A 128-gene signature has been proposed to predict outcome in patients with stages II and III colorectal cancers. In the present study, we aimed to reproduce and validate the 128-gene signature in external and independent material.
Gene expression data from the original material were retrieved from the Gene Expression Omnibus (GEO) (n?=?111) in addition to a Danish data set (n?=?37). All patients had stages II and III colon cancers. A Prediction Analysis of Microarray classifier, based on the 128-gene signature and the original training set of stage I (n?=?65) and stage IV (n?=?76) colon cancers, was reproduced. The stages II and III colon cancers were subsequently classified as either stage I-like (good prognosis) or stage IV-like (poor prognosis) and assessed by the 36 months cumulative incidence of relapse.
In the GEO data set, results were reproducible in stage III, as patients predicted to be stage I-like had a significant lower risk of relapse than patients predicted as stage IV-like (P?=?0.04, Gray test). Results were not reproducible in stage II patients (P?>?0.05, Gray test). In the Danish data set, two of four stage III patients with relapse were correctly predicted as stage IV-like, and the remaining patients were predicted as stage I-like and unclassifiable, respectively. Stage II patients could not be stratified.
The 128-gene signature showed reproducibility in stage III colon cancer, but could not predict recurrence in stage II. Individual patient predictions in an independent Danish material were unsatisfactory. Additional validation in larger cohorts is warranted.
Genome-wide gene expression (GWGE) profiles of mucosal colonic biopsies have suggested the existence of a continuous inflammatory state in quiescent ulcerative colitis (UC). The aim of this study was to use DNA microarray-based GWGE profiling of mucosal colonic biopsies and isolated colonocytes from UC patients and controls in order to identify the cell types responsible for the continuous inflammatory state.
Adjacent mucosal colonic biopsies were obtained endoscopically from the descending colon in patients with active UC (n = 8), quiescent UC (n = 9), and with irritable bowel syndrome (controls, n = 10). After isolation of colonocytes and subsequent extraction of total RNA, GWGE data were acquired using Human Genome U133 Plus 2.0 GeneChip Array (Affymetrix, Santa Clara, CA). Data analysis was carried out by principal component analysis and projection to latent structure-discriminant analysis using the SIMCA-P 11 software (Umetrics, Umeå, Sweden).
A clear separation between active UC, quiescent UC, and control biopsies were found, whereas the model for the colonocytes was unable to distinguish between quiescent UC and controls. The differentiation between quiescent UC and control biopsies was governed by unique profiles containing gene expressions with significant fold changes. These primarily belonged to the family of homeostatic chemokines, revealing a plausible explanation for the abnormal regulated innate immune response seen in patients with UC.
This study has demonstrated the presence of a continuous inflammatory state in quiescent UC, which seems to reflect an altered gene expression profile of lamina propria cells.
Ulcerative colitis is the most prevailing entity of several disorders under the umbrella term inflammatory bowel disease, with potentially serious symptoms and devastating consequences for affected patients. The exact molecular etiology of ulcerative colitis is not yet revealed. In this study, we characterized the molecular phenotype of ulcerative colitis through transcriptomic and metabonomic profiling of colonic mucosal biopsies from patients and controls. We have characterized the extent to which metabonomic and transcriptomic molecular phenotypes are associated with ulcerative colitis versus controls and other disease-related phenotypes such as steroid dependency and age at diagnosis, to determine if there is evidence of enrichment of differential expression in candidate genes from genome-wide association studies and if there are particular pathways influenced by disease-associated genes. Both transcriptomic and metabonomic data have previously been shown to predict the clinical course of ulcerative colitis and related clinical phenotypes, indicating that molecular phenotypes reveal molecular changes associated with the disease. Our analyses indicate that variables of both transcriptomics and metabonomics are associated with disease case and control status, that a large proportion of transcripts are associated with at least one metabolite in mucosal colonic biopsies, and that multiple pathways are connected to disease-related metabolites and transcripts.
Nuclear magnetic resonance (NMR) spectroscopy and appropriate multivariate statistical analyses have been employed on mucosal colonic biopsies, colonocytes, lymphocytes, and urine from patients with ulcerative colitis (UC) and controls in order to explore the diagnostic possibilities, define new potential biomarkers, and generate a better understanding of the pathophysiology. Samples were collected from patients with active UC (n = 41), quiescent UC (n = 33), and from controls (n = 25) and analyzed by NMR spectroscopy. Data analysis was carried out by principal component analysis and orthogonal-projection to latent structure-discriminant analysis using the SIMCA P+11 software package (Umetrics, Umea, Sweden) and Matlab environment. Significant differences between controls and active UC were discovered in the metabolic profiles of biopsies and colonocytes. In the biopsies from patients with active UC higher levels of antioxidants and of a range of amino acids, but lower levels of lipid, glycerophosphocholine (GPC), myo-inositol, and betaine were found, whereas the colonocytes only displayed low levels of GPC, myo-inositol and choline. Interestingly, 20% of inactive UC patients had similar profiles to those who were in an active state. This study demonstrates the possibilities of metabonomics as a diagnostic tool in active and quiescent UC and provides new insight into pathophysiologic mechanisms.
Comment In: J Proteome Res. 2010 May 7;9(5):2794-520302326
To use microarray-based miRNA profiling of colonic mucosal biopsies from patients with ulcerative colitis (UC), Crohn's disease (CD), and controls in order to identify new potential miRNA biomarkers in inflammatory bowel disease.
Colonic mucosal pinch biopsies from the descending part were obtained endoscopically from patients with active UC or CD, quiescent UC or CD, as well as healthy controls. Total RNA was isolated and miRNA expression assessed using the miRNA microarray Geniom Biochip miRNA Homo sapiens (Febit GmbH, Heidelberg, Germany). Data analysis was carried out by principal component analysis and projection to latent structure-discriminant analysis using the SIMCA-P+12 software package (Umetrics, Umea, Sweden). The microarray data were subsequently validated by quantitative real-time polymerase chain reaction (qPCR) performed on colonic tissue samples from active UC patients (n = 20), patients with quiescent UC (n = 19), and healthy controls (n = 20). The qPCR results were analyzed with Mann-Whitney U test. In silico prediction analysis were performed to identify potential miRNA target genes and the predicted miRNA targets were then compared with all UC associated susceptibility genes reported in the literature.
The colonic mucosal miRNA transcriptome differs significantly between UC and controls, UC and CD, as well as between UC patients with mucosal inflammation and those without. However, no clear differences in the transcriptome of patients with CD and controls were found. The miRNAs with the strongest differential power were identified (miR-20b, miR-99a, miR-203, miR-26b, and miR-98) and found to be up-regulated more than a 10-fold in active UC as compared to quiescent UC, CD, and controls. Two miRNAs, miR-125b-1* and let-7e*, were up-regulated more than 5-fold in quiescent UC compared to active UC, CD, and controls. Four of the seven miRNAs (miR-20b, miR-98, miR-125b-1*, and let-7e*) were validated by qPCR and found to be specifically upregulated in patients with UC. Using in silico analysis we found several predicted pro-inflammatory target genes involved in various pathways, such as mitogen-activated protein kinase and cytokine signaling, which are both key signaling pathways in UC.
The present study provides the first evidence that miR-20b, miR-98, miR-125b-1*, and let-7e* are deregulated in patients with UC. The level of these miRNAs may serve as new potential biomarkers for this chronic disease.
The objective of this study was to investigate whether statin (3-hydroxy-3-methylglutaryl-coenzyme A reductase inhibitor) use is associated with risk of Parkinson's disease (PD) in Denmark. We identified 1,931 patients with a first time diagnosis of PD reported in hospital or outpatient clinic records between 2001 and 2006. We density matched to these patients 9,651 population controls by birth year and sex relying on the Danish population register. For every participant, we identified pharmacy records of statin and anti-Parkinson drug prescriptions since 1995 and before index date from a prescription medication use database for all Danish residents. Whenever applicable, the index dates for cases and their corresponding controls were advanced to the date of first recorded prescription for anti-Parkinson drugs. In our primary analyses, we excluded all statin prescriptions 2-years before PD diagnosis. Employing logistic regression adjusting for age, sex, diagnosis of chronic obstructive pulmonary disease, and Charlson comorbidity, we observed none to slightly inverse associations between PD diagnosis and statin prescription drug use. Inverse associations with statin use were only observed for short-term (