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Series GSE14797 Query DataSets for GSE14797
Status Public on Feb 11, 2010
Title Non-invasive detection of molecular biomarkers in subjects with a history of insulin resistance and colorectal adenomas
Organism Homo sapiens
Experiment type Expression profiling by array
Summary We have developed novel molecular methodology utilizing a stool sample, which contains intact sloughed colon cells, in order to quantify colonic gene expression profiles. In this study, our goal was to identify diagnostic gene sets (combinations) for the noninvasive classification of different phenotypes. For this purpose, the effects of a legume enriched, low glycemic index, high fermentable fiber diet was evaluated in subjects with four possible combinations of risk factors, including insulin resistance (IR) and a history of adenomatous polyps. In a randomized crossover design controlled feeding study each participant (a total of 23, 5-12/group) consumed the experimental diet (1.5 cups of cooked dry beans) and a control diet (isocaloric average American diet) for 4 wk with a 3 wk washout period between diets. Using prior biological knowledge, the complexity of feature selection was reduced in order to perform an exhaustive search on all allowable feature (gene) sets of size 3, and among these, 27 had (unbiased) error estimates of 0.15 or less. Linear discriminant analysis (LDA) was successfully used to identify the best single genes and two- to three-gene combinations for distinguishing subjects with IR, a history of polyps or exposure to a chemoprotective legume-rich diet. These results support our premise that gene products (RNA) isolated from stool have diagnostic value in terms of assessing colon cancer risk.

Keywords: Exfoliated cells, legumes, insulin resistance, polyps
 
Overall design 86 slides, 4 treatment groups, 23 patients
 
Contributor(s) Zhao C, Ivanov I, Dougherty ER, Hartman TJ, Lanza E, Bobe G, Colburn NH, Lupton JR, Davidson LA, Chapkin RS
Citation(s) 19470793
Submission date Feb 11, 2009
Last update date Oct 28, 2014
Contact name Jennifer Goldsby
E-mail(s) jsgoldsby@tamu.edu
Phone 979-845-3908
Organization name Texas A&M University
Department Nutrition and Food Sciences
Street address 112 Cater-Mattil
City College Station
State/province TX
ZIP/Postal code 77845
Country USA
 
Platforms (1)
GPL2895 GE Healthcare/Amersham Biosciences CodeLink Human Whole Genome Bioarray
Samples (86)
GSM370111 Patient 1 baseline 1
GSM370112 Patient 1 baseline 2
GSM370113 Patient 1 diet period 1
Relations
BioProject PRJNA112083

Download family Format
SOFT formatted family file(s) SOFTHelp
MINiML formatted family file(s) MINiMLHelp
Series Matrix File(s) TXTHelp

Supplementary file Size Download File type/resource
GSE14797_RAW.tar 214.1 Mb (http)(custom) TAR (of TXT)
Processed data included within Sample table

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