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). 
Gene Expression Ominus
Then, we assessed the association of NNMT expression with clinical and molecular parameters using CSIOVDB database and GSE28739 dataset.  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). 
CSIOVDB database
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).  Next, we evaluate the association of NNMT expression with the prognosis of ovarian cancer patients in both GSE9891 dataset and TCGA dataset.  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). 
TCGA dataset
Next, we evaluate the association of NNMT expression with the prognosis of ovarian cancer patients in both GSE9891 dataset and TCGA dataset.  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). 
GSE9891 dataset
Finally, GSE140082 dataset was used to explore the association of NNMT expression with bevacizumab response.



GSE140082 dataset