Integrating bioinformatics and experimental validation to unveil disulfidptosis-related lncRNAs as prognostic biomarker and therapeutic target in hepatocellular carcinoma

Abstract

Background: Hepatocellular carcinoma (HCC) stands as a prevalent malignancy globally, characterized by significant morbidity and mortality. Despite continuous advancements in the treatment of HCC, the prognosis of patients with this cancer remains unsatisfactory. This study aims at constructing a disulfidoptosis‑related long noncoding RNA (lncRNA) signature to probe the prognosis and personalized treatment of patients with HCC.

Methods: The data of patients with HCC were extracted from The Cancer Genome Atlas (TCGA) databases. Univariate, multivariate, and least absolute selection operator Cox regression analyses were performed to build a disulfidptosis-related lncRNAs (DRLs) signature. Kaplan-Meier plots were used to evaluate the prognosis of the patients with HCC. Functional enrichment analysis was used to identify key DRLs-associated signaling pathways. Spearman's rank correlation was used to elucidate the association between the DRLs signature and immune microenvironment. The function of TMCC1-AS1 in HCC was validated in two HCC cell lines (HEP3B and HEPG2).

Results: We identified 11 prognostic DRLs from the TCGA dataset, three of which were selected to construct the prognostic signature of DRLs. We found that the survival time of low-risk patients was considerably longer than that of high-risk patients. We further observed that the composition and the function of immune cell subpopulations were significantly different between high- and low-risk groups. Additionally, we identified that sorafenib, 5-Fluorouracil, and doxorubicin displayed better responses in the low-score group than those in the high-score group, based on IC50 values. Finally, we confirmed that inhibition of TMCC1-AS1 impeded the proliferation, migration, and invasion of hepatocellular carcinoma cells.

Conclusions: The DRL signatures have been shown to be a reliable prognostic and treatment response indicator in HCC patients. TMCC1-AS1 showed potential as a novel prognostic biomarker and therapeutic target for HCC.

Keywords: Disulfidptosis; Hepatocellular carcinoma; Immune microenvironment; Long non-coding RNA; Prognostic signature; TMCC1-AS1.

Fig. 1

The flow diagram of the research process

Fig. 2

Construction and validation of the prognostic signature of DRLs. (A) Forest plot of univariate analysis results showing 11 OS-related DRLs. (B) Heatmap showing the expression of 11 OS-related DRLs in the normal and tumor samples. (C) Cross-validation plot for the penalty term. (D) Diagram for LASSO expression coefficients. ^**p < 0.01, ^***p < 0.001

Fig. 3

Independent prognostic analysis and establishment of a nomogram. (A) Univariate Cox regression analysis of the clinical characteristics and riskScore with the OS. (B) Multivariate analysis of the clinical characteristics and riskScore with the OS. (C) A nomogram predicting the 1-, 3- and 5-years survival rates of HCC using stage and independent prognostic factors (stage and risk score). (D) The calibration curves showing the concordance between the prediction by nomogram and actual survival

Fig. 4

Relationship between the prognostic signature of DRLs and clinical characteristics. (A)–(F) Kaplan–Meier curve for overall survival in different clinical features such as age (A, B), grade (C, D), and stage (E, F)

Fig. 5

Functional enrichment analyses. (A) GO functional enrichment analysis with bubble plot (BP, biological process; CC, cellular component; MF, molecular function). (B) KEGG pathway enrichment analysis with bubble plot

Fig. 6

Infiltrations and functions of immune cells between high- and low-risk groups. (A) Heatmap for immune infiltration based on TIMER, CIBERSORT, quanTIseq, MCP-counter, xCELL and EPIC algorithms among high- and low-risk groups. (B) Single sample gene set enrichment analysis (ssGSEA) showing different extent of immune cell infiltrations in the high- and low-risk groups. (C) ssGSEA analyses showing different functions of immune cell in the high- and low-risk groups. (D) The expression of immune checkpoint genes between high- and low-risk groups. ^*p < 0.05, ^**p < 0.01, ^***p < 0.001

Fig. 7

TMB analyses and drug sensitivity between high- and low-risk groups. (A-B) Waterfall plot displaying the mutation information of the genes with high mutation frequencies in the high- (A) and low- (B) risk groups. (C) Kaplan–Meier curve for OS of patients with HCC in high and low TMB (p = 0.031). (D) Kaplan–Meier curve for OS of patients with HCC according to the TMB and the risk signature of DRLs. (E) The TIDE scores of high- and low-risk groups. (F-H) The correlation between the risk score of DRLs signature and sensitivity of drugs such as sorafenib (F), 5-Fluorouracil (G), and doxorubicin (H). ^***p < 0.001

Fig. 8

Knockdown of TMCC1-AS1 inhibited cell proliferation in HCC. (A) The expression of TMCC1-AS1 was assessed in 8 HCC tissues and 8 normal liver tissues by RT-qPCR assay. (B) RT-qPCR analysis showing the expression of TMCC1-AS1 in two HCC cell lines (HEP3B and HEPG2) and a normal liver cell (NC). (C-D) The efficiency of si-TMCC1-AS1 transfection in HEP3B (C) and HEPG2 (D) cells was assessed by RT-qPCR. (E-F) Cell proliferation of HEP3B (E) and HEPG2 (F) cells transfected with control (si-NC) or si-TMCC1-AS1 was measured via CCK8 assay. Data are presented as the mean ± SDs. ^***p < 0.001

Fig. 9

Inhibition of TMCC1-AS1 prevented cell migration and invasion in HCC. (A-D) Representative data from Transwell migration and invasion assays showing the migratory and invasive capacities of TMCC1-AS1-deficient HEP3B (A, B) and HEPG2 (C, D) cells. Scales bar, 100 μM. The data are the means ± SDs and are representative of three independent experiments. (E-H) Representative data from wound healing migration assays showing HEP3B (E, F) and HEPG2 (G, H) cell migration of control cells compared to TMCC1-AS1-depleted cells. Scales bar, 100 μM. Data are presented as the mean ± SDs. The data are the means ± SDs and are representative of three independent experiments. ^***p < 0.001