Article

New road map through the land of IBD.

Harvard Medical School, Boston, Massachusetts, USA.
Inflammatory Bowel Diseases (Impact Factor: 5.48). 07/2008; 14(6):868-9. DOI: 10.1002/ibd.20394
Source: PubMed
0 Bookmarks
 · 
101 Views
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Ulcerative colitis (UC) and Crohn's disease (CD) are inflammatory bowel diseases (IBD) with variable, overlapping clinical features and complex pathophysiologies. To identify pathogenic processes underlying these disease subtypes, we used single endoscopic pinch biopsies to elucidate patterns of gene expression in active and inactive areas of UC and CD and compared these to infectious colitis and healthy control samples. Unsupervised classification of a total of 36 samples yielded promising separation between the affected IBD, unaffected IBD, non-IBD colitis, and normal control samples, suggesting each sample type had a distinctive gene expression pattern. Genes differentially expressed in the CD samples compared to in the controls were related to IFNgamma-inducible TH1 processes (IFITM1, IFITM3, STAT1, and STAT3) and antigen presentation (TAP1, PSME2, PSMB8). The most noticeable change in the UC samples was reduced expression of genes regulating biosynthesis, metabolism, and electrolyte transport (HNF4G, KLF5, AQP8, ATP2B1, and SLC16A). Twenty-five percent of genes down-regulated in the UC samples were also down-regulated in the infectious colitis samples. Unaffected biopsy samples of IBD patients also registered differences expression of genes compared to in the normal controls. Of these differentially expressed genes, only 2 were up-regulated, PSKH1, a regulator of mRNA processing, and PPID, a suppressor of apoptosis. The study shows that the gene expression patterns of IBD, CD in particular, are quite different from those of infectious colitis, highlighting distinctive expression of genes and pathways in UC and CD.
    Inflammatory Bowel Diseases 08/2007; 13(7):807-21. · 5.48 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Early detection of cancer can greatly improve prognosis. Identification of proteins or peptides in the circulation, at different stages of cancer, would greatly enhance treatment decisions. Mass spectrometry (MS) is emerging as a powerful tool to identify proteins from complex mixtures such as plasma that may help identify novel sets of markers that may be associated with the presence of tumors. To examine this feature we have used a genetically modified mouse model, Apc(Min), which develops intestinal tumors with 100% penetrance. Utilizing liquid chromatography-tandem mass spectrometry (LC-MS/MS), we identified total plasma proteome (TPP) and plasma glycoproteome (PGP) profiles in tumor-bearing mice. Principal component analysis (PCA) and agglomerative hierarchial clustering analysis revealed that these protein profiles can be used to distinguish between tumor-bearing Apc(Min) and wild-type control mice. Leave-one-out cross-validation analysis established that global TPP and global PGP profiles can be used to correctly predict tumor-bearing animals in 17/19 (89%) and 19/19 (100%) of cases, respectively. Furthermore, leave-one-out cross-validation analysis confirmed that the significant differentially expressed proteins from both the TPP and the PGP were able to correctly predict tumor-bearing animals in 19/19 (100%) of cases. A subset of these proteins was independently validated by antibody microarrays using detection by two color rolling circle amplification (TC-RCA). Analysis of the significant differentially expressed proteins indicated that some might derive from the stroma or the host response. These studies suggest that mass spectrometry-based approaches to examine the plasma proteome may prove to be a valuable method for determining the presence of intestinal tumors.
    Journal of Proteome Research 09/2006; 5(8):1866-78. · 5.00 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: ChemInform is a weekly Abstracting Service, delivering concise information at a glance that was extracted from about 200 leading journals. To access a ChemInform Abstract, please click on HTML or PDF.
    Chemical Reviews 09/2007; 107(8):3654-86. · 45.66 Impact Factor

Full-text (2 Sources)

Download
2 Downloads
Available from
Dec 19, 2014