Multi-Omic Profiling of Multi-Biosamples Reveals the Role of Amino Acid and Nucleotide Metabolism in Endometrial Cancer - Yi, Runqiu; Xie, Liying; Wang, Xiaoqing; Shen, Chengpin; Chen, Xiaojun; Qiao, Liang (Frontiers in Oncology, 2022)
Background Endometrial cancer (EC) is one of the most common gynecological cancers. The traditional diagnosis of EC relies on histopathology, which, however, is invasive and may arouse tumor spread. There have been many studies aiming at finding metabolomic biomarkers of EC as an effort to improve the early diagnosis of the cancer in a non- or minimally-invasive way, which can also provide valuable information for understanding the disease. However, most of these studies only analyze single type of samples by metabolomics, and cannot provide a comprehensive view on the altered metabolism in EC patients. Our study tries to gain a pathway-based view of multi-types of samples for understanding the metabolomic disorder in EC by combining metabolomics and proteomics. Methods Forty-four EC patients and forty-three controls were recruited for the research. We collected endometrial tissue, urine and intrauterine brushings samples. Untargeted metabolomics and untargeted proteomics were both performed on the endometrial tissue samples, while only untargeted metabolomics was performed on the urine and intrauterine brushings samples. Results By integrating the differential metabolites and proteins between EC patients and controls detected in the endometrial tissue samples, we identified several EC related significant pathways, such as amino acid metabolism and nucleotide metabolism. The significance of these pathways and the potential of metabolite biomarkers-based diagnosis were then further verified by using urine and intrauterine brushings samples. It was found that the regulation of metabolites involved in the significant pathways showed similar trends in the intrauterine brushings and the endometrial tissue samples, while opposite trends in the urine and the endometrial tissue samples. Conclusions With multi-omics characterization of multi-biosamples, the metabolomic changes related to EC are illustrated in a pathway-based way. The network of altered metabolites and related proteins provides a comprehensive view of altered metabolism in the endometrial tissue samples. The verification of these critical pathways by using urine and intrauterine brushings samples provides evidence for the possible non- or minimally-invasive biopsy for EC diagnosis in the future.