Pan-cancer analysis identifies LPCATs family as a prognostic biomarker and validation of LPCAT4/WNT/β-catenin/c-JUN/ACSL3 in hepatocellular carcinoma

Abstract

Lipid remodeling regulators are now being investigated as potential therapeutic targets for cancer therapy as a result of their involvement, which includes promoting cancer cells' adaptation to the restricted environment. Lysophosphatidylcholine acyltransferases (LPCATs, LPCAT1-4) are enzymes that regulate the remodeling of bio-membranes. The functions of these enzymes in cancer are largely unknown. In the current study, we found that genes belonging to the LPCAT family participated in tumor advancement and were strongly linked to dismal prognosis in many different malignancies. We constructed the LPCATs scores model and explored this model in pan-cancer. Malignant pathways in pan-cancer were positively related to LPCATs scores, and all pathways had strong links to the tumor microenvironment (TME). Multiple immune-associated features of the TME in pan-cancer were likewise associated with higher LPCATs scores. In addition, the LPCATs score functioned as a prognostic marker for immune checkpoint inhibitor (ICI) therapies in patients with cancer. LPCAT4 enhanced cell growth and cholesterol biosynthesis by up-regulating ACSL3 in hepatocellular carcinoma (HCC). WNT/β-catenin/c-JUN signaling pathway mediated LPCAT4's regulation on ACSL3. These findings demonstrated that genes in the LPCAT family might be used as cancer immunotherapy and prognosis-related biomarkers. Specifically, LPCAT4 could be a treatment target of HCC.

Keywords: LPCATs; bioinformatics; cholesterol biosynthesis; liver hepatocellular carcinoma.

Figure 1

LPCATs family genes expression distribution in pan-cancer.

Figure 2

Single-nucleotide variants and gene copy number variants (CNV) of LPCATs family genes in pan-cancer. (A) Overall perspective of LPCAT1-4 genes was demonstrated in pan-cancer. (B) The single-nucleotide variant status of LPCAT1-4 genes in pan-cancer was showed. (C) The mutation frequency of LPCAT1-4 genes in pan-cancer was demonstrated. (D) The proportion of different types of CNV of LPCATs family genes in pan-cancer was demonstrated. (E) The CNV of LPCAT family genes heterozygous amplification and deletion were demonstrated. (F) The CNV of LPCAT family genes homozygous amplification and deletion were demonstrated.

Figure 3

Construction of LPCATs score and its value in pan-cancer. (A) The ssGSEA analysis was used to construct LPCATs score in pan-cancer. (B) The uniCox analysis was used to evaluate association among OS, PFS, DSS, DFI and LPCATs score. (C) The correlation between the LPCATs score and the GSVA score in cases of pan-cancer.

Figure 4

Analysis of association between LPCATs Score and immune infiltrating, potent anticancer inhibitors. (A) The link between LPCATs Score and immune infiltrating score in pan-cancer was illustrated. (B) The value of LPCATs Score in predicating response outcomes and OS in immune checkpoint blockade (ICB) sub-cohorts was demonstrated. (C) The link between gene expression and the sensitivity of GDSC pharmaceuticals (top 30) was represented. (D) The top 30 CTRP pharmaceuticals and their sensitivity to pan-cancer expression profiles are presented.

Figure 5

Identification of LPCAT4 biological function in LIHC. (A) LPCAT4 mRNA expression level was examined by RT-PCR assay. (B) LPCAT4 protein expression level in LIHC tissues. (C) Western blot assay was used to examine LPCAT4 protein down-regulation efficiency. (D) MTT assay was used to analyze cell growth. (E) Colony formation ability in LPCAT4 down-regulation and control group.

Figure 6

Functional enrichment analysis of LPCAT4 in LIHC. (A) Volcano plot indicated the significantly down-regulated and up-regulated DEGs. (B) GO analysis of DEGs. (C) KEGG analysis of DEGs.

Figure 7

LPCAT4 increased the expression levels of cholesterol biosynthesis via up-regulating ACSL3. (A) Cholesterol synthesis ability was analyzed in LPCAT4 down-regulation and control group. (B, C) ACSL3 mRNA and protein expression levels were analyzed by RT-PCR and western blot assays, respectively. (D) Overexpression of LPCAT4 increased cholesterol biosynthesis, while knockdown of ACSL3 dismissed this effect. (E) Down-regulation of LPCAT4 decreased cholesterol biosynthesis, while overexpression of ACSL3 could counteract this effect.

Figure 8

LPCAT4 regulated ACSL3 expression via WNT/β-catenin/c-JUN signaling pathway. (A) GSEA analysis indicated that WNT signaling pathway was found to be significantly enriched in the high LPCAT4 expression group. (B) Western blot assay was used to examine protein expression level. (C) The three transcription factor-binding sites of c-JUN on potential ACSL3 promoter region were indicated. (D) RT-PCR was used to examine ACSL3 mRNA expression. (E) The ChIP assay was used to validate binding domains of c-JUN in the potential ACSL3 promoter. (F) The luciferase assay was used to confirm which binding sites were functional. (G, H) Western blot assay was used to examine protein expression level.