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. 2007;16(11):535-48.
doi: 10.3727/096504007783438376.

Analysis of gene expression profiles reveals novel correlations with the clinical course of colorectal cancer

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Analysis of gene expression profiles reveals novel correlations with the clinical course of colorectal cancer

Duccio Cavalieri et al. Oncol Res. 2007.

Abstract

In order to discover potential markers of prognosis in colorectal cancer (CRC) we have determined gene expression profiles, using cDNA microarrays in CRC samples obtained from 19 patients in Dukes stages C and D, with favorable clinical course (Dukes C patients, survival >5 years after surgery, group A, n=7) or unfavorable clinical course (Dukes stage C and D patients, survival <5 years after surgery, group B, n=12). Gene expression was measured in RNA from each tumor, using a pool of equal amounts of RNA from all tumors as a reference. To identify and rank differentially expressed genes we used three different analytical methods: (i) Significance Analysis of Microarrays (SAM), (ii) Cox's Proportional Hazard Model, and (iii) Trend Filter (a mathematical method for the assessment of numerical trends). The level of expression of a gene in an individual tumor was regarded as of interest when that gene was identified as differentially expressed by at least two of these three methods. By these stringent criteria we identified eight genes (ITGB2, MRPS11, NPR1, TXNL2, PHF10, PRSS8, KCNK3, JAK3) that were correlated with prolonged survival after surgery. Pathway analysis showed that patients with favorable prognosis had several activated metabolic pathways (carbon metabolism, transcription, amino acid and nitrogen metabolism, signaling and fibroblast growth factor receptor pathways). To further validate individual gene expression findings, the RNA level of each gene identified as a marker with microarrays was measured by real-time RT-PCR in CRC samples from an independent group of 55 patients. In this set of patients the Cox Proportional Hazard Model analysis demonstrated a significant association between increased patient survival and low expression of ITGB2 (p = 0.011) and NPR1 (p = 0.023) genes.

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