RNA-seq of human hypertrophic scar fibroblast cell treated with fkbp10 siRNA against untreated controls
Ontology highlight
ABSTRACT:
INSTRUMENT(S): Illumina HiSeq 4000
ORGANISM(S): Homo sapiens
SUBMITTER: xiaolu Huang
PROVIDER: E-MTAB-9471 | biostudies-arrayexpress |
REPOSITORIES: biostudies-arrayexpress
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Project description:human hypertrophic scar fibroblast cell treated with pcolce siRNA and control siRNA for 48 hours
2020-08-26 | E-MTAB-9472 | biostudies-arrayexpress
Project description:Hypertrophic scar (HTS) formation is characterized by exuberant fibroproliferation for reasons that remain poorly understood1. One important but often overlooked component of wound repair is mechanical force, which regulates reciprocal cell-matrix interactions through focal adhesion components including focal adhesion kinase (FAK)1,2. Here we report that FAK is activated following cutaneous injury and that this activation is potentiated by mechanical loading. Transgenic mice lacking fibroblast-specific FAK exhibit significantly less fibrosis in a preclinical model of HTS formation. Inflammatory pathways involving monocyte chemoattractant protein-1 (MCP-1), a chemokine highly implicated in human skin fibrosis3, are triggered following FAK activation, mechanistically linking physical force to fibrosis. Further, small molecule inhibition of FAK effectively abrogates fibroproliferative mechanisms in human cells and significantly reduces scar formation in vivo. Collectively, these findings establish a molecular basis for HTS formation based on the mechanical activation of fibroblast-specific FAK and demonstrate the therapeutic potential of targeted mechanomodulatory strategies. Wildtype murine tissue was harvested at either day 6 or 14 post-injury following 48 hours or 10 days of mechanical loading, respectively (n=4 mice per group per time point). Murine RNA was isolated, labeled, and hybridized to the GeneChip microarray according to the manufacturer’s protocols (Affymetrix, Santa Clara, CA, USA). Each gene in the microarray was represented by 20 oligonucleotide pairs, with each pair consisting of an oligonucleotide perfectly matched to the cDNA sequence, and a second oligonucleotide containing a single base mismatch. Raw microarray data (sample intensity files) were processed using GeneSpring GX 11.0 (Agilent Technologies Inc., Santa Clara, CA, USA).
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Project description:Keloids are scars that extend beyond original wounds and are resistant to treatment. In order to improve understanding of the molecular basis of keloid scarring, we have assessed the genomic profiles of keloid fibroblasts and keratinocytes. Skin and scar tissues were obtained for isolation of primary keratinocytes and fibroblasts. Keloid scars were excised from patients undergoing scar excision surgery, normal skin samples were isolated from patients undergoing elective plastic surgery. Primary culters were prepared for keratinocytes and fibroblasts, and were harvested for analysis up to passage three. Nine keloid scars, for adjacent non-lesional keloid skin samples, and three normal skin samples were obtained and cultured. RNA was isolated using RNeasy, and quality verified using an Agilent 2100 Bioanalyzer. Labeling and hybridization to Affymetrix Human Gene 1.0 ST microarray chips was performed by the Vanderbilt Genome Sciences Resource at Vanderbilt University Medical Center.
2013-05-28 | E-GEOD-44270 | biostudies-arrayexpress
Project description:Estrogen receptor M-NM-1 (ERM-NM-1) is a nuclear receptor that is the driving transcription factor expressed in the majority of breast cancers. Recent studies have demonstrated that the liver receptor homolog-1 (LRH-1), another nuclear receptor, is ERM-NM-1-regulated in breast cancer cells. Further, LRH-1 stimulates proliferation and promotes motility and invasion of breast cancer cells. To determine the mechanisms of LRH-1 action in breast cancer cells, we carried out gene expression microarray analysis following siRNA-mediated LRH-1 knockdown. Interestingly, gene ontology (GO) category enrichment analysis of the genes differentially regulated in the presence or absence of LRH-1 identified estrogen responsive genes as the most highly enriched GO categories. To further define LRH-1 target genes, we performed chromatin immunoprecipitation coupled to massively parallel sequencing (ChIP-seq) to identify genomic targets of LRH-1. Remarkably, ChIP-seq showed LRH-1 binding at many ERM-NM-1 binding sites. Analysis of select binding sites confirmed regulation of ERM-NM-1-regulated genes by LRH-1 through binding to estrogen response elements, as exemplified by the TFF1/pS2 gene. Finally, LRH-1 over-expression stimulated ERM-NM-1 recruitment, whilst LRH-1 knockdown reduced ERM-NM-1 recruitment to ERM-NM-1 binding sites. Taken together, our findings establish a key role for LRH-1 in the regulation of ERM-NM-1 target genes in breast cancer cells and identify a mechanism in which co-operative binding of LRH-1 and ERM-NM-1 at estrogen response elements controls the expression of estrogen-responsive genes. MCF-7 cells were transfected with LRH-1 siRNA #2, #3, or with a non-targeting siRNA (siControl) for 72 hours. Following assessment of RNA integrity, four biological replicates for each siRNA treatment were used for microarray analysis.
2013-09-01 | E-GEOD-47803 | biostudies-arrayexpress
Project description:Mouse models of cancer recapitulate many of the molecular and biological features of the human disease. We sought to exploit these experimental merits in a systematic comparative proteomics search for circulating proteins associated with lung tumor development. In-depth quantitative proteomics was applied to plasmas from three mouse models of lung adenocarcinoma driven by mutant EGFR or Kras or induced by urethane exposure and a mouse model of small cell lung cancer driven by loss of Trp53 and Rb. To further refine our lung cancer-specific and broad carcinoma signatures, we intersected these lung cancer proteome profiles with those from other well-established mouse models of pancreatic, ovarian, colon, prostate and breast cancer, as well as two mouse models of inflammation. A set of proteins regulated by Titf1/Nkx2-1, a master transcription factor in cells from the peripheral airways and a known lineage-survival oncogene in lung cancer was identified in plasmas of mouse models of lung adenocarcinoma. An EGFR network of proteins was discerned in the plasma of mice with lung tumors driven by a mutant human EGFR. Levels of these proteins returned toward baseline upon treatment with a tyrosine kinase inhibitor. Moreover, a distinct plasma signature was uncovered in the Trp53/Rb mutant small cell lung cancer model that included a set of proteins associated with neuroendocrine development. Our studies have identified novel plasma protein signatures among molecularly or histopathologically defined lung cancer subtypes. siRNA transfection experiments were performed in NCI-H3255 and HCC4019 lung adenocarcinoma cell lines using ON-TARGETplus SMARTpool small interfering RNAs (siRNAs) targeting TITF1 (L-019105-01-0005) along with a negative control (ON-TARGETplus siCONTROL nontargeting siRNA pool; D-001810-10-05) obtained from Dharmacon. 400000 cells were seeded in antibiotic-free RPMI-1640 media supplemented with 10% FBS, in 6-well culture plates. The next day, cells were transfected at a final concentration of 100nM siRNA using 6ul DharmaFECT 1 (Dharmacon) according to the manufacturer's instructions. 72-hours post-transfection, RNA was harvested using Trizol (Invitrogen) and protein using RIPA buffer for microarray expression and western blotting, respectively. RNA from TITF1 knockdown and control experiments was profiled by the MSKCC Genomics Core using the Illumina Human HT-12 v3.0 array platform according to manufacturer's instructions. Two biological replicates were profiled for each condition. Resulting data files were exported using GenomeStudio software, log2 transformed, quantile-normalized and analyzed using Partek Genomics Suite (v6.5). Average values of replicates for each gene were then compared between the TITF1 knockdown and non-targeting treatments for each cell line to identify candidate TITF1 regulated genes.
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