SPOCK1 promotes the progression of breast cancer by modulating cancer-associated fibroblasts and exerts a synergistic effect with ANXA2

Abstract

Background: SPOCK1, a matricellular glycoprotein, has been implicated in tumor progression, metastasis, and the tumor immune microenvironment, yet its specific roles in breast cancer (BRCA) remain unclear. This study aimed to systematically explore the expression pattern, prognostic significance, mutation landscape, immune association, and spatial localization of SPOCK1 in breast cancer through integrated multi-omics analyses.

Methods: Transcriptomic, genomic, and clinical data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) were utilized. Bulk RNA sequencing and single-cell RNA sequencing (scRNA-seq) analyses were conducted, including functional enrichment, immune infiltration assessments, mutation profiling, and transcription factor activity analysis. Multiplex immunohistochemistry (mIHC) was performed to validate the spatial distribution of SPOCK1+ cancer-associated fibroblasts (CAFs) within the tumor microenvironment. Statistical analyses were performed using R and GraphPad Prism.

Results: SPOCK1 was broadly overexpressed in multiple cancer types and significantly associated with poor prognosis in BRCA. High SPOCK1 expression correlated with immune checkpoint activation, enhanced immune infiltration, and enriched metastasis-related pathways such as epithelial-mesenchymal transition (EMT) and TGF-β signaling. Single-cell analysis identified CAFs as the primary cell population expressing SPOCK1, with spatial mIHC confirming their close proximity to tumor cells. Furthermore, SPOCK1-high CAFs exhibited stronger intercellular communications with malignant cells via collagen, fibronectin, and IGFBP signaling pathways, alongside distinct transcription factor and metabolic profiles. In breast cancer CAF cell lines with knockdown of ANXA2 we found that the expression of both SPOCK1 and IGF1 was reduced.

Conclusion: SPOCK1 serves as a critical regulator of breast cancer progression, influencing tumor metastasis and reshaping the immune microenvironment via CAF-mediated mechanisms. These findings suggest that targeting SPOCK1+ CAFs could offer new therapeutic opportunities for breast cancer treatment.

Keywords: AnxA2; SPOCK1; breast cancer; cancer-associated fibroblasts; tumor microenvironment.

Figure 1

(A) Correlation analysis of gene SPOCK1 with characterized genes in pan-cancer; (B) Correlation of some genes with immune genes in pan-cancer; (C) Correlation of gene SPOCK1 with immune cell score in pan-cancer. *P < 0.05; **P < 0.01; ***P < 0.001; ****P < 0.0001.

Figure 2

(A–C) KM curves of gene SPOCK1 at different times and states on the TCGA dataset; (D) expression differences of gene SPOCK1 in different subgroups. (Normal refers to normal samples, Primary refers to primary tumor samples, and Bone refers to tumor samples that have undergone bone metastasis). *P < 0.05; **P < 0.01.

Figure 3

(A) Mutation frequency distribution of the top 20 tumor driver genes with differential mutation frequencies in molecular subtypes; (B) Comparison of TMB on molecular subtypes; (C) Survival curves of some mutated genes; (D) Density maps of immune checkpoint genes; (E) Difference of HRD Score in high and low expression groups; (F) Difference of intratumor in high and low expression groups. heterogeneity difference. *P < 0.05; ***P < 0.001.

Figure 4

(A) KEGG pathway enrichment analysis of up-regulated genes in the high-expression subgroup; (B) some pathways significantly enriched to in the high-expression subgroup; (C) correlation analysis of the gene SPOCK1 with oncogenic pathway scores as well as immune cell scores in the TCGA dataset are shown; (D) difference analysis of immune cell scores in the subgroups; (E) difference analysis of 10 pathway scores in the subgroups. *P < 0.05; **P < 0.01; ***P < 0.001; ****P < 0.0001.

Figure 5

(A) Cellular annotation UMAP plot after single-cell dimensionality reduction clustering; (B) Cellular maker gene expression display plot in cells; (C) KEGG functional enrichment scores of different maker genes in different cells; (D) Plot of the proportion of cells in different samples; (E) Gene expression of the gene SPOCK1 in the cells; (F) Gene SPOCK1 in the CAF cells expression differences in normal and tumor samples; (G) differences in the distribution of high and low SPOCK1 groupings in CAF cells in normal and tumor samples. ***P < 0.001.

Figure 6

(A) Direction of communication as well as the number of exchanges between cells; (B) Direction of communication as well as intensity of exchanges between cells; (C-F) Communication diagrams of OLLAGEN signaling, FN1 signaling, THBS signaling and IGFBP signaling between cells; (G) Identification of different cell populations of the output or input signaling that contributes the most to the signaling.

Figure 7

(A) Heatmap display of relevant transcription factors in different cells; (B) Display of transcription factors with the highest Specificity Score in different cells; (C) Heatmap analysis of the scoring of metabolite pathways in cell subtypes.

Figure 8

Spatial transcriptomics images of Breast cancer tumor cells and SPOCK1+ CAF cells. (A, B) Annotation information from single-cell RNA sequencing was projected onto spatial transcriptomics data, enabling the localization of specific cell types within the tissue context. (C, D) Spatial distribution patterns of distinct cell subpopulations were visualized, highlighting their localization and potential spatial interactions within the tumor microenvironment.

Figure 9

(A), mIHC showing the localization of SPOCK1+ CAF cells and tumor cells in breast cancer tissues; (B-E), mIHC plots showing the marker proteins; (F), positive correlation trend between ANXA2 and SPOCK1 in TCGA; (G), knockdown of ANXA2 from human breast cancer fibroblasts (CP-H172) resulted in reduction of both SPOCK and IGF1.