Project description:Transcriptional profiling was conducted on RNA from 8 xenograft L2987lung tumor tissue samples to identify genes affected by treatment with a VEGFR-2 small molecule inhibitor Experiment Overall Design: Baseline and 14 days post treatement gene expression profiling was performed using 8 xenograft L2987 lung tumor tissue samples to identify genes affected by a VEGFR-2 small molecule inhibitor
Project description:Lung tumors, as well as normal tumor-adjacent (NTA) tissue of non-small cell lung cancer (NSCLC) patients, were collected and subjected label-free quantitation shotgun proteomics in data-independent mode to identify differences between the tumors and adjacent tissue. By employing in-depth proteomics, we identified several pathways that are up- or downregulated in the tumors of non-small cell lung cancer patients.
Project description:This SuperSeries is composed of the following subset Series: GSE36420: Gene expression profiling of C57BL/6 mouse lung tissue with various treatments using the MA07 array GSE36421: Gene expression profiling of C57BL/6 mouse lung tissue with various treatments using the MA10 array GSE36422: Gene expression profiling of C57BL/6 mouse lung tissue with various treatments using the MA11 array Refer to individual Series
Project description:Mardinoglu2015 - Tissue-specific genome-scale
metabolic network - Lung
This model is described in the article:
The gut microbiota modulates
host amino acid and glutathione metabolism in mice.
Mardinoglu A, Shoaie S, Bergentall
M, Ghaffari P, Zhang C, Larsson E, Bäckhed F, Nielsen
J.
Mol. Syst. Biol. 2015; 11(10):
834
Abstract:
The gut microbiota has been proposed as an environmental
factor that promotes the progression of metabolic diseases.
Here, we investigated how the gut microbiota modulates the
global metabolic differences in duodenum, jejunum, ileum,
colon, liver, and two white adipose tissue depots obtained from
conventionally raised (CONV-R) and germ-free (GF) mice using
gene expression data and tissue-specific genome-scale metabolic
models (GEMs). We created a generic mouse metabolic reaction
(MMR) GEM, reconstructed 28 tissue-specific GEMs based on
proteomics data, and manually curated GEMs for small intestine,
colon, liver, and adipose tissues. We used these functional
models to determine the global metabolic differences between
CONV-R and GF mice. Based on gene expression data, we found
that the gut microbiota affects the host amino acid (AA)
metabolism, which leads to modifications in glutathione
metabolism. To validate our predictions, we measured the level
of AAs and N-acetylated AAs in the hepatic portal vein of
CONV-R and GF mice. Finally, we simulated the metabolic
differences between the small intestine of the CONV-R and GF
mice accounting for the content of the diet and relative gene
expression differences. Our analyses revealed that the gut
microbiota influences host amino acid and glutathione
metabolism in mice.
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