Transcriptomic profiles differentiate normal rectal epithelium and adenocarcinoma.

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.

Gene expression profile is associated with chemoradiation resistance in rectal cancer.

AIM: Patients with rectal cancer who achieve a complete pathological response after preoperative chemoradiation (CRT) have an improved oncological outcome. Identifying factors associated with a lack of response could help our understanding of the underlying biology of treatment resistance. This study aimed to develop a gene expression signature for CRT-resistant rectal cancer using high-throughput nucleotide microarrays. METHOD: Pretreatment biopsies of rectal adenocarcinomas were prospectively collected and freshly frozen according to an institutional review board-approved protocol. Total tumour mRNA was extracted and gene expression levels were measured using microarrays. Patients underwent proctectomy after completing standard long-course CRT and the resected specimens were graded for treatment response. Gene expression profiles for nonresponders were compared with those of responders. Differentially expressed genes were analyzed for functional significance using the Ingenuity Pathway Analysis (IPA) software. RESULTS: Thirty-three patients treated between 2006 and 2009 were included. We derived 812-gene and 183-gene signatures separating nonresponders from responders. The classifiers were able to identify nonresponders with a sensitivity and specificity of 100% using the 812-gene signature, and sensitivity and specificity of 33% and 100% using the 183-gene signature. IPA canonical pathway analysis revealed a significant ratio of differentially expressed genes in the 'DNA double-strand break repair by homologous recombination' pathway. CONCLUSION: Certain rectal cancer gene profiles are associated with poor response to CRT. Alterations in the DNA double-strand break repair pathway could contribute to treatment resistance and provides an opportunity for further studies.

Genetic and epigenetic classifications define clinical phenotypes and determine patient outcomes in colorectal cancer.

BACKGROUND: A molecular classification of colorectal cancer has been proposed based on microsatellite instability (MSI), CpG island methylator phenotype (CIMP), and mutations in the KRAS and BRAF oncogenes. This study examined the prevalence of these molecular classes, and differences in clinical presentation and outcome. METHODS: Demographics, tumour characteristics and survival were recorded for 391 subjects with colorectal cancer. Tumour DNA was analysed for MSI (high (MSI-H) or microsatellite stable (MSS)), CIMP (high (CIMP-H) or no (CIMP-neg)) and BRAF and KRAS mutations. Clinical differences between four phenotypes were examined. RESULTS: Most tumours were MSS/CIMP-neg (69.8 per cent), with a nearly equal distribution of MSI-H/CIMP-H, MSI-H/CIMP-neg and MSS/CIMP-H types. MSS/CIMP-neg tumours were less likely to be poorly differentiated (P = 0.009). CIMP-H tumours were more common in older patients (P < 0.001). MSI-H/CIMP-H tumours had a high frequency of BRAF mutation and a low rate of KRAS mutation; the opposite was true for MSS/CIMP-neg tumours (P < 0.001). The four molecular phenotypes tended towards divergent survival (P = 0.067 for stages 1-III). MSI-H cancers were associated with better disease-free survival (hazard ratio 2.00 (95 per cent confidence interval 1.03 to 3.91); P = 0.040). CONCLUSION: Colorectal cancers are molecularly and clinically heterogeneous. These different molecular phenotypes may reflect variable prognosis.