RNA modifications are reversible, dynamically regulated, and involved in a variety of diseases such as cancers. Given the lack of efficient and reliable biomarkers for early diagnosis of ovarian cancer (OV), this study was designed to explore the role of RNA modification genes (RMGs) in the diagnosis of OV. Herein, 132 RMGs were retrieved in PubMed, 638 OV and 18 normal ovary samples were retrieved in The Cancer Genome Atlas (TCGA), and GSE18520 cohorts were collected for differential analysis. Finally, PUS7 (Pseudouridine Synthase 7) as differentially expressed RMGs (DEGs-RMGs) was identified as a diagnostic biomarker candidate and evaluated for its specificity and sensitivity using Receiver Operating Characteristic (ROC) analysis in TCGA and GEO data. The protein expression, mutation, protein interaction networks, correlated genes, related pathways, biological processes, cell components, and molecular functions of PUS7 were analyzed as well. The upregulation of PUS7 protein in OV was confirmed by the staining images in HPA and tissue arrays. Collectively, the findings of the present study point towards the potential of PUS7 as a diagnostic marker and therapeutic target for ovarian cancer.

Glioblastoma multiforme (GBM) is the most common and aggressive form of brain cancer. Prognosis evaluation is of great significance in guiding individualized treatment and monitoring of GBM. By integrating different prognostic variables, nomograms simplify the statistical risk prediction model into numerical estimates for death or recurrence, and are hence widely applied in prognosis prediction. In the past two decades, the application of high-throughput profiling technology and the establishment of TCGA database and other public data deposits have provided opportunities to identify cancer-related molecules and prognostic biomarkers. As a result, both molecular features and clinical characteristics of cancer have been reported to be the key factors in nomogram model construction. This article comprehensively reviewed 35 studies of GBM nomograms, analyzed the present situation of GBM nomograms, and discussed the role and significance of nomograms in personalized risk assessment and clinical treatment decision-making. To facilitate the application of nomograms in the prognostic prediction of GBM patients, a website has been established for the online access of nomograms based on the studies of this review, which is called Consensus Nomogram Spectrum for Glioblastoma (CNSgbm) and is accessible through https://bioinfo.henu.edu.cn/nom/NomList.jsp.