curve, Kaplan-Meier analysis, Cox regression analyses, nomogram, and calibration. The risk groups of the gene set enrichment analysis, immune analysis, and prediction of the half-maximal inhibitory concentration (IC50) were also analyzed. Quantitative real-time polymerase chain reaction (qPCR) was used to confirm the levels of AC026412.3, AL451069.3, and AL031985.3 in normal hepatic and HCC cell lines. Results: We identified 3 srlncRNAs (AC026412.3, AL451069.3, and AL031985.3) and constructed a new risk model. The results of the ROC curve and Kaplan-Meier analysis suggested that it was concordant with the prediction. Furthermore, a nomogram model was constructed to accurately predict patient prognosis. The risk score also correlated with immune cell infiltration status, immune checkpoint expression, and chemosensitivity. The results of qPCR revealed that AC026412.3 and AL451069.3 were significantly upregulated in hepatoma cell lines. Conclusion: The novel srlncRNA (AC026412.3, AL451069.3, and AL031985.3) signatures may provide insights into new therapies and prognosis predictions for patients with HCC.

Keywords: hepatocellular carcinoma; immune landscape; lncRNA; prognosis; senescence.