What are the prospects for combination therapy for glioblastoma?

The Proliferation of Glioblastoma Is Contributed to Kinesin Family Member 18A and Medical Data Analysis of GBM

Background: Glioblastoma (GBM) is widely known as a classical kind of malignant tumor originating in the brain with high morbidity and mortality. Targeted therapy has shown great promise in treating glioblastoma, but more promising targets, including effective therapeutic targets, remain to be identified. 18A (KIF18A) is a microtubule-based motor protein that is dysregulated and involved in the progression of multiple human cancers. However, the possible effects of KIF18A on GBM progression are still unclear.

Methods: We performed DEG analysis, medical data analysis, and network analysis to identify critical genes affecting glioma progression. We also performed immunohistochemical analysis of the KIF18A levels in 94 patients with glioblastoma and the associated surrounding tissues. Patients were divided into two groups according to the high and low expression. Using a clinical analysis, we showed the potential associations between KIF18A expression and clinical characteristics of 94 GBM patients. We then investigated the effects of KIF18A on GBM cell proliferation by colony establishment, MTT, and immune blogging. The possible effect of KIF18A on GBM tumor growth was determined in mice.

Results: We identified KIF18A as a potential gene affecting GBM progression. We further demonstrated that GBM tissues expressed KIF18A much higher, and its presentation was associated with recurrence in glioblastoma patients. We believe KIF18A promotes GBM cell proliferation.

Conclusion: We demonstrated that KIF18A could be a promising target in treating GBM.

Nucleobindin-2 Promotes the Growth and Invasion of Glioblastoma

Background: Glioblastoma is one of the most malignant tumors in the brain with high mortality. In recent years, immunotherapy and targeted therapy show great prospects in the treatments for glioblastoma, whereas more effective therapeutic targets are still urgently needed to be developed. Nucleobindin-2 (NUCB2) is the precursor protein of nesfatin-1, which have a variety of metabolic functions, such as food intake and temperature regulation. In recent years, the potential link between NUCB2 and the development of multiple cancer was gradually revealed; however, the effects of NUCB2 on the progression of glioblastoma are still unclear. Methods: Immunohistochemical assays were performed to explore the NUCB2 expression levels in 94 samples of glioblastoma and corresponding nontumor tissues; patients were divided into NUCB2 high expression group and low expression group. Clinical analysis related to the clinical features, the potential link between NUCB2 expression levels, and clinical features were analyzed; the effects of NUCB2 on cell proliferation and invasion of glioblastoma were detected through colony formation and MTT assay, and transwell assay respectively. The possible effects of NUCB2 on tumor growth and metastasis were measured in mice. Results: In this study, we demonstrated that NUCB2 over-expression was correlated with the high degree of recurrence of patients with glioblastoma. Further, we also revealed that NUCB2 promoted cell proliferation and invasion of glioblastoma in vitro and promoted the growth and metastasis of glioblastoma in mice. Conclusion: This study provided evidence that NUCB2 might be a novel therapeutic target of glioblastoma.

Drug and disease signature integration identifies synergistic combinations in glioblastoma

Glioblastoma (GBM) is the most common primary adult brain tumor. Despite extensive efforts, the median survival for GBM patients is approximately 14 months. GBM therapy could benefit greatly from patient-specific targeted therapies that maximize treatment efficacy. Here we report a platform termed SynergySeq to identify drug combinations for the treatment of GBM by integrating information from The Cancer Genome Atlas (TCGA) and the Library of Integrated Network-Based Cellular Signatures (LINCS). We identify differentially expressed genes in GBM samples and devise a consensus gene expression signature for each compound using LINCS L1000 transcriptional profiling data. The SynergySeq platform computes disease discordance and drug concordance to identify combinations of FDA-approved drugs that induce a synergistic response in GBM. Collectively, our studies demonstrate that combining disease-specific gene expression signatures with LINCS small molecule perturbagen-response signatures can identify preclinical combinations for GBM, which can potentially be tested in humans.

Inherent or acquired resistance to treatment of glioblastoma (GBM) is nearly universal. Here, the authors introduce a platform to identify synergistic drug combinations for patient-specific treatment of GBM based on gene expression signatures and small molecule perturbation-response profiles.