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Heterogeneity of gene expression in stromal fibroblasts of human breast carcinomas and normal breast.

Oncogene | 2010

Breast carcinoma invasion is associated with prominent alterations in stromal fibroblasts. Carcinoma-associated fibroblasts (CAF) support and promote tumorigenesis, whereas normal mammary fibroblasts (NF) are thought to suppress tumor progression. Little is known about the difference in gene expression between CAF and NF or the patient-to-patient variability in gene expression. Paired CAF and NF were isolated from six primary human breast carcinoma specimens. RNA was extracted from low-passage cultures of CAF and NF and analyzed with Affymetrix Human Genome U133 Plus 2.0 arrays. The array data were examined with an empirical Bayes model and filtered according to the posterior probability of equivalent expression and fold difference in expression. Twenty-one genes (27 probe sets) were up-regulated in CAF, as compared with NF. Known functions of these genes relate to paracrine or intracellular signaling, transcriptional regulation, extracellular matrix and cell adhesion/migration. Ten genes (14 probe sets) were down-regulated in CAF, including the pluripotency transcription factor KLF4. Quantitative RT-PCR analysis of 10 genes validated the array results. Immunohistochemical staining for three gene products confirmed stromal expression in terms of location and relative quantity. Surprisingly, the variability of gene expression was slightly higher in NF than in CAF, suggesting inter-individual heterogeneity of normal stroma.

Pubmed ID: 20062080 RIS Download

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Associated grants

  • Agency: NCI NIH HHS, United States
    Id: R01 CA107012
  • Agency: NCI NIH HHS, United States
    Id: R01 CA107012-01A1

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A commercial graphing software company that offers scientific software for statistical analyses, curve fitting and data analysis. It offers four programs: Prism, InStat, StatMate and QuickCalcs.

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Statistical analysis software that combines scientific graphing, comprehensive curve fitting (nonlinear regression), understandable statistics, and data organization. Designed for biological research applications in pharmacology, physiology, and other biological fields for data analysis, hypothesis testing, and modeling.

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