Calcium-sensing Receptor, a Potential Biomarker Revealed by Large-scale Public Databases and Experimental Verification in Metastatic Breast Cancer

Abstract

Introduction: Breast cancer (BC) is a common cancer characterized by a high molecular heterogeneity. Therefore, understanding its biological properties and developing effective treatments for patients with different molecular features is imperative. Calcium-sensing receptor (CaSR) has been implicated in several regulatory functions in various types of human cancers. However, its underlying pathological mechanism in BC progression remains elusive.

Methods: We utilized The Cancer Genome Atlas and Gene Expression Omnibus databases to explore the function of CaSR in the metastasis of BC. Gene ontology analysis, Kyoto Encyclopedia of Genes and Genomes analysis, and Gene Set Enrichment Analysis of biological processes and cell signaling pathways revealed that CaSR could be activated or inhibited. Importantly, quantitative reverse transcriptase-polymerase chain reaction and western blotting were used to verify the gene expression of the CaSR. Wound healing and transwell assays were conducted to assess the effect of CaSR on the migration of BC cells.

Results: We demonstrated that CaSR expression in metastatic BC was higher than that in non-metastatic BC. It is the first time that database information has been used to reveal the biological process and molecular mechanism of CaSR in BC. Moreover, the CaSR expression in normal breast epithelial cells was notably less compared to that in BC cells. The activation of CaSR by Cinacalcet (a CaSR agonist) significantly enhanced the migration of BC cells, whereas NPS-2143 (a CaSR antagonist) treatment dramatically inhibited these effects.

Conclusion and future perspective: Bioinformatics techniques and experiments demonstrated the involvement of CaSR in BC metastasis. Our findings shed new light on the receptor therapy and molecular pathogenesis of BC, and emphasize the crucial function of CaSR, facilitating the metastasis of BC.

Keywords: bioinformatics; breast cancer; calcium-sensing receptor; metastasis; potential biomarker.

Figure 1.

Correlation between CaSR gene expression and breast cancer metastasis. (A) Box plot was created using the CaSR expression from the GSE29431 dataset. (B) Box plot showing CaSR expression in the GSE73540 dataset. (C) A box plot was created using the CaSR expression from the GSE102484 dataset. CaSR, calcium-sensing receptor.

Figure 2.

Differentially expressed CaSR-related prognostic genes. (A) PCA analysis before GEO data integration. (B) PCA analysis after GEO data integration. (C) Volcano map of differentially expressed genes between high and low CaSR expression groups in the integrated GEO dataset. (D) Volcano map of differentially expressed genes between high and low CaSR expression groups in the TCGA dataset. (E) Venn diagram illustrating genes that are expressed differently and genes that are related to prognosis. CaSR, calcium-sensing receptor; TCGA, The Cancer Genome Atlas; GEO, Gene Expression Omnibus.

Figure 3.

Go functional annotation and KEGG pathway enrichment analysis of CaSR-related prognostic genes. (A) Go functional annotation. (B) Biological process, BP (hemidesmosome assembly, cell chemotaxis, etc). (C) Cellular component, CC (extracellular region, proteinaceous extracellular matrix, etc). (D) Molecular function, MF (chemokine activity, heparin-binding, etc). (E,F) KEGG pathway enrichment analysis (cytokine-cytokine receptor interaction, chemokine signaling pathway). CaSR, calcium-sensing receptor; KEGG, Kyoto Encyclopedia of Genes and Genomes.

Figure 4.

GSEA between high and low CaSR expression groups. (A,B) GSEA enrichment analysis of integration GEO data. (C,D) GSEA enrichment analysis of TCGA data. CaSR, calcium-sensing receptor; TCGA, The Cancer Genome Atlas; GEO, Gene Expression Omnibus; GSEA, Gene Set Enrichment Analysis.

Figure 5.

PPI network and prognosis analysis of differentially expressed CaSR-related prognostic genes. (A) PPI network of differentially expressed CaSR-related prognostic genes. (B,C) PPI network function analysis of differentially expressed CaSR-related prognostic genes. (D) Hub genes of CaSR-related prognostic genes in the PPI network. (E) The correlation of hub genes expression in integrated GEO datasets. (F) The correlation of hub genes expression in TCGA datasets. (G) The relationship between the expression of hub genes and the prognosis of patients with BC. BC, breast cancer; CaSR, calcium-sensing receptor; TCGA, The Cancer Genome Atlas; GEO, Gene Expression Omnibus, PPI, protein-protein interaction.

Figure 6.

The expression of CaSR in normal breast cells and BC cells. (A) Experimental findings from qRT-PCR demonstrated that CaSR expression was elevated in BC cells compared to normal breast cells. (B) Western blotting revealed that the level of CaSR was elevated in BC cells compared to normal breast cells (*P < 0.05, **P < 0.01, ***P < 0.001). BC, breast cancer; CaSR, calcium-sensing receptor; qRT-PCR, quantitative reverse transcriptase-polymerase chain reaction.

Figure 7.

Effects of CaSR on the migration of BC cells. (A) Transwell assay results of BC cells treated with CIN or NPS. Migrating cells were quantified after 16 h (x100). (B) Results from the wound healing experiment of BC cells treated with either CIN or NPS. The rate of wound healing was assessed at 0 h and 24 h (x100, *P < 0.05, **P < 0.01, ***P < 0.001). BC, breast cancer; CaSR, calcium-sensing receptor.