In this study, two microarray datasets (GSE21422 and GSE29044) were retrieved from the NCBI Gene Expression Omnibus (GEO, https://www.ncbi.nlm.nih.gov/geo). The combined cohort comprised 119 human samples, consisting of 78 IDC tissues and 41 adjacent normal tissues (detailed in Table 1). Differential expression of ACOT7 between tumor and normal tissues was analyzed using the limma R package, with significance thresholds set at |log2 Fold Change (FC)| > 0.5 and an adjusted p-value < 0.01. Visualization was performed using volcano plots (ggplot2) and heatmaps (pheatmap).

Transcriptomic data and corresponding clinical information for breast invasive carcinoma (BRCA) were retrieved from The Cancer Genome Atlas (TCGA) via the Genomic Data Commons (GDC) Data Portal (https://cancergenome.nih.gov). Following the exclusion of non-invasive ductal carcinoma cases based on pathological records, a total of 793 breast invasive carcinoma samples and 93 normal samples were included. The limma R package was utilized for data preprocessing (log2 transformation and quantile normalization) and to identify differentially expressed genes (DEGs). DEGs were filtered using the criteria: |log2 Fold Change (FC)| > 0.5; adjusted p-value < 0.01.The results visualized using volcano plots (ggplot2) and heatmaps (pheatmap).

The Human Protein Atlas (HPA, https://www.proteinatlas.org) is a comprehensive database mapping protein localization and expression in human tissues via immunohistochemistry (IHC). To assess the tissue distribution of ACOT7, we retrieved IHC staining images from the HPA for both invasive breast carcinoma and normal breast tissues. Specifically, ACOT7 protein expression was evaluated in invasive breast carcinoma tissue from a 43-year-old female and normal breast tissue from a 45-year-old female using antibody HPA025762.

Kaplan-Meier plotter (https://kmplot.com) is an online tool designed to assess survival outcomes for various cancers based on gene expression data. It integrates extensive transcriptomic and clinical survival data from public databases (e. g., GEO, TCGA), enabling researchers to quickly assess the association between the expression of specific genes and patient survival. We utilized this tool to evaluate the prognostic value of ACOT7. Specifically, we analyzed the association between ACOT7 expression and Overall Survival (OS), Relapse-Free Survival (RFS), and Distant Metastasis-Free Survival (DMFS) in patients with breast cancer.

The Gene Multiple Association Network Integration Algorithm (GeneMANIA; http://www.genemania.org) is a web-based interface used for predicting gene functions via the integration of diverse genomic and proteomic datasets. In this study, GeneMANIA was employed to construct a functional interaction network centered on ACOT7.

The Tumor Immune Evaluation Resource (TIMER, https://cistrome.shinyapps.io/timer/) is a comprehensive web platform for analyzing the interplay between gene expression and immune cell infiltration in the tumor microenvironment. It integrates genomic and transcriptomic data from 32 cancer types in TCGA. In this study, we utilized the ‘Gene’ and ‘SCNA’ (Somatic Copy Number Alteration) modules of TIMER to assess the association between ACOT7 expression, as well as its copy number status, and immune cell infiltration levels in the TCGA BRCA cohort.

Genes significantly associated with ACOT7 expression (both positive and negative) were identified from the TCGA BRCA dataset. Gene Ontology (GO) functional annotation (including Biological Process [BP], Cellular Component [CC], Molecular Function [MF]) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using the clusterProfiler R package. Enriched terms with a p-value < 0.05 were considered statistically significant, and the results were visualized by ggplot2.

To elucidate the biological mechanisms associated with ACOT7, Gene Set Enrichment Analysis (GSEA) was performed. First, a ranked gene list was generated based on the correlation between ACOT7 expression and the whole transcriptome. The KEGG gene set collection (c2.cp.kegg.v7.2.symbols.gmt) was utilized as the reference database using the clusterProfiler package. Statistical significance was assessed using a default permutation test (1000 permutations). Gene set were considered significantly enriched using the following criteria: Normalized Enashment Score (NES) > 1.0, nominal p-value < 0.05 and False Discovery Rate (FDR) < 0.25.

This study was approved by the Ethics Committee of Anning First People’s Hospital (Approval No.: 2025-007-01). Tumor tissues and paired adjacent non-tumor tissues were collected from 15 patients with histologically confirmed invasive carcinoma. Following surgical resection, all specimens were immediately flash-frozen in liquid nitrogen and stored at -80 °C. Patients who had received neoadjuvant therapy were excluded from the study.

Three breast invasive carcinoma cell lines (T47D, BT549 and MCF7) and a normal breast epithelial cell line (MCF10A) were obtained from Beina Biological (China). T47D cells were cultured in high-glucose DMEM (Gibco); BT549 cells were maintained in RPMI 1640 medium (Gibco) supplemented with Insulin-Transferrin-Selenium (100 × ITS, YEASEN, China); MCF7 cells were grown in high-glucose DMEM containing 1% Non-Essential Amino Acid (NEAA, Procell, China) and 10 µg/mL Insulin (Procell, China); and MCF10A cells were cultured in specialized MCF10A medium. All complete medium were supplemented with 10% fetal bovine serum (FBS, Gibco) and 1% antibiotic-antimycotic solution (containing 10,000 U/mL penicillin, 10 mg/mL streptomycin, and 25 µg/mL amphotericin B; Servicebio, China). All cell lines were incubated at 37 °C in a humidified atmosphere containing 5% CO₂.

Total RNA was extracted from cell lines and clinical tissues using Trizol reagent, following the manufacturer’s instructions. Subsequently, RNA was reverse transcribed into cDNA. The cDNA of the indicated gene was quantified using the SYBR Master mixture (YEASEN, China) on the Xi’an Tian-long automatic medical PCR system. The thermal cycling conditions consisted of an initial denaturation at 95 °C for 2 min, followed by 40 cycles, each cycle including denaturation at 95 °C for 10 s; annealing/extension at 60 °C for 30 s, and finally incubation at 72 °C for 5 min. The relative mRNA expression levels were calculated using the 2-ΔΔCt method, normalized to the internal reference gene, GAPDH. All primer sequences were synthesized by Sangon Biotech (Shanghai, China) and are listed in Table 2.

Statistical analyses were performed using GraphPad Prism 10.1.2. Quantitative data are presented as the mean ± standard deviation (SD) from three independent experiments. Comparisons between two groups were analyzed using Student’s t-test, while comparisons among multiple groups were assessed using one-way ANOVA. A p-value < 0.05 was considered statistically significant.

Analysis of the two GEO databases consistently revealed a pronounced upregulation of ACOT7 transcripts in invasive ductal carcinoma relative to non-malignant controls (Figures 1A–F). Consistent results were obtained from differential expression analysis based on the TCGA database, which examined ACOT7 expression in BRCA (Figures 2A–C). Given the unequal number of tumor and normal samples in TCGA BRCA, the paired analysis was performed, revealing a significant increase in ACOT7 gene expression in breast tumor samples (Figure 2D). Furthermore, to explore the expression of ACOT7 in BRCA, we first analyzed clinical tissue samples. Analysis revealed a significant upregulation of ACOT7 mRNA in invasive breast cancer compared to adjacent normal tissues (P < 0.01; Figure 2E). Subsequently, we verified this trend at the cell line level. Compared to the normal mammary epithelial cell line MCF10A, ACOT7 expression was significantly elevated across a panel of breast cancer cell lines, including T47D, BT549, and MCF7 (P < 0.05; Figure 2F). Collectively, these results indicate that the upregulation of ACOT7 may be implicated in the pathogenesis and progression of breast cancer.

We used HPA online database to analyze the protein expression of ACOT7 in BRCA tissues and normal breast tissues. The results revealed a significantly higher level of ACOT7 expression in BRCA tissue samples compared to normal breast tissue samples (Figure 3).

To evaluate the prognostic impact of ACOT7, we utilized the Kaplan-Meier plotter to stratify patients into high and low expression cohorts. Elevated ACOT7 levels were significantly associated with diminished overall survival and distant metastasis-free survival, identifying it as an adverse prognostic factor in BRCA (Figures 4A–C). No statistically significant difference was observed in relapse-free survival (P = 0.073 > 0.05).

GeneMANIA interaction network analysis of ACOT7 (Figure 5) showed that its core interacting proteins were significantly enriched in biological processes closely related to tumorigenesis and progression. In addition to multiple acyl-CoA thioesterase members (including ACOT11, ACOT12, ACOT13, THEM4, and THEM5) in the lipid metabolism pathway, which are closely related to ACOT7 through co-expression, several key cancer-related proteins were identified in the network. These included the tumor suppressor DLC1, DNA damage repair protein BRCA1, and mitotic regulator RCC2. These results suggest that ACOT7 is not only participates in the regulation of fatty acid metabolism, but also may influence cell cycle progression and genomic stability through metabolic reprogramming or non-metabolic functions, thereby contributing to tumorigenesis. In addition, the coexistence of other metabolism-related proteins such as ALDH9A1 and HTD2 broadens the scope of ACOT7’s potential functions within the tumor metabolic network, paving the way for further investigation into the molecular mechanisms of ACOT7 in cancer and other diseases.

We assessed the association of ACOT7 expression with immune cell infiltration levels in BRCA via the TIMER database. The results showed that ACOT7 expression was positively correlated with tumor purity (partial.cor = 0.071) and infiltration of B cells (partial.cor = 0.104) and dendritic cells (partial.cor = 0.085). On the contrary, it was negatively correlated with the infiltration of macrophages (partial.cor = -0.145) and CD8+ T cells (partial.cor = -0.074), while no significant association was observed with neutrophil infiltration (P = 0.669; Figures 6A, B). These data suggest that ACOT7 may play a dual role in the tumor immune microenvironment: on the one hand, it enhances immune surveillance by promoting the anti-tumor immune response of B cells and dendritic cells; on the other hand, it participates in the immune escape process by inhibiting the function of macrophages and CD8+ T cells. This effect may be related to its mechanism of regulating lipid metabolism and influencing macrophage M1/M2 polarization and inflammatory phenotype transformation.

To elucidate the potential mechanism of ACOT7 in BRCA, we systematically performed GO, KEGG, and GSEA enrichment analyses. GO analysis revealed that the expression of ACOT7 was significantly associated with epigenetic regulatory pathways such as miRNA-mediated gene silencing and centromeric chromatin assembly (Figure 7A, B). These results suggest that the function of ACOT7 in BRCA may not only be limited to lipid metabolism, but also be involved in tumorigenesis by regulating the epigenetic status of cells, thus revealing its potential role as a new regulatory factor. KEGG enrichment analysis indicated that ACOT7 may be a key node in the miRNA-mediated gene silencing network, and may regulate tumor progression by coordinating downstream target genes. Furthermore, ACOT7 was also linked to pathways including bitter taste transduction, the tumor immune microenvironment (neutrophil extracellular trap formation), and hormone metabolism (steroid hormone biosynthesis), providing clues for exploring its novel functions in BRCA immune regulation and hormonal responses (Figure 7C, D). GSEA enrichment analysis demonstrated that ACOT7 was significantly enriched in the oxidative phosphorylation pathway (Figure 7E), indicting that its high expression is positively correlated with a high-energy metabolic state in tumor cells. This suggests that ACOT7 may enhance mitochondrial function to promote energy production and biosynthesis, thereby supporting the rapid growth and invasion of breast cancer.