L.X. Chen1, J. Qian2,3, Z. Wang4, X.L. Cong5 and J. Ma1

Author information

1School of Pharmaceutical Sciences, Jilin University, Changchun, Jilin, China;
2Bio-teq center of Fudan University, Fudan University, Shanghai, China;
3School of Life Sciences, Fudan University, Shanghai, China;
4Shanghai East Hospital, Shanghai Key Laboratory of Signaling and Disease Research, School of Life Sciences and Technology, Tongji University, Shanghai, China;
5Tissue Bank, China-Japan Union Hospital of Jilin University, Changchun, Jilin, China

Abstract

Ovarian cancer (OC) has been regarded as the most malignant gynecological neoplasm and leading mortality-causing cancer in females worldwide. It has a high fatality rate and is difficult to be detected early. The classification of OC has drawn the attention of numerous researchers, while the difference between layer classification is still unclear. This study explored the common genes between proteomics and transcriptomics and the potential mechanism related to layer classification. Our results provide several potential biomarkers in the early diagnosis of ovarian cancer. We identified 962 differentially expressed mRNA (DEGs) and 544 differentially expressed proteins (DEPs). The comprehensive analysis of the two omics found that the proteins in the MAPK pathway showed corresponding changes in ovarian cancer progression. Furthermore, CD14 and MECOM were up regulated in OC and higher in the advanced OC than in the early stage. In conclusion, our research provided 2 potential early prognostic biomarkers for OC.

Keywords:

ovarian cancer, transcriptomics, proteomics, CD14, MECOM

Publication type

Journal Article

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