Potential serum metabolites and long‐chain noncoding RNA biomarkers for endometrial cancer tissue. Issue 2 (12th December 2022)

• Record Type: Journal Article
• Authors: Hao, Chenjun; Lin, Shaodan; Liu, Ping; Liang, Weiguo; Li, Zhi; Li, Yanqiu
• Is Part Of: Journal of obstetrics and gynaecology research. Volume 49:Issue 2(2023)
• Page Start: 725
• Page End: 743
• Publication Date: 2022-12-12
• Subjects: endometrial carcinoma -- LC–MS -- lncRNA -- metabolic markers; Gynecology -- Periodicals; Obstetrics -- Periodicals; 618.1005
• DOI: 10.1111/jog.15494
• Languages: English
• ISSNs: 1341-8076

Abstract

Abstract: Background: Endometrial carcinoma (EC) is one of the most common tumors in the female reproductive system. There are nearly 200 000 new cases every year. It is the third most common gynecological malignant tumor leading to female death. The incidence rate is closely related to lifestyle, and the incidence rate varies in different regions. The incidence rate of EC is ranking the first in the female reproductive system cancer just second only to breast, lung, and colorectal cancer in North America and Europe and the incidence rate of EC is only second, followed by breast cancer and cervical cancer in China. Purpose: The potential metabolic markers of endometrial cancer were screened by liquid chromatograph mass spectrometer (LC‐MS), and the tissues of patients with hysteromyoma and endometrial cancer were sequenced to explore the relationship between the disease and change in the content of long‐chain noncoding RNA (lncRNA). Methods: Serum and tissue samples were collected from patients with endometrial dysplasia, endometrial cancer stage I, and endometrial cancer stage III. The metabolites in all serum samples were extracted, and the metabolites in all samples were detected by LC–MS/MS technology. The Pareto‐scaling method was used for normalization, and the MetaboAnalyst 4.0 software was used for different analyses. The T test between groups showed that p ≤ 0.05 was regarded as the metabolite with a difference. Further, the function of differential metabolites was determined by metabolite function enrichment and co‐expression analysis. Meanwhile, the differentially expressed lncRNA was detected by Illumina second‐generation high‐throughput sequencing technology, and the expression was analyzed by DEGseq software. Different lncRNA were screened according to p < 0.05. LncRNA with significant differences were screened by p < 0.01, q < 0.001, fold change ≥2, and false discovery rate (FDR) ≤0.001. Results: Through synthesis of T test, cluster heatmap, and ROC curve analysis, five biomarkers with potential diagnostic ability were obtained, including 2, 3‐Pyridinedicarboxylic acid (area under the curve (AUC) = 0.69), Hematommic acid, ethyl ester (AUC = 0.69), Maltitol (AUC = 0.69), 13(S)‐HODE (AUC = 0.88), and D‐Mannitol (AUC = 0.69) had potential diagnostic ability between EC phase I versus EC phase III. At the same time, lncRNA sequencing results showed that when endometrial atypical hyperplasia continued to change, including LINC00511, PVT1, and IQCH‐AS1 (downregulated), and only changed significantly in the endometrial dysplasia group, including MALAT1, CARMN (downregulated) and LINC00648, BISPR, LINC01534, and LINC00930 (upregulated). Moreover, both differential metabolites and differential lncRNA were annotated to the lipid metabolism pathway, suggesting that this pathway played an important role in the occurrence and development of endometrial carcinoma. Conclusions: It can combine the results of metabolomics and lncRNA sequencing to assist in the early diagnosis of endometrial precancerous lesions and endometrial cancer patients, to enhance the sensitivity and specificity of diagnosis, which has a certain clinical application prospect.