Hormone and Metabolic Research

Characteristics of Ovarian Cancer Immune Cell Invasion and Bioinformatics to Predict the Effect of Immunotherapy

AbstractRecent studies have confirmed that tumor immune cell infiltration (ICI) is associated with sensitivity of ovarian cancer (OC) immunotherapy and disease progression of OC patients. However, studies related to immune infiltration in OC, has not been elucidated. Two algorithms are used to analyze the OC data in the TCGA and GEO databases. After combining the two data sets, the immune cell content of the sample was estimated by Cell-type Identification By Estimate Relative Subsets of RNA Transcripts (CIBERSORT method). An unsupervised consistent clustering algorithm was used to analyze ICI subtypes and their differentially expressed genes (DEGs). Two subgroups and three ICI gene clusters were identified by unsupervised consensus clustering algorithm. The ICI score was obtained by analyzing the gene characteristics through principal component analysis (PCA). The ICI score ranged from –15.8132 to 18.7211, which was associated with the prognosis of OC patients with immunotherapy. The Toll-like receptor pathway, B-cell receptor pathway, antigen processing and presentation pathway, NK-cell-mediated cytotoxicity pathway, and arginine-proline metabolism pathway were activated in the high ICI score group, suggesting that immune cells in the high ICI score group were activated, thus leading to a better prognosis in this group of patients. Patients with G3–G4 in the high ICI rating group were more sensitive to immunotherapy and had a better prognosis in patients with high tumor mutation burden (TMB). This study suggests that ICI scores can be used as a feasible auxiliary indicator for predicting the prognosis of patients with OC.

Downregulation of lncRNA ASMTL-AS1 in Epithelial Ovarian Cancer Correlates with Worse Prognosis and Cancer Progression

AbstractGiven the characters of “Silent killer”, epithelial ovarian cancer (EOC) usually suffered late diagnosis and poor prognosis. Therefore, this study aimed to explore the prognostic significance of ASMTL-AS1 in EOC and investigated the effect of lncRNA ASMTL-AS1 dysregulation on tumor cellular function. ASMTL-AS1 expression was analyzed in 133 EOC tissues and five kinds of cell lines by RT-qPCR. The expression of ASMTL-AS1 was tested for correlation with clinical data using the chi-square test and clinical follow-up using Kaplan-Meier method with log-rank test. Further, the prognostic parameters in predicting EOC overall survival were assessed by using multivariate Cox proportional hazards analysis. In vitro assays, including MTT assay and transwell assay, were conducted using EOC cell lines with overexpression of ASMTL-AS1. In tumorous tissues and cell lines, ASMTL-AS1 was lowly expressed compared with normal ones. This downregulation was associated with the advanced FIGO stage, positive ascites cytology, and lymph node. In particular, low levels of ASMTL-AS1 were revealed to have a high prognostic impact on EOC. ASMTL-AS1 overexpression strongly decreased cell proliferation, migration, and invasion in vitro partly by moderating miR-1228-3p. This study demonstrates a significant role for lowly expressed ASMTL-AS1 in EOC allowing for the prediction of prognosis for EOC. Considering that ASMTL-AS1 is strongly involved in cell growth and invasion, ASMTL-AS1 may be a promising marker for EOC prognosis and therapy