Aghakhani2022 - Human breast cancer-associated fibroblast model
Ontology highlight
ABSTRACT:
SUBMITTER: 
Sahar Aghakhani
PROVIDER: MODEL2307090001 | BioModels | 2023-07-09
REPOSITORIES: BioModels
Dataset's files
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| S-EPMC9057104 | biostudies-literature
Project description:BackgroundThe most numerous cells in the tumor microenvironment, cancer-associated fibroblasts (CAFs) play a crucial role in cancer development. Our objective was to develop a cancer-associated fibroblast breast cancer predictive model.MethodsWe acquire breast cancer (BC) scRNA-seq data from Gene Expression Omnibus (GEO), and "Seurat" was used for data processing, including quality control, filtering, principal component analysis, and t-SNE. Afterward, "singleR" software was used to annotate cells. Seurat's "FindAllMarkers" program is used to locate particular CAF markers. clusterProfiler was used to analyze Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment. The Cancer Genome Atlas (TCGA) database was utilized to provide univariate Cox regression, least absolute shrinkage operator (LASSO) analysis using bulk RNA-seq data. For model development, multivariate Cox regression studies are used. Utilizing pRRophetic and Tumor Immune Dysfunction and Exclusion (TIDE) algorithms, chemosensitivity and immunotherapy response were predicted. The "rms" software was used to facilitate and simplify modeling.ResultsIntegrating the scRNA-seq (GSE176078) dataset yielded 28 cell clusters. In addition, well-known cell types helped identify 12 cell types. We found 193 marker genes that are elevated in CAFs. In addition, a five-gene predictive model associated to CAF was created in the training set. In the training set, the validation set, and the external validation set, greater risk scores were associated with a worse prognosis. And individuals with a higher risk score were more susceptible to immunotherapy and conventional chemotherapy medicines.ConclusionIn conclusion, we establish a strong prognostic model comprised of 5 genes related with CAF that might serve as a potent prognostic indicator and aid clinicians in making more rational medication choices.
| S-EPMC9735320 | biostudies-literature
Project description:It is established that the interaction between microenvironment and cancer cells has a critical role in tumor development, given the dependence of neoplastic cells on stromal support. However, how this communication promotes the activation of normal (NFs) into cancer-associated fibroblasts (CAFs) is still not well understood. Most microRNA (miRNA) studies focused on tumor cell, but there is increasing evidence of their involvement in reprogramming NFs into CAFs. Here we show that miR-9, upregulated in various breast cancer cell lines and identified as pro-metastatic miRNA, affects the properties of human breast fibroblasts, enhancing the switch to CAF phenotype, thus contributing to tumor growth. Expressed at higher levels in primary triple-negative breast CAFs versus NFs isolated from patients, miR-9 improves indeed migration and invasion capabilities when transfected in immortalized NFs; viceversa, these properties are strongly impaired in CAFs upon miR-9 inhibition. We also demonstrate that tumor-secreted miR-9 can be transferred via exosomes to recipient NFs and this uptake results in enhanced cell motility. Moreover, we observed that this miRNA is also secreted by fibroblasts and in turn able to alter tumor cell behavior, by modulating its direct target E-cadherin, and NFs themselves. Consistently with the biological effects observed, gene expression profiles of NFs upon transient transfection with miR-9 show the modulation of genes mainly involved in cell motility and extracellular matrix remodeling pathways. Finally, we were able to confirm the capability of NFs transiently transfected with miR-9 to promote in vivo tumor growth. Taken together, these data provide new insights into the role of miR-9 as an important player in the cross-talk between cancer cells and stroma.
| S-EPMC4973361 | biostudies-literature
Project description:BackgroundCancer-associated fibroblasts (CAFs) comprise a heterogeneous population of stromal cells within the tumour microenvironment. CAFs exhibit both tumour-promoting and tumour-suppressing functions, making them exciting targets for improving cancer treatments. Careful isolation, identification, and characterisation of CAF heterogeneity is thus necessary for ex vivo validation and future implementation of CAF-targeted strategies in cancer.MethodsMurine 4T1 (metastatic) and 4T07 (poorly/non-metastatic) orthotopic triple negative breast cancer tumours were collected after 7, 14, or 21 days. The tumours were analysed via flow cytometry for the simultaneous expression of six CAF markers: alpha smooth muscle actin (αSMA), fibroblast activation protein alpha (FAPα), platelet derived growth factor receptor alpha and beta (PDGFRα and PDGFRβ), CD26/DPP4 and podoplanin (PDPN). All non-CAFs were excluded from the analysis using a lineage marker cocktail (CD24, CD31, CD45, CD49f, EpCAM, LYVE-1, and TER-119). In total 128 murine tumours and 12 healthy mammary fat pads were analysed.ResultsWe have developed a multicolour flow cytometry strategy based on exclusion of non-CAFs and successfully employed this to explore the temporal heterogeneity of freshly isolated CAFs in the 4T1 and 4T07 mouse models of triple-negative breast cancer. Analysing 128 murine tumours, we identified 5-6 main CAF populations and numerous minor ones based on the analysis of αSMA, FAPα, PDGFRα, PDGFRβ, CD26, and PDPN. All markers showed temporal changes with a distinct switch from primarily PDGFRα+ fibroblasts in healthy mammary tissue to predominantly PDGFRβ+ CAFs in tumours. CD26+ CAFs emerged as a large novel subpopulation, only matched by FAPα+ CAFs in abundance.ConclusionWe demonstrate that multiple subpopulations of CAFs co-exist in murine triple negative breast cancer, and that the abundance and dynamics for each marker differ depending on tumour type and time. Our results form the foundation needed to isolate and characterise specific CAF populations, and ultimately provide an opportunity to therapeutically target specific CAF subpopulations.
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Project description:Cancer-associated fibroblasts (CAFs) are key components in tumor microenvironment (TME). The secreted products of CAFs play important roles in regulating tumor cells and further impacting clinical prognosis. This study aims to reveal the relationship between CAF-secreted cytokines and breast cancer (BC) by constructing the risk signature. We performed three algorithms to reveal CAF-related cytokines in the TCGA BC dataset and identified five prognosis-related cytokines. Then we used single-cell RNA sequencing (ScRNA-Seq) datasets of BC to confirm the expression level of these five cytokines in CAFs. METABRIC and other independent datasets were utilized to validate the findings in further analyses. Based on the identified five-cytokine signature derived from CAFs, BC patients with high-risk score (RS) had shorter overall survival than low-RS cases. Further analysis suggested that the high-RS level correlated with cell proliferation and mast cell infiltration in BCs of the Basal-like subtype. The results also indicated that the level of RS could discriminate the high-risk BC cases harboring driver mutations (i.e., PI3KCA, CDH1, and TP53). Additionally, the status of five-cytokine signature was associated with the frequency and molecular timing of whole genome duplication (WGD) events. Intratumor heterogeneity (ITH) analysis among BC samples indicated that the high-RS level was associated with the increase of tumor subclones. This work demonstrated that the prognostic signature based on CAF-secreted cytokines was associated with clinical outcome, tumor progression, and genetic alteration. Our findings may provide insights to develop novel strategies for early intervention and prognostic prediction of BC.
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Project description:Studies have shown that cancer-associated fibroblasts (CAFs) play an irreplaceable role in the occurrence and development of tumors. Therefore, exploring the action and mechanism of CAFs on tumor cells is particularly important. In this study, we compared the effects of CAFs-derived exosomes and normal fibroblasts (NFs)-derived exosomes on breast cancer cells migration and invasion. The results showed that exosomes from both CAFs and NFs could enter into breast cancer cells and CAFs-derived exosomes had a more enhancing effect on breast cancer cells migration and invasion than NFs-derived exosomes. Furthermore, microRNA (miR)-18b was upregulated in CAFs-derived exosomes, and CAFs-derived exosomes miR-18b can promote breast cancer cell migration and metastasis by specifically binding to the 3'UTR of Transcription Elongation Factor A Like 7 (TCEAL7). The miR-18b-TCEAL7 pathway promotes nuclear Snail ectopic activation by activating nuclear factor-kappa B (NF-κB), thereby inducing epithelial-mesenchymal transition (EMT) and promoting cell invasion and metastasis. Moreover, CAFs-derived exosomes miR-18b could promote mouse xenograft model tumor metastasis. Overall, our findings suggest that CAFs-derived exosomes miR-18b promote nuclear Snail ectopic by targeting TCEAL7 to activate the NF-κB pathway, thereby inducing EMT, invasion, and metastasis of breast cancer. Targeting CAFs-derived exosome miR-18b may be a potential treatment option to overcome breast cancer progression.
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