Applications of Multi-omics Approaches for Exploring the Molecular Mechanism of Ovarian Carcinogenesis

Abstract

Ovarian cancer ranks as the fifth most common cause of cancer-related death in females. The molecular mechanisms of ovarian carcinogenesis need to be explored in order to identify effective clinical therapies for ovarian cancer. Recently, multi-omics approaches have been applied to determine the mechanisms of ovarian oncogenesis at genomics (DNA), transcriptomics (RNA), proteomics (proteins), and metabolomics (metabolites) levels. Multi-omics approaches can identify some diagnostic and prognostic biomarkers and therapeutic targets for ovarian cancer, and these molecular signatures are beneficial for clarifying the development and progression of ovarian cancer. Moreover, the discovery of molecular signatures and targeted therapy strategies could noticeably improve the prognosis of ovarian cancer patients.

Identification and Validation of Autophagy-Related Genes in Primary Ovarian Insufficiency by Gene Expression Profile and Bioinformatic Analysis

“…It is essential and necessary to take stock of the field, frame the progress, outline the controversies, and evaluate future directions in elucidating the genetics of POI. Multidisciplinary approaches could help to explore molecular signatures [ 34 ], which accounts for the progression of disease and contribute to searching for specific treatment [ 35 ]. Identification of effective and novel therapy strategies based on multiomics methods can make it possible to have a better management and improve the prognosis of patients [ 36 ].…”

Applications of Proteomics in Ovarian Cancer: Dawn of a New Era

“…However, tumour resistance to platinum-based chemotherapy presents an emerging challenge to current regimes [ 118 ]. Several groups have identified ways in which resistance occurs, many of which are related to key oncogenic signaling pathways [ 119 ].…”

Artificial Intelligence and Medicine

“…Integration of multidisciplinary research domains, such as medical imaging, image fusion, natural language processing, etc., which can follow the full course of disease diagnosis and treatment, is an essential development direction of AIM. In addition, the application of multi-omics data fusion approaches for illness diagnosis and therapy, such as genomics, proteomics, and radiomics, has been a research hotspot in recent years and merits in-depth study (50,51).…”