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. 2025 Aug 23;25:1363. doi: 10.1186/s12885-025-14680-1

The role of collagen type VI alpha 6 chain as a potential tumor suppressor in breast cancer: an immune regulation perspective

Jian-Di Li 1,#, Li-Li Deng 2,#, Jia-Yuan Luo 1, Chao-Hua Mo 3, Bang-Teng Chi 1, Wan-Ying Huang 1, Rong-Quan He 2, Di-Yuan Qin 4, Chang Song 1, Wen Zou 1,✉, Gang Chen 1,✉
PMCID: PMC12374434  PMID: 40846911

Abstract

Background

Collagen type VI alpha 6 chain (COL6A6), an essential component of epithelial cell basal lamina, is hypothesized to function as a tumor suppressor in various cancers, yet its role in breast cancer remains unclear. This study aimed to elucidate COL6A6 expression patterns, assess its impact on the tumor immune microenvironment, and uncover underlying molecular mechanisms in breast cancer progression.

Methods

Immunohistochemical staining of COL6A6 was conducted on 136 breast cancer tissues and 50 non-breast-cancer controls in-house. Global microarray and high-throughput sequencing datasets were analyzed to confirm mRNA expression trends, supported by single-cell RNA sequencing for expression intensity and distribution. Prognostic evaluation utilized a multicenter cohort of breast cancer patients through Kaplan–Meier survival and decision curve analyses. Tumor deconvolution and gene set enrichment analyses predicted COL6A6’s association with the tumor immune microenvironment and its molecular mechanisms. Mouse models, spatial transcriptomic sequencing, and transcriptional regulation analyses were employed to elucidate the intimate relationship between COL6A6 expression and immune cell distribution. Potential therapeutic agents for breast cancer patients were predicted by targeting the COL6A6 protein.

Results

COL6A6 protein staining intensity was significantly lower in breast cancer tissues compared to normal breast tissues (p < 0.0001). Integrated analysis confirmed COL6A6 downregulation in 4818 breast cancer tissues versus 1236 non-breast-cancer tissues (standardized mean difference =  − 1.27 [− 1.66, − 0.87]), supported by single-cell RNA sequencing. Reduced COL6A6 mRNA expression moderately discriminated breast cancer from non-breast-cancer tissues (pooled area under the curve = 0.88, sensitivity = 84.85%, specificity = 72.68%). Decreased COL6A6 expression correlated with poorer overall and relapse-free survival. It had a negative correlation with the purity of the tumor but a positive correlation with the quantity of stromal and immune cells in the tumor microenvironment. Immune regulatory pathways such as adaptive immune response, T cell differentiation, T cell proliferation, macrophage activation, and natural killer cell-mediated cytotoxicity were associated with the gene sets that were enriched in the analysis. Immune-related biological processes, such as immunoglobulin production, generation of immune response mediators, myeloid leukocyte activation, leukocyte chemotaxis, and neutrophil migration, were significantly enriched in mouse models immunized with a COL6A6 peptide vaccine. The downregulation of COL6A6 was associated with reduced immune cell infiltration in malignant regions of breast cancer tissue slices, which might be negatively regulated by the CBX2 transcription factor. MK-886 may serve as a promising therapeutic agent for breast cancer treatment by targeting COL6A6 (Vina score =  − 8.0).

Conclusions

COL6A6 may operate as a tumor suppressor in breast cancer, underscoring its correlation with immune activity in the tumor microenvironment. These findings suggest COL6A6 as a promising therapeutic target and prognostic biomarker warranting further investigation.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-025-14680-1.

Keywords: Breast cancer, COL6A6, Immunohistochemical staining, scRNA-seq, Tumor microenvironment, GSEA

Background

With an estimated 2.3 million new cases each year, breast cancer continues to be the most prevalent cancer diagnosed and the leading cause of cancer-related mortality in women globally [1]. Breast cancer is a complex disease influenced by various genetic and environmental factors that affect its development and progression [2, 3]. Even though breast cancer treatment and management have advanced significantly [4, 5], a deeper comprehension of the underlying molecular pathways causing this illness is still desperately needed [6]. Investigating the tumor microenvironment [7], which comprises not only the malignant cells themselves but also the surrounding stromal and immune cells that are essential for tumor growth and dissemination [8], is one intriguing line of inquiry.

In this regard, it has been determined that the protein collagen type VI alpha 6 chain (COL6A6) may have a role in the onset and spread of breast cancer. COL6A6 is a component of the basal lamina in epithelial cells, which is an essential structural component in the extracellular matrix. It is anticipated that COL6A6 controls the interactions between epithelial cells and fibronectin [9]. The dysregulation of extracellular matrix proteins has been linked to various cancers, including breast cancer [10, 11]. COL6A6 has been demonstrated to be downregulated in lung adenocarcinoma and is involved in T cell activation [12]. Pituitary adenoma cell proliferation and migration may be inhibited by induced COL6A6 overexpression [13], suggesting a potential tumor-suppressive role for COL6A6. Although COL6A6 has been reported to show a downregulation trend in small-sample-size single-centered research [14, 15], its comprehensive expression patterns and impact on the immune landscape in breast cancer have yet to be fully elucidated.

Our study aimed to fill this knowledge vacuum by defining the expression profile of COL6A6 in breast cancer, examining its relationship to the tumor immune milieu, and identifying the molecular pathways driving the advancement of breast cancer.

Methods

In-house invasive ductal breast cancer tissue specimen

Invasive ductal breast cancer specimens resected at the First Affiliated Hospital of Guangxi Medical University from 2012 to 2015 were chosen based on the following criteria: (I) female patients; (II) patients diagnosed with primary breast invasive ductal carcinoma following the WHO classification; (III) preoperative patients who have not received adjuvant or neoadjuvant therapy; and (IV) patients who have received standardized postoperative treatments. Patients with archived wax-block cancer tissue that was too small to be re-sliced were excluded. All participants in the study provided their informed consent to participate. The Ethics Committee of the First Affiliated Hospital of Guangxi Medical University approved this study (NO.2022-KT-GUIWEI-135). The 1964 Declaration of Helsinki, its subsequent revisions, and other related ethical norms were followed in the conduct of this investigation.

Immunohistochemical staining experiment

The rabbit polyclonal antibody against COL6A6 was sourced from Abcam (ab150926). We conducted immunohistochemical staining experiments on breast cancer tissues and non-breast-cancer control tissues using a two-step method, with the antibody diluted at a ratio of 1:1000 [16, 17]. Human bone marrow tissue served as the positive control for COL6A6, while phosphate-buffered saline was used in place of the primary antibody as the negative control. All specimens were processed according to the kit instructions, with positive and negative controls included for each staining. Two experienced pathologists independently evaluated the trials in a double-blinded manner. In cases of disagreement, a third pathologist reviewed the results to reach a final judgment. At high magnification (× 400), five consecutive fields were evaluated. The interpretation criteria for the immunohistochemical staining data were as follows: (I) staining intensity was recorded as previously described [18]; (II) the percentages of positively stained breast cancer cells or breast epithelial cells were scored out of 100 cells as previously described [19]; and (III) the immunohistochemical score was computed using the formula: immunohistochemical score = intensity × percentage.

Microarrays and high-throughput bulk RNA sequencing analysis

We collected the global microarrays and high-throughput sequencing datasets to verify COL6A6 mRNA expression trends. Datasets were sourced from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus, and the Genotype-Tissue Expression project. The following search terms were used: (((breast OR mammary) AND (cancer OR carcinoma OR tumor OR neoplas* OR adenoma OR malignan*)) OR (BRCA OR luminal OR HER-2+ OR TNBC OR triple-negative breast cancer)). Datasets were included based on the following criteria: (I) human breast tissues; (II) primary breast cancer rather than metastatic tumor; and (III) tumor tissue samples without prior treatment by radiotherapy, chemotherapy, or any other therapeutic methods. Datasets were excluded if they: (I) were derived from a cell line, and (II) included stromal tumors rather than breast epithelial carcinoma. The datasets were double-blindly screened by two independent authors. Eligible datasets were transformed to the log2(x + 1) scale, and each dataset was integrated into platform expression matrices. Inter-study batch effects were removed using the ComBat function of the sva package [20].

Based on the processed platform expression matrices, the standardized mean difference (SMD) was computed to evaluate the comprehensive mRNA expression level of COL6A6 in breast cancer [21]. Subgroup analyses were conducted across various molecular subtypes of breast cancer, including Luminal A, Luminal B, HER2+, and triple-negative breast cancer (TNBC). The area under the curve (AUC) of COL6A6 was measured using summary receiver operating characteristic (SROC) curve analysis, along with its sensitivity and specificity, to distinguish breast cancer tissues from non-breast cancer cells [22].

Single-cell RNA sequencing analysis

Single-cell RNA sequencing analyses were conducted to assess COL6A6 expression distribution and intensity using the Seurat package [23]. The dataset GSE176078, sourced from the Gene Expression Omnibus (Chromium, 10X Genomics), included samples from 26 breast cancer patients [24]. Low-quality cells and genes were filtered out based on the following criteria: (I) cells must express at least 300 genes; (II) genes must be expressed in at least three cells; (III) the proportion of mitochondria genes must be less than 20%; (IV) the proportion of ribosome genes must be greater than 3%; (V) the proportion of red blood cell genes must be less than 0.1%. Inter-sample batch effects were removed using the Harmony algorithm [25]. Cell identities were identified using classical markers based on their expression levels [26, 27].

Prognostic prediction analysis

Using information from the Kaplan-Meier plotter, we examined global multicenter cohorts of patients with breast cancer to evaluate the predictive importance of COL6A6 [28]. Using the median COL6A6 expression value, patients were classified with high and low COL6A6 expression. Using the survival and survminer packages, Kaplan-Meier curves were produced and hazard ratios (HR) for overall and relapse-free survival were calculated. Decision curve analysis was performed to confirm the clinical implications of COL6A6 expression levels.

Tumor immune microenvironment deconvolution

We conducted tumor deconvolution calculations to investigate the association between COL6A6 and the tumor immune microenvironment. We used TIMER, MCPcounter, and CIBERSORT algorithms to determine the immune and stromal cell abundances for each breast cancer patient using high-throughput sequencing data from the TCGA cohort [29–31]. We examined the tumor immune microenvironment in high- and low-COL6A6-expression groups. Spearman correlation analysis was used to evaluate the association between COL6A6 expression and immune and stromal scores.

Gene set enrichment analysis

Gene set enrichment analysis was performed on breast cancer tissue samples to explore the molecular mechanisms associated with COL6A6. The referenced gene sets included “c2.cp.v2023.1.Hs.symbols” and “c5.all.v2023.1.Hs.symbols” [32]. The GSEABase and clusterProfiler packages were employed to map the enrichment results [33]. The p-values for the enrichment results were adjusted using the Benjamini-Hochberg method.

In-depth functional annotation and transcriptional regulatory mechanism analysis

To elucidate the precise molecular mechanisms underlying COL6A6, we identified and annotated COL6A6-responsive genes through gene expression analysis in mice models immunized with a COL6A6 peptide vaccine (Gene Expression Omnibus accession number: GSE245813) [34]. We then constructed the protein interaction network of COL6A6 to explore the intricate relationships between COL6A6 and its associated genes [35]. To predict the biological functions of COL6A6, RNA interference (RNAi) analysis was conducted in breast cancer cell lines [36]. Furthermore, the upstream transcriptional regulator of COL6A6 was identified in breast cancer cell lines following the knockdown of transcriptional factors [37, 38]. The expression association between COL6A6 and its transcriptional factors was confirmed using bulk RNA sequencing, single-cell RNA sequencing, and spatial transcriptomic analyses [39]. Most importantly, the malignant region and tumor immune microenvironment within breast cancer slices were deconvoluted to visualize the correlation between COL6A6 expression and immune cell distribution. Finally, a potential therapeutic agent for the treatment of breast cancer patients was identified through targeting the COL6A6 protein [40].

Statistical analysis

For calculating the SMD value, a heterogeneity I2 test was performed to determine the level of heterogeneity. A random-effect model was used when heterogeneity was statistically significant [41]. Begg’s test was employed to evaluate for potential publication bias [42]. An unpaired Wilcoxon test was used to ascertain the COL6A6 antibody expression levels in the tissues of breast cancer patients and non-cancer control subjects. The Kaplan-Meier curves’ significance was evaluated using the log-rank test. An absolute value of the Spearman correlation coefficient greater than 0.30 was considered statistically relevant. A significance threshold of p < 0.05 was adopted. Figure 1 illustrates the overall design of our study.

Fig. 1.

Fig. 1

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Flow diagram

Results

Protein activity of COL6A6 in breast cancer tissues

Based on in-house immunohistochemical staining results, COL6A6 protein exhibited lowly positive staining intensity in normal breast tissues but negative staining intensity in breast cancer tissues (Fig. 2A and B). COL6A6 protein staining intensity was markedly lower in breast cancer tissues compared to normal breast tissue (Fig. 2C, p < 0.0001). The decreased expression level of COL6A6 protein demonstrated moderate discriminatory ability in differentiating between breast cancer and normal breast tissues (Fig. 2D, AUC = 0.879).

Fig. 2.

Fig. 2

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Downregulation of COL6A6 protein in breast cancer tissues A, B COL6A6 protein showed lowly positive staining intensity in normal breast tissues but indicated negative staining intensity in breast cancer tissues. C Compared with normal breast tissues, COL6A6 protein staining intensity was significantly lower in breast cancer tissues. D Decreased COL6A6 protein expression level indicated moderate discriminatory ability in differentiating breast cancer tissues and normal breast tissues

mRNA expression level of COL6A6 in breast cancer tissues

A total of 1236 non-breast-cancer tissue specimens and 4818 breast cancer tissue specimens were included in the 19 platform expression matrices that were created by integrating 61 microarrays and high-throughput bulk RNA sequencing datasets (Additional file 1: Supplemental Table 1). Breast cancer tissues had much lower levels of COL6A6 mRNA than non-cancerous breast tissues, according to the SMD forest plot (Fig. 3A). The expression of COL6A6 was significantly lower in all molecular subtypes of breast cancer compared to controls (Additional file 1: Supplemental Fig. 1). No publication bias was detected in the SMD analysis (Fig. 3B). The SROC curve, with an AUC value of 0.8768, demonstrated a moderate ability to discriminate between breast cancer and non-breast-cancer tissues (sensitivity = 84.85%, specificity = 72.58%) (Fig. 3C).

Fig. 3.

Fig. 3

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Downregulation of COL6A6 mRNA in breast cancer tissues A Forest plot of integrated standardized mean difference indicated COL6A6 mRNA was significantly downregulated in breast cancer tissues. B Funnel plot indicated no publication bias. C Decreased COL6A6 mRNA expression level indicated moderate discriminatory ability in differentiating breast cancer tissues and normal breast tissues

Expression verification of COL6A6 in breast cancer single cells

We acquired the single-cell profiles of 96,146 high-quality cells from 26 breast cancer patients, preserving 24,353 genes. These cells were annotated into seven cell clusters (Fig. 4A): T cells (34.9271%), epithelial cells (28.5763%), fibroblasts (13.9746%), monocytes and macrophages (8.4538%), endothelial cells (7.5531%), B cells (3.4812%), and plasma cells (3.0339%). A cell-stacked histogram for each breast cancer patient was shown in Fig. 4B. In breast cancer lesions, COL6A6 expression was positive in cancer-associated fibroblasts but negative in epithelial cells (Fig. 4C).

Fig. 4.

Fig. 4

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Downregulation of COL6A6 mRNA in single cells of breast cancer A Cell annotation after UMAP dimension reduction B Cell stacked histogram of each breast cancer patient C Density plot of COL6A6 mRNA expression level in single cells of breast cancer

Prognostic value of COL6A6 in breast cancer cohorts

Analysis of global multicentered cohorts of breast cancer patients revealed that higher COL6A6 mRNA expression levels were associated with better overall survival and relapse-free survival outcomes (Fig. 5A and B). In particular, the level of COL6A6 mRNA expression was expected to be protective for patients’ prognoses with breast cancer (HRoverall survival = 0.576 [0.438, 0.758], sample size = 943; HRrelapse-free survival = 0.613 [0.526, 0.714], sample size = 2032). The potential clinical value of COL6A6 in predicting patients’ one-, three-, and five-year survival outcomes was further highlighted by decision curve analysis (Fig. 5C).

Fig. 5.

Fig. 5

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Prognostic value of COL6A6 downregulation in breast cancer patients A Overall survival plot B Relapse-free survival plot C Decision curve analysis

Immune association of COL6A6 in the breast cancer microenvironment

The immune microenvironment of breast cancer tissues varied significantly between groups with high and low COL6A6 expression. When compared to the high-COL6A6-expression group, the low-COL6A6-expression group displayed significantly higher tumor purity but poorer immune and stromal scores (Fig. 6A–C, p < 0.0001). Furthermore, dendritic cell, endothelial cell, fibroblast, macrophage, neutrophil, natural killer cell, CD4+T cell, and CD8+T cell infiltration levels were reduced in breast cancer tissues in the low-COL6A6-expression group (Fig. 6D–L, p < 0.0001). Reduced COL6A6 expression was positively correlated with the abundance of dendritic cells, endothelial cells, fibroblasts, macrophages, neutrophils, natural killer cells, CD4+T cells, and CD8+T cells in the tumor microenvironment, but negatively correlated with tumor purity, according to Spearman correlation analysis (Fig. 7).

Fig. 6.

Fig. 6

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Immune infiltration abundances of breast cancer patients with different COL6A6 expression levels A Tumor purity B Stromal score C Immune score D Dendritic cell E Endothelial cell F Fibroblast G Macrophage H Neutrophil I Natural killer cell J CD4+ T cell K CD8+ T cell L T cell

Fig. 7.

Fig. 7

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Spearman correlation between COL6A6 expression and tumor immune microenvironment in breast cancer patients A Tumor purity B Stromal score C Immune score D Dendritic cell E Endothelial cell F Fibroblast G Macrophage H Neutrophil I Natural killer cell J CD4+ T cell K CD8+ T cell L T cell

Prospective molecular function of COL6A6 in breast cancer

The participation of COL6A6 in multiple immune regulatory pathways was revealed by gene set enrichment analysis (Fig. 8). Adaptive immune response, leukocyte migration, macrophage activation, MHC class II protein complex binding, natural killer cell-mediated cytotoxicity, T cell differentiation, T cell proliferation, T cell migration, T cell receptor signaling pathways, cell adhesion molecule, extracellular matrix receptor interaction, and T helper 1 type immune response were among these pathways.

Fig. 8.

Fig. 8

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Potential molecular mechanisms of COL6A6 underlying breast cancer A GO B KEGG

Preliminary functional verification of COL6A6 in breast cancer

Immune-related biological processes, such as immunoglobulin production, generation of immune response mediators, myeloid leukocyte activation, leukocyte chemotaxis, and neutrophil migration, were significantly enriched in mice models immunized with a COL6A6 peptide vaccine (Fig. 9A). These findings offer valuable insights into the potential role of COL6A6 in immune regulation. The protein interaction network illustrates the intricate relationships between COL6A6 and other proteins (Fig. 9B), indicating its involvement in various cellular processes. The RNAi results reveal a positive gene effect score for COL6A6 in breast cancer cell lines following RNAi treatment (Fig. 9C), suggesting that COL6A6 may play an inhibitory role in breast cancer cell biology.

Fig. 9.

Fig. 9

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Preliminary functional verification of COL6A6 in breast cancer A Functional annotation of COL6A6-responsive genes identified through gene expression analysis in mice models immunized with a COL6A6 peptide vaccine (Gene Expression Omnibus accession number: GSE245813). B Protein interaction network depicting the relationships between COL6A6 and its associated genes. C RNA interference analysis of COL6A6 expression in breast cancer cell lines

Furthermore, COL6A6 expression was upregulated following the knockdown of the CBX2 transcriptional factor in breast cancer cell lines (Fig. 10A). In breast cancer tissues, there was a notable overexpression of the CBX2 transcriptional factor, in contrast to COL6A6 (Fig. 10B). A negative correlation was observed between the expression levels of the CBX2 transcriptional factor and COL6A6 (Fig. 10C). The CBX2 transcriptional factor exhibited specific expression in malignant mammary cells (Fig. 10D). The expression patterns of the CBX2 transcriptional factor and COL6A6 were opposite in malignant regions of breast cancer tissue slices. The downregulation of COL6A6 was associated with reduced immune cell infiltration, suggesting a potential link between COL6A6 expression and the immune response in breast cancer (Fig. 10E).

Fig. 10.

Fig. 10

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Potential transcriptional regulatory mechanisms of COL6A6 in breast cancer A Upregulation of COL6A6 following the knockdown of the CBX2 transcriptional factor in breast cancer cell lines. B Significant overexpression of the CBX2 transcriptional factor in breast cancer tissue compared to normal tissue, in contrast to COL6A6. C A negative correlation between the expression levels of the CBX2 transcriptional factor and COL6A6. D Specific expression of the CBX2 transcriptional factor in malignant mammary cells. E Opposite expression patterns of the CBX2 transcriptional factor and COL6A6 in malignant regions of breast cancer tissue slices. Downregulation of COL6A6 is associated with reduced immune cell infiltration

Fortunately, molecular docking results demonstrate the binding of the lipoxygenase inhibitor MK-886 to the COL6A6 protein, with a Vina score of −8.0, indicating a strong binding affinity (Fig. 11). This finding suggests that MK-886 may serve as a promising therapeutic agent for breast cancer treatment by targeting COL6A6.

Fig. 11.

Fig. 11

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Molecular docking of COL6A6 protein with a potential therapeutic agent

Discussion

Breast cancer is the leading type of cancer in women, resulting in the loss of hundreds of thousands of lives annually, thereby necessitating further investigations into its underlying mechanisms [43]. Although COL6A6 is downregulated during lymph node metastasis of breast cancer, its roles in breast cancer remain unclear [14, 15]. Our investigation of COL6A6’s expression profile, prognostic significance, immunological connection, and molecular function in breast cancer was thorough and provided insight into the protein’s possible functions in immune modulation and disease development.

Our immunohistochemistry research revealed a significant downregulation of COL6A6 protein levels in breast cancer tissues relative to non-cancer tissues, indicating a possible function for COL6A6 as a tumor suppressor. This was corroborated by the mRNA expression analysis from integrated datasets encompassing 6054 tissue samples, which consistently showed downregulated COL6A6 mRNA in breast cancer tissues. Our study is the first to reveal lower protein expression levels in breast cancer tissues, despite earlier research showing a downregulation tendency of COL6A6 mRNA in small sample-sized breast cancer tissues [14, 44]. We verified the comprehensive mRNA expression status of COL6A6 using large sample sizes and multicentered datasets. We also showed that COL6A6 has a moderate discriminatory capacity to distinguish between malignant and non-cancerous tissues, highlighting its potential as a diagnostic biomarker. Furthermore, our examination of international multicentered datasets showed a positive correlation between better overall and relapse-free survival outcomes for patients with breast cancer and higher COL6A6 mRNA expression. Decision curve analysis supports this link, suggesting that COL6A6 may play a similar role to that of COL6A6 in other cancers [12, 45, 46] as a useful prognostic indicator for breast cancer. Furthermore, the differential expression of COL6A6—positive expression in cancer-associated fibroblasts and negative expression in epithelial cells—was further validated by single-cell RNA sequencing data. Notably, the association between COL6A6 and fibroblasts has been reported in several cancers [47–49]. These results highlight the therapeutic significance of COL6A6 and imply that it may have diverse functions in various cellular constituents of the tumor microenvironment.

The immunomodulatory significance of COL6A6 in breast cancer is highlighted by the significant changes in the immunological milieu between groups with high and low expression of the protein. COL6A6, an essential part of the basal lamina in epithelial cells, is important in controlling the contacts between fibronectin and epithelial cells as well as establishing a connection between malignant epithelial cells and the tumor microenvironment. COL6A6, which is thought to be a tumor suppressor [50], has been connected to tumor immunity and could be useful in lung adenocarcinoma immunotherapy [12]. In the ApoE−/− mice model, anti-COL6A6 treatment was observed to promote M2 polarization of monocytes/macrophages [51]. The present work indicates that COL6A6 could potentially enhance anti-tumor immunity by promoting an immunological-active tumor microenvironment, as suggested by the strong negative association between COL6A6 expression and tumor purity and the positive correlation with different immune cell types. Remarkably, gene set enrichment analysis revealed COL6A6’s participation in several immune regulatory pathways, adding more evidence to support the protein’s putative function in regulating the immune system in breast cancer. COL6A6’s involvement in various processes, including antigen presentation, T cell activation, macrophage activation, and natural killer cell-mediated cytotoxicity, suggests that it has a complex impact on the immunological environment around breast cancer. In this study, we uncovered that the downregulation of COL6A6 is linked to diminished immune cell infiltration in the malignant areas of breast cancer tissue sections. This downregulation may be under negative regulation by the CBX2 transcription factor. Moreover, in mouse models immunized with a COL6A6 peptide vaccine, immune-related biological processes, including immunoglobulin production, generation of immune response mediators, myeloid leukocyte activation, leukocyte chemotaxis, and neutrophil migration, were significantly enriched. Notably, the lipoxygenase inhibitor MK-886, which has a Vina score of − 8.0, was predicted to be a promising therapeutic agent for breast cancer treatment by targeting COL6A6. MK-886 has been reported to effectively inhibit the proliferation of breast cancer cells while exhibiting no toxicity to bone marrow cells [52]. Collectively, COL6A6 is closely associated with tumor immunity and holds potential as a therapeutic target for breast cancer patients.

While our study provides valuable insights into COL6A6’s role in breast cancer, there are limitations to consider. The study’s retrospective design and the necessity for validation in larger, forward-looking cohorts are recognized. Future research should focus on the mechanistic understanding of how COL6A6 modulates the immune microenvironment and its potential as a therapeutic target.

Conclusions

Our research outlines the molecular roles, immunological connections, expression dynamics, and prognostic implications of COL6A6 in breast cancer. These results emphasize COL6A6’s role in immune regulation within the tumor microenvironment and its potential as a biomarker for prognosis and disease stratification. To further understand the precise molecular pathways of COL6A6 that underlie the development of breast cancer and immunological responses, as well as the implications for future treatment options that target this fascinating protein, more research is necessary.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary Material 1. (580.8KB, docx)

Acknowledgements

We appreciated technical support from Guangxi Key Laboratory of Medical Pathology.

Abbreviations

COL6A6

Collagen type VI alpha 6 chain

TCGA

The Cancer Genome Atlas

SMD

Standardized mean difference

AUC

Area under the curve

SROC

Summary receiver operating characteristic

Author contributions

Conceptualization: Jian-Di Li, Li-Li Deng, Wen Zou, and Gang Chen; Methodology: Jian-Di Li, Li-Li Deng, Rong-Quan He, Di-Yuan Qin, Wen Zou, and Gang Chen; Formal analysis and investigation: Jian-Di Li, Li-Li Deng, Bang-Teng Chi, and Chang Song; Writing—original draft preparation: Jian-Di Li and Li-Li Deng; Writing—review and editing: Rong-Quan He, Di-Yuan Qin, Wen Zou, and Gang Chen; Funding acquisition: Wen Zou; Resources: Jia-Yuan Luo, Chao-Hua Mo, and Wan-Ying Huang; Supervision: Gang Chen.

Funding

This study was funded by Guangxi Zhuang Autonomous Region Health Commission Scientific Research Project (Z-A20220530) and Future Academic Star of Guangxi Medical University (WLXSZX24125).

Data availability

The in-house immunohistochemical data used during the current study are available from the corresponding author on reasonable request. The datasets analyzed in this study are available in the Gene Expression Omnibus (https://www.ncbi.nlm.nih.gov/geo/) under the following accession numbers: GSE3744, GSE5764, GSE6883, GSE7307, GSE7904, GSE10780, GSE10810, GSE18672, GSE20711, GSE21422, GSE22384, GSE22544, GSE25407, GSE26304, GSE26910, GSE29044, GSE29431, GSE31448, GSE33447, GSE36295, GSE37751, GSE38959, GSE41119, GSE42568, GSE45827, GSE50428, GSE50567, GSE54002, GSE57297, GSE59246, GSE61304, GSE61724, GSE64790, GSE65194, GSE70951, GSE71053, GSE73540, GSE76250, GSE79058, GSE80754, GSE81838, GSE83591, GSE86374, GSE92252, GSE103512, GSE103865, GSE115144, GSE118432, GSE133998, GSE134359, GSE135565, GSE139274, GSE140494, GSE146558, GSE147472, GSE153796, GSE176078, GSE243275, and GSE245813. The TCGA-GTEx dataset can be accessed through The Cancer Genome Atlas (https://www.cancer.gov/ccg/research/genome-sequencing/tcga) and the Genotype-Tissue Expression project (https://gtexportal.org/home/).

Declarations

Ethics approval and consent to participate

All participants in the study provided their informed consent to participate. This study was approved by The Ethics Committee of the First Affiliated Hospital of Guangxi Medical University (NO.2022-KT-GUIWEI-135).

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Footnotes

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Jian-Di Li and Li-Li Deng have contributed equally as first author.

Contributor Information

Wen Zou, Email: GXMUzw830@163.com.

Gang Chen, Email: chengang@gxmu.edu.cn.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary Material 1. (580.8KB, docx)

Data Availability Statement

The in-house immunohistochemical data used during the current study are available from the corresponding author on reasonable request. The datasets analyzed in this study are available in the Gene Expression Omnibus (https://www.ncbi.nlm.nih.gov/geo/) under the following accession numbers: GSE3744, GSE5764, GSE6883, GSE7307, GSE7904, GSE10780, GSE10810, GSE18672, GSE20711, GSE21422, GSE22384, GSE22544, GSE25407, GSE26304, GSE26910, GSE29044, GSE29431, GSE31448, GSE33447, GSE36295, GSE37751, GSE38959, GSE41119, GSE42568, GSE45827, GSE50428, GSE50567, GSE54002, GSE57297, GSE59246, GSE61304, GSE61724, GSE64790, GSE65194, GSE70951, GSE71053, GSE73540, GSE76250, GSE79058, GSE80754, GSE81838, GSE83591, GSE86374, GSE92252, GSE103512, GSE103865, GSE115144, GSE118432, GSE133998, GSE134359, GSE135565, GSE139274, GSE140494, GSE146558, GSE147472, GSE153796, GSE176078, GSE243275, and GSE245813. The TCGA-GTEx dataset can be accessed through The Cancer Genome Atlas (https://www.cancer.gov/ccg/research/genome-sequencing/tcga) and the Genotype-Tissue Expression project (https://gtexportal.org/home/).

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