4.7 Article

Confrontation of fibroblasts with cancer cells in vitro: gene network analysis of transcriptome changes and differential capacity to inhibit tumor growth

出版社

BMC
DOI: 10.1186/s13046-015-0178-x

关键词

Fibroblast; Stroma; Transcriptome; Systems biology; Differential expression; Cancer associated fibroblasts (CAFs); Cancer cell growth

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资金

  1. Concern Foundation, Los Angeles
  2. Cancer Research Institute, New York
  3. Swedish Research Council
  4. Swedish Cancer Society
  5. Hungarian Academy of Sciences
  6. BBSRC
  7. Hungarian Science Foundation [OTKA K-83314]
  8. BILS (Bioinformatics Infrastructure for Life Sciences)
  9. computational biology at The Genome Analysis Centre
  10. BBSRC [BBS/E/T/000PR6193, BBS/E/F/00044500, BBS/E/T/000PR5885] Funding Source: UKRI
  11. Biotechnology and Biological Sciences Research Council [BBS/E/F/00044500, BBS/E/T/000PR5885, BBS/E/T/000PR6193] Funding Source: researchfish

向作者/读者索取更多资源

Background: There is growing evidence that emerging malignancies in solid tissues might be kept under control by physical intercellular contacts with normal fibroblasts. Methods: Here 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. Results: The 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. Conclusions: We 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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