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Colorectal cancer (CRC) is one of the most common life-threatening malignances worldwide. CRC relapse markedly decreases the 5-year survival of patients following surgery. Aberrant expression of genes involved in pathways regulating the cell cycle, cell proliferation, or cell death are frequently reported in CRC tumorigenesis. We hypothesized that genes involved in CRC relapse might serve as prognostic indicators. We first evaluated the significance of gene sequences in the feces of patients with CRC relapse by consulting a public database. Tumorigenesis of target tissues was tested through tumor cell growth, cell cycle regulation, and chemotherapeutic efficacy. We found a highly significant correlation between CRC relapse and growth arrest-specific 2 (GAS2) gene expression. Based on cell models, the overexpressed GAS2 was associated with cellular growth rate, cell cycle regulation, and with chemotherapeutic sensitivity. Cell division was impaired by treating cells with 2-[4-(7-chloro-2-quinoxalinyloxy)phenoxy]-propionic acid (XK469), even when the cells were overexpressing GAS2. Thus, downregulation of GAS2 expression might control CRC relapse after curative resection. GAS2 could serve as a noninvasive marker from the feces of patients with prediagnosed CRC. Our findings suggest that GAS2 could have potential clinical applications for predicting early CRC relapse after radical resection, and that XK469 might impair tumor cell division by reducing GAS2 expression or blocking its cellular translocation. This will help in selecting the best therapeutic option, 5-fluorouracil in combination with XK469, for patients overexpressing GAS2 in CRC cells. Thus, GAS2 might act as a prognostic biomolecule and potential therapeutic target in patients with CRC relapse. [ABSTRACT FROM AUTHOR]

Background: The development and progression of colorectal cancer (CRC) involve a complex process of multiple genetic changes. Tumor suppressor p53 is capable of determining the fate of CRC cells. However, the role of a p53-inducible modulator, ribosomal protein S27-like (RPS27L), in CRC is unknown. Methods: Here, the differential expression of RPS27L was examined in the feces and colonic tissues of CRC patients, to explore its possible correlation with patient survival and to investigate the cellular mechanisms underlying their clinical outcomes. Eighty intermediate-stage CRC patients (42 at stage II and 38 at stage III) were divided into two groups according to their fecal RPS27L mRNA levels. The survival probabilities of the groups were estimated using the Kaplan–Meier method. The RPS27L protein in the colonic tissues of stage III patients with different prognoses was further examined immunohistochemically. RPS27L expression in LoVo cells was manipulated to examine the possible cellular responses in vitro. Results: Elevated RPS27L expression, in either feces or tissues, was related to a better prognosis. In vitro, RPS27L-expressing LoVo cells ceased DNA synthesis and apoptotic activity while the expression of their DNA repair molecules was upregulated. Conclusions: Elevated RPS27L may improve the prognoses of certain CRC patients by enhancing the DNA repair capacity of their colonic cells, and can be determined in feces. By integrating clinical, molecular, and cellular data, our study demonstrates that fecal RPS27L may be a useful index for predicting prognoses and guiding personalized therapeutic strategies, especially in patients with intermediate-stage CRC. [ABSTRACT FROM AUTHOR]

The interplay between copy number variation (CNV) and differential gene expression may be able to shed light on molecular process underlying breast cancer and lead to the discovery of cancer-related genes. In the current study, genes concurrently identified in array comparative genomic hybridization (CGH) and gene expression microarrays were used to derive gene signatures for Han Chinese breast cancers. We performed 23 array CGHs and 81 gene expression microarrays in breast cancer samples from Taiwanese women. Genes with coherent patterns of both CNV and differential gene expression were identified from the 21 samples assayed using both platforms. We used these genes to derive signatures associated with clinical ER and HER2 status and disease-free survival. Distributions of signature genes were strongly associated with chromosomal location: chromosome 16 for ER and 17 for HER2. A breast cancer risk predictive model was built based on the first supervised principal component from 16 genes (RCAN3, MCOLN2, DENND2D, RWDD3, ZMYM6, CAPZA1, GPR18, WARS2, TRIM45, SCRN1, CSNK1E, HBXIP, CSDE1, MRPL20, IKZF1, and COL20A1), and distinct survival patterns were observed between the high- and low-risk groups from the combined dataset of 408 microarrays. The risk score was significantly higher in breast cancer patients with recurrence, metastasis, or mortality than in relapse-free individuals (0.241 versus 0, P<0.001). The concurrent gene risk predictive model remained discriminative across distinct clinical ER and HER2 statuses in subgroup analysis. Prognostic comparisons with published gene expression signatures showed a better discerning ability of concurrent genes, many of which were rarely identifiable if expression data were pre-selected by phenotype correlations or variability of individual genes. We conclude that parallel analysis of CGH and microarray data, in conjunction with known gene expression patterns, can be used to identify biomarkers with prognostic values in breast cancer. [ABSTRACT FROM AUTHOR]