Publication Details

Title :

Molecular classification of colorectal cancer using the gene expression profile of tumor samples


Experimental Biology and Medicine (Maywood)

Impact Factor:



Rashid M1,2,3, Vishwakarma RK1,2,3, Deeb AM2,3,4, Hussein MA1,2,3, Aziz MA2,3,5.


1 Department of Biostatistics and Bioinformatics, King Abdullah International Medical Research Center, Riyadh 11426, Saudi Arabia.

2 King Saud bin Abdulaziz University for Health Sciences, Riyadh 11426, Saudi Arabia.

3 Ministry of the National Guard-Health Affairs, Riyadh 11426, Saudi Arabia.

4 King Abdullah International Medical Research Center, Research Office, Riyadh 11426, Saudi Arabia.

5 King Abdullah International Medical Research Center, Colorectal Cancer Research Program, Riyadh 11426, Saudi Arabia.

Year of Publication:





Molecular classifications of colorectal cancer are benefitting cancer research by providing insights into subtype-specific disease prognosis and improved therapeutic interventions. Different conventional DNA markers, such as microsatellite instability, CpG island methylator phenotype, chromosomal instability, and BRAF and KRAS mutations, have been used to classify colorectal cancer patients but have not yet shown promising prognostic values. Here, for the first time, to the best of our knowledge, we show a classification of colorectal cancer tumors from Saudi Arabian patients based on the gene expression profile. An existing method of colorectal cancer subtyping has been applied to the gene expression profile of tumors from Saudi colorectal cancer patients. A survival analysis was done on the predicted colorectal cancer subtypes. In silico functional analyses were conducted on the gene signature used for the subtype prediction. The predicted subtypes showed a distinct but statistically insignificant overall survival distribution (log-rank test, P = 0.069). A comparison of the predicted subtypes in Saudi colorectal cancer patients with that of French patients showed significant dissimilarity in the two populations (Chi-square test, P = 0.0091). Functional analyses of the gene signatures used for subtyping suggest their association with “cancer” and “gastrointestinal diseases.” Most of the signature genes were found differentially expressed in colorectal cancer tumors compared to adjacent normal tissues. This classification framework might facilitate the treatment of colorectal cancer patients.