Inflammatory Response-Related Long Non-Coding RNA Signature Predicts the Prognosis of Hepatocellular Carcinoma

Abstract

Background: Hepatocellular carcinoma (HCC) is a high mortality malignant tumor with genetic and phenotypic heterogeneity, making predicting prognosis challenging. Meanwhile, the inflammatory response is an indispensable player in the tumorigenesis process and regulates the tumor microenvironment, which can affect the prognosis of tumor patients.

Methods: Using HCC samples in the TCGA-LIHC dataset, we explored lncRNA expression profiles associated with the inflammatory response. The inflammatory response-related lncRNA signature was constructed by univariate Cox regression, LASSO regression, and multivariate Cox regression methods based on inflammatory response-related differentially expressed lncRNAs in HCC.

Results: Seven inflammatory response-related lncRNA signatures were identified in predicting HCC prognosis. Kaplan-Meier (K-M) survival analysis indicated that high-risk group HCC patients were associated with poor prognosis. The utility of the inflammatory response-related lncRNA signatures was proved by the AUC and DCA analysis. The nomogram further confirmed the accuracy of the novel signature in predicting HCC patients' prognoses. In validation, our novel signature is more accurate than traditional clinicopathological performance for prognosis prediction of HCC patients. GSEA analysis further elucidated the underlying mechanisms and pathways of HCC progression in the low- and high-risk groups. Moreover, immune cells infiltration responses and immune function analyses revealed a significant difference between high- and low-risk groups in cytolytic activity, MHC class I, type I INF response, type II INF response, inflammation-promoting, and T cell coinhibition. Finally, HHLA2, NRP1, CD276, TNFRSF9, TNFSF4, CD80, and VTCN1 were expressed higher in high-risk groups in the immune checkpoint analysis.

Conclusions: A novel inflammatory response-related lncRNA signature (AC145207.5, POLHAS1, AL928654.1, MKLN1AS, AL031985.3, PRRT3AS1, and AC023157.2) is capable of predicting the prognosis of HCC patients and providing new immune targeted therapies insight.

Figure 1

Flow chart of this study.

Figure 2

Go and KEGG enrichment analysis of inflammatory response-related DEGs. (a) GO analysis. (b) KEGG analysis. The inflammatory response-based lncRNA prognostic signature.

Figure 3

Development of inflammatory response-related lncRNA prognostic signature. (a) Univariate Cox regression analysis. (b, d) LASSO regression analysis. (c) Multivariate Cox regression analysis. Multivariate examination of the prognostic signature.

Figure 4

Validation of the seven inflammatory response-related lncRNAs signature. (a) K–M survival analysis result. (b) The AUC values for forecasting overall survival based on risk factors. (c) Survival status and the risk score distribution of HCC patients. (d) The AUC of the ROC curves represented 1-, 3-, and 5-year survival rate of HCC patients. (e) The DCA curves for the signature and clinicopathological manifestation.

Figure 5

Assessment of the clinical prognostic value of the inflammatory response-related lncRNA signature in HCC patients based on univariate and multivariate COX analyses. (a) Univariate independent Cox analysis. (b) Multivariate independent Cox analysis. (c) The lncRNA-mRNA interaction.

Figure 6

Heatmap of inflammatory response-related lncRNAs prognosis signature associated with clinical pathology.

Figure 7

Nomogram and calibration curves constructed based on prognostic inflammatory response-related lncRNA signature and prognosis related clinicopathological factors.

Figure 8

GSEA for inflammatory response-related lncRNAs signature.

Figure 9

The immune responses of the inflammatory response-related lncRNA signature in two risk group.

Figure 10

Immunity analyses and gene expression. (a) Relevant functional analysis of immune cell subsets. (b) Analyses of immune checkpoints between the two HCC risk groups.

Figure 11

Analyses of m6A modification expression between the low and high HCC risk groups.