Prognosis of stage II colon cancer by non-neoplastic mucosa gene expression profiling

Abstract

We have assessed the possibility to build a prognosis predictor (PP), based on non-neoplastic mucosa microarray gene expression measures, for stage II colon cancer patients. Non-neoplastic colonic mucosa mRNA samples from 24 patients (10 with a metachronous metastasis, 14 with no recurrence) were profiled using the Affymetrix HGU133A GeneChip. Patients were repeatedly and randomly divided into 1000 training sets (TSs) of size 16 and validation sets (VS) of size 8. For each TS/VS split, a 70-gene PP, identified on the TS by selecting the 70 most differentially expressed genes and applying diagonal linear discriminant analysis, was used to predict the prognoses of VS patients. Mean prognosis prediction performances of the 70-gene PP were 81.8% for accuracy, 73.0% for sensitivity and 87.1% for specificity. Informative genes suggested branching signal-transduction pathways with possible extensive networks between individual pathways. They also included genes coding for proteins involved in immune surveillance. In conclusion, our study suggests that one can build an accurate PP for stage II colon cancer patients, based on non-neoplastic mucosa microarray gene expression measures.

p16INK4a Gene Promoter Hypermethylation in Mucosa as a Prognostic Factor for Patients with Colorectal Cancer

“…Several studies have shown that the colorectal mucosa in patients with CRC is characterized by alterations at the DNA, RNA, and protein levels that can be associated with premalignant behavior (2)(3)(4)(5), metastatic potential (6), and prognosis (7)(8)(9). Dietary factors such as folate, alcohol, and methionine in combination with polymorphisms in genes like methylenetetrahydrofolate reductase may be associated with CRC because of their influence on DNA methylation processes (10,11).…”

“…Barrier et al (9) recently showed that microarray gene expression profiles of non-neoplastic mucosa could be used to predict the postoperative prognosis of stage II colon cancer patients. Previous studies at our laboratory have shown that the expression of folate-associated genes in mucosa is associated with the survival of CRC patients (8,12).…”

A breast cancer prognostic signature predicts clinical outcomes in multiple tumor types

“…The ovarian cancer dataset from Bild et al (5) were assayed with Affymetrix U133A (retrieved with record GSE3149 from Gene Expression Omnibus). Two colon cancer datasets were all generated with Affymetrix U133A arrays (7,6). The lung adenocarcinoma datasets from Shedden et al (8) were generated with Affymetrix U133A.…”

“…If a gene has multiple probes, the average expression of multiple probes was used in the classification. The patient cohort from Barrier et al (6) was used as training set (n=50), while the cohort from another study by Barrier et al (7) was used as an independent validation set (n=24). A training model was built with the 25 signature genes to classify recurrence in colon cancer patients using a linear discriminant analysis function in SAS 9.1.…”

“…The prognostic signature correctly predicted recurrence in 94% (47/50) of patients, with a sensitivity of 100% (25/25) and a specificity of 88% (22/25). The model identified in the training cohort was applied to predict recurrence in each patient in the validation set (n=24) with a patient cohort retrieved from Barrier et al (7). In the validation, the prognostic signature correctly predicted recurrence in 75% (18/24) patients, with a sensitivity of 80% (8/10) and a specificity of 71.43% (10/14).…”