Jun Li1,2, Huiran Yue1,2, Hailin Yu1,2, Xin Lu1,2, Xiaohong Xue3,4. 1. Department of Gynecology, Obstetrics and Gynecology Hospital, Fudan University, No.419, Fangxie Road, Shanghai, 200011, China. 2. Shanghai Key Laboratory of Female Reproductive Endocrine Related Diseases, Shanghai, 200011, China. 3. Department of Gynecology, Obstetrics and Gynecology Hospital, Fudan University, No.419, Fangxie Road, Shanghai, 200011, China. xiaohongxuevip@126.com. 4. Shanghai Key Laboratory of Female Reproductive Endocrine Related Diseases, Shanghai, 200011, China. xiaohongxuevip@126.com.
Abstract
BACKGROUND: The role of nicotinamide N-methyltransferase (NNMT) in ovarian cancer is still elusive. Our aim is to explore the expression of NNMT in ovarian cancer and to assess its association with patient prognosis and treatment response. METHODS: We first analyzed the differential expression of NNMT among fallopian tube epithelium, primary ovarian cancers, metastatic ovarian cancers, and recurrent ovarian cancers using Gene Expression Ominus (GEO) database (GSE10971, GSE30587, GSE44104 and TCGA datasets). Then, we assessed the association of NNMT expression with clinical and molecular parameters using CSIOVDB database and GSE28739 dataset. Next, we evaluate the association of NNMT expression with the prognosis of ovarian cancer patients in both GSE9891 dataset and TCGA dataset. Finally, GSE140082 dataset was used to explore the association of NNMT expression with bevacizumab response. RESULTS: NNMT expression was significantly elevated in lymphovascular space invasion (LVSI)-positive ovarian cancers compared with that in LVSI-negative ovarian cancers (TCGA dataset, P < 0.05), Moreover, increased expression of NNMT was associated with increased tumor stage, grade, and mesenchymal molecular subtype (CSIOVDB database). Survival analysis indicated that increased expression of NNMT was associated with a reduced OS in both GSE9891 dataset (HR: 2.28, 95%CI: 1.51-3.43, Log-rank P < 0.001) and TCGA dataset (HR: 1.55, 95%CI: 1.02-2.36, Log-rank P = 0.039). Multivariate analysis further confirmed the negative impact of NNMT expression on OS in ovarian cancer patients in those two datasets. Furthermore, the NNMT-related nomogram showed that NNMT shared a larger contribution to OS, compared with debulking status. More interestingly, bevacizumab conferred significant improvements in OS for patients with low NNMT expression (HR: 0.56, 95%CI: 0.31-0.99, Log-rank P = 0.049). In contrast, patients with high NNMT expression didn't benefit from bevacizumab treatment significantly (HR: 0.85, 95%CI: 0.48-1.49, Log-rank P = 0.561). NNMT expression was positively correlated with the expression of genes, LDHA and PGAM1, involved in Warburg effect. CONCLUSIONS: In conclusion, NNMT expression is associated with the aggressive behavior of ovarian cancer, correlates with a poor prognosis, and is predictive of sensitivity to bevacizumab treatment.
BACKGROUND: The role of nicotinamide N-methyltransferase (NNMT) in ovarian cancer is still elusive. Our aim is to explore the expression of NNMT in ovarian cancer and to assess its association with patient prognosis and treatment response. METHODS: We first analyzed the differential expression of NNMT among fallopian tube epithelium, primary ovarian cancers, metastatic ovarian cancers, and recurrent ovarian cancers using Gene Expression Ominus (GEO) database (GSE10971, GSE30587, GSE44104 and TCGA datasets). Then, we assessed the association of NNMT expression with clinical and molecular parameters using CSIOVDB database and GSE28739 dataset. Next, we evaluate the association of NNMT expression with the prognosis of ovarian cancerpatients in both GSE9891 dataset and TCGA dataset. Finally, GSE140082 dataset was used to explore the association of NNMT expression with bevacizumab response. RESULTS:NNMT expression was significantly elevated in lymphovascular space invasion (LVSI)-positive ovarian cancers compared with that in LVSI-negative ovarian cancers (TCGA dataset, P < 0.05), Moreover, increased expression of NNMT was associated with increased tumor stage, grade, and mesenchymal molecular subtype (CSIOVDB database). Survival analysis indicated that increased expression of NNMT was associated with a reduced OS in both GSE9891 dataset (HR: 2.28, 95%CI: 1.51-3.43, Log-rank P < 0.001) and TCGA dataset (HR: 1.55, 95%CI: 1.02-2.36, Log-rank P = 0.039). Multivariate analysis further confirmed the negative impact of NNMT expression on OS in ovarian cancerpatients in those two datasets. Furthermore, the NNMT-related nomogram showed that NNMT shared a larger contribution to OS, compared with debulking status. More interestingly, bevacizumab conferred significant improvements in OS for patients with low NNMT expression (HR: 0.56, 95%CI: 0.31-0.99, Log-rank P = 0.049). In contrast, patients with high NNMT expression didn't benefit from bevacizumab treatment significantly (HR: 0.85, 95%CI: 0.48-1.49, Log-rank P = 0.561). NNMT expression was positively correlated with the expression of genes, LDHA and PGAM1, involved in Warburg effect. CONCLUSIONS: In conclusion, NNMT expression is associated with the aggressive behavior of ovarian cancer, correlates with a poor prognosis, and is predictive of sensitivity to bevacizumab treatment.
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