Integrating Biological Covariates into Gene Expression-Based Predictors of Radiation Sensitivity.

The use of gene expression-based classifiers has resulted in a number of promising potential signatures of patient diagnosis, prognosis, and response to therapy. However, these approaches have also created difficulties in trying to use gene expression alone to predict a complex trait. A practical approach to this problem is to integrate existing biological knowledge with gene expression to build a composite predictor. We studied the problem of predicting radiation sensitivity within human cancer cell lines from gene expression. First, we present evidence for the need to integrate known biological conditions (tissue of origin, RAS, and p53 mutational status) into a gene expression prediction problem involving radiation sensitivity. Next, we demonstrate using linear regression, a technique for incorporating this knowledge. The resulting correlations between gene expression and radiation sensitivity improved through the use of this technique (best-fit adjusted R2 increased from 0.3 to 0.84). Overfitting of data was examined through the use of simulation. The results reinforce the concept that radiation sensitivity is not driven solely by gene expression, but rather by a combination of distinct parameters. We show that accounting for biological heterogeneity significantly improves the ability of the model to identify genes that are associated with radiosensitivity.

Loss of Rab25 promotes the development of intestinal neoplasia in mice and is associated with human colorectal adenocarcinomas.

Transformation of epithelial cells is associated with loss of cell polarity, which includes alterations in cell morphology as well as changes in the complement of plasma membrane proteins. Rab proteins regulate polarized trafficking to the cell membrane and therefore represent potential regulators of this neoplastic transition. Here we have demonstrated a tumor suppressor function for Rab25 in intestinal neoplasia in both mice and humans. Human colorectal adenocarcinomas exhibited reductions in Rab25 expression independent of stage, with lower Rab25 expression levels correlating with substantially shorter patient survival. In wild-type mice, Rab25 was strongly expressed in cells luminal to the proliferating cells of intestinal crypts. While Rab25-deficient mice did not exhibit gross pathology, ApcMin/+ mice crossed onto a Rab25-deficient background showed a 4-fold increase in intestinal polyps and a 2-fold increase in colonic tumors compared with parental ApcMin/+ mice. Rab25-deficient mice had decreased beta1 integrin staining in the lateral membranes of villus cells, and this pattern was accentuated in Rab25-deficient mice crossed onto the ApcMin/+ background. Additionally, Smad3+/- mice crossed onto a Rab25-deficient background demonstrated a marked increase in colonic tumor formation. Taken together, these results suggest that Rab25 may function as a tumor suppressor in intestinal epithelial cells through regulation of protein trafficking to the cell surface.

Metastasis-Associated Gene Expression Changes Predict Poor Outcomes in Patients with Dukes Stage B and C Colorectal Cancer.

PURPOSE: Colorectal cancer prognosis is currently predicted from pathologic staging, providing limited discrimination for Dukes stage B and C disease. Additional markers for outcome are required to help guide therapy selection for individual patients. EXPERIMENTAL DESIGN: A multisite single-platform microarray study was done on 553 colorectal cancers. Gene expression changes were identified between stage A and D tumors (three training sets) and assessed as a prognosis signature in stage B and C tumors (independent test and external validation sets). RESULTS: One hundred twenty-eight genes showed reproducible expression changes between three sets of stage A and D cancers. Using consistent genes, stage B and C cancers clustered into two groups resembling early-stage and metastatic tumors. A Prediction Analysis of Microarray algorithm was developed to classify individual intermediate-stage cancers into stage A-like/good prognosis or stage D-like/poor prognosis types. For stage B patients, the treatment adjusted hazard ratio for 6-year recurrence in individuals with stage D-like cancers was 10.3 (95% confidence interval, 1.3-80.0; P = 0.011). For stage C patients, the adjusted hazard ratio was 2.9 (95% confidence interval, 1.1-7.6; P = 0.016). Similar results were obtained for an external set of stage B and C patients. The prognosis signature was enriched for downregulated immune response genes and upregulated cell signaling and extracellular matrix genes. Accordingly, sparse tumor infiltration with mononuclear chronic inflammatory cells was associated with poor outcome in independent patients. CONCLUSIONS: Metastasis-associated gene expression changes can be used to refine traditional outcome prediction, providing a rational approach for tailoring treatments to subsets of patients. (Clin Cancer Res 2009;15(24):7642-51).