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



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.



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.



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.
UKM Medical Molecular Biology Institute, Universiti Kebangsaan Malaysia (UKM), Cheras, Kuala Lumpur, Malaysia.
Nurul Ainin
NA
Abdul Aziz
Department of Physiology, Faculty of Medicine, Universiti Kebangsaan Malaysia, Jalan Yaacob Latif, Bandar Tun Razak, Cheras, 56000, Kuala Lumpur, Malaysia. norfilza@ppukm.ukm.edu.my.
Norfilza M
NM
Mokhtar
UKM Medical Molecular Biology Institute, Universiti Kebangsaan Malaysia (UKM), Cheras, Kuala Lumpur, Malaysia.
Roslan
R
Harun
UKM Medical Molecular Biology Institute, Universiti Kebangsaan Malaysia (UKM), Cheras, Kuala Lumpur, Malaysia.
Md Manir Hossain
MM
Mollah
Histopathology Unit, Department of Pathology, Universiti Kebangsaan Malaysia Medical Centre, Kuala Lumpur, Malaysia.
Isa
I
Mohamed Rose
Department of Surgery, Universiti Kebangsaan Malaysia Medical Centre, Kuala Lumpur, Malaysia.
Ismail
I
Sagap
Department of Community Health, Faculty of Medicine, Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia.
Azmi
A
Mohd Tamil
UKM Medical Molecular Biology Institute, Universiti Kebangsaan Malaysia (UKM), Cheras, Kuala Lumpur, Malaysia.
Wan Zurinah
WZ
Wan Ngah
UKM Medical Molecular Biology Institute, Universiti Kebangsaan Malaysia (UKM), Cheras, Kuala Lumpur, Malaysia. rahmanj@ppukm.ukm.edu.my.
Rahman
R
Jamal
D015179:Colorectal Neoplasms / Q000175:diagnosis* / Q000235:genetics*; D019295:Computational Biology; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D020411:Oligonucleotide Array Sequence Analysis; D011379:Prognosis; D016019:Survival Analysis; D059467:Transcriptome
Colorectal cancer; Microarray analysis; Real-time PCR; Survivalm