A pan-cancer analysis targeting the oncogenic role of ATP-binding cassette transporter A1 in human tumors

Abstract

Objectives: ABCA1 is involved in the development and progression of a wide range of malignant tumors, so to further clarify the role of ABCA1 expression therein, and to search for new breakthroughs in the treatment of tumors and cancers, we launched a thorough pan-cancer analysis of ABCA1.

Methods: Based on the manipulation of TCGA (The Cancer Genome Atlas), GEO (Gene Expression Omnibus), Human Protein Atlas (HPA) datasets and various bioinformatics tools, The oncogenic role of ABCA1 in 33 tumor types was explored from six aspects: gene expression, prognosis, variation, immunohistochemistry, correlation of tumor-associated fibroblastic infiltration, and enriched analysis of related genes. The potential value of ABCA1 was also mined, such as: ABCA1 may be a potential marker of tumor metastasis, play a role in cancer resistance, and its expression may inhibit the spread of tumor cells.

Results: Based on the analysis results, we found that ABCA1 is expressed elevated and mutated in tumor samples of 33 cancer types compared with matched normal tissues, and these mutations may be related to the mechanism of cancer, metastatic ability, and prognosis, etc. Meanwhile, we also investigated the correlation between ABCA1 expression and tumor-associated fibroblast infiltration, and described its association with corresponding miRNAs, which can provide scientific basis for clinical diagnosis.

Conclusions: Our study thoroughly illustrates the impact of ABCA1's systemic presence across various forms of cancer. Given its specificity to tumors, ABCA1 holds promise as a biomarker for cancer diagnosis, monitoring for recurrence, and predicting outcomes. Consequently, our research could significantly bolster the case for utilizing ABCA1 in the therapeutic approach to cancer.

Keywords: ABCA1; bioinformatics; pan-cancer; prognosis; survival.

Figure 1

Expression level of ABCA1 gene in different tumors and pathological stages. (A) The expression status of the ABCA1 gene in different cancers or specific cancer subtypes was analyzed through TIMER2. *P < 0.05; **P < 0.01; ***P < 0.001. (B) ABCA1 gene conservation analysis among vertebrates was visualized using the UCSC genome browser. (C) For the type of DLBC (Tumor N = 47; Normal N = 337), GBM (Tumor N = 163; Normal N = 207), LGG (Tumor N = 518; Normal N = 207), SKCM (Tumor N = 461; Normal N = 558), TGCT (Tumor N = 137; Normal N = 165), and THYM (Tumor N = 118; Normal N = 339) in the TCGA project, the corresponding normal tissues of the GTEx database were included as controls. The box plot data were supplied. *P < 0.05. (D) Based on the TCGA data, the expression levels of the ABCA1 gene were analyzed by the main pathological stages (stage I, stage II, stage III, and stage IV) of ACC, BLCA, CESC, COAD, KICH, LUAD, PAAD, and THCA. Log2 (TPM+1) was applied for log-scale.

Figure 2

Correlation between ABCA1 gene expression and survival prognosis of cancers in TCGA. We used the GEPIA2 tool to perform overall survival (A) and disease-free survival (B) analyses of different tumors in TCGA by ABCA1 gene expression. The survival map and Kaplan-Meier curves with positive results are given. Red label indicated positively correlated, blue label indicated negatively correlated.

Figure 3

Mutation feature of ABCA1 in different tumors of TCGA. We analyzed the mutation features of ABCA1 for the TCGA tumors using the cBioPortal tool. The alteration frequency with mutation type (A) and mutation site (B) are displayed. We display the mutation site with the highest alteration frequency (A1407T) in the 3D structure of ABCA1 (C). We also analyzed the potential correlation between mutation status and overall, disease-specific, disease-free and progression-free survival of UCEC (D) using the cBioPortal tool.

Figure 4

Gene expression and immunohistochemistry of ABCA1 in tumors and normal tissues. For the type of LUAD, BRCA, OV, LIHC, TGCT, and THCA in the TCGA project, the corresponding normal tissues of the GTEx database were included as controls. The box plot data were supplied. *P < 0.05. We also used the HPA database to obtain immunohistochemical results of ABCA1 in tumors and normal tissues. The protein expression of GPC2 in immunohistochemical images of tumor (left) and normal (right) groups. (A) Lung. (B) Breast. (C) Ovary. (D) Liver. (E) Testis. (F) Thyroid.

Figure 5

Correlation analysis between ABCA1 expression and immune infiltration of cancer-associated fibroblasts. We used different algorithms (EPIC, MCPCOUNTER, and XCELL, among others) to explore potential correlations between ABCA1 gene expression levels and levels of infiltration of all types of CD8+T cells and cancer-associated fibroblasts in TCGA. (A) Heat maps of ABCA1’s association with infiltration of CD8+T cells and tumor-associated fibroblasts. (B) This plot is a representative scatter plot between ABCA1 and tumor-associated fibroblast infiltration.

Figure 6

ABCA1-related gene enrichment analysis. (A) The corresponding heatmap data in the detailed cancer types are displayed. (B) Using the GEPIA2 approach, we also obtained the top 100 ABCA1-correlated genes in TCGA projects and analyzed the expression correlation between ABCA1 and selected targeting genes, including RDX, ITSN1, PLSCR4,STOM and SPAG9. (C) Based on the ABCA1-binding and interacted genes, KEGG pathway analysis was performed. (D) We first obtained the available experimentally determined ABCA1-binding proteins using the STRING tool. (E) Sankey diagram of ABCA1: The picture demonstrates the pan-oncogene and pathway associated with ABCA1 gene. (ABCA1 single gene is highly associated with other pan-cancer pathways are enzyme-linked receptor protein signaling pathway, F1F0-ATP synthase, mitochondria, positive regulation of epithelial cell migration, EGF epidermal growth factor receptor signaling pathway, and positive regulation of cell migration).

Figure 7

ABCA1 gene upstream miRNA prediction. We predicted miRNAs for the target gene ABCA1 using the starbase database, and 15 target miRNAs that can represent the target gene ABCA1 are given in the figure.