RESUMO
Circumventing chemoresistance is crucial for effectively treating cancer including glioblastoma, a lethal brain cancer. The gap junction protein connexin 43 (Cx43) renders glioblastoma resistant to chemotherapy; however, targeting Cx43 is difficult because mechanisms underlying Cx43-mediated chemoresistance remain elusive. Here we report that Cx43, but not other connexins, is highly expressed in a subpopulation of glioblastoma and Cx43 mRNA levels strongly correlate with poor prognosis and chemoresistance in this population, making Cx43 the prime therapeutic target among all connexins. Depleting Cx43 or treating cells with αCT1-a Cx43 peptide inhibitor that sensitizes glioblastoma to the chemotherapy temozolomide-inactivates phosphatidylinositol-3 kinase (PI3K), whereas overexpression of Cx43 activates this signaling. Moreover, αCT1-induced chemo-sensitization is counteracted by a PI3K active mutant. Further research reveals that αCT1 inactivates PI3K without blocking the release of PI3K-activating molecules from membrane channels and that Cx43 selectively binds to the PI3K catalytic subunit ß (PIK3CB, also called PI3Kß or p110ß), suggesting that Cx43 activates PIK3CB/p110ß independent of its channel functions. To explore the therapeutic potential of simultaneously targeting Cx43 and PIK3CB/p110ß, αCT1 is combined with TGX-221 or GSK2636771, two PIK3CB/p110ß-selective inhibitors. These two different treatments synergistically inactivate PI3K and sensitize glioblastoma cells to temozolomide in vitro and in vivo. Our study has revealed novel mechanistic insights into Cx43/PI3K-mediated temozolomide resistance in glioblastoma and demonstrated that targeting Cx43 and PIK3CB/p110ß together is an effective therapeutic approach for overcoming chemoresistance.
RESUMO
Current cancer biomarkers present variability in their predictive power and demonstrate limited clinical efficacy, possibly due to the lack of functional relevance of biomarker genes to cancer progression. To address this challenge, a biomarker discovery pipeline was developed to integrate gene expression profiles from The Cancer Genome Atlas and essential survival gene datasets from The Cancer Dependency Map, the latter of which catalogs genes driving cancer progression. By applying this pipeline to lung adenocarcinoma, lung squamous cell carcinoma, and glioblastoma, genes highly associated with cancer progression were identified and designated as progression gene signatures (PGSs). Analysis of area under the receiver operating characteristics curve revealed that PGSs predicted patient survival more accurately than previously identified cancer biomarkers. Moreover, PGSs stratified patients with high risk for progressive disease indicated by worse prognostic outcomes, increased frequency of cancer progression, and poor responses to chemotherapy. The robust performance of these PGSs were recapitulated in four independent microarray datasets from Gene Expression Omnibus and were further verified in six freshly dissected tumors from glioblastoma patients. Our results demonstrate the power of an integrated approach to cancer biomarker discovery and the possibility of implementing PGSs into clinical biomarker tests.
Assuntos
Biomarcadores Tumorais/análise , Perfilação da Expressão Gênica/métodos , Adenocarcinoma de Pulmão/metabolismo , Adenocarcinoma de Pulmão/patologia , Carcinoma Pulmonar de Células não Pequenas/metabolismo , Carcinoma Pulmonar de Células não Pequenas/patologia , Carcinoma de Células Escamosas/metabolismo , Carcinoma de Células Escamosas/patologia , Progressão da Doença , Feminino , Regulação Neoplásica da Expressão Gênica , Glioblastoma/metabolismo , Glioblastoma/patologia , Humanos , Neoplasias Pulmonares/metabolismo , Neoplasias Pulmonares/patologia , Masculino , Prognóstico , TranscriptomaRESUMO
Glioblastoma, the most common malignant tumor in the brain, lacks effective treatments and is currently incurable. To identify novel drug targets for this deadly cancer, the publicly available results of RNA interference screens from the Project Achilles database were analyzed. Ten candidate genes were identified as survival genes in 15 glioblastoma cell lines. RAN, member RAS oncogene family (RAN) was expressed in glioblastoma at the highest level among all candidates based upon cDNA microarray data. However, Kaplan-Meier survival analysis did not show any correlation between RAN mRNA levels and patient survival. Because RAN is a small GTPase that regulates nuclear transport controlled by karyopherin subunit beta 1 (KPNB1), RAN was further analyzed together with KPNB1. Indeed, GBM patients with high levels of RAN also had more KPNB1 and levels of KPNB1 alone did not relate to patient prognosis. Through a Cox multivariate analysis, GBM patients with high levels of RAN and KPNB1 showed significantly shorter life expectancy when temozolomide and promoter methylation of O6-methylguanine DNA methyltransferase were used as covariates. These results indicate that RAN and KPNB1 together are associated with drug resistance and GBM poor prognosis. Furthermore, the functional blockade of RAN and KPNB1 by importazole remarkably suppressed cell viability and activated apoptosis in GBM cells expressing high levels of RAN, while having a limited effect on astrocytes and GBM cells with undetectable RAN. Together, our results demonstrate that RAN activity is important for GBM survival and the functional blockade of RAN/KPNB1 is an appealing therapeutic approach.