Dataset Information

Integrative genome-wide expression analysis bears evidence of estrogen receptor-independent transcription in heregulin-stimulated MCF-7 cells.

ABSTRACT: Heregulin beta-1 (HRG) is an extracellular ligand that activates mitogen-activated protein kinase (MAPK) and phosphatidylinositol-3-OH kinase (PI3K)/Akt signaling pathways through ErbB receptors. MAPK and Akt have been shown to phosphorylate the estrogen receptor (ER) at Ser-118 and Ser-167, respectively, thereby mimicking the effects of estrogenic activity such as estrogen responsive element (ERE)-dependent transcription. In the current study, integrative analysis was performed using two tiling array platforms, comprising histone H3 lysine 9 (H3K9) acetylation and RNA mapping, together with array comparative genomic hybridization (CGH) analysis in an effort to identify HRG-regulated genes in ER-positive MCF-7 breast cancer cells. Through application of various threshold settings, 333 (326 up-regulated and 7 down-regulated) HRG-regulated genes were detected. Prediction of upstream transcription factors (TFs) and pathway analysis indicated that 21% of HRG-induced gene regulation may be controlled by the MAPK cascade, while only 0.6% of the gene expression is controlled by ERE. A comparison with previously reported estrogen (E2)-regulated gene expression data revealed that only 12 common genes were identified between the 333 HRG-regulated (3.6%) and 239 E2-regulated (5.0%) gene groups. However, with respect to enriched upstream TFs, 4 common TFs were identified in the 14 HRG-regulated (28.6%) and 13 E2-regulated (30.8%) gene groups. These results indicated that while E2 and HRG may induce common TFs, the regulatory mechanisms that govern HRG- and E2-induced gene expression differ.

SUBMITTER: Nagashima T

PROVIDER: S-EPMC2266794 | biostudies-literature | 2008

REPOSITORIES: biostudies-literature

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Integrative genome-wide expression analysis bears evidence of estrogen receptor-independent transcription in heregulin-stimulated MCF-7 cells.

Nagashima Takeshi T Suzuki Takahiro T Kondo Shinji S Kuroki Yoko Y Takahashi Kaoru K Ide Kaori K Yumoto Noriko N Hasegawa Aki A Toyoda Tetsuro T Kojima Toshio T Konagaya Akihiko A Suzuki Harukazu H Hayashizaki Yoshihide Y Sakaki Yoshiyuki Y Hatakeyama Mariko M

PloS one 20080319 3

Heregulin beta-1 (HRG) is an extracellular ligand that activates mitogen-activated protein kinase (MAPK) and phosphatidylinositol-3-OH kinase (PI3K)/Akt signaling pathways through ErbB receptors. MAPK and Akt have been shown to phosphorylate the estrogen receptor (ER) at Ser-118 and Ser-167, respectively, thereby mimicking the effects of estrogenic activity such as estrogen responsive element (ERE)-dependent transcription. In the current study, integrative analysis was performed using two tiling ...[more]

PMID: 18350142

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Project description:"Despite the success of the aromatase inhibitors (AIs) in treating estrogen receptor positive breast cancer, 15-20% of patients receiving adjuvant AIs will relapse within 5-10 years of treatment initiation. Long term estrogen deprivation (LTED) of breast cancer cells in culture has been successfully used to mimic AI-induced estrogen depletion to dissect mechanisms of AI resistance. However, we hypothesized that a subset of patients receiving AI therapy may maintain low circulating concentrations of estrogens that influence the development of endocrine resistance. We sought to expand established LTED models to account for these observations. MCF-7 cells were grown in medium with charcoal stripped serum supplemented with defined concentrations of E2 or the estrogenic androgen metabolite 3βAdiol. Cells were selected in the EC10 and EC90 of E2 or 3βAdiol, or estrogen deprived. Estrogen-independence was evaluated during selection by assessing cell growth in the absence or presence of E2 or 3βAdiol. Following >7 months of selection, estrogen-independence developed in estrogen-deprived cells and cells maintained in low concentrations of steroid hormone. Functional analyses demonstrated that estrogen-deprived and low-steroid selected cells developed estrogen-independence via unique mechanisms, independent and dependent of ERα, respectively. Estrogen-independent growth in low-steroid selected cells could be blocked by kinase inhibitors. However, these cells were completely resistant to kinase inhibition in the presence of low steroid hormone concentrations. These data offer a novel perspective on the development of resistance to AI therapy, and may yield novel approaches to treat AI-resistant tumors. MCF-7 cells were selected for >7months in IMEM+10% Charcoal Stripped FBS, supplmented with defined steroid hormone conditions. Following outgrowth of estrogen-independent cells, cell lines were grown in estrogen-free conditions and gene expression analysis was performed to identify drivers of estrogen-independent growth. Cells were assessed in biological triplicates."

Project description:Despite the success of the aromatase inhibitors (AIs) in treating estrogen receptor positive breast cancer, 15-20% of patients receiving adjuvant AIs will relapse within 5-10 years of treatment initiation. Long term estrogen deprivation (LTED) of breast cancer cells in culture has been successfully used to mimic AI-induced estrogen depletion to dissect mechanisms of AI resistance. However, we hypothesized that a subset of patients receiving AI therapy may maintain low circulating concentrations of estrogens that influence the development of endocrine resistance. We sought to expand established LTED models to account for these observations. MCF-7 cells were grown in medium with charcoal stripped serum supplemented with defined concentrations of E2 or the estrogenic androgen metabolite 3βAdiol. Cells were selected in the EC10 and EC90 of E2 or 3βAdiol, or estrogen deprived. Estrogen-independence was evaluated during selection by assessing cell growth in the absence or presence of E2 or 3βAdiol. Following >7 months of selection, estrogen-independence developed in estrogen-deprived cells and cells maintained in low concentrations of steroid hormone. Functional analyses demonstrated that estrogen-deprived and low-steroid selected cells developed estrogen-independence via unique mechanisms, independent and dependent of ERα, respectively. Estrogen-independent growth in low-steroid selected cells could be blocked by kinase inhibitors. However, these cells were completely resistant to kinase inhibition in the presence of low steroid hormone concentrations. These data offer a novel perspective on the development of resistance to AI therapy, and may yield novel approaches to treat AI-resistant tumors. MCF-7 cells were selected for >7months in IMEM+10% Charcoal Stripped FBS, supplmented with defined steroid hormone conditions. Following outgrowth of estrogen-independent cells, cell lines were grown in estrogen-free conditions and gene expression analysis was performed to identify drivers of estrogen-independent growth. Cells were assessed in biological triplicates.

Project description:In the context of the Human Toxome project, mass spectroscopy-based metabolomics characterization of estrogen-stimulated MCF-7 cells was studied in order to support the untargeted deduction of pathways of toxicity. A targeted and untargeted approach using overrepresentation analysis (ORA), quantitative enrichment analysis (QEA) and pathway analysis (PA) and a metabolite network approach were compared. Any untargeted approach necessarily has some noise in the data owing to artifacts, outliers and misidentified metabolites. Depending on the chemical analytical choices (sample extraction, chromatography, instrument and settings, etc.), only a partial representation of all metabolites will be achieved, biased by both the analytical methods and the database used to identify the metabolites. Here, we show on the one hand that using a data analysis approach based exclusively on pathway annotations has the potential to miss much that is of interest and, in the case of misidentified metabolites, can produce perturbed pathways that are statistically significant yet uninformative for the biological sample at hand. On the other hand, a targeted approach, by narrowing its focus and minimizing (but not eliminating) misidentifications, renders the likelihood of a spurious pathway much smaller, but the limited number of metabolites also makes statistical significance harder to achieve. To avoid an analysis dependent on pathways, we built a de novo network using all metabolites that were different at 24 h with and without estrogen with a p value <0.01 (53) in the STITCH database, which links metabolites based on known reactions in the main metabolic network pathways but also based on experimental evidence and text mining. The resulting network contained a "connected component" of 43 metabolites and helped identify non-endogenous metabolites as well as pathways not visible by annotation-based approaches. Moreover, the most highly connected metabolites (energy metabolites such as pyruvate and alpha-ketoglutarate, as well as amino acids) showed only a modest change between proliferation with and without estrogen. Here, we demonstrate that estrogen has subtle but potentially phenotypically important alterations in the acyl-carnitine fatty acids, acetyl-putrescine and succinoadenosine, in addition to likely subtle changes in key energy metabolites that, however, could not be verified consistently given the technical limitations of this approach. Finally, we show that a network-based approach combined with text mining identifies pathways that would otherwise neither be considered statistically significant on their own nor be identified via ORA, QEA, or PA.

Dataset Information

Integrative genome-wide expression analysis bears evidence of estrogen receptor-independent transcription in heregulin-stimulated MCF-7 cells.

Publications

Integrative genome-wide expression analysis bears evidence of estrogen receptor-independent transcription in heregulin-stimulated MCF-7 cells.

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