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Blocking of CA-MSC-induced desmoplasia reprograms the tumor immune microenvironment and enhances cancer immunotherapy

ABSTRACT: We determined the immune cell composition and their gene expression, by performing single-cell RNA sequencing (scRNA-seq), in anti-PD-L1-treated 2F8cis tumors, a hot and immunoresponsive ovarian murine tumor model, and anti-PD-L1-treated 2F8cis/CA-MSC tumors. We also evaluated the ability of hedgehog inhibitor (HHi) therapy to reverse CA-MSC effects. Adipose-derived mesenchymal stem cells (MSC) were cultured with 2F8cis, an ovarian mouse tumor cell line, to generate cancer-associated MSC (CA-MSC). 2F8cis tumor cell alone or 2F8cis/CA-MSCs co-cultured cells at ratio 1:1 were injected into C57BL/6J mice. Tumor infiltrating CD45+ cells were isolated from anti-PD-L1-treated 2F8cis (Group 1, n=3), anti-PD-L1-treated 2F8cis/CA-MSCs (Group 2, n=3), anti-PD-L1+ IPI-926-treated 2F8cis/CA-MSCs (Group 3, n=3) tumors. Samples were labeled with different TotalSeq oligo-conjugated antibodies and loaded into the Chromium instrument (10x Genomics). The resulting barcoded cDNAs were used to construct libraries. Single-cell cDNA libraries were then processed for RNA sequencing using an Illumina NextSeq-500 platform. Anti-PD-L1-treated 2F8cis/CA-MSC tumors showed a high number of Monocytes and macrophages over-expressing Ccr2 and Tgfbi when compared to anti-PD-L1 responsive 2F8cis tumors. Our results also indicated that IPI-926 restored response to anti-PD-L1 therapy decresing the expression of Ccr2 and Tgfbi both in monocytes and macrophages. Our study represents the first detailed analysis generated by RNA-seq technology of 2F8cis/CA-MSC+ enriched tumor transcriptomes, treated with anti-PDL1 alone or in combination with HHi, and compared with anti-PDL1-treated tumors. The optimized data analysis workflows reported here should provide a framework for comparative investigations of expression profiles.

ORGANISM(S): Mus musculus

PROVIDER: GSE185013 | GEO | 2021/10/06

REPOSITORIES: GEO

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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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Blocking of CA-MSC-induced desmoplasia reprograms the tumor immune microenvironment and enhances cancer immunotherapy

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