Identification of Risk Molecular Subtype of Colon Cancer with Lymphovascular Invasion

Author:

Jin Qing1ORCID,Liang Binhua2,Chen Xiujie3,Liu Huiwen1

Affiliation:

1. Department of Histology and Embryology, College of Basic Medicine, Harbin Medical University, Harbin, China

2. Department of Biochemistry and Medical Genetics, University of Manitoba, Winnipeg, Canada

3. Department of Pharmacogenomics, College of Bioinformatics and Science Technology, Harbin Medical University, Harbin, China

Abstract

Background: Although surgical resection generally yields excellent outcomes, a number of patients with colon cancer still have relapse or metastasis after surgery. Adjuvant chemotherapy in tumor stage III has been demonstrated to eradicate micrometastasis and improve survival, whereas the benefits of adjuvant chemotherapy in tumor stage II remain controversial. The leading cause is the lack of understanding of the molecular basis of underlying metastatic mechanisms. Objective: This study aimed to identify molecular subtype(s) of colon cancer with a high risk of metastasis and provide potential biomarkers for prognostic prediction in tumor stage II. Method: Based on the assumption that colon cancer evolves because of the stepwise accumulation of a series of genetic mutations, we performed a systematic investigation on the molecular basis of colon cancer through applying restart random walk on the PPI network. To compare functional similarity of patients, we extracted mutation-propagating modules of each patient and calculated their enrichment score in 50 hallmark gene sets. According to functional similarity matrix, we classified colon cancers with positive lymphovascular invasion and the prognosis of molecular subtypes. We determined the molecular characteristics of subtypes by enrichment analysis of subtype-specific genetic mutations. Additionally, we identified potential biomarkers for predicting patients with a high risk of metastasis in stage II through differential analysis of miRNA expression profiles of subtypes. Then we used two independent data sets to construct a random forest classifier and performed 10-fold cross-validation of miRNA biomarkers. Results: Firstly, we identified two molecular subtypes of colon cancer with positive lymphovascular invasion as well as their associated biological characteristics: LVI1=Canonical subtype (110, 85%); LVI2=Metastatic subtype (20, 15%). Secondly, we identified 11 miRNA biomarkers for predicting patients with a high risk of metastasis in tumor stage II. Conclusion: Our findings put forward a detailed classification for colon cancer and provided risk biomarkers for stage II patients to determine whether to take adjuvant chemotherapy after surgery.

Funder

National Science Foundation of China

Publisher

Bentham Science Publishers Ltd.

Subject

Computational Mathematics,Genetics,Molecular Biology,Biochemistry

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