ESCRT may function as a tumor biomarker, transitioning from pan-cancer analysis to validation within breast cancer

Abstract

Background: Studies have shown that ESCRT genes affect cell aging, immune environment, and tumors. BRCA was used to explore its effects on tumor prognosis and therapy.

Methods: The data sets of Cancer Genome Atlas (TCGA), Genome-Tissue Expression Plan (GTEX), Human Protein Mapping (HPA), Gene Expression Omnibus (GEO), Clinical Proteomic Tumor Analysis Consortium (CPTAC), R software package, and bioinformatics methods were used to mine the potential carcinogenic effects of ESCRT, including the expression level, prognostic value, and immune value of ESCRT in various types of tumor tissues, and the potential function of ESCRT family genes was further verified in breast cancer.

Results: ESCRT showed significant differential expression in various cancers, such as bladder urothelial carcinoma and liver, cervical, renal, esophageal, head, and neck cancers (P <0.05). Abnormal ESCRT expression is associated with poor prognosis in various cancers, such as adrenocortical carcinoma, bladder urothelial carcinoma, breast cancer, and cervical cancer (P <0.05). The expression level of ESCRT was significantly associated with immune cell infiltration and the modulation of the stromal/immune score (all P <0.05). Enrichment analysis showed that ESCRT is associated with immune-related functions and transport signaling pathways in various tumor cells. Moreover, ESCRT serves as an early diagnostic marker for several tumors and is significantly associated with prognosis. This confirms that ESCRT is associated with most immune-infiltrating cells in pan-carcinomas. Taken together, these studies highlight the importance of the ESCRT family gene VPS37D in breast cancer initiation, progression, and immune response.

Conclusion: This study highlights ESCRT's potential in tumor detection via pan-cancer analysis, showing expression variations between tumor and normal tissues, its role in cancer progression through the immune microenvironment, and its specificity and sensitivity in detection. The VPS37D gene, with significant variation in breast cancer, predicts patient prognosis and is related to the tumor microenvironment, suggesting that ESCRT is a novel biomarker for early diagnosis and prognosis assessment.

Keywords: ESCRT; VPS37D; biomarker; immune cell infiltration; pan-cancer.

Figure 1

Main biological functions of ESCRT. ① Viral release in the nucleus, Maintaining nuclear pore stability, nuclear envelope repair and remodeling, virus secretion; ② endocytosis, endomorphism; ③ cell division; ④ Lysosomal membrane repair and autophagy; ⑤ exdosomes secretion, ILV formation; and ⑥ MVB formation, microautophagy.

Figure 2

ESCRT family gene expression. (A) Gene expression levels in pan-cancer patients; (B) Differential expression of ESCRT between 18 tumor and normal tissue samples (*P <0.05, **P <0.01, ***P <0.001).

Figure 3

The prognosis value of ESCRT in pan-cancer. (A) Prognostic analysis of ESCRT-0 representative gene HGS in LIHC and KIRC; (B) Prognostic analysis of ESCRT-I representative gene VPS37D in BRCA and COAD; (C) ESCRT-II representative gene SNF 8 in STAD and KIRC; (D) ESCRT-III representative prognostic analysis of CHMP4C in LUSC and CESC; (E) Prognostic analysis of VPS 4-VTA 1 representative gene VPS4B in PAAD and ACC.

Figure 4

The correlation between ESCRT expression and immune infiltration. (A) Correlation of ESCRT expression with StromalScore; (B) Correlation of ESCRT expression with ImmuneScore; (C) Correlation of ESCRT expression with EstimateScore; and (D, E) Correlation of ESCRT expression with tumor cell stemness.

Figure 5

Correlation analysis of ESCRT expression and antitumor drug sensitivity.

Figure 6

Differential analysis of the ESCRT family genes in breast cancer. (A) Heatmap of the ESCRT family genes; (B) Volcanic map of differential genes; and (C) VPS37D immunosynthesis. 1.BRCA Organization 2. Normal breast tissue.

Figure 7

Enrichment analysis of significantly differential genes. (A) Differential genetic relationship chart; (B) Results of differential gene enrichment analysis.

Figure 8

Correlation analysis between VPS37D expression and BRCA clinical characteristics (*P <0.05, **P <0.01, ***P <0.001).

Figure 9

Analysis of the immune cell infiltration. (A) Differences in VPS37D expression levels in the immune score; (B) Immune infiltration score, matrix score, and estimated score were correlated with VPS37D expression; (C) The relationship between VPS37D expression obtained by the ssGSEA algorithm and immune cells; and (D) The association between VPS37D expression, as determined by the Cibersort algorithm, and immune cell populations (*P < 0.05, **P < 0.01, ***P < 0.001). ns, no significance.