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ARHGEF6 downregulation as a key mediator of tumor cell apoptosis in breast cancer

  • Authors:
    • Yang Zhang
    • Dandan Zhou
    • Xuting Shen
    • Qinqin Song
    • Liuyang Yang
    • Wenbo Li
    • Xinxin Zhao
    • Wenxiang Fang
    • Bian Liu
    • Chencen Xing
    • Jisong Liu
    • Haoshu Fang
    • Qilun Zhang
  • View Affiliations / Copyright

    Affiliations: Department of Central Laboratory, The Third People's Hospital of Bengbu Affiliated to Bengbu Medical University, Bengbu, Anhui 233000, P.R. China, Department of Critical Care Medicine, Shanghai East Hospital, Tongji University School of Medicine, Shanghai 200120, P.R. China, Department of Pathophysiology, Anhui Medical University, Hefei, Anhui 230032, P.R. China, Department of Burn and Plastic Surgery, The Third People's Hospital of Bengbu Affiliated to Bengbu Medical University, Bengbu, Anhui 233000, P.R. China, Core Facility Center for Medical Sciences, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui 230001, P.R. China, Animal Experiment Center, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui 230001, P.R. China, Department of Medical Education, The Fifth People's Hospital of Bengbu, Bengbu, Anhui 233000, P.R. China
    Copyright: © Zhang et al. This is an open access article distributed under the terms of Creative Commons Attribution License.
  • Article Number: 522
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    Published online on: September 12, 2025
       https://doi.org/10.3892/ol.2025.15268
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Abstract

The present study aimed to identify novel clinical biomarkers for breast cancer (BRCA) through bioinformatics analyses and cellular experiments, due to the ongoing need for improved diagnosis and prognosis in BRCA. The GSE21422 and The Cancer Genome Atlas‑BRCA (TCGA‑BRCA) datasets were utilized to identify differentially expressed genes (DEGs) in BRCA. Common DEGs were subjected to comprehensive analyses, including risk score modeling, expression profiling, receiver operating characteristic curve evaluation, survival analysis and the development of a prognostic nomogram, to pinpoint clinically significant genes. Cellular assays were subsequently performed to investigate the functional roles of these key genes in BRCA. Through bioinformatics analyses, 5 genes with diagnostic value were identified: Aldehyde dehydrogenase 1 family member A1 (ALDH1A1), Rac/Cdc42 guanine nucleotide exchange factor 6 (ARHGEF6), enhancer of zeste 2 polycomb repressive complex 2 subunit, integrin α1 (ITGA1) and PIK3R1, as well as 3 genes with prognostic value: ALDH1A1, ARHGEF6 and ITGA1. Among them, ARHGEF6 was recognized as the key gene in BRCA. Overexpression of ARHGEF6 was shown to suppress cell proliferation, invasion and migration, while promoting apoptosis in BRCA. In conclusion, by bioinformatics analysis, new diagnostic and prognostic biomarkers for patients with BRCA have been identified and the key gene, ARHGEF6, is a suppressor gene in BRCA progression. These findings provide new directions for BRCA clinical application.
View Figures

Figure 1

Overlapping DEGs were obtained from
GSE21422 and TCGA datasets. (A) DEGs in the GSE21422 dataset
includes 1,081 downregulated genes, 973 upregulated genes and
15,216 non-significant genes. (B) DEGs in TCGA dataset includes 903
upregulated genes, 1,498 downregulated genes and 14,785
non-significant genes. (C) The Venn diagram of overlapping DEGs
from the GSE21422 and TCGA datasets. Purple represents upregulated
GSE21422 DEGs, orange represents downregulated GSE21422 DEGs, green
represents upregulated TCGA DEGs and yellow represents
downregulated TCGA DEGs. (D) The enriched GO terms of overlapping
DEGs, including BP, CC and MF. (E) The enriched KEGG pathways of
the overlapping DEGs. (F) The protein-protein interaction network
of overlapping DEGs analyzed by BottleNeck algorithm, with 30
nodes. DEGs, differentially expressed genes; TCGA, The Cancer
Genome Atlas; GO, Gene Ontology; BP, Biological Process; CC, Cell
Component; MF, Molecular Function; KEGG, Kyoto Encyclopedia of
Genes and Genomes.

Figure 2

Prognostic signature genes were
identified by the risk score model. (A) Detailed table shows the
feature gene selection corresponding to the λmin value.
Each row represents a feature gene, and the columns include the
gene name and its corresponding coefficient. (B) The LASSO
regression coefficient plot illustrates the selection of 8
signature genes out of the 30 interactive genes. The vertical axis
represents the coefficient magnitude, and the horizontal axis
represents log(λ) values, where λ is the regularization parameter.
The vertical line at λmin indicates the selection of the
feature genes. (C) Risk score (top), survival time (middle) and
signature gene expression (bottom) from the low-risk group to
high-risk group. (D) Kaplan-Meier survival curve based on
progression-free survival reveals a significantly worse prognosis
in the high-risk group, indicating the prognostic risk model's
capability. (E) AUC values from the ROC curve analysis demonstrate
good predictive accuracy of the risk model for survival at 1, 3 and
5 years, with the highest prediction accuracy observed at the
1-year mark (AUC=0.699). LASSO, Least Absolute Shrinkage and
Selection Operator; AUC, area under the curve; HR, hazard ratio;
CI, confidence interval.

Figure 3

Gene mutation analysis of 8 signature
genes in BRCA. (A) The CNV percentage of 8 signature genes in BRCA
samples was evaluated to assess the genomic alterations. (B) A
heatmap displaying the SNV percentage of the 8 signature genes in
breast cancer samples (n=1,026) was generated to visualize the
mutation frequency. (C) The gene mutation details of signature
genes, including variant classification, variant type, SNV Class,
variants per sample, variant classification summary and the top 10
mutated genes. (D) The mutation types of 8 signature genes altered
in 71 (100%) of 71 BRCA samples. BRCA, breast cancer; CNV, copy
number variation; Hete Amp, heterozygous amplification; Homo Amp,
homozygous amplification; Hete Del, heterozygous deletion; Homo
Del, homozygous deletion; SNV, single nucleotide variant.

Figure 4

Candidate genes with diagnostic and
prognostic value in BRCA were identified. (A) The expression levels
of 8 signature genes in normal and BRCA tumor groups. (B-I) The
receiver operating calibration curve analysis of 8 signature genes.
The top 5 genes with the highest AUC values are ALDH1A1, ARHGEF6,
EZH2, ITGA1 and PIK3R1. (J-N) The Kaplan-Meier survival analysis of
PIK3R1, ALDH1A1, ARHGEF6, EZH2 and ITGA1. ***P<0.001. BRCA,
breast cancer; AUC, area under the curve; HR, hazard ratio; CI,
confidence interval; ALDH1A1, aldehyde dehydrogenase 1 family
member A1; ARHGEF6, Rac/Cdc42 guanine nucleotide exchange factor 6;
EZH2, enhancer of zeste 2 polycomb repressive complex 2 subunit;
ITGA1, integrin α1; ID1, inhibitor of DNA binding 1; FN1,
fibronectin.

Figure 5

ARHGEF6 was targeted in the present
study as the key gene. (A) Univariate and (B) multivariate Cox
regression analyses were performed to assess the prognostic
significance of PIK3R1, ALDH1A1, ARHGEF6, EZH2 and ITGA1. (C) The
prognostic nomogram integrated ALDH1A1, ARHGEF6, ITGA1 and pTNM
stage to predict the 1-, 3- and 5-year survival probability. (D)
The performance of the prognostic nomogram was evaluated using
calibration curves. ALDH1A1, aldehyde dehydrogenase 1 family member
A1; ARHGEF6, Rac/Cdc42 guanine nucleotide exchange factor 6; EZH2,
enhancer of zeste 2 polycomb repressive complex 2 subunit; ITGA1,
integrin α1; CI, confidence interval.

Figure 6

ARHGEF6 is a suppressor gene in BRCA.
(A) The ARHGEF6 protein level was downregulated in the BRCA tumor
group from the Human Protein Atlas database. (B) Lower ARHGEF6
expression is associated with higher IC50 values for
paclitaxel. The downregulation of ARHGEF6 was also observed in BRCA
samples based on individual (C) cancer stages, (D) age, (E) nodal
metastasis status, (F) TP53 mutation status and (G) major subclass.
*P<0.05, ***P<0.001 and ****P<0.0001. ARHGEF6, Rac/Cdc42
guanine nucleotide exchange factor 6; TCGA, The Cancer Genome
Atlas; BRCA, breast cancer.

Figure 7

Over-ARHGEF6 suppresses
proliferation, invasion and migration of BRCA cell lines. ARHGEF6
was overexpressed in Hs578t and MDA-MB-231 cells, which was
detected by (A) reverse transcription-quantitative PCR and (B)
western blotting assays. (C) Over-ARHGEF6 suppressed proliferation
of Hs578t and (D) Over-ARHGEF6 suppressed proliferation of
MDA-MB-231 cells, detected by CCK-8. (E) Over-ARHGEF6 suppressed
invasion and (F) Over-ARHGEF6 suppressed migration in BRCA cell
lines (magnification ×100). *P<0.05. BRCA, breast cancer;
ARHGEF6, Rac/Cdc42 guanine nucleotide exchange factor 6; NC,
negative control; Over-ARHGEF6, ARHGEF6 overexpression; OD, optical
density.

Figure 8

Over-ARHGEF6 promotes cell apoptosis.
(A) Spearman's correlation analysis showed that ARHGEF6 had a
positive correlation with apoptosis. (B) Flow cytometry showed that
over-ARHGEF6 suppressed cell apoptosis. (C) Over-ARHGEF6
downregulated BCL2 mRNA expression. (D) Over-ARHGEF6 upregulated
caspase3 mRNA expression. (E) Over-ARHGEF6 upregulated p53 mRNA
expression. (F) Over-ARHGEF6 downregulated BCL2 and upregulated
caspase3, c-caspase3 and p53 protein expression. *P<0.05,
**P<0.01. ARHGEF6, Rac/Cdc42 guanine nucleotide exchange factor
6; NC, negative control; Over-ARHGEF6, ARHGEF6 overexpression; TPM,
transcripts per million; c-caspase3, cleaved-caspase3.
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Spandidos Publications style
Zhang Y, Zhou D, Shen X, Song Q, Yang L, Li W, Zhao X, Fang W, Liu B, Xing C, Xing C, et al: ARHGEF6 downregulation as a key mediator of tumor cell apoptosis in breast cancer. Oncol Lett 30: 522, 2025.
APA
Zhang, Y., Zhou, D., Shen, X., Song, Q., Yang, L., Li, W. ... Zhang, Q. (2025). ARHGEF6 downregulation as a key mediator of tumor cell apoptosis in breast cancer. Oncology Letters, 30, 522. https://doi.org/10.3892/ol.2025.15268
MLA
Zhang, Y., Zhou, D., Shen, X., Song, Q., Yang, L., Li, W., Zhao, X., Fang, W., Liu, B., Xing, C., Liu, J., Fang, H., Zhang, Q."ARHGEF6 downregulation as a key mediator of tumor cell apoptosis in breast cancer". Oncology Letters 30.5 (2025): 522.
Chicago
Zhang, Y., Zhou, D., Shen, X., Song, Q., Yang, L., Li, W., Zhao, X., Fang, W., Liu, B., Xing, C., Liu, J., Fang, H., Zhang, Q."ARHGEF6 downregulation as a key mediator of tumor cell apoptosis in breast cancer". Oncology Letters 30, no. 5 (2025): 522. https://doi.org/10.3892/ol.2025.15268
Copy and paste a formatted citation
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Spandidos Publications style
Zhang Y, Zhou D, Shen X, Song Q, Yang L, Li W, Zhao X, Fang W, Liu B, Xing C, Xing C, et al: ARHGEF6 downregulation as a key mediator of tumor cell apoptosis in breast cancer. Oncol Lett 30: 522, 2025.
APA
Zhang, Y., Zhou, D., Shen, X., Song, Q., Yang, L., Li, W. ... Zhang, Q. (2025). ARHGEF6 downregulation as a key mediator of tumor cell apoptosis in breast cancer. Oncology Letters, 30, 522. https://doi.org/10.3892/ol.2025.15268
MLA
Zhang, Y., Zhou, D., Shen, X., Song, Q., Yang, L., Li, W., Zhao, X., Fang, W., Liu, B., Xing, C., Liu, J., Fang, H., Zhang, Q."ARHGEF6 downregulation as a key mediator of tumor cell apoptosis in breast cancer". Oncology Letters 30.5 (2025): 522.
Chicago
Zhang, Y., Zhou, D., Shen, X., Song, Q., Yang, L., Li, W., Zhao, X., Fang, W., Liu, B., Xing, C., Liu, J., Fang, H., Zhang, Q."ARHGEF6 downregulation as a key mediator of tumor cell apoptosis in breast cancer". Oncology Letters 30, no. 5 (2025): 522. https://doi.org/10.3892/ol.2025.15268
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