TY - GEN
T1 - Discovery of Stomach Adenocarcinoma Biomarkers by Consensus Scoring of Random Sampling and Machine Learning Modeling
AU - Chen, Ji
AU - Hao, Yang
AU - Wang, Tianjun
AU - Huang, Daiyun
AU - Liu, Xin
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - Stomach adenocarcinoma (STAD) is a subtype of gastric cancer with high incidence and mortality. Lack of early detection results in the poor prognosis of this cancer, leading to low survival rate of patients. In this study, machine learning methods, specifically support vector machine (SVM) based recursive feature elimination (SVM-RFE), were applied to discover the potential biomarkers of STAD with the data form the Cancer Genome Atlas (TCGA). After the optimal parameter set was determined, random sampling was conducted to minimize the limitation caused by small sample size (64 paired tumor and adjacent non-tumor samples). As a result, five genes (COL10A1, CST1, ESM1, HOXC11 and HOXC9) were identified to be essential to the predictive model built by SVM-RFE. In addition, other three genes GAD1, HOXA11 and PRKCG are of less importance but still could be potential biomarkers of STAD.
AB - Stomach adenocarcinoma (STAD) is a subtype of gastric cancer with high incidence and mortality. Lack of early detection results in the poor prognosis of this cancer, leading to low survival rate of patients. In this study, machine learning methods, specifically support vector machine (SVM) based recursive feature elimination (SVM-RFE), were applied to discover the potential biomarkers of STAD with the data form the Cancer Genome Atlas (TCGA). After the optimal parameter set was determined, random sampling was conducted to minimize the limitation caused by small sample size (64 paired tumor and adjacent non-tumor samples). As a result, five genes (COL10A1, CST1, ESM1, HOXC11 and HOXC9) were identified to be essential to the predictive model built by SVM-RFE. In addition, other three genes GAD1, HOXA11 and PRKCG are of less importance but still could be potential biomarkers of STAD.
KW - RFE
KW - SVM
KW - biomarker
KW - gastric cancer
KW - machine learning
KW - recursive feature elimination
KW - stomach adenocarcinoma
KW - support vector machine
UR - http://www.scopus.com/inward/record.url?scp=85134307780&partnerID=8YFLogxK
U2 - 10.1109/ICBCB55259.2022.9802469
DO - 10.1109/ICBCB55259.2022.9802469
M3 - Conference Proceeding
AN - SCOPUS:85134307780
T3 - 2022 10th International Conference on Bioinformatics and Computational Biology, ICBCB 2022
SP - 112
EP - 115
BT - 2022 10th International Conference on Bioinformatics and Computational Biology, ICBCB 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 10th International Conference on Bioinformatics and Computational Biology, ICBCB 2022
Y2 - 13 May 2022 through 15 May 2022
ER -
