Dataset Information

Validated prediction of pro-invasive growth factors using a transcriptome-wide invasion signature derived from a complex 3-D invasion assay

ABSTRACT: The invasion of activated fibroblasts represents a key pathomechanism in fibrotic diseases, carcinogenesis and metastasis. Here, invading fibroblasts contribute to fibrotic extracellular matrix (ECM) formation and the initiation, progression, or resistance of cancer, respectively. To construct a transcriptome-wide signature of fibroblast invasion, we used a multiplex phenotypic 3D invasion assay using murine lung fibroblasts. Microarray-based gene expression profiles of invading and non-invading fibroblasts were highly distinct: 1049 genes were differentially regulated (>1.5-fold). An unbiased pathway analysis (Ingenuity) identified a significant enrichment for the functional clusters ‘invasion of cells’, ‘idiopathic pulmonary fibrosis (IPF)’ and ‘metastasis’. Particularly, matrix metalloprotease13 (MMP13), transforming growth factor (TGF)β1, Caveolin1 (Cav1), Phosphatase and Tensin Homolog (Pten), and secreted frizzled-related protein1 (Sfrp1) were among the highest regulated genes. In silico analysis by Ingenuity predicted TGFβ1, epidermal growth factor (EGF), fibroblast growth factor2 (FGF2), and platelet-derived growth factor (PDGF)-BB to induce invasion. As such, these growth factors were tested in the 3D invasion assay and displayed a significant induction of invasion, thus validating the transcriptome profile. Accordingly, our transcriptomic invasion signature describes the invading fibroblast phenotype in unprecedented detail and provides a tool for future functional studies of cell invasion and therapeutic modulation thereof.

ORGANISM(S): Mus musculus

PROVIDER: GSE55322 | GEO | 2015/10/05

SECONDARY ACCESSION(S): PRJNA239320

REPOSITORIES: GEO

ACCESS DATA

Similar Datasets

Project description:Full title: Comprehensive Characterization of Three-Dimensional Models for Prostate Cancer Growth and Invasion in Laminin-rich Extracellular Matrix Prostate Cancer (PrCa) cells undergo acinar morphogenesis and spheroid formation in three-dimensional (3D) culture, supported by laminin-rich extracellular matrix (lrECM, Matrigel). We developed miniaturized 3D model systems that facilitate investigation of morphogenesis and invasion of normal and PrCa cell lines in lrECM. Primary and non-transformed cell lines formed round structures with strong cell-cell contacts and epithelial polarization, lumen and a complete basal lamina (BL). In contrast, most PrCa cell lines formed either defective, “mass” spheroids with incomplete BL, or invasive “stellate” structures. The bioinformatic analyses of genome-wide mRNA expression data revealed massive alteration of key functional and signaling pathways in 3D cultures, with lipid and steroid metabolism, epigenetic reprogramming, and differentiation-related transcription factors induced across all cell lines by lrECM. In invasive cells, AKT, PI3Kinase, mTOR, and hedgehog signaling pathways were most highly activated, validated by small molecule inhibitors compounds specifically targeting key regulatory molecules. Compounds against AKT and PI3kinase pathways were significantly more effective in invasive cells, compared to mass or round/normal phenotype spheroids, and monolayer culture. A severe morphologic conversion was observed in PC-3 and PC-3M cells, transforming initially round, normal-appearing epithelial spheroids into rapidly invading cell masses. Markers for EMT (epithelial-mesenchymal transition) were highly expressed already in early stage, round spheroids prior to invasive conversion, and were not further increased in invasive cells. This indicates that PrCa cells can display extraordinary plasticity. EMT may be involved in providing a metastable genotype that allows morphological transformation, but is not be required for invasive processes themselves. Total RNA was obtained from non-transformed prostate epithelial cells and prostate cancer cells cultured in monolayer and three-dimensional laminin-rich extracellular matrix (growth factor-reduced Matrigel).

Dataset Information

Validated prediction of pro-invasive growth factors using a transcriptome-wide invasion signature derived from a complex 3-D invasion assay

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure