299O - Genomic Signature identifying origins of EOC from Fallopian tube and ovary epithelium

Date 16 December 2016
Event ESMO Asia 2016 Congress
Session Gynaecological cancers
Topics Ovarian Cancer
Translational Research
Presenter Li-jun Di
Citation Annals of Oncology (2016) 27 (suppl_9): ix94-ix103. 10.1093/annonc/mdw585
Authors D. Hao1, J. Wang2, J. li2, L. Wang3, L. Di2
  • 1Faculty Of Health Sciences, University of Macau University of Macau University of Macau, Macau/MO
  • 2Faculty Of Health Sciences, University of Macau University of Macau University of Macau, NA - Macau/MO
  • 3Faculty Of Health Medicine, University of Macau, 111111 - Macau/MO

Abstract

Background

The molecular mechanism of epithelial ovarian cancer (EOC) is poorly understood. As a result, the treatment and overall survival of EOC have improved little for decades. Although large-scale genomic analyses have identified the recurrently altered pathways in EOC, the most essential knowledge about EOC, including the tissue origin, the classification of clinically associated subtypes are still largely unknown.

Methods

Data retrival from public accessible database covering clinical patient tumor samples. The data include the gene expression analyzed by microarray and RNA-seq, the patient survival information, the disease prognostic information etc. The analysis of the clinical data is using standard bioinfomatic tools. The experiments were performed following standard procedures.

Results

A comprehensive list of datasets covering multiple levels of genomic data have been collected to identify the tissue origin for different histological types of EOC, and confirmed that both ovary epithelium and fallopian tube accounts for the majority of EOCs. Based on the collected datasets, we also applied a meta-analytic strategy and have defined two new clinically associated subtypes of high-grade serous ovarian cancer which, coincidentally, almost equivalent to the EOC classification by tissue origin defined by genomic data. Based on these analysis, we were able to predict some target genes which show significant correlation to the risk of cancer patient and by taking advantage of phamacogenomics data, we also identified the drugs that targeting the pathways related to these genes. Preliminary experiments in ovarian cancer cell lines demonstrated the therapeutic effect of these drugs.

Conclusions

To our knowledge, this is for the first time that clinical genomic data is used to analyze EOC in a perspective of establishing new genomic signatures with clinical utility and identifying novel targets to improve the treatment of EOC. This research is funded by FDCT/025/2014/A1, FDCT/088/2014/A2, MYRG2015-00037-FHS, MYRG2015-00167-FHS, MYRG2016‐00251‐FHS.

Clinical trial indentification

NA

Legal entity responsible for the study

University of Macau

Funding

University of Macau, and Foundation for development of Science and technology in Macau

Disclosure

All authors have declared no conflicts of interest.