Authors: Meng Pan; Jie Zhang
Addresses: Department of Optoelectronic Engineering, Jinan University, Guangzhou 510632, China ' Department of Physics, Jinan University, Guangzhou 510632, China
Abstract: Many researches have addressed patient classification using prognostic factors or gene expression profiles (GEPs). This study tried to identify whether a prognostic factor was genetic by using GEPs. If significant GEP difference was observed between two statuses of a factor, the factor might be genetic. If the GEP difference was largely less significant than the survival difference, the survival difference might not be due to the genes; then, the factor might be non-genetic or partly non-genetic. A practice was made in this study using public dataset GSE40967, which contains GEP data of 566 colon cancer patients, messages of tumour-node-metastasis (TNM) staging, etc. Prognostic factors T, N, M, and TNM were observed being non-genetic or partly non-genetic, which should be a complement for future gene expression classifiers.
Keywords: gene expression profiles; genetic; non-genetic; prognostic factor; differentially expressed genes; test statistic; colon cancer; classification; survival; p-value; reasoning.
International Journal of Computational Science and Engineering, 2019 Vol.19 No.4, pp.546 - 553
Received: 16 Jan 2016
Accepted: 27 Apr 2016
Published online: 27 Aug 2019 *