Assessment of prognostic role of a novel 7-lncRNA signature in HCC patients

Junchi Qu; Di Tao; Wei Huang; Liting Lu; Junming Fan; Shineng Zhang; Fengting Huang

doi:10.1016/j.heliyon.2023.e18493

Assessment of prognostic role of a novel 7-lncRNA signature in HCC patients

Heliyon. 2023 Jul 20;9(8):e18493. doi: 10.1016/j.heliyon.2023.e18493. eCollection 2023 Aug.

Authors

Junchi Qu^{1

2

3}, Di Tao^{1

2}, Wei Huang¹, Liting Lu¹, Junming Fan¹, Shineng Zhang^{1

2}, Fengting Huang^{1

2}

Affiliations

¹ Department of Gastroenterology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou 510120, China.
² Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou 510120, China.
³ Department of Gastroenterology, The First People's Hospital of PingJiang, Yueyang 410400, China.

Abstract

Background: Hepatocellular carcinoma (HCC) is characterized by extensive risk factors, high morbidity and mortality. Clinical prognostic evaluation assay assumes a nonspecific quality. Better HCC prognostics are urgently needed. Long noncoding RNAs (lncRNAs) exerts a crucial role in tumorigenesis and development. Excavating specific lncRNAs signature to ameliorate the high-risk survival prediction in HCC patients is worthwhile.

Methods: Differentially expressed lncRNAs (DElncRNAs) profile was acquired from The Cancer Genome Atlas database (TCGA). Then, the lncRNAs high-risk survival prognostic model was established using the least absolute shrinkage and selection operator (LASSO)-Cox regression algorithm. The lncRNAs were evaluated in clinical specimen by PCR. The receiver operating characteristic curve (ROC) analysis was further conducted to assess the potential prognostic value of the model. Moreover, a visible nomogram containing clinicopathological features and prognostic model was developed for prediction of survival property. Potential molecular mechanism was assessed by GO, KEGG, GSEA enrichment analysis and CIBERSORT immune infiltration analysis.

Results: A novel 7-lncRNA risk model (AL161937.2, LINC01063, AC145207.5, POLH-AS1, LNCSRLR, MKLN1-AS, AC105345.1) was constructed and validated for HCC prognosis prediction. Kaplan-Meier analysis revealed that patients in the high-risk group suffered a poor prognosis (p = 1.813 × 10^-8). These genes were detected by PCR, and the expression trend was in accordance with TCGA database. Interestingly, the risk score served as an independent risk factor for HCC patients (HR: 1.166, 95% CI:1.119-1.214, p < 0.001). The nomogram was established, and the predictive accuracy in the nomogram was prior to the TNM stage according to the ROC curve analysis. Cell proliferation related pathway, decreased CD4⁺ T cell, CD8⁺ T cell, NK cell and elevated Neutrophil, Macrophage M0 were observed in high-risk group. Besides, suppression of MKLN1-AS expression inhibited cell proliferation of HCC cells by CCK8 assay in vitro.

Conclusion: The 7-lncRNA signature may exert a particular prognostic prediction role in HCC and provide new insight in HCC carcinogenesis.

Keywords: Hepatocellular carcinoma; Immune microenvironment; Nomogram; Risk model; lncRNA.