Ann Surg Treat Res.  2024 May;106(5):263-273. 10.4174/astr.2024.106.5.263.

CTLA4 expression profiles and their association with clinical outcomes of breast cancer: a systemic review

• Jin T
• Park KS
• Nam SE
• Lim SH
• Kim JH
• Noh WC
• Yoo YB
• Park WS
• Yun IJ

• KMID: 2555723
• DOI: http://doi.org/10.4174/astr.2024.106.5.263

Abstract

Purpose
The cytotoxic T-lymphocyte-associated protein 4 (CTLA4) is involved in the progression of various cancers, but its biological roles in breast cancer (BRCA) remain unclear. Therefore, we performed a systematic multiomic analysis to expound on the prognostic value and underlying mechanism of CTLA4 in BRCA.
Methods
We assessed the effect of CTLA4 expression on BRCA using a variety of bioinformatics platforms, including Oncomine, GEPIA, UALCAN, PrognoScan database, Kaplan-Meier plotter, and R2: Kaplan-Meier scanner.
Results
CTLA4 was highly expressed in BRCA tumor tissue compared to normal tissue (P < 0.01). The CTLA4 messenger RNA levels in BRCA based on BRCA subtypes of Luminal, human epidermal growth factor receptor 2, and triple-negative BRCA were considerably higher than in normal tissues (P < 0.001). However, the overexpression of CTLA4 was associated with a better prognosis in BRCA (P < 0.001) and was correlated with clinicopathological characteristics including age, T stage, estrogen receptors, progesterone receptors, and prediction analysis of microarray 50 (P < 0.01). The infiltration of multiple immune cells was associated with increased CTLA4 expression in BRCA (P < 0.001). CTLA4 was highly enriched in antigen binding, immunoglobulin complexes, lymphocyte-mediated immunity, and cytokine-cytokine receptor interaction.
Conclusion
This study provides suggestive evidence of the prognostic role of CTLA4 in BRCA, which may be a therapeutic target for BRCA. Furthermore, CTLA4 may influence BRCA prognosis through antigen binding, immunoglobulin complexes, lymphocyte-mediated immunity, and cytokine-cytokine receptor interaction. These findings help us understand how CTLA4 plays a role in BRCA and set the stage for more research.

Keyword

Breast neoplasms; CTLA4; Multiomics; Prognosis

Figure

• 

  Fig. 1 The expression of CTLA4 messenger RNA (mRNA) in different types of cancers (Oncomine and The Cancer Genome Atlas [TCGA] database). (A) This graphic generated by Oncomine (https://www.oncomine.org/resource/login.html) indicates the numbers of datasets with statistically significant (P < 0.01) mRNA overexpression (red) or down-expression (blue) of CTLA4 (different types of cancer vs. corresponding normal tissue). The threshold was designed with the following parameters: P-value of 1e-4, fold change of 2, and gene ranking of 10%. (B) Human CTLA4 expression levels in different tumor types from the TCGA database were determined. ***P <0.001.

• 

  Fig. 2 The expression of CTLA4 messenger RNA in breast cancer (BRCA). (A) Expression of CTLA4 in cancer tissue and normal tissue generated by GEPIA web (Gene Expression Profiling Interactive Analysis; http://gepia.cancer-pku.cn/index.html), P < 0.01. (B) Expression of CTLA4 in BRCA based on BRCA subtypes by UALCAN web (Utility for Alleviating Laboratory, and Computational Analysis; http://ualcan.path.uab.edu/index.html). TCGA, The Cancer Genome Atlas; HER2, human epidermal growth factor 2.

• 

  Fig. 3 Overall survival (OS) of CTLA4 in breast cancer. (A) OS of CTLA4 in breast cancer using PrognoScan (http://dna00.bio.kyutech.ac.jp/PrognoScan-cgi/PrognoScan.cgi). (B) OS of CTLA4 in breast cancer using Kaplan-Meier plotter (https://kmplot.com/analysis/index.php?p=service). (C) OS of CTLA4 in breast cancer using R2: Kaplan-Meier scanner (https://hgserver1.amc.nl/cgi-bin/r2/main.cgi). HR, hazard ratio; CI, confidence interval; TCGA, The Cancer Genome Atlas.

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  Fig. 4 The relationship between CTLA4 expression and immune cell infiltration in breast cancer. NK, natural killer; Th, T helper; Tgd, T gamma delta; DC, dendritic cell; pDC, plasmacytoid DC; iDC, immature DC; aDC, activated DC; Tcm, T central memory; Tem, T effector memory; TFH, T follicular helper; Treg, regulatory T cell.

• 

  Fig. 5 The correlation between CTLA4 expression and immune cell infiltration in breast cancer. Correlation between CTLA4 expression and (A) activated dendritic cells (aDC), (B) B cells, (C) CD8 T cells, (D) cytotoxic cells, (E) dendritic cells (DC), (F) immature dendritic cells (iDC), (G) macrophages, (H) neutrophils, (I) natural killer (NK) CD56dim cells, (J) plasmacytoid DC (pDC), (K) T cells, (L) T helper (Th) cells, (M) T central memory (Tcm), (N) T effector memory (Tem), (O) T follicular helper (TFH), (P) Th1 cells, (Q) Th2 cells, and (R) regulatory T cells (Treg). TPM, transcripts per million. P < 0.001.

• 

  Fig. 6 Functional enrichment analysis of samples with high and low CTLA4 expression. (A) Volcano plot of differentially expressed genes (DEGs), |log2 (FC)| > 1 and adjusted P < 0.05. (B) Heatmap of DEGs. TPM, transcripts per million.**P < 0.01 and ***P < 0.001.

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  Fig. 7 Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis of differentially expressed genes with low and high expression CTLA4 in breast cancer. (A) GO analysis. (B) KEGG analysis. P < 0.001.

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  Fig. 8 Identification of known and predicted structural proteins essential for CTLA4 functions and top 5 hub genes (cytoHubba). (A) The protein-protein interaction network of CTLA4 was generated using the Cytoscape STRING plug-in. GRB2, growth factor receptor-bound protein 2; CD80, T-lymphocyte activation antigen CD80; LCK, tyrosine-protein kinase Lck; CD86, T-lymphocyte activation antigen CD86; CD276, immune costimulatory protein b7-h3; PTPN11, tyrosine-protein phosphatase non-receptor type 11; FOXP3, forkhead box protein P3; ICOSL, ICOS ligand; B7RP1, inducible T-cell co-stimulator ligand; PPP2R4, serine/threonine-protein phosphatase 2A activator. (B) The top 5 hub genes were identified using the Cytoscape cytoHubba plug-in with extracted data from the degree of calculation methods.

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