TY - CHAP
T1 - Network biomarker construction for molecular investigation and diagnosis of lung cancer via microarray data
AU - Wang, Yu Chao
AU - Chen, Bor Sen
N1 - Publisher Copyright:
© 2014 Springer Science+Business Media Dordrecht. All rights reserved.
PY - 2014/3/1
Y1 - 2014/3/1
N2 - Lung cancerLung cancer is the leading cause of cancer deaths worldwide. Many studies have investigated the carcinogenic process and identified the biomarkers for signature classification. However, those biomarkers are mainly identified based only on analysis of genome-wide expression profiles, that is, the identification method cannot elucidate how the different genes in the biomarker gene set are related to each other. Therefore, from the systems perspective, we developed a network biomarkerNetwork biomarker construction scheme, which integrated microarray gene expression profiles and protein-protein interaction information, for molecular investigation and diagnosis of lung cancer. The network biomarkerNetwork biomarker consisted of two protein association networksProtein association network constructed for cancer samples and non-cancer samples. Based on the network biomarker, a total of 40 significant proteins were identified with carcinogenesis relevance values (CRVs) to gain insights into the lung carcinogenesis mechanism. In addition, the network biomarker was also acted as the diagnostic tool, demonstrated to be effective to diagnose the smokers with lung cancerLung cancer. Taken together, the network biomarker not only successfully sheds light on the mechanisms in lung carcinogenic process but also provides potential therapeutic targets to combat against cancer.
AB - Lung cancerLung cancer is the leading cause of cancer deaths worldwide. Many studies have investigated the carcinogenic process and identified the biomarkers for signature classification. However, those biomarkers are mainly identified based only on analysis of genome-wide expression profiles, that is, the identification method cannot elucidate how the different genes in the biomarker gene set are related to each other. Therefore, from the systems perspective, we developed a network biomarkerNetwork biomarker construction scheme, which integrated microarray gene expression profiles and protein-protein interaction information, for molecular investigation and diagnosis of lung cancer. The network biomarkerNetwork biomarker consisted of two protein association networksProtein association network constructed for cancer samples and non-cancer samples. Based on the network biomarker, a total of 40 significant proteins were identified with carcinogenesis relevance values (CRVs) to gain insights into the lung carcinogenesis mechanism. In addition, the network biomarker was also acted as the diagnostic tool, demonstrated to be effective to diagnose the smokers with lung cancerLung cancer. Taken together, the network biomarker not only successfully sheds light on the mechanisms in lung carcinogenic process but also provides potential therapeutic targets to combat against cancer.
KW - Akaike's information criterion
KW - Analysis of variance (ANOVA)
KW - Lung cancer
KW - Microarray data
KW - Network biomarker
KW - Protein association network
KW - Protein-protein interaction (PPI)
UR - http://www.scopus.com/inward/record.url?scp=84930921031&partnerID=8YFLogxK
U2 - 10.1007/978-94-017-9047-5_1
DO - 10.1007/978-94-017-9047-5_1
M3 - Chapter
AN - SCOPUS:84930921031
SN - 9401790469
SN - 9789401790468
SP - 3
EP - 29
BT - A Systems Theoretic Approach to Systems and Synthetic Biology II
PB - Springer Netherlands
ER -