A Multi-Omics Approach Revealed Common Dysregulated Pathways in Type One and Type Two Endometrial Cancers.
Valeria CapaciLorenzo MonastaMichelangelo AloisioEduardo SommellaEmanuela SalviatiPietro CampigliaManuela Giovanna BasilicataFeras KharratDanilo LicastroGiovanni Di LorenzoFederica RomanoGiuseppe RicciBlendi UraPublished in: International journal of molecular sciences (2023)
Endometrial cancer (EC) is the most frequent gynecologic cancer in postmenopausal women. Pathogenetic mechanisms that are related to the onset and progression of the disease are largely still unknown. A multi-omics strategy can help identify altered pathways that could be targeted for improving therapeutical approaches. In this study we used a multi-omics approach on four EC cell lines for the identification of common dysregulated pathways in type 1 and 2 ECs. We analyzed proteomics and metabolomics of AN3CA, HEC1A, KLE and ISHIKAWA cell lines by mass spectrometry. The bioinformatic analysis identified 22 common pathways that are in common with both types of EC. In addition, we identified five proteins and 13 metabolites common to both types of EC. Western blotting analysis on 10 patients with type 1 and type 2 EC and 10 endometria samples confirmed the altered abundance of NPEPPS. Our multi-omics analysis identified dysregulated proteins and metabolites involved in EC tumor growth. Further studies are needed to understand the role of these molecules in EC. Our data can shed light on common pathways to better understand the mechanisms involved in the development and growth of EC, especially for the development of new therapies.
Keyphrases
- endometrial cancer
- mass spectrometry
- postmenopausal women
- single cell
- bone mineral density
- ms ms
- high resolution
- machine learning
- liquid chromatography
- south africa
- electronic health record
- wastewater treatment
- microbial community
- big data
- cancer therapy
- case control
- deep learning
- artificial intelligence
- protein kinase
- drug induced
- capillary electrophoresis
- data analysis
- body composition
- simultaneous determination