Identification of novel synergistic targets for rational drug combinations with PI3 kinase inhibitors using siRNA synthetic lethality screening against GBM

Crucial Roles of miR-625 in Human Cancer

Genetic and epigenetic characteristics are core factors of cancer. MicroRNAs (miRNAs) are small non-coding RNAs which regulate gene expression at the post-transcriptional level via binding to corresponding mRNAs. Recently, increasing evidence has proven that miRNAs regulate the occurrence and development of human cancer. Here, we mainly review the abnormal expression of miR-625 in a variety of cancers. In summarizing the role and potential molecular mechanisms of miR-625 in various tumors in detail, we reveal that miR-625 is involved in a variety of biological processes, such as cell proliferation, invasion, migration, apoptosis, cell cycle regulation, and drug resistance. In addition, we discuss the lncRNA-miRNA-mRNA and circRNA-miRNA-mRNA networks and briefly explain the specific mechanisms of competing endogenous RNAs. In conclusion, we reveal the potential value of miR-625 in cancer diagnosis, treatment, and prognosis and hope to provide new ideas for the clinical application of miR-625.

TMEM2 Combined with IDH and 1p19q in Refining Molecular Subtypes for Predicting Survival of Patients with Glioma

Gliomas are common intracranial tumors with high morbidity and mortality in adults. Transmembrane protein 2 (TMEM2) is involved in the malignant behavior of solid tumors. TMEM2 regulates cell adhesion and metastasis as well as intercellular communication by degrading nonprotein components of the extracellular matrix. This study aimed to evaluate the relationship between TMEM2 expression levels and glioma subtypes or patient prognosis. Our findings revealed that TMEM2 expression was abnormally upregulated in high-grade glioma. Moreover, combining TMEM2, the status of isocitrate dehydrogenase (IDH) and 1p19q, we subdivided molecular subtypes with significant differences in survival. Patients in the MT-codel-low subgroup had better prognosis than those in the WT-no-codel-high subgroup, who fared the worst. Additionally, correlation analysis of TMEM2 and immune cell infiltration indicated an altered tumor microenvironment (TME) and cell redistribution in the TMEM2 high-expression subtype. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed that focal adhesion and PI3K-Akt signaling pathways were enriched in the TMEM2-expressing group. In conclusion, aberrant TMEM2 expression can be used as an independent prognostic marker for refining glioma molecular subtyping and accurate prognosis. These findings will improve rational decision making to provide individualized therapy for patients with glioma.

Super-enhancer-associated TMEM44-AS1 aggravated glioma progression by forming a positive feedback loop with Myc

Background

Long non-coding RNAs (lncRNAs) have been considered as one type of gene expression regulator for cancer development, but it is not clear how these are regulated. This study aimed to identify a specific lncRNA that promotes glioma progression.

Methods

RNA sequencing (RNA-seq) and quantitative real-time PCR were performed to screen differentially expressed genes. CCK-8, transwell migration, invasion assays, and a mouse xenograft model were performed to determine the functions of TMEM44-AS1. Co-IP, ChIP, Dual-luciferase reporter assays, RNA pulldown, and RNA immunoprecipitation assays were performed to study the molecular mechanism of TMEM44-AS1 and the downstream target.

Results

We identified a novel lncRNA TMEM44-AS1, which was aberrantly expressed in glioma tissues, and that increased TMEM44-AS1 expression was correlated with malignant progression and poor survival for patients with glioma. Expression of TMEM44-AS1 increased the proliferation, colony formation, migration, and invasion of glioma cells. Knockdown of TMEM44-AS1 in glioma cells reduced cell proliferation, colony formation, migration and invasion, and tumor growth in a nude mouse xenograft model. Mechanistically, TMEM44-AS1 is directly bound to the SerpinB3, and sequentially activated Myc and EGR1/IL-6 signaling; Myc transcriptionally induced TMEM44-AS1 and directly bound to the promoter and super-enhancer of TMEM44-AS1, thus forming a positive feedback loop with TMEM44-AS. Further studies demonstrated that Myc interacts with MED1 regulates the super-enhancer of TMEM44-AS1. More importantly, a novel small-molecule Myc inhibitor, Myci975, alleviated TMEM44-AS1-promoted the growth of glioma cells.

Conclusions

Our study implicates a crucial role of the TMEM44-AS1-Myc axis in glioma progression and provides a possible anti-glioma therapeutic agent.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13046-021-02129-9.

Small interfering RNA (siRNA) to target genes and molecular pathways in glioblastoma therapy: Current status with an emphasis on delivery systems

Glioblastoma multiforme (GBM) is one of the worst brain tumors arising from glial cells, causing many deaths annually. Surgery, chemotherapy, radiotherapy and immunotherapy are used for GBM treatment. However, GBM is still an incurable disease, and new approaches are required for its successful treatment. Because mutations and amplifications occurring in several genes are responsible for the progression and aggressive behavior of GBM cells, genetic approaches are of great importance in its treatment. Small interfering RNA (siRNA) is a new emerging tool to silence the genes responsible for disease progression, particularly cancer. SiRNA can be used for GBM treatment by down-regulating genes such as VEGF, STAT3, ELTD1 or EGFR. Furthermore, the use of siRNA can promote the chemosensitivity of GBM cells. However, the efficiency of siRNA in GBM is limited via its degradation by enzymes, and its off-targeting effects. SiRNA-loaded carriers, especially nanovehicles that are ligand-functionalized by CXCR4 or angiopep-2, can be used for the protection and targeted delivery of siRNA. Nanostructures can provide a platform for co-delivery of siRNA plus anti-tumor drugs as another benefit. The prepared nanovehicles should be stable and biocompatible in order to be tested in human studies.

Prediction and analysis of hub genes between glioblastoma and low-grade glioma using bioinformatics analysis

ABSTRACT

Gliomas are an intractable tumor in the central nervous system. The present study aimed to identify the differentially expressed genes (DEGs) between glioblastoma multiforme (GBM) and low-grade gliomas (LGG) in order to investigate the mechanisms of different grades of gliomas. The Cancer Genome Atlas (TCGA) database was used to identify DEGs between GBM and LGG, and 2641 genes have been found differentially expressed. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were used to determine the related functions and pathways of DEGs. Protein-protein interaction (PPI) network extracted a total of 444 nodes and 1953 interactions, and identified the top 6 hub genes in gliomas. The microarray data of the datasets GSE52009 and GSE4412, which were obtained from Gene Expression Omnibus (GEO) database, were used to externally validate DEGs expression levels. Gene Expression Profiling Interactive Analysis (GEPIA) database which was based on TCGA was used to explore the survival of hub genes in LGG and GBM. Additionally, the Oncomine database and Chinese Glioma Genome Atlas (CGGA) database were used to validate the mRNA expression level and prognostic value of hub genes. Gene Set Enrichment Analysis (GSEA) identified further hub genes-related pathways. In summary, through biological information and survival analysis, 6 hub genes may be new biomarkers for diagnosis and for guiding the choice of treatment strategies for different grades of gliomas.

Bioinformatic gene analysis for potential therapeutic targets of Huntington's disease in pre-symptomatic and symptomatic stage

Background

Huntington’s disease (HD) is a neurodegenerative disorder characterized by psychiatric symptoms, serious motor and cognitive deficits. Certain pathological changes can already be observed in pre-symptomatic HD (pre-HD) patients; however, the underlying molecular pathogenesis is still uncertain and no effective treatments are available until now. Here, we reanalyzed HD-related differentially expressed genes from the GEO database between symptomatic HD patients, pre-HD individuals, and healthy controls using bioinformatics analysis, hoping to get more insight in the pathogenesis of both pre-HD and HD, and shed a light in the potential therapeutic targets of the disease.

Methods

Pre-HD and symptomatic HD differentially expressed genes (DEGs) were screened by bioinformatics analysis Gene Expression Omnibus (GEO) dataset GSE1751. A protein–protein interaction (PPI) network was used to select hub genes. Subsequently, Gene Ontology (GO) enrichment analysis of DEGs and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis of hub genes were applied. Dataset GSE24250 was downloaded to verify our hub genes by the Kaplan–Meier method using Graphpad Prism 5.0. Finally, target miRNAs of intersected hub genes involved in pre-HD and symptomatic HD were predicted.

Results

A total of 37 and 985 DEGs were identified in pre-HD and symptomatic HD, respectively. The hub genes, SIRT1, SUZ12, and PSMC6, may be implicated in pre-HD, and the hub genes, FIS1, SIRT1, CCNH, SUZ12, and 10 others, may be implicated in symptomatic HD. The intersected hub genes, SIRT1 and SUZ12, and their predicted target miRNAs, in particular miR-22-3p and miR-19b, may be significantly associated with pre-HD.

Conclusion

The PSMC6, SIRT1, and SUZ12 genes and their related ubiquitin-mediated proteolysis, transcriptional dysregulation, and histone metabolism are significantly associated with pre-HD. FIS1, CCNH, and their related mitochondrial disruption and transcriptional dysregulation processes are related to symptomatic HD, which might shed a light on the elucidation of potential therapeutic targets in HD.

Combined elevation of TRIB2 and MAP3K1 indicates poor prognosis and chemoresistance to temozolomide in glioblastoma

Introduction

Glioblastoma (GBM) is the most lethal primary malignant brain tumor in adults with poor survival due to acquired therapeutic resistance and rapid recurrence. Currently, the standard clinical strategy for glioma includes maximum surgical resection, radiotherapy, and temozolomide (TMZ) chemotherapy; however, the median survival of patients with GBM remains poor despite these comprehensive therapies. Therefore, the identification of new prognostic biomarkers is urgently needed to evaluate the malignancy and long‐term outcome of glioma.

Aims

To further investigate prognostic biomarkers and potential therapeutic targets for GBM.

Results

In this study, we identified tribbles pseudokinase 2 (TRIB2) as one of the genes that is most correlated with pathological classification, radioresistance, and TMZ resistance in glioma. Additionally, the expression of mitogen‐activated protein kinase kinase kinase 1 (MAP3K1) showed a strong correlation with TRIB2. Moreover, a combined increase in TRIB2 and MAP3K1 was observed in GBM and indicated a poor prognosis of patients with glioma. Finally, enriched TRIB2 expression and MAP3K1 expression were shown to be associated with resistance to TMZ and radiotherapy.

Conclusion

Combined elevation of TRIB2 and MAP3K1 could be novel prognostic biomarkers and potential therapeutic targets to evaluate the malignancy and long‐term outcomes of GBM.

Identification of differentially expressed key genes between glioblastoma and low-grade glioma by bioinformatics analysis

Gliomas are a very diverse group of brain tumors that are most commonly primary tumor and difficult to cure in central nervous system. It’s necessary to distinguish low-grade tumors from high-grade tumors by understanding the molecular basis of different grades of glioma, which is an important step in defining new biomarkers and therapeutic strategies. We have chosen the gene expression profile GSE52009 from gene expression omnibus (GEO) database to detect important differential genes. GSE52009 contains 120 samples, including 60 WHO II samples and 24 WHO IV samples that were selected in our analysis. We used the GEO2R tool to pick out differently expressed genes (DEGs) between low-grade glioma and high-grade glioma, and then we used the database for annotation, visualization and integrated discovery to perform gene ontology analysis and Kyoto encyclopedia of gene and genome pathway analysis. Furthermore, we used the Cytoscape search tool for the retrieval of interacting genes with molecular complex detection plug-in applied to achieve the visualization of protein–protein interaction (PPI). We selected 15 hub genes with higher degrees of connectivity, including tissue inhibitors metalloproteinases-1 and serum amyloid A1; additionally, we used GSE53733 containing 70 glioblastoma samples to conduct Gene Set Enrichment Analysis. In conclusion, our bioinformatics analysis showed that DEGs and hub genes may be defined as new biomarkers for diagnosis and for guiding the therapeutic strategies of glioblastoma.

Current Challenges and Opportunities in Treating Glioblastoma

Glioblastoma multiforme (GBM), the most common and aggressive primary brain tumor, has a high mortality rate despite extensive efforts to develop new treatments. GBM exhibits both intra- and intertumor heterogeneity, lending to resistance and eventual tumor recurrence. Large-scale genomic and proteomic analysis of GBM tumors has uncovered potential drug targets. Effective and “druggable” targets must be validated to embark on a robust medicinal chemistry campaign culminating in the discovery of clinical candidates. Here, we review recent developments in GBM drug discovery and delivery. To identify GBM drug targets, we performed extensive bioinformatics analysis using data from The Cancer Genome Atlas project. We discovered 20 genes, BOC, CLEC4GP1, ELOVL6, EREG, ESR2, FDCSP, FURIN, FUT8-AS1, GZMB, IRX3, LITAF, NDEL1, NKX3-1, PODNL1, PTPRN, QSOX1, SEMA4F, TH, VEGFC, and C20orf166AS1 that are overexpressed in a subpopulation of GBM patients and correlate with poor survival outcomes. Importantly, nine of these genes exhibit higher expression in GBM versus low-grade glioma and may be involved in disease progression. In this review, we discuss these proteins in the context of GBM disease progression. We also conducted computational multi-parameter optimization to assess the blood-brain barrier (BBB) permeability of small molecules in clinical trials for GBM treatment. Drug delivery in the context of GBM is particularly challenging because the BBB hinders small molecule transport. Therefore, we discuss novel drug delivery methods, including nanoparticles and prodrugs. Given the aggressive nature of GBM and the complexity of targeting the central nervous system, effective treatment options are a major unmet medical need. Identification and validation of biomarkers and drug targets associated with GBM disease progression present an exciting opportunity to improve treatment of this devastating disease.

Targeting dual specificity protein kinase TTK attenuates tumorigenesis of glioblastoma

Accumulating evidence has proved that glioma stem-like cells (GSCs) are responsible for tumorigenesis, treatment resistance, and subsequent tumor recurrence in glioblastoma (GBM). In this study, we identified dual specificity protein kinase TTK (TTK) as the most up-regulated and differentially expressed kinase encoding genes in GSCs. Functionally, TTK was essential for in vitro clonogenicity and in vivo tumor propagation in GSCs. Clinically, TTK expression was highly enriched in GBM, moreover, was inversely correlated with a poor prognosis in GBM patients. Mechanistically, mitochondrial fission regulator 2 (MTFR2) was identified as one of the most correlated genes to TTK and transcriptionally regulated TTK expression via activation of TTK promoter. Collectively, MTFR2-dependent regulation of TTK plays a key role in maintaining GSCs in GBM and is a potential novel druggable target for GBM.

The Identification of Key Genes and Pathways in Glioma by Bioinformatics Analysis

Glioma is the most common malignant tumor in the central nervous system. This study aims to explore the potential mechanism and identify gene signatures of glioma. The glioma gene expression profile GSE4290 was analyzed for differentially expressed genes (DEGs). Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were applied for the enriched pathways. A protein-protein interaction (PPI) network was constructed to find the hub genes. Survival analysis was conducted to screen and validate critical genes. In this study, 775 downregulated DEGs were identified. GO analysis demonstrated that the DEGs were enriched in cellular protein modification, regulation of cell communication, and regulation of signaling. KEGG analysis indicated that the DEGs were enriched in the MAPK signaling pathway, endocytosis, oxytocin signaling, and calcium signaling. PPI network and module analysis found 12 hub genes, which were enriched in synaptic vesicle cycling rheumatoid arthritis and collecting duct acid secretion. The four key genes CDK17, GNA13, PHF21A, and MTHFD2 were identified in both generation (GSE4412) and validation (GSE4271) dataset, respectively. Regression analysis showed that CDK13, PHF21A, and MTHFD2 were independent predictors. The results suggested that CDK17, GNA13, PHF21A, and MTHFD2 might play important roles and potentially be valuable in the prognosis and treatment of glioma.

Network modeling of kinase inhibitor polypharmacology reveals pathways targeted in chemical screens

Small molecule screens are widely used to prioritize pharmaceutical development. However, determining the pathways targeted by these molecules is challenging, since the compounds are often promiscuous. We present a network strategy that takes into account the polypharmacology of small molecules in order to generate hypotheses for their broader mode of action. We report a screen for kinase inhibitors that increase the efficacy of gemcitabine, the first-line chemotherapy for pancreatic cancer. Eight kinase inhibitors emerge that are known to affect 201 kinases, of which only three kinases have been previously identified as modifiers of gemcitabine toxicity. In this work, we use the SAMNet algorithm to identify pathways linking these kinases and genetic modifiers of gemcitabine toxicity with transcriptional and epigenetic changes induced by gemcitabine that we measure using DNaseI-seq and RNA-seq. SAMNet uses a constrained optimization algorithm to connect genes from these complementary datasets through a small set of protein-protein and protein-DNA interactions. The resulting network recapitulates known pathways including DNA repair, cell proliferation and the epithelial-to-mesenchymal transition. We use the network to predict genes with important roles in the gemcitabine response, including six that have already been shown to modify gemcitabine efficacy in pancreatic cancer and ten novel candidates. Our work reveals the important role of polypharmacology in the activity of these chemosensitizing agents.

MicroRNA-625 inhibits the proliferation and increases the chemosensitivity of glioma by directly targeting AKT2

Glioma is a malignant tumor for which new therapies are needed. Growing evidence has demonstrated that microRNAs (miRNAs) have a major effect on glioma development. Here, we aimed to characterize a novel anti-cancer miRNA, miR-625, by investigating its expression, function, and mechanism of action in glioma progression. The expression of miR-625 and its target mRNA in human glioma tissues and cell lines was assessed by real-time PCR, western blotting, and immunohistochemistry. Functional significance was assessed by examining cell cycle progression, proliferation, apoptosis, and chemosensitivity to temozolomide in vitro, and by examining growth of subcutaneous glioblastoma in a mouse model in vivo. We found that miR-625 expression was significantly lower in human glioma samples and cell lines than in normal brain tissue and human astrocytes. Furthermore, miR-625 overexpression not only suppressed glioma cell proliferation in culture and in the tumor xenograft model but also induced cell cycle arrest and apoptosis. AKT2 was identified as a direct miR-625 target in glioma cell lines, and AKT2 overexpression reversed the suppressive effects of miR-625 in the cell lines and the tumor xenograft model. Finally, we found that the sensitivity of glioma cells to temozolomide was increased by miR-625 overexpression, and this was reversed by concomitant AKT2 expression. In conclusion, our findings suggest that the miR-625-AKT2 axis could be a new prognostic marker and diagnostic target for gliomas.

Glioma: experimental models and reality

In theory, in vitro and in vivo models for human gliomas have great potential to not only enhance our understanding of glioma biology, but also to facilitate the development of novel treatment strategies for these tumors. For reliable prediction and validation of the effects of different therapeutic modalities, however, glioma models need to comply with specific and more strict demands than other models of cancer, and these demands are directly related to the combination of genetic aberrations and the specific brain micro-environment gliomas grow in. This review starts with a brief introduction on the pathological and molecular characteristics of gliomas, followed by an overview of the models that have been used in the last decades in glioma research. Next, we will discuss how these models may play a role in better understanding glioma development and especially in how they can aid in the design and optimization of novel therapies. The strengths and weaknesses of the different models will be discussed in light of genotypic, phenotypic and metabolic characteristics of human gliomas. The last part of this review provides some examples of how therapy experiments using glioma models can lead to deceptive results when such characteristics are not properly taken into account.

Circulating biomarker panels for targeted therapy in brain tumors

An important goal of oncology is the development of cancer risk-identifier biomarkers that aid early detection and target therapy. High-throughput profiling represents a major concern for cancer research, including brain tumors. A promising approach for efficacious monitoring of disease progression and therapy could be circulating biomarker panels using molecular proteomic patterns. Tailoring treatment by targeting specific protein-protein interactions and signaling networks, microRNA and cancer stem cell signaling in accordance with tumor phenotype or patient clustering based on biomarker panels represents the future of personalized medicine for brain tumors. Gathering current data regarding biomarker candidates, we address the major challenges surrounding the biomarker field of this devastating tumor type, exploring potential perspectives for the development of more effective predictive biomarker panels.

Contemporary murine models in preclinical astrocytoma drug development

Despite 6 decades of research, only 3 drugs have been approved for astrocytomas, the most common malignant primary brain tumors. However, clinical drug development is accelerating with the transition from empirical, cytotoxic therapy to precision, targeted medicine. Preclinical animal model studies are critical for prioritizing drug candidates for clinical development and, ultimately, for their regulatory approval. For decades, only murine models with established tumor cell lines were available for such studies. However, these poorly represent the genomic and biological properties of human astrocytomas, and their preclinical use fails to accurately predict efficacy in clinical trials. Newer models developed over the last 2 decades, including patient-derived xenografts, genetically engineered mice, and genetically engineered cells purified from human brains, more faithfully phenocopy the genomics and biology of human astrocytomas. Harnessing the unique benefits of these models will be required to identify drug targets, define combination therapies that circumvent inherent and acquired resistance mechanisms, and develop molecular biomarkers predictive of drug response and resistance. With increasing recognition of the molecular heterogeneity of astrocytomas, employing multiple, contemporary models in preclinical drug studies promises to increase the efficiency of drug development for specific, molecularly defined subsets of tumors.

Evolutionarily conserved genetic interactions with budding and fission yeast MutS identify orthologous relationships in mismatch repair-deficient cancer cells

Background

The evolutionarily conserved DNA mismatch repair (MMR) system corrects base-substitution and insertion-deletion mutations generated during erroneous replication. The mutation or inactivation of many MMR factors strongly predisposes to cancer, where the resulting tumors often display resistance to standard chemotherapeutics. A new direction to develop targeted therapies is the harnessing of synthetic genetic interactions, where the simultaneous loss of two otherwise non-essential factors leads to reduced cell fitness or death. High-throughput screening in human cells to directly identify such interactors for disease-relevant genes is now widespread, but often requires extensive case-by-case optimization. Here we asked if conserved genetic interactors (CGIs) with MMR genes from two evolutionary distant yeast species (Saccharomyces cerevisiae and Schizosaccharomyzes pombe) can predict orthologous genetic relationships in higher eukaryotes.

Methods

High-throughput screening was used to identify genetic interaction profiles for the MutSα and MutSβ heterodimer subunits (msh2Δ, msh3Δ, msh6Δ) of fission yeast. Selected negative interactors with MutSβ (msh2Δ/msh3Δ) were directly analyzed in budding yeast, and the CGI with SUMO-protease Ulp2 further examined after RNA interference/drug treatment in MSH2-deficient and -proficient human cells.

Results

This study identified distinct genetic profiles for MutSα and MutSβ, and supports a role for the latter in recombinatorial DNA repair. Approximately 28% of orthologous genetic interactions with msh2Δ/msh3Δ are conserved in both yeasts, a degree consistent with global trends across these species. Further, the CGI between budding/fission yeast msh2 and SUMO-protease Ulp2 is maintained in human cells (MSH2/SENP6), and enhanced by Olaparib, a PARP inhibitor that induces the accumulation of single-strand DNA breaks. This identifies SENP6 as a promising new target for the treatment of MMR-deficient cancers.

Conclusion

Our findings demonstrate the utility of employing evolutionary distance in tractable lower eukaryotes to predict orthologous genetic relationships in higher eukaryotes. Moreover, we provide novel insights into the genome maintenance functions of a critical DNA repair complex and propose a promising targeted treatment for MMR deficient tumors.

Electronic supplementary material

The online version of this article (doi:10.1186/s13073-014-0068-4) contains supplementary material, which is available to authorized users.

Differential microRNA expression signatures and cell type-specific association with Taxol resistance in ovarian cancer cells

Paclitaxel (Taxol) resistance remains a major obstacle for the successful treatment of ovarian cancer. MicroRNAs (miRNAs) have oncogenic and tumor suppressor activity and are associated with poor prognosis phenotypes. miRNA screenings for this drug resistance are needed to estimate the prognosis of the disease and find better drug targets. miRNAs that were differentially expressed in Taxol-resistant ovarian cancer cells, compared with Taxol-sensitive cells, were screened by Illumina Human MicroRNA Expression BeadChips. Quantitative reverse transcription-polymerase chain reaction (qRT-PCR) was used to identify target genes of selected miRNAs. Kaplan–Meier survival analysis was applied to identify dysregulated miRNAs in ovarian cancer patients using data from The Cancer Genome Atlas. A total of 82 miRNAs were identified in ovarian carcinoma cells compared to normal ovarian cells. miR-141, miR-106a, miR-200c, miR-96, and miR-378 were overexpressed, and miR-411, miR-432, miR-494, miR-409-3p, and miR-655 were underexpressed in ovarian cancer cells. Seventeen miRNAs were overexpressed in Taxol-resistant cells, including miR-663, miR-622, and HS_188. Underexpressed miRNAs in Taxol-sensitive cells included miR-497, miR-187, miR-195, and miR-107. We further showed miR-663 and miR-622 as significant prognosis markers of the chemo-resistant patient group. In particular, the downregulation of the two miRNAs was associated with better survival, perhaps increasing the sensitivity of cancer cells to Taxol. In the chemo-sensitive patient group, only miR-647 could be a prognosis marker. These miRNAs inhibit several interacting genes of p53 networks, especially in TUOS-3 and TUOS-4, and showed cell line-specific inhibition effects. Taken together, the data indicate that the three miRNAs are closely associated with Taxol resistance and potentially better prognosis factors. Our results suggest that these miRNAs were successfully and reliably identified and would be used in the development of miRNA therapies in treating ovarian cancer.

Synthetic sickness or lethality points at candidate combination therapy targets in glioblastoma

Synthetic lethal interactions in cancer hold the potential for successful combined therapies, which would avoid the difficulties of single molecule-targeted treatment. Identification of interactions that are specific for human tumors is an open problem in cancer research. This work aims at deciphering synthetic sick or lethal interactions directly from somatic alteration, expression and survival data of cancer patients. To this end, we look for pairs of genes and their alterations or expression levels that are "avoided" by tumors and "beneficial" for patients. Thus, candidates for synthetic sickness or lethality (SSL) interaction are identified as such gene pairs whose combination of states is under-represented in the data. Our main methodological contribution is a quantitative score that allows ranking of the candidate SSL interactions according to evidence found in patient survival. Applying this analysis to glioblastoma data, we collect 1,956 synthetic sick or lethal partners for 85 abundantly altered genes, most of which show extensive copy number variation across the patient cohort. We rediscover and interpret known interaction between TP53 and PLK1, as well as provide insight into the mechanism behind EGFR interacting with AKT2, but not AKT1 nor AKT3. Cox model analysis determines 274 of identified interactions as having significant impact on overall survival in glioblastoma, which is more informative than a standard survival predictor based on patient's age.

Current and future directions for Phase II trials in high-grade glioma

Despite surgery, radiation and chemotherapy, the prognosis for high-grade glioma (HGG) is poor. Our understanding of the molecular pathways involved in gliomagenesis and progression has increased in recent years, leading to the development of novel agents that specifically target these pathways. Results from most single-agent trials have been modest at best, however. Despite the initial success of antiangiogenesis agents in HGG, the clinical benefit is short-lived and most patients eventually progress. Several novel agents, multi-targeted agents and combination therapies are now in clinical trials for HGG and several more strategies are being pursued.

MicroRNA-26a promotes tumor growth and angiogenesis in glioma by directly targeting prohibitin

BACKGROUNDS AND AIMS

Glioma accounts for the majority of primary malignant brain tumors in adults. Upregulation of microRNA-26a (miR-26a) has been observed in glioma. However, the biological function and molecular mechanism of miR-26a in glioma remain to be elucidated.

METHODS

Glioma cells stably overexpressing or down-expressing miR-26a were analyzed for both in vitro and in vivo biological functions. Novel target of miR-26a was identified by bioinformatics searching and molecular biological assays. Glioma specimens and normal brain tissues were analyzed for both expression levels of miR-26a and its target.

RESULTS

Forced expression of miR-26a in glioma cells significantly increased both growth rate and colony formation in vitro and tumor growth and angiogenesis in vivo, while reduced expression of miR-26a played opposite roles. MiR-26a directly targeted prohibitin (PHB) whose expression levels were downregulated in glioma specimens. The levels of miR-26a were inversely correlated with PHB expression levels in glioma samples and strongly correlated with clinical WHO grades of glioma.

CONCLUSION

These results reveal that miR-26a regulates PHB and promotes glioma progression both in vitro and in vivo and that miR-26a and its target PHB are associated with glioma development, which can be helpful in developing microRNA-based treatment for glioma in the future.

A kinome-wide RNAi screen in Drosophila Glia reveals that the RIO kinases mediate cell proliferation and survival through TORC2-Akt signaling in glioblastoma

Glioblastoma, the most common primary malignant brain tumor, is incurable with current therapies. Genetic and molecular analyses demonstrate that glioblastomas frequently display mutations that activate receptor tyrosine kinase (RTK) and Pi-3 kinase (PI3K) signaling pathways. In Drosophila melanogaster, activation of RTK and PI3K pathways in glial progenitor cells creates malignant neoplastic glial tumors that display many features of human glioblastoma. In both human and Drosophila, activation of the RTK and PI3K pathways stimulates Akt signaling along with other as-yet-unknown changes that drive oncogenesis. We used this Drosophila glioblastoma model to perform a kinome-wide genetic screen for new genes required for RTK- and PI3K-dependent neoplastic transformation. Human orthologs of novel kinases uncovered by these screens were functionally assessed in mammalian glioblastoma models and human tumors. Our results revealed that the atypical kinases RIOK1 and RIOK2 are overexpressed in glioblastoma cells in an Akt-dependent manner. Moreover, we found that overexpressed RIOK2 formed a complex with RIOK1, mTor, and mTor-complex-2 components, and that overexpressed RIOK2 upregulated Akt signaling and promoted tumorigenesis in murine astrocytes. Conversely, reduced expression of RIOK1 or RIOK2 disrupted Akt signaling and caused cell cycle exit, apoptosis, and chemosensitivity in glioblastoma cells by inducing p53 activity through the RpL11-dependent ribosomal stress checkpoint. These results imply that, in glioblastoma cells, constitutive Akt signaling drives RIO kinase overexpression, which creates a feedforward loop that promotes and maintains oncogenic Akt activity through stimulation of mTor signaling. Further study of the RIO kinases as well as other kinases identified in our Drosophila screen may reveal new insights into defects underlying glioblastoma and related cancers and may reveal new therapeutic opportunities for these cancers.

Glioblastomas, the most common primary brain tumor, harbor mutations in receptor tyrosine kinases (RTKs), such as EGFR, and components of the Pi-3 kinase (PI3K) signaling pathway. However, the genes that act downstream of RTK and PI3K signaling to drive glioblastoma remain unclear. To investigate the genetic and molecular basis of this disease, we created a glioblastoma model in the fruit fly Drosophila melanogaster. To identify new genes involved in glioblastoma development, we performed a screen for the genes required for tumor cell proliferation using our Drosophila glioblastoma model and then functionally assessed the activity of human versions of novel genes identified in this screen. Our results revealed that the RIO kinases become overexpressed in human glioblastomas but not in normal human glial or neuronal cells. We found that overexpression of the RIO kinases promotes and maintains signals that drive tumor cell proliferation and survival in RTK- and PI3K-dependent human glioblastoma, and reduction of RIO kinase expression decreased proliferation and prompted cell death and chemosensitivity in glioblastoma cells. Therefore, disruption of the RIO kinases may provide new therapeutic opportunities to target glioblastoma and other RTK- or PI3K-dependent cancers.

Signal transduction molecule patterns indicating potential glioblastoma therapy approaches

PURPOSE

The expression of an array of signaling molecules, along with the assessment of real-time cell proliferation, has been performed in U87 glioma cell line and in patients' glioblastoma established cell cultures in order to provide a better understanding of cellular and molecular events involved in glioblastoma pathogenesis. Experimental therapy was performed using a phosphatidylinositol-3'-kinase (PI3K) inhibitor.

PATIENTS AND METHODS

xMAP technology was employed to assess expression levels of several signal transduction molecules and real-time xCELLigence platform for cell behavior.

RESULTS

PI3K inhibition induced the most significant effects on global signaling pathways in patient-derived cell cultures, especially on members of the mitogen-activated protein-kinase family, P70S6 serine-threonine kinase, and cAMP response element-binding protein expression and further prevented tumor cell proliferation.

CONCLUSION

The PI3K pathway might be a prime target for glioblastoma treatment.

Shifting the balance of mitochondrial apoptosis: therapeutic perspectives

Signaling via the intrinsic (mitochondrial) pathway of apoptosis represents one of the critical signal transduction cascades that control the regulation of cell death. This pathway is typically altered in human cancers, thereby providing a suitable target for therapeutic intervention. Members of the Bcl-2 family of proteins as well as cell survival signaling cascades such as the PI3K/Akt/mTOR pathway are involved in the regulation of mitochondria-mediated apoptosis. Therefore, further insights into the molecular mechanisms that form the basis for the control of mitochondria-mediated apoptosis will likely open new perspectives to bypass evasion of apoptosis and treatment resistance in human cancers.

An off-target nucleostemin RNAi inhibits growth in human glioblastoma-derived cancer stem cells

Glioblastomas (GBM) may contain a variable proportion of active cancer stem cells (CSCs) capable of self-renewal, of aggregating into CD133⁺ neurospheres, and to develop intracranial tumors that phenocopy the original ones. We hypothesized that nucleostemin may contribute to cancer stem cell biology as these cells share characteristics with normal stem cells. Here we report that nucleostemin is expressed in GBM-CSCs isolated from patient samples, and that its expression, conversely to what it has been described for ordinary stem cells, does not disappear when cells are differentiated. The significance of nucleostemin expression in CSCs was addressed by targeting the corresponding mRNA using lentivirally transduced short hairpin RNA (shRNA). In doing so, we found an off-target nucleostemin RNAi (shRNA22) that abolishes proliferation and induces apoptosis in GBM-CSCs. Furthermore, in the presence of shRNA22, GBM-CSCs failed to form neurospheres in vitro or grow on soft agar. When these cells are xenotransplanted into the brains of nude rats, tumor development is significantly delayed. Attempts were made to identify the primary target/s of shRNA22, suggesting a transcription factor involved in one of the MAP-kinases signaling-pathways or multiple targets. The use of this shRNA may contribute to develop new therapeutic approaches for this incurable type of brain tumor.