Dataset Information

Quantitative proteomic analysis of MSC and electrically stimulated MSC (epMSC) secretomes

ABSTRACT: This study aimed to investigate the effects of electrical stimulation (ES) on the secretome of mesenchymal stem cells (MSCs). Using quantitative proteomics, we identified a total of 435 proteins secreted by MSCs and ES-treated MSCs (epMSCs), among which 418 were common between groups, with 14 and 8 unique to the epMSC and MSC groups, respectively. Differential expression analysis revealed that 42 proteins were upregulated and 49 were downregulated in the epMSC secretome. Functional enrichment analyses indicated that ES enhances the pro-angiogenic properties of MSCs by modulating pathways such as VEGFA-VEGFR2 signaling and the complement cascade. These findings provide insight into how ES alters MSC-derived secretomes to promote vascularization, which may have therapeutic relevance in regenerative medicine.

INSTRUMENT(S):

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Stem Cell, Adipose Tissue

SUBMITTER: Seungjun Lee

LAB HEAD: Seungjun Lee

PROVIDER: PXD066035 | Pride | 2025-09-22

REPOSITORIES: Pride

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Publications

Enhanced Angiogenic Potential of Electrically Stimulated Human Adipose-Derived Mesenchymal Stem Cells (MSCs) for Ischemic Tissue Regeneration.

Yi Jongdarm J Lee Seungjun S Ryu Chiseon C Kim Gaeun G Kim Junghyun J Lee Jae Young JY

MedComm 20250909 9

Effective treatment of ischemic disease requires the reconstruction of blood vessels through the delivery of angiogenic factors, such as chemicals, proteins, and cells. In particular, substantial efforts have focused on enhancing the therapeutic potential of mesenchymal stem cells (MSCs) for treating ischemic diseases. In this study, we investigated the use of electrical stimulation (ES) to potentiate the proangiogenic properties of human adipose-derived MSCs. Electrically potentiated MSCs (epMS ...[more]

PMID: 40937194

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Project description:Carcinoma-associated mesenchymal stem cells (CA-MSCs) are critical stromal progenitor cells within the tumor microenvironment. We previously demonstrated that CA-MSCs differentially express BMP genes, promote tumor cell growth, increase cancer ‘stemness’ and chemotherapy resistance. Here we use RNA sequencing of normal omental MSCs and ovarian CA-MSCs to demonstrate CA-MSCs have global changes in gene expression. Using these expression profiles we create a unique predictive algorithm to classify CA-MSCs. Our classifier, accurately distinguishes normal omental, ovary and bone marrow MSCs from ovarian cancer CA-MSCs. Suggesting broad applicability, the model correctly classifies pancreatic and endometrial cancer CA-MSCs and distinguishes cancer associated fibroblasts (CAFs) from CA-MSCs. Using this classifier, we definitively demonstrate ovarian CA-MSCs arise from tumor mediated reprograming of local tissue MSCs. While cancer cells alone cannot induce a CA-MSC phenotype, the in vivo ovarian tumor micoenvironment (TME) can reprogram omental or ovary MSCs to protumorigenic CA-MSC (classifier score of >0.96). In vitro studies suggest that both tumor secreted factors and hypoxia are critical to induce the CA-MSC phenotype. Interestingly, while the breast cancer TME can reprogram BM MSCs into CA-MSCs, the ovarian TME cannot, demonstrating for the first time that tumor mediated CA-MSC conversion is tissue and cancer type dependent. Together these findings (1) provide a critical tool to define CA-MSCs and (2) highlight cancer cell influence on distinct normal tissues providing powerful insights into the mechanisms underlying cancer specific metastatic niche formation. Carcinoma-associated mesenchymal stem cells (CA-MSCs) are critical stromal progenitor cells within the tumor microenvironment. We previously demonstrated that CA-MSCs differentially express BMP genes, promote tumor cell growth, increase cancer ‘stemness’ and chemotherapy resistance. Here we use RNA sequencing of normal omental MSCs and ovarian CA-MSCs to demonstrate CA-MSCs have global changes in gene expression. Using these expression profiles we create a unique predictive algorithm to classify CA-MSCs. Our classifier, accurately distinguishes normal omental, ovary and bone marrow MSCs from ovarian cancer CA-MSCs. Suggesting broad applicability, the model correctly classifies pancreatic and endometrial cancer CA-MSCs and distinguishes cancer associated fibroblasts (CAFs) from CA-MSCs. Using this classifier, we definitively demonstrate ovarian CA-MSCs arise from tumor mediated reprograming of local tissue MSCs. While cancer cells alone cannot induce a CA-MSC phenotype, the in vivo ovarian tumor micoenvironment (TME) can reprogram omental or ovary MSCs to protumorigenic CA-MSC (classifier score of >0.96). In vitro studies suggest that both tumor secreted factors and hypoxia are critical to induce the CA-MSC phenotype. Interestingly, while the breast cancer TME can reprogram BM MSCs into CA-MSCs, the ovarian TME cannot, demonstrating for the first time that tumor mediated CA-MSC conversion is tissue and cancer type dependent. Together these findings (1) provide a critical tool to define CA-MSCs and (2) highlight cancer cell influence on distinct normal tissues providing powerful insights into the mechanisms underlying cancer specific metastatic niche formation.

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	LJD.pdResult	Other
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