ArticleJournal of experimental & clinical cancer research : CR2015
Confrontation of fibroblasts with cancer cells in vitro: gene network analysis of transcriptome changes and differential capacity to inhibit tumor growth.
Article in Journal of experimental & clinical cancer research : CR, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed, 13 citations in OpenAlex.
- Anticancer Effect of Nature-Inspired Indolizine-Based Pentathiepines in 2D and 3D Cellular Model.Cancers · 2025Article
- Exploring the multifaceted role of direct interaction between cancer cells and fibroblasts in cancer progression.Frontiers in molecular biosciences · 2024Review
- Fibroblasts as Turned Agents in Cancer Progression.Cancers · 2023Review
- Review
- EviNet: a web platform for network enrichment analysis with flexible definition of gene sets.Nucleic acids research · 2018Article
- Fibroblasts in the Tumor Microenvironment: Shield or Spear?International journal of molecular sciences · 2018Review
- NEArender: an R package for functional interpretation of 'omics' data via network enrichment analysis.BMC bioinformatics · 2017Article
- RhoA knockout fibroblasts lose tumor-inhibitory capacity in vitro and promote tumor growth in vivo.Proceedings of the National Academy of Sciences of the United States of America · 2017Article
- Intracellular and intercellular signaling networks in cancer initiation, development and precision anti-cancer therapy: RAS acts as contextual signaling hub.Seminars in cell & developmental biology · 2016Review
- Growth differentiation factor 15 contributes to cancer-associated fibroblasts-mediated chemo-protection of AML cells.Journal of experimental & clinical cancer research : CR · 2016Article
- A Network Biology Approach to Decipher Stress Response in Bacteria Using Escherichia coli As a Model.Omics : a journal of integrative biology · 2016Article
- Electric Cell-Substrate Impedance Sensing (ECIS) with Microelectrode Arrays for Investigation of Cancer Cell-Fibroblasts Interaction.PloS one · 2016Article
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Authors and funding
12 authors at 4 institutions in 5 countries.
Funding
Abstract
backgroundThere is growing evidence that emerging malignancies in solid tissues might be kept under control by physical intercellular contacts with normal fibroblasts.
methodsHere we characterize transcriptional landscapes of fibroblasts that confronted cancer cells. We studied four pairs of in vitro and ex vivo fibroblast lines which, within each pair, differed in their capacity to inhibit cancer cells. The natural process was modeled in vitro by confronting the fibroblasts with PC-3 cancer cells. Fibroblast transcriptomes were recorded by Affymetrix microarrays and then investigated using network analysis.
resultsThe network enrichment analysis allowed us to separate confrontation- and inhibition-specific components of the fibroblast transcriptional response. Confrontation-specific differences were stronger and were characterized by changes in a number of pathways, including Rho, the YAP/TAZ cascade, NF-kB, and TGF-beta signaling, as well as the transcription factor RELA. Inhibition-specific differences were more subtle and characterized by involvement of Rho signaling at the pathway level and by potential individual regulators such as IL6, MAPK8, MAP2K4, PRKCA, JUN, STAT3, and STAT5A.
conclusionsWe investigated the interaction between cancer cells and fibroblasts in order to shed light on the potential mechanisms and explain the differential inhibitory capacity of the latter, which enabled both a holistic view on the process and details at the gene/protein level. The combination of our methods pointed to proteins, such as members of the Rho pathway, pro-inflammatory signature and the YAP1/TAZ cascade, that warrant further investigation via tools of experimental perturbation. We also demonstrated functional congruence between the in vitro and ex vivo models. The microarray data are made available via the Gene Expression Omnibus as GSE57199.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.