Transcriptomic Profiles Differentiate Normal Rectal Epithelium and Adenocarcinoma

Author:

Hogan J.12,Dejulius K.34,Liu X.5,Coffey J. C.126,Kalady M. F.34

Affiliation:

1. Department of General Surgery, Graduate Entry Medical School, University Hospital Limerick, Limerick, Ireland

2. University of Limerick, Limerick, Ireland

3. Department of Colorectal Surgery, Digestive Diseases Institute, Cleveland Clinic, Cleveland, Ohio

4. Cancer Biology Department, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio

5. Department of Anatomic Pathology, Cleveland Clinic, Cleveland, Ohio

6. 4i Centre for Interventions in Infection, Inflammation and Immunity, Graduate Entry Medical School, University of Limerick, Limerick, Ireland

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.

Publisher

International College of Surgeons

Subject

Surgery

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