title: Transcriptomic profiles differentiate normal rectal epithelium and adenocarcinoma.
abstract: Adenocarcinoma is a histologic diagnosis based on subjective findings. Transcriptional profiles have been used to differentiate normal tissue from disease and could provide a means of identifying malignancy. The goal of this study was to generate and test transcriptomic profiles that differentiate normal from adenocarcinomatous rectum. Comparisons were made between cDNA microarrays derived from normal epithelium and rectal adenocarcinoma. Results were filtered according to standard deviation to retain only highly dysregulated genes. Genes differentially expressed between cancer and normal tissue on two-groups t test (P < 0.05, Bonferroni P value adjustment) were further analyzed. Genes were rank ordered in terms of descending fold change. For each comparison (tumor versus normal epithelium), those 5 genes with the greatest positive fold change were grouped in a classifier. Five separate tests were applied to evaluate the discriminatory capacity of each classifier. Genetic classifiers derived comparing normal epithelium with malignant rectal epithelium from pooled stages had a mean sensitivity and specificity of 99.6% and 98.2%, respectively. The classifiers derived from comparing normal and stage I cancer had comparable mean sensitivities and specificities (97% and 98%, respectively). Areas under the summary receiver-operator characteristic curves for each classifier were 0.981 and 0.972, respectively. One gene was common to both classifiers. Classifiers were tested in an independent Gene Expression Omnibus-derived dataset. Both classifiers retained their predictive properties. Transcriptomic profiles comprising as few as 5 genes are highly accurate in differentiating normal from adenocarcinomatous rectal epithelium, including early-stage disease.
authors.affiliation: 1 Department of General Surgery, Graduate Entry Medical School, University Hospital Limerick, Limerick, Ireland.
authors.forename: J
authors.initials: J
authors.lastname: Hogan
authors.forename: K
authors.initials: K
authors.lastname: Dejulius
authors.forename: X
authors.initials: X
authors.lastname: Liu
authors.forename: J C
authors.initials: JC
authors.lastname: Coffey
authors.forename: M F
authors.initials: MF
authors.lastname: Kalady
mesh_terms: D000230:Adenocarcinoma / Q000235:genetics* / Q000473:pathology; D005260:Female; D020869:Gene Expression Profiling; D006801:Humans; D008297:Male; D046228:Microarray Analysis; D009367:Neoplasm Staging; D011237:Predictive Value of Tests; D012004:Rectal Neoplasms / Q000235:genetics* / Q000473:pathology; D012007:Rectum / Q000473:pathology*; D012680:Sensitivity and Specificity
keywords: Classifier; Diagnostic accuracy; Rectal cancer; Transcriptomic profiles