A 19-Gene expression signature as a predictor of survival in colorectal cancer

Abstract

Background: Histopathological assessment has a low potential to predict clinical outcome in patients with the same stage of colorectal cancer. More specific and sensitive biomarkers to determine patients' survival are needed. We aimed to determine gene expression signatures as reliable prognostic marker that could predict survival of colorectal cancer patients with Dukes' B and C.

Methods: We examined microarray gene expression profiles of 78 archived tissues of patients with Dukes' B and C using the Illumina DASL assay. The gene expression data were analyzed using the GeneSpring software and R programming.

Results: The outliers were detected and replaced with randomly chosen genes from the 90 % confidence interval of the robust mean for each group. We performed three statistical methods (SAM, LIMMA and t-test) to identify significant genes. There were 19 significant common genes identified from microarray data that have been permutated 100 times namely NOTCH2, ITPRIP, FRMD6, GFRA4, OSBPL9, CPXCR1, SORCS2, PDC, C12orf66, SLC38A9, OR10H5, TRIP13, MRPL52, DUSP21, BRCA1, ELTD1, SPG7, LASS6 and DUOX2. This 19-gene signature was able to significantly predict the survival of patients with colorectal cancer compared to the conventional Dukes' classification in both training and test sets (p < 0.05). The performance of this signature was further validated as a significant independent predictor of survival using patient cohorts from Australia (n = 185), USA (n = 114), Denmark (n = 37) and Norway (n = 95) (p < 0.05). Validation using quantitative PCR confirmed similar expression pattern for the six selected genes.

Conclusion: Profiling of these 19 genes may provide a more accurate method to predict survival of patients with colorectal cancer and assist in identifying patients who require more intensive treatment.

Keywords: Colorectal cancer; Microarray analysis; Real-time PCR; Survivalm.

Fig. 1

a Cancerous tissue section of patients Dukes' B well-differentiated adenocarcinoma. Hematoxylin (purple) stains chromatin in the nucleus and eosin (pink orangish) gives color to the protein that resides in the cytoplasm of muscle cells. Tumor cells appear to thicken and be seen spreading muscular propia but did not penetrate serous layer. b. Well differentiated adenocarcinoma Dukes’ C tissue section invaded into muscular propia and involved lymph nodes

Fig. 2

Hierarchical clustering of gene expression datasets. Hierarchical clustering of 78 CRC samples in training and test sets which graphically displays the intensity of the gene expression for each gene. Samples were clustered based on the 19 significant genes. The color of each square boxes represents the ratio of gene expression. Red boxes indicates up regulated genes while green boxes represents down regulated genes. The column represent individual tissue samples while rows represent individual of genes

Fig. 3

Survival analysis. Kaplan–Meier survival analysis using six different microarray datasets (Training and test sets (Illumina-based), dataset from Denmark (Affymetrix), dataset from the USA (Affymetrix) and dataset from Australia (Affymetrix)). The 19-gene signature segregates patients into two risk groups (red, high risk; black, low risk). The p values correspond to the likelihood ratio test comparing the survival curves

Fig. 4

Validation of detected genes using qPCR. The normalized gene expression ratio for six genes including FRMD6, ELTD1, ITPRIP, MRPL52, TRIP13 and SLC38A9 which was determined using qPCR (p < 0.05). (*) represents the significant genes