Gene Set-Based Functionome Analysis of Pathogenesis in Epithelial Ovarian Serous Carcinoma and the Molecular Features in Different FIGO Stages.
Serous carcinoma (SC) is the most common subtype of epithelial ovarian carcinoma and is divided into four stages by the Federation of Gynecologists and Obstetrics (FIGO) staging system. Currently, the molecular functions and biological processes of SC at different FIGO stages have not been quantified. Here, we conducted a whole-genome integrative analysis to investigate the functions of SC at different stages. The function, as defined by the GO term or canonical pathway gene set, was quantified by measuring the changes in the gene expressional order between cancerous and normal control states. The quantified function, i.e., the gene set regularity (GSR) index, was utilized to investigate the pathogenesis and functional regulation of SC at different FIGO stages. We showed that the informativeness of the GSR indices was sufficient for accurate pattern recognition and classification for machine learning. The function regularity presented by the GSR indices showed stepwise deterioration during SC progression from FIGO stage I to stage IV. The pathogenesis of SC was centered on cell cycle deregulation and accompanied with multiple functional aberrations as well as their interactions.
Institute of Oral Biology, National Yang-Ming University, Taipei 112, Taiwan. cm_chang@vghtpe.gov.tw.|School of Medicine, National Yang-Ming University, Taipei 112, Taiwan. cm_chang@vghtpe.gov.tw.|Department of Obstetrics and Gynecology, Taipei Veterans General Hospital, Taipei 112, Taiwan. cm_chang@vghtpe.gov.tw.
Chia-Ming
CM
Chang
School of Medicine, National Yang-Ming University, Taipei 112, Taiwan. cmjuang@gmail.com.|Department of Obstetrics and Gynecology, Taipei Veterans General Hospital, Taipei 112, Taiwan. cmjuang@gmail.com.|Institute of Clinical Medicine, School of Medicine, National Yang-Ming University, Taipei 112, Taiwan. cmjuang@gmail.com.
Chi-Mu
CM
Chuang
School of Medicine, National Yang-Ming University, Taipei 112, Taiwan. monglien@gmail.com.|Department of Medical Research, Taipei Veterans General Hospital, Taipei 112, Taiwan. monglien@gmail.com.
Mong-Lien
ML
Wang
School of Medicine, National Yang-Ming University, Taipei 112, Taiwan. mjyang@vghtpe.gov.tw.|Department of Obstetrics and Gynecology, Taipei Veterans General Hospital, Taipei 112, Taiwan. mjyang@vghtpe.gov.tw.
Ming-Jie
MJ
Yang
Department of Obstetrics and Gynecology, Tri-Service General Hospital, National Defense Medical Center, Taipei 112, Taiwan. sundoor66@gmail.com.
Cheng-Chang
CC
Chang
School of Medicine, National Yang-Ming University, Taipei 112, Taiwan. msyen@vghtpe.gov.tw.|Department of Obstetrics and Gynecology, Taipei Veterans General Hospital, Taipei 112, Taiwan. msyen@vghtpe.gov.tw.
Ming-Shyen
MS
Yen
Institute of Oral Biology, National Yang-Ming University, Taipei 112, Taiwan. shchiou@vghtpe.gov.tw.|Department of Obstetrics and Gynecology, Taipei Veterans General Hospital, Taipei 112, Taiwan. shchiou@vghtpe.gov.tw.|Department of Medical Research, Taipei Veterans General Hospital, Taipei 112, Taiwan. shchiou@vghtpe.gov.tw.|Department &amp; Institute of Pharmacology, National Yang-Ming University, Taipei 112, Taiwan. shchiou@vghtpe.gov.tw.
Shih-Hwa
SH
Chiou
D000077216:Carcinoma, Ovarian Epithelial; D002471:Cell Transformation, Neoplastic / Q000235:genetics / Q000473:pathology; D016000:Cluster Analysis; D019295:Computational Biology / Q000379:methods; D018284:Cystadenocarcinoma, Serous / Q000175:diagnosis* / Q000235:genetics*; D030561:Databases, Nucleic Acid; D005260:Female; D020869:Gene Expression Profiling; D015972:Gene Expression Regulation, Neoplastic; D063990:Gene Ontology; D053263:Gene Regulatory Networks; D006801:Humans; D000069550:Machine Learning; D009367:Neoplasm Staging; D009375:Neoplasms, Glandular and Epithelial / Q000175:diagnosis* / Q000235:genetics*; D010051:Ovarian Neoplasms / Q000175:diagnosis* / Q000235:genetics*; D059467:Transcriptome; D057188:Workflow
epithelial serous ovarian cancer; function; gene expression microarray; gene set; integrative analysis; machine learning