High-throughput arrays identify distinct genetic profiles associated with lymph node involvement in rectal cancer

Molecular Biology: Are We Getting Any Closer to Providing Clinically Useful Information?

Advances in molecular biology and biomarker research have significantly impacted our understanding and treatment of multiple solid malignancies. In rectal cancer, where neoadjuvant chemoradiation is widely used for locally advanced disease, most efforts have focused on the identification of predictors of response in an attempt to appropriately select patients for multimodality therapy. A variety of biomarkers have been studied, including genetic mutations, chromosomal copy number alterations, and single as well as multigene expression patterns. Also, as transanal resection of rectal tumors requires accurate preoperative detection of lymph node metastasis, the identification of biomarkers of regional nodal involvement has been another important field of active research. While preliminary results have been promising, lack of external validation means has a limited translation to clinical use. This review summarizes recent developments in rectal cancer biomarker research, highlighting the challenges associated with their adoption, and evaluating their potential for clinical use.

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.