Preprint Article Version 1 This version is not peer-reviewed

Molecular Classification of Colorectal Cancer Using Gene Expression Profile of Tumor Samples

Version 1 : Received: 1 April 2018 / Approved: 2 April 2018 / Online: 2 April 2018 (09:55:26 CEST)

How to cite: Rashid, M.; Vishwakarma, R.K.; Deeb, A.; Hussein, M.A.; Aziz, M.A. Molecular Classification of Colorectal Cancer Using Gene Expression Profile of Tumor Samples. Preprints 2018, 2018040016 (doi: 10.20944/preprints201804.0016.v1). Rashid, M.; Vishwakarma, R.K.; Deeb, A.; Hussein, M.A.; Aziz, M.A. Molecular Classification of Colorectal Cancer Using Gene Expression Profile of Tumor Samples. Preprints 2018, 2018040016 (doi: 10.20944/preprints201804.0016.v1).

Abstract

Molecular classifications of colorectal cancer (CRC) are benefitting cancer research by providing insights into subtype-specific disease prognosis and better therapeutic intervention. So far different conventional DNA markers such as microsatellite instability (MSI), CpG island methylator phenotype (CIMP), chromosomal instability (CIN), and BRAF and KRAS mutations have been used to classify CRC patients but have not shown promising prognostic values. Here, for the first time, we show classification of CRC tumors from Saudi Arabian patients based on gene expression profile (GEP). An existing method of CRC subtyping has been applied to the GEP of tumors from Saudi CRC patients. Survival analysis was carried out on predicted CRC subtypes. In-silico functional analyses were conducted on the gene signature used for subtype prediction. The predicted subtypes showed distinct but statistically insignificant overall survival distribution (log-rank test, p = 0.069). Comparison of predicted subtypes in Saudi CRC patients with that of the French one showed significant dissimilarity in the two populations (Chi-square test, p = 0.0091). Functional analyses of the gene signature used for subtyping suggest their association with “cancer” and “gastrointestinal diseases”. Most of the signature genes were found differentially expressed in CRC tumors compared to adjacent normal tissues. Such a classification framework might help improve the treatment of colorectal cancer patients.

Subject Areas

colorectal cancer; gene expression; molecular classification; molecular subtyping

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