No abstract

Objectives. Glioblastoma (GBM) is a malignant brain tumor which is the most common and aggressive type of central nervous system cancer, with high morbidity and mortality. Despite lots of systematic studies on the molecular mechanism of glioblastoma, the pathogenesis is still unclear, and effective therapies are relatively rare with surgical resection as the frequently therapeutic intervention. Identification of fundamental molecules and gene networks associated with initiation is critical in glioblastoma drug discovery. In this study, an approach for the prediction of potential drug was developed based on perturbation-induced gene expression signatures. Methods. We first collected RNA-seq data of 12 pairs of glioblastoma samples and adjacent normal samples from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were identified by DESeq2, and coexpression networks were analyzed with weighted gene correlation network analysis (WGCNA). Furthermore, key driver genes were detected based on the differentially expressed genes and potential chemotherapeutic drugs and targeted drugs were found by correlating the gene expression profiles with drug perturbation database. Finally, RNA-seq data of glioblastoma from The Cancer Genome Atlas (TCGA) dataset was collected as an independent validation dataset to verify our findings. Results. We identified 1771 significantly DEGs with 446 upregulated genes and 1325 downregulated genes. A total of 24 key drivers were found in the upregulated gene set, and 81 key drivers were found in the downregulated gene set. We screened the Crowd Extracted Expression of Differential Signatures (CREEDS) database to identify drug perturbations that could reverse the key factors of glioblastoma, and a total of 354 drugs were obtained with p value < 10-10. Finally, 7 drugs that could turn down the expression of upregulated factors and 3 drugs that could reverse the expression of downregulated key factors were selected as potential glioblastoma drugs. In addition, similar results were obtained through the analysis of TCGA as independent dataset. Conclusions. In this study, we provided a framework of workflow for potential therapeutic drug discovery and predicted 10 potential drugs for glioblastoma therapy.

A 48-year-old man presented with 3 days of mild horizontal diplopia in the left direction, followed by the onset of headache 17 days later. A physical examination revealed isolated left abducens nerve palsy. Head computed tomography (CT) and magnetic resonance imaging (MRI) scans revealed soft-tissue density neoplasms that occupied the sphenoidal sinus and further invaded to destroy the clivus. Immunohistochemical staining of neoplasms was performed from biopsies samples. The pathological diagnosis was extranodal natural killer (NK)/T-cell lymphoma (ENKL), nasal type, associated with Epstein-Barr virus (EBV). The patient subsequently exhibited secondary symptoms (fever, night sweats), enlarged lymph nodes, renal metastases, and hemophagocytic syndrome, with clinical diagnosis stage IV of ENKL. The patient has a poor prognosis. This report is unique in two aspects: the unilateral abducens nerve palsy as the initial and isolated symptom of ENKL, and the primary sphenoidal sinus ENKL.