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The role of proto-oncogene Fra-1 in remodeling the tumor microenvironment in support of breast tumor cell invasion and progression.

ABSTRACT: A growing body of evidence indicates that interactions between neoplastic cells and tumor-associated macrophages (TAMs) in the tumor microenvironment (TME) are crucial in promoting tumor cell invasion and progression. Macrophages have an ambiguous role in these processes as this M1 phenotype correlates with tumoricidal capacity, whereas TAMs of M2 phenotype exert tumor-promoting effects. In this study, we provide evidence that interactions between mouse breast tumor cells and TAMs remodel the TME, leading to the upregulation of Fra-1, a member of the FOS family of transcription factor. In turn, this proto-oncogene initiates activation of the IL-6/JAK/Stat3 signaling pathway. This creates a malignant switch in breast tumor cells, leading to increased release of proangiogenic factors MMP-9, vascular endothelial growth factor and transforming growth factor-beta from tumor cells and intensified invasion and progression of breast cancer. Proof of the concept for the crucial role played by transcription factor Fra-1 in regulating these processes was established by specific knockdown of Fra-1 with small interfering RNA, which resulted in a marked suppression of tumor cell invasion, angiogenesis and metastasis in a mouse breast cancer model. Such a strategy could eventually lead to future efficacious treatments of metastatic breast cancer.

SUBMITTER: Luo YP

PROVIDER: S-EPMC3032566 | biostudies-literature | 2010 Feb

REPOSITORIES: biostudies-literature

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The role of proto-oncogene Fra-1 in remodeling the tumor microenvironment in support of breast tumor cell invasion and progression.

Luo Y P YP Zhou H H Krueger J J Kaplan C C Liao D D Markowitz D D Liu C C Chen T T Chuang T-H TH Xiang R R Reisfeld R A RA

Oncogene 20091207 5

A growing body of evidence indicates that interactions between neoplastic cells and tumor-associated macrophages (TAMs) in the tumor microenvironment (TME) are crucial in promoting tumor cell invasion and progression. Macrophages have an ambiguous role in these processes as this M1 phenotype correlates with tumoricidal capacity, whereas TAMs of M2 phenotype exert tumor-promoting effects. In this study, we provide evidence that interactions between mouse breast tumor cells and TAMs remodel the TM ...[more]

PMID: 19966854

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Project description:Background: Immunosuppressive cell interactions are responsible for tumor progression and metastasis, as well as anti-tumor immune dysfunction. However, the communication pattern remains unclear. Methods: We first integrated two single-cell RNA-seq datasets (GSE72056 and GSE103322) of different tumor types to increase the diversity of immunosuppressive cells. Then, based on the analysis results of the communication network, gene regulatory network (GRN), and highly activated pathways, we identified the hub gene in the immunosuppressive tumor microenvironment (TME). To further explore the molecular features of the identified gene, we performed several in silico analysis and in vitro experiments including qRT-PCR and CCK-8 assay. Results: Four types of immunosuppressive cells were identified, including cancer-associated fibroblasts (CAFs), tumor-associated macrophages (TAMs), tumor-associated neutrophils (TANs), and regulatory T cells (Tregs). Based on GRNs and the interactions of immunosuppressive cells and tumor cells, we constructed an intercellular communication signature that divided the pan-cancer TME into two clusters with distinct immunological features and different responses to immunotherapy. In combination with pathway analysis, JunB proto-oncogene (JUNB) was identified as the hub gene of the immunosuppressive TME, and it designed a non-inflamed TME of bladder cancer according to evidence that JUNB was negatively correlated with immunomodulators, chemokines, major histocompatibility complex molecules, immune cell infiltration abundances, anti-cancer immune response, and immune checkpoint inhibitors. Moreover, JUNB may predict an unfavorable response to immunotherapy. The signaling network of the four types of cells demonstrated the dominant roles of CAFs and TAMs in the TME. Further investigation uncovered that the complement signal was highly activated in the interactions between subpopulations of the inflammatory phenotype of CAFs and TAMs. Functional experiment results demonstrated the upregulated JUNB in bladder cancer tissues and low-immunity-score tissues. In addition, CAFs showed a pro-tumor proliferation effect via JUNB. Conclusion: Our findings gave insights into the immunosuppressive TME communication network and provided potential therapeutic targets.

Project description:BackgroundThe abundance of immune and stromal cells in the tumor microenvironment (TME) is informative of levels of inflammation, angiogenesis, and desmoplasia. Radiomics, an approach of extracting quantitative features from radiological imaging to characterize diseases, have been shown to predict molecular classification, cancer recurrence risk, and many other disease outcomes. However, the ability of radiomics methods to predict the abundance of various cell types in the TME remains unclear. In this study, we employed a radio-genomics approach and machine learning models to predict the infiltration of 10 cell types in breast cancer lesions utilizing radiomic features extracted from breast Dynamic Contrast Enhanced Magnetic Resonance Imaging.MethodsWe performed a retrospective study utilizing 73 patients from two independent institutions with imaging and gene expression data provided by The Cancer Imaging Archive (TCIA) and The Cancer Genome Atlas (TCGA), respectively. A set of 199 radiomic features including shape-based, morphological, texture, and kinetic characteristics were extracted from the lesion volumes. To capture one-to-one relationships between radiomic features and cell type abundance, we performed linear regression on each radiomic feature/cell type abundance combination. Each regression model was tested for statistical significance. In addition, multivariate models were built for the cell type infiltration status (i.e. "high" vs "low") prediction. A feature selection process via Recursive Feature Elimination was applied to the radiomic features on the training set. The classification models took the form of a binary logistic extreme gradient boosting framework. Two evaluation methods including leave-one-out cross validation and external independent test, were used for radiomic model learning and testing. The models' performance was measured via area under the receiver operating characteristic curve (AUC).ResultsUnivariate relationships were identified between a set of radiomic features and the abundance of fibroblasts. Multivariate models yielded leave-one-out cross validation AUCs ranging from 0.5 to 0.83, and independent test AUCs ranging from 0.5 to 0.68 for the multiple cell type invasion predictions.ConclusionsOn two independent breast cancer cohorts, breast MRI-derived radiomics are associated with the tumor's microenvironment in terms of the abundance of several cell types. Further evaluation with larger cohorts is needed.

Dataset Information

The role of proto-oncogene Fra-1 in remodeling the tumor microenvironment in support of breast tumor cell invasion and progression.

Publications

The role of proto-oncogene Fra-1 in remodeling the tumor microenvironment in support of breast tumor cell invasion and progression.

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