Journal
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
Volume 24, Issue 18, Pages -Publisher
MDPI
DOI: 10.3390/ijms241814010
Keywords
epithelial ovarian cancer; endoplasmic reticulum stress; risk classifier; TRPM2
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In this study, a risk classifier based on 10 differentially expressed genes related to endoplasmic reticulum stress was established to evaluate the prognosis of ovarian cancer patients and assist in medical decision-making. The prediction ability of the classifier was tested and confirmed, and TRPM2 was identified as a potential therapeutic target for ovarian cancer cells.
Epithelial ovarian cancer (EOC) is the most lethal gynecological malignant tumor. Endoplasmic reticulum (ER) stress plays an important role in the malignant behaviors of several tumors. In this study, we established a risk classifier based on 10 differentially expressed genes related to ER stress to evaluate the prognosis of patients and help to develop novel medical decision-making for EOC cases. A total of 378 EOC cases with transcriptome data from the TCGA-OV public dataset were included. Cox regression analysis was used to establish a risk classifier based on 10 ER stress-related genes (ERGs). Then, through a variety of statistical methods, including survival analysis and receiver operating characteristic (ROC) methods, the prediction ability of the proposed classifier was tested and verified. Similar results were confirmed in the GEO cohort. In the immunoassay, the different subgroups showed different penetration levels of immune cells. Finally, we conducted loss-of-function experiments to silence TRPM2 in the human EOC cell line. We created a 10-ERG risk classifier that displays a powerful capability of survival evaluation for EOC cases, and TRPM2 could be a potential therapeutic target of ovarian cancer cells.
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