Dan Yang

SRSF9 Forms Phase-Separated Condensates to Promote Ovarian Cancer Progression by Inducing RNA Alternative Splicing That Is Inhibited by m6A Modification

Abstract Deregulation of RNA alternative splicing and modification can play an important role in tumor initiation and progression. Elucidation of the interplay between alternative splicing and modifications of RNA could provide important insights into cancer biology. In this study, we showed that serine/arginine-rich splicing factor 9 (SRSF9) recognized non-N6-methyladenosine (m6A)–modified NUMB mRNA and induced an oncogenic isoform switch in ovarian cancer. NUMB mRNA m6A modification antagonized SRSF9-mediated alternative splicing. Notably, SRSF9 formed phase-separated condensates within the nucleus, which was indispensable for its splicing function as well as its tumor-promoting effect in ovarian cancer. Furthermore, SRSF9 was aberrantly upregulated in ovarian cancer, correlating with poor patient prognosis. Loss of SRSF9 or antisense oligonucleotide–mediated isoform switch of NUMB mRNA inhibited ovarian cancer growth in vitro and in vivo. In conclusion, this study reveals that SRSF9 condensation promotes ovarian cancer progression through modulation of alternative splicing, in competition with m6A modification. Significance: Phase separation increases activity of the splicing factor SRSF9 to support progression of ovarian cancer by generating an oncogenic isoform of NUMB mRNA competitively with m6A modification, which provides promising therapeutic targets.

Development and validation of a prognostic model for endometrial carcinoma using causal genes identified by Mendelian randomization

Endometrial carcinoma (EC) remains an ambiguous pathogenesis. This study aimed to investigate the potential of causal genes in predicting EC prognosis. The prognostic biomarkers of EC were identified using univariate Cox regression analyses based on data from The Cancer Genome Atlas Uterine Corpus Endometrial Carcinoma (TCGA-UCEC). Mendelian randomization (MR) analyses were conducted to infer causal relationships, utilizing expression quantitative trait loci (eQTLs) derived from prognostic genes as exposures, and a dataset from European populations with EC as outcomes. Single nucleotide polymorphisms (SNPs) that significantly influenced gene expression (eQTLs) were selected as instrumental variables. The inverse variance weighted (IVW) method was employed as the primary analytical approach. Sensitivity analyses were performed to ensure robustness of the findings. Causal genes with potential prognostic significance were further evaluated using multivariate Cox regression analysis, Kaplan–Meier (KM) overall survival curves, and receiver operating characteristic (ROC) curve analysis. Additionally, results from gene ontology (GO) and gene set enrichment analysis (GSEA) of differentially expressed genes (DEGs), along with immune infiltration analyses in the high- and low-risk groups, are presented. 18 genes exhibiting a negative correlation with EC demonstrated a protective effect, whereas 9 genes identified as risk factors for EC exerted an adverse effect on the disease. A prognostic model was developed consisting of 8 genes selected from 27 genes. According to the KM overall survival curve data, ECs classified with high-risk ratings exhibited significantly poor prognoses ( P  < .0001). The ROC curve analysis indicated that the area under the curve (AUC) for this risk model in predicting the 1-, 3-, and 5-year EC survival rates were 0.704, 0.735, and 0.766, respectively. Furthermore, GO and GSEA results of DEGs in both the high- and low-risk groups revealed strong associations with pathways related to cell motility and immune response, among others. In addition, an analysis of immune cell infiltration demonstrated significant differences between the high- and low-risk groups. A prognostic model for EC using causal genes identified using MR has good sensitivity and specificity. These findings provide new insights into ECs pathogenesis and suggest promising strategies for the diagnosis and treatment of ECs.

Adnexal masses: Diagnostic performance of contrast‐enhanced ultrasound using the simple rules from the International Ovarian Tumor Analysis group

AbstractObjectiveTo evaluate the role of the Simple Rules (SR) from the International Ovarian Tumor Analysis group in contrast‐enhanced ultrasound (CEUS) of for the differential diagnosis of benign and malignant adnexal tumors.MethodsA total of 180 patients with suspected malignant adnexal masses admitted to Lanzhou University Second Hospital were included, all of whom received conventional ultrasound (US) and CEUS examination before surgery. All masses were assessed using SR in US and SR in CEUS. To compare the diagnostic performance, the sensitivity, specificity, negative and positive predictive values, Youden index, and area under the curves values of SR in US and SR in CEUS were obtained.ResultsSensitivity, negative predictive values, Youden index, and area under the curves were better for SR in CEUS than SR in US. The specificity and negative predictive value of SR in CEUS were lower than that of SR in US. Compared with SR in US, SR in CEUS significantly reduced the number of uncertain masses (21, 36.7% vs. 66, 11.7%).ConclusionWe concluded that SR in CEUS performed well in the diagnosis of malignant adnexal masses. SR in CEUS is a supplement to SR in US.