A novel 7‑hypoxia‑related long non‑coding RNA signature associated with prognosis and proliferation in melanoma

Abstract

Hypoxia‑related long non‑coding RNAs (lncRNAs) are important indicators of the poor prognosis of cancers. The present study aimed to explore the potential relationship between melanoma and hypoxia‑related lncRNAs. The transcriptome and clinical data of patients with melanoma were downloaded from The Cancer Genome Atlas database. The prognostic hypoxia‑related lncRNAs were screened out using Pearson's correlation test and univariate Cox analysis. As a result, a hypoxia‑related‑lncRNA signature based on the expression of 7 lncRNAs was constructed, with one unfavourable [MIR205 host gene (MIR205HG)] and six favourable (T cell receptor β variable 11‑2, HLA‑DQB1 antisense RNA 1, AL365361.1, AC004847.1, ubiquitin specific peptidase 30 antisense RNA 1 and AC022706.1) lncRNAs as prognostic factors for melanoma. Patients with melanoma were divided into high‑ and low‑risk groups based on the risk score obtained. Survival analyses were performed to assess the prognostic value of the present risk model. Potential tumour‑associated biological pathways associated with the present signature were explored using gene set enrichment analysis. The CIBERSORT algorithm demonstrated the important role of the hypoxia‑related lncRNAs in regulating tumour‑infiltrating immune cells. Clinical samples collected from our center partly confirmed our findings. Cell Counting Kit‑8 and flow cytometry assays indicated the suppression of proliferation of melanoma cells following inhibition of MIR205HG expression. Indicators of the canonical Wnt/β‑catenin signalling pathway were detected by western blotting. The present study demonstrated that MIR205HG could promote melanoma cell proliferation partly via the canonical Wnt/β‑catenin signalling pathway. These findings indicated a 7‑hypoxia‑related‑lncRNA signature that can serve as a novel predictor of melanoma prognosis.

Keywords: MIR205 host gene; hypoxia; long non‑coding RNA; melanoma; proliferation.

Figure 1.

Construction of the hypoxia-related-lncRNA signature. (A) Overlap between two hypoxia-related gene sets (KRIEG and WINTER) and mRNA expression levels in melanoma. (B) Multivariate Cox regression analysis was used to identify hypoxia-related lncRNAs. (C) Heatmap demonstrating hypoxia-related-lncRNA signature expression in patients. (D) Patients sorted into high- and low-risk groups according to the median risk score. (E) Survival status and survival time of each patient. The SR was calculated in both the high- and low-risk group. (F) Survival curve analysis of the 7-hypoxia-related-lncRNA signature in training cohort. (G) Time-dependent ROC curve analysis in training cohort. (H) Survival curve of the 7-hypoxia-related-lncRNA signature in sub-validation cohort 1. (I) Time-dependent ROC curves analysis in sub-validation cohort 1. (J) Survival curve of the 7-hypoxia-related-lncRNA signature in sub-validation cohort 2. (K) Time-dependent ROC curves analysis in sub-validation cohort 2. lncRNA, long non-coding RNA; ROC, receiver operating characteristic; SR, survival rate.

Figure 2.

Association of the 7-hypoxia-related-long non-coding RNA signature with clinicopathological features in melanoma. Association between the signature risk scores and the clinicopathological features, including (A) age (>65 vs. ≤65; unpaired Student's t-test, P=0.9469), (B) sex (female vs. male; unpaired Student's t-test, P=0.2866), (C) American Joint Committee on Cancer stage (stage I–II vs. stage III–IV; unpaired Student's t-test, P=0.0246), (D) M stage (stage 0 vs. stage 1; unpaired Student's t-test, P=0.6898), (E) N stage (stage <1 vs. stage ≥1; unpaired Student's t-test, P=0.0104) and (F) T stage (stage 0–2 vs. stage 3–4; unpaired Student's t-test, P<0.001).

Figure 3.

Hypoxia-related-lncRNA signature is an independent factor of prognostic indicators of melanoma. (A and B) Univariate and multivariate Cox regression analysis demonstrated the association between overall survival and clinicopathological parameters and the risk score. (C) Receiver operating characteristic curve analysis indicated the prognostic accuracy of clinicopathological parameters and the hypoxia-related lncRNA prognostic risk score. lncRNA, long non-coding RNA.

Figure 4.

PCA. PCA between the high-risk group and the low-risk group based on (A) the hypoxia-related-lncRNA signature, (B) hypoxia-related lncRNAs, (C) hypoxia-related genes and (D) all gene sets. The red and green dots represent high- and low-risk genes, respectively. lncRNA, long non-coding RNA; PCA, principal component analysis.

Figure 5.

Construction and validation of the prognostic nomogram. (A) Construction of the nomogram was based on traditional clinical variables and the risk score. (B and C) Calibration plot for the internal validation of the nomogram at 3 and 5 years. (D) Time-dependent receiver operating characteristic curves indicating the area under the curve of the nomogram.

Figure 6.

Co-expression RNA regulation network construction and functional enrichment analysis. (A) Construction of a hypoxia-related competing endogenous RNA regulation network based on predicted microRNAs and hypoxia-related mRNAs. (B-K) Gene Ontology-Biological Process gene sets enriched in the high-risk group, including activation of immune response (NES=1.75; P=0.012), regulation of immune system process (NES=1.63; P=0.002), adaptive immune response (NES=2.05; P<0.001), development of immune system (NES=1.82; P<0.001), positive regulation of immune response (NES=1.94; P<0.001), positive regulation of cell death (NES=1.77; P=0.002), negative regulation of cell cycle (NES=1.57; P=0.028), positive regulation of Wnt signalling pathway (NES=1.85; P<0.001) and regulation of Wnt signalling pathway (NES=1.75; P=0.004). NES, normalized enrichment score.

Figure 7.

Melanoma is associated with a variety of TIICs. (A) Related percentage of 22 types of TIICs calculated by the CIBERSORT algorithm shown in a bar plot. (B) Differences in infiltration levels of TIICs between the high- and low-risk groups based on the expression of 7 hypoxia-related long non-coding RNAs (unpaired Student's t-test). *P<0.05, **P<0.01 and ***P<0.001. TIICs, tumour-infiltrating immune cells.

Figure 8.

Silencing of MIR205HG inhibits proliferation of melanoma via the canonical Wnt/β-catenin signaling pathway. (A-C) RT-qPCR to detect the expression levels of HLA-DQB1-AS1, MIR205HG-1 and TRBV11-2 in melanoma or paired tissues from 20 patients (Paired Student's t-test; *P<0.05 and **P<0.01). (D) RT-qPCR to detect the relative silencing levels of lncMIR205HG (Data are presented as the mean ± SD; n=3; one-way ANOVA and Dunnett's test; *P<0.05 and **P<0.01). (E) Flow cytometric analysis of the cell cycle distribution in A375 cells after transfection with NC or MIR205HG siRNA. The percentages of cells in G₀/G₁, S and G₂/M phase are shown in the bar graph (n=3; unpaired Student's t-test; *P<0.05 and **P<0.01). (F) Proliferation of A375 cells transfected with NC or si-MIR205HG-1 was assessed using a Cell Counting Kit-8 assay (n=3; one-way ANOVA and Dunnett's test; **P<0.01). (G) β-catenin, p-β-catenin, c-Myc, GSK3-β and p-GSK3-β levels in A375 cells transfected with siRNAs determined by western blotting, ratio of phosphorylated protein to total protein (p/t, phosphorylated/total) about GSK3-β and β-catenin were calculated (n=3; unpaired Student's t-test; *P<0.05 and **P<0.01). MIR205HG, MIR205 host gene; NC, negative control; p-, phosphorylated; RT-qPCR, reverse transcription-quantitative PCR; siRNA/si, small interfering RNA; ns, non-significant.