In terms of gynaecological malignancies, Ovarian Cancer (OC) has the worst prognosis and the greatest fatality rate. The majority of OC patients are frequently diagnosed at advanced stages due to the lack of distinct early symptoms. Thus, the demand for improved OC biomarkers for use in clinical practise and research is critical. Sequencing and biotechnological techniques have advanced at an increasingly rapid rate during the past ten years. In order to examine tissue and liquid generated samples from OC patients, a variety of omics technologies, including as genomic or transcriptome sequencings and proteomic or metabolomics mass spectra, have been frequently used. Our understanding of the condition has improved as a result of the integration of multiomics data, which also revealed important OC biomarkers.

In this review, we emphasise prospective uses of multi-omics for discovering novel biomarkers and enhancing clinical evaluations, as well as recent developments and perspectives in the use of multi-omics technology in ovarian cancer research.

Proteins and their post-translational modifications (PTMs) are being examined to gain a better understanding of disease because they are the key functional components of the majority of biological activities. Proteomics based on mass spectrometry (MS) is an objective, large-scale approach that allows for the characterisation of practically full proteomes. Additionally, numerous quantitative proteomics techniques have been created to isolate and measure proteins, including tandem mass tagging (TMT), isotope-coded affinity tags (ICAT), isobaric tags for relative and absolute quantitation (iTRAQ), stable isotope labelling with amino acids in cell culture (SILAC), and label-free approaches.

New methods, such as proximity ligation and extension assays, which allow for large-scale targeted protein detection utilising a matched pair of DNA-conjugated antibodies, offer an effective alternative to MS for the identification of low-abundant proteins from small clinical sample sets.