L-Arginine (L-Arg) is the substrate for both inducible nitric oxide synthase and arginase, which are upregulated in human IBD and in mouse colitis models. We have found that L-Arg supplementation enhances wound restitution in vitro, and improves the clinical parameters of weight loss, survival, and colon weight/length, in dextran sulfate sodium (DSS) induced murine colitis. Our aim was to further identify the potential mechanisms underlying the clinical benefit of L-Arg supplementation.
L-arginine supplementation improves responses to injury and inflammation in dextran sulfate sodium colitis.
Sex, Age, Specimen part
View SamplesWe quantified differential gene (mRNA) expression in human coronary artery cells treated with native HDL, reconstituted HDL, lipid-free apolipoprotein A-I, small unilamellar vesicles, or PBS control.
HDL-transferred microRNA-223 regulates ICAM-1 expression in endothelial cells.
Specimen part
View SamplesWild-type c57Bl/6 mice were placed on high-fat diet (21% fat) for 3 weeks, and total RNA from liver was used for affymetrix microarray analysis. Data were analyzed using GeneSpring GX12.0.
No associated publication
No sample metadata fields
View SamplesThis SuperSeries is composed of the SubSeries listed below.
Experimentally derived metastasis gene expression profile predicts recurrence and death in patients with colon cancer.
Sex, Age, Disease stage, Race
View SamplesBackground and Aims: Staging inadequately predicts metastatic risk in colon cancer patients. We used a gene expression profile derived from invasive murine colon cancer cells that were highly metastatic in an immunocompetent mouse model to identify colon cancer patients at risk for recurrence in a phase I, exploratory biomarker study.
Experimentally derived metastasis gene expression profile predicts recurrence and death in patients with colon cancer.
Sex, Age, Disease stage, Race
View SamplesColorectal carcinoma is the third leading cause of cancer-related death in the United States. In order to understand the mechanism/signaling pathways responsible for invasion, migration and metastasis in colorectal cancer, we developed an integrative and comparative genetic approach to infer transcriptional regulatory mechanisms underlying colon cancer progression. Accordingly, we filtered fourteen human colorectal cancer (CRC) microarray data sets, from an immune competent mouse model of metastasis to identify known and novel transcriptional regulators in CRC. Using this approach, Nuclear Factor of Activated T cells (NFAT) family of transcription factors were identified as metastasis driver of colon cancer. NFAT family of transcription factors is known to induce gene transcription in various disease processes, including carcinogenesis. We used parental and metastatic derivatives of MC38 mouse colon cancer cells (MC38Par and MC38Met, respectively) to evaluate the role of NFATc1 in cancer cell invasiveness. We found that high NFATc1 expression correlates with significantly increased (p<0.0001) Trans-Endothelial Invasion (TEI) in MC38Met cells. Conversely, RNAi-based inhibition of NFATc1 expression and functional inhibition with calcineurin inhibitor FK506 in MC38Met cells, both resulted in significant decreased TEI (p=0.0193 & p=0.0003). Furthermore, a set of predicted NFATc1 target mRNAs identified in our original analysis were downregulated by knock-down of NFATc1 or functional inhibition with FK506 in MC38Met cells. The expression level (mRNA) of predicted gene targets were high in human CRC specimens which had higher than median NFATc1 mRNA expression (n=11 out of total 22). The tumor-associated NFATc1 co-regulated gene signature is significantly correlated with both disease-specific and disease-free survival in Stage II and III CRC patients. We have successfully demonstrated a bioinformatics approach to identify a tumor promoter driver gene NFATc1. Our studies suggest a role of NFATc1 towards invasion and its co-regulated gene signature for poor outcomes in colorectal cancer.
Nuclear factor of activated T-cell activity is associated with metastatic capacity in colon cancer.
No sample metadata fields
View SamplesThe purpose of this study was to identify differentially expressed genes in laser-capture microdissected (LCM) invasive mammary carcinomas (IMCs).
Identification of human triple-negative breast cancer subtypes and preclinical models for selection of targeted therapies.
Specimen part, Disease, Disease stage
View SamplesThe identification of novel tumor-specific markers may improve understanding of melanoma progression and prognostic accuracy. Whole genome expression profiling of 46 primary melanomas, 12 metastases, and 16 normal skin samples using Affymetrix U133 PLUS 2.0 array generated gene lists including both known and new melanoma genes.
Transcriptome profiling identifies HMGA2 as a biomarker of melanoma progression and prognosis.
Sex, Age, Disease
View SamplesThe prognosis of colorectal cancer (CRC) stage II and III patients is still a challenge due to the difficulties of finding robust biomarkers and assays. The majority of published gene signatures of CRC have been generated on frozen colorectal tissues. Because collection of fresh frozen tissues is not routine and the quantity and quality of RNA derived from formalin-fixed paraffin-embedded (FFPE) tissues is vastly inferior to that derived from fresh frozen tissue, a clinical test for improving staging of colon cancer will need to be designed for FFPE tissues in order to be widely applicable. We have designed a custom Nanostring nCounter assay for quantitative assessment of expression of 414 gene elements consisting of multiple published gene signatures for colon cancer prognosis, and systematically compared the gene expression quantification between nCounter data from FFPE and Affymetrix microarray array data from matched frozen tissues using 414 genes.
Comparison of Nanostring nCounter® Data on FFPE Colon Cancer Samples and Affymetrix Microarray Data on Matched Frozen Tissues.
Disease
View SamplesBackground and Aims: Staging inadequately predicts metastatic risk in colon cancer patients. We used a gene expression profile derived from invasive murine colon cancer cells that were highly metastatic in an immunocompetent mouse model to identify colon cancer patients at risk for recurrence in a phase I, exploratory biomarker study.
Experimentally derived metastasis gene expression profile predicts recurrence and death in patients with colon cancer.
Sex, Age, Disease stage, Race
View Samples