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

NA Abdul Aziz, NM Mokhtar, R Harun… - BMC medical …, 2016 - Springer
NA Abdul Aziz, NM Mokhtar, R Harun, MMH Mollah, I Mohamed Rose, I Sagap…
BMC medical genomics, 2016Springer
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 …
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.
Springer