An integrative characterization of recurrent molecular aberrations in glioblastoma genomes

Blockage of EGFR/AKT and mevalonate pathways synergize the antitumor effect of temozolomide by reprogramming energy metabolism in glioblastoma

BACKGROUND

Metabolism reprogramming plays a vital role in glioblastoma (GBM) progression and recurrence by producing enough energy for highly proliferating tumor cells. In addition, metabolic reprogramming is crucial for tumor growth and immune-escape mechanisms. Epidermal growth factor receptor (EGFR) amplification and EGFR-vIII mutation are often detected in GBM cells, contributing to the malignant behavior. This study aimed to investigate the functional role of the EGFR pathway on fatty acid metabolism remodeling and energy generation.

METHODS

Clinical GBM specimens were selected for single-cell RNA sequencing and untargeted metabolomics analysis. A metabolism-associated RTK-fatty acid-gene signature was constructed and verified. MK-2206 and MK-803 were utilized to block the RTK pathway and mevalonate pathway induced abnormal metabolism. Energy metabolism in GBM with activated EGFR pathway was monitored. The antitumor effect of Osimertinib and Atorvastatin assisted by temozolomide (TMZ) was analyzed by an intracranial tumor model in vivo.

RESULTS

GBM with high EGFR expression had characteristics of lipid remodeling and maintaining high cholesterol levels, supported by the single-cell RNA sequencing and metabolomics of clinical GBM samples. Inhibition of the EGFR/AKT and mevalonate pathways could remodel energy metabolism by repressing the tricarboxylic acid cycle and modulating ATP production. Mechanistically, the EGFR/AKT pathway upregulated the expressions of acyl-CoA synthetase short-chain family member 3 (ACSS3), acyl-CoA synthetase long-chain family member 3 (ACSL3), and long-chain fatty acid elongation-related gene ELOVL fatty acid elongase 2 (ELOVL2) in an NF-κB-dependent manner. Moreover, inhibition of the mevalonate pathway reduced the EGFR level on the cell membranes, thereby affecting the signal transduction of the EGFR/AKT pathway. Therefore, targeting the EGFR/AKT and mevalonate pathways enhanced the antitumor effect of TMZ in GBM cells and animal models.

CONCLUSIONS

Our findings not only uncovered the mechanism of metabolic reprogramming in EGFR-activated GBM but also provided a combinatorial therapeutic strategy for clinical GBM management.

A denoised multi-omics integration framework for cancer subtype classification and survival prediction

The availability of high-throughput sequencing data creates opportunities to comprehensively understand human diseases as well as challenges to train machine learning models using such high dimensions of data. Here, we propose a denoised multi-omics integration framework, which contains a distribution-based feature denoising algorithm, Feature Selection with Distribution (FSD), for dimension reduction and a multi-omics integration framework, Attention Multi-Omics Integration (AttentionMOI) to predict cancer prognosis and identify cancer subtypes. We demonstrated that FSD improved model performance either using single omic data or multi-omics data in 15 The Cancer Genome Atlas Program (TCGA) cancers for survival prediction and kidney cancer subtype identification. And our integration framework AttentionMOI outperformed machine learning models and current multi-omics integration algorithms with high dimensions of features. Furthermore, FSD identified features that were associated to cancer prognosis and could be considered as biomarkers.

Trametinib in Patients With NF1-, GNAQ-, or GNA11-Mutant Tumors: Results From the NCI-MATCH ECOG-ACRIN Trial (EAY131) Subprotocols S1 and S2

PURPOSE

NCI-MATCH is a precision medicine trial using genomic testing to allocate patients with advanced malignancies to targeted treatment subprotocols. This report combines two subprotocols evaluating trametinib, a MEK1/2 inhibitor, in patients with Neurofibromatosis 1 (NF1[S1] or GNA11/Q [S2]) altered tumors.

METHODS

Eligible patients had tumors with deleterious inactivating NF1 or GNA11/Q mutations by the customized Oncomine AmpliSeq panel. Prior MEK inhibitor treatment was excluded. Glioblastomas (GBMs) were permitted, including malignancies associated with germline NF1 mutations (S1 only). Trametinib was administered at 2 mg once daily over 28-day cycles until toxicity or disease progression. Primary end point was objective response rate (ORR). Secondary end points included progression-free survival (PFS) at 6 months, PFS, and overall survival. Exploratory analyses included co-occurring genomic alterations and PTEN loss.

RESULTS

Fifty patients were eligible and started therapy: 46 with NF1 mutations (S1) and four with GNA11 mutations (S2). In the NF1 cohort, nonsense single-nucleotide variants were identified in 29 and frameshift deletions in 17 tumors. All in S2 had nonuveal melanoma and GNA11 Q209L variant. Two partial responses (PR) were noted in S1, one patient each with advanced lung cancer and GBM for an ORR of 4.3% (90% CI, 0.8 to 13.1). One patient with melanoma in S2 had a PR (ORR, 25%; 90% CI, 1.3 to 75.1). Prolonged stable disease (SD) was also noted in five patients (four in S1 and one in S2) with additional rare histologies. Adverse events were as previously described with trametinib. Comutations in TP53 and PIK3CA were common.

CONCLUSION

Although these subprotocols did not meet the primary end point for ORR, significant responses or prolonged SD noted in some disease subtypes warrants further investigation.

Cellular and molecular features related to exceptional therapy response and extreme long-term survival in glioblastoma

Glioblastoma Multiforme (GBM) remains the most common malignant primary brain tumor with a dismal prognosis that rarely exceeds beyond 2 years despite extensive therapy, which consists of maximal safe surgical resection, radiotherapy, and/or chemotherapy. Recently, it has become clear that GBM is not one homogeneous entity and that both intra-and intertumoral heterogeneity contributes significantly to differences in tumoral behavior which may consequently be responsible for differences in survival. Strikingly and in spite of its dismal prognosis, small fractions of GBM patients seem to display extremely long survival, defined as surviving over 10 years after diagnosis, compared to the large majority of patients. Although the underlying mechanisms for this peculiarity remain largely unknown, emerging data suggest that still poorly characterized both cellular and molecular factors of the tumor microenvironment and their interplay probably play an important role. We hereby give an extensive overview of what is yet known about these cellular and molecular features shaping extreme long survival in GBM.

Palindrome-Embedded Hairpin Structure and Its Target-Catalyzed Padlock Cyclization for Label-Free MicroRNA-Initiated Rolling Circle Amplification

Highly sensitive detection of microRNAs (miRNAs) is of great significance in early diagnosis of cancers. Here, we develop a palindrome-embedded hairpin structure and its target-catalyzed padlock cyclization for rolling circle amplification, named PHP-RCA for simplicity, which can be applied in label-free ultrasensitive detection of miRNA. PHP-RCA is a facile system that consists of only an oligonucleotide probe with a palindrome-embedded hairpin structure (PHP). The two ends of PHP were extended as overhangs and designed with the complementary sequences of the target. Hence, the phosphorylated PHP can be cyclized by T4 DNA ligase in the presence of the target that serves as the ligation template. This ligation has formed a palindrome-embedded dumbbell-shaped probe (PDP) that allows phi29 polymerase to perform a typical target-primed RCA on PDP by taking miRNA as a primer, resulting in the production of a lengthy tandem repeat. Benefits from the palindromic sequences and hairpin-shaped structure in padlock double-stranded structures can be infinitely produced during the RCA reaction and provide numerous binding sites for SYBR Green I, a double-stranded dye, achieving a sharp response signal for label-free target detection. We have demonstrated that the proposed system exhibits a good linear range from 0.1 fM to 5 nM with a low detection limit of 0.1 fM, and the non-target miRNA can be clearly distinguished. The advantages of high efficiency, label-free signaling, and the use of only one oligonucleotide component make the PHP-RCA suitable for ultrasensitive, economic, and convenient detection of target miRNAs. This simple and powerful system is expected to provide a promising platform for tumor diagnosis, prognosis, and therapy.

An integrated analysis of the cancer genome atlas data discovers a hierarchical association structure across thirty three cancer types

Cancer cells harbor molecular alterations at all levels of information processing. Genomic/epigenomic and transcriptomic alterations are inter-related between genes, within and across cancer types and may affect clinical phenotypes. Despite the abundant prior studies of integrating cancer multi-omics data, none of them organizes these associations in a hierarchical structure and validates the discoveries in extensive external data. We infer this Integrated Hierarchical Association Structure (IHAS) from the complete data of The Cancer Genome Atlas (TCGA) and compile a compendium of cancer multi-omics associations. Intriguingly, diverse alterations on genomes/epigenomes from multiple cancer types impact transcriptions of 18 Gene Groups. Half of them are further reduced to three Meta Gene Groups enriched with (1) immune and inflammatory responses, (2) embryonic development and neurogenesis, (3) cell cycle process and DNA repair. Over 80% of the clinical/molecular phenotypes reported in TCGA are aligned with the combinatorial expressions of Meta Gene Groups, Gene Groups, and other IHAS subunits. Furthermore, IHAS derived from TCGA is validated in more than 300 external datasets including multi-omics measurements and cellular responses upon drug treatments and gene perturbations in tumors, cancer cell lines, and normal tissues. To sum up, IHAS stratifies patients in terms of molecular signatures of its subunits, selects targeted genes or drugs for precision cancer therapy, and demonstrates that associations between survival times and transcriptional biomarkers may vary with cancer types. These rich information is critical for diagnosis and treatments of cancers.

Alterations in Molecular Profiles Affecting Glioblastoma Resistance to Radiochemotherapy: Where Does the Good Go?

Simple Summary

Glioblastoma is a type of brain cancer that remains incurable. Despite multiple past and ongoing preclinical studies and clinical trials, involving adjuvants to the conventional therapy and based on molecular targeting, no relevant benefit for patients’ survival has been achieved so far. The current first-line treatment regimen is based on ionizing radiation and the monoalkylating compound, temozolomide, and has been administered for more than 15 years. Glioblastoma is extremely resistant to most agents due to a mutational background that elicits quick response to insults and adapts to microenvironmental and metabolic changes. Here, we present the most recent evidence concerning the molecular features and their alterations governing pathways involved in GBM response to the standard radio-chemotherapy and discuss how they collaborate with acquired GBM’s resistance.

Abstract

Glioblastoma multiforme (GBM) is a brain tumor characterized by high heterogeneity, diffuse infiltration, aggressiveness, and formation of recurrences. Patients with this kind of tumor suffer from cognitive, emotional, and behavioral problems, beyond exhibiting dismal survival rates. Current treatment comprises surgery, radiotherapy, and chemotherapy with the methylating agent, temozolomide (TMZ). GBMs harbor intrinsic mutations involving major pathways that elicit the cells to evade cell death, adapt to the genotoxic stress, and regrow. Ionizing radiation and TMZ induce, for the most part, DNA damage repair, autophagy, stemness, and senescence, whereas only a small fraction of GBM cells undergoes treatment-induced apoptosis. Particularly upon TMZ exposure, most of the GBM cells undergo cellular senescence. Increased DNA repair attenuates the agent-induced cytotoxicity; autophagy functions as a pro-survival mechanism, protecting the cells from damage and facilitating the cells to have energy to grow. Stemness grants the cells capacity to repopulate the tumor, and senescence triggers an inflammatory microenvironment favorable to transformation. Here, we highlight this mutational background and its interference with the response to the standard radiochemotherapy. We discuss the most relevant and recent evidence obtained from the studies revealing the molecular mechanisms that lead these cells to be resistant and indicate some future perspectives on combating this incurable tumor.

Chromatin accessibility analysis identifies GSTM1 as a prognostic marker in human glioblastoma patients

BACKGROUND

Glioblastoma (GBM) is a malignant human brain tumor that has an extremely poor prognosis. Classic mutations such as IDH (isocitrate dehydrogenase) mutations, EGFR (epidermal growth factor receptor) alternations, and MGMT (O6-methylguanine-methyltransferase) promoter hypermethylation have been used to stratify patients and provide prognostic significance. Epigenetic perturbations have been demonstrated in glioblastoma tumorigenesis. Despite the genetic markers used in the management of glioblastoma patients, new biomarkers that could predict patient survival independent of known biomarkers remain to be identified.

METHODS

ATAC-seq (assay for transposase accessible chromatin followed by sequencing) and RNA-seq have been used to profile chromatin accessible regions using glioblastoma patient samples with short-survival versus long-survival. Cell viability, cell cycle, and Western blot analysis were used to characterize the cellular phenotypes and identify signaling pathways.

RESULTS

Analysis of chromatin accessibility by ATAC-seq coupled with RNA-seq methods identified the GSTM1 (glutathione S-transferase mu-1) gene, which featured higher chromatin accessibility in GBM tumors with short survival. GSTM1 was confirmed to be a significant prognostic marker to predict survival using a different GBM patient cohort. Knockdown of GSTM1 decreased cell viability, caused cell cycle arrest, and decreased the phosphorylation levels of the NF-kB (nuclear factor kappa B) p65 subunit and STAT3 (signal transducer and activator of transcription 3) (pSer727).

CONCLUSIONS

This report demonstrates the use of ATAC-seq coupled with RNA-seq to identify GSTM1 as a prognostic marker of GBM patient survival. Activation of phosphorylation levels of NF-kB p65 and STAT3 (pSer727) by GSTM1 is shown. Analysis of chromatin accessibility in patient samples could generate an independent biomarker that can be used to predict patient survival.

Molecular profiling of long-term IDH-wildtype glioblastoma survivors

BACKGROUND

Glioblastoma (GBM) represents an aggressive cancer type with a median survival of only 14 months. With fewer than 5% of patients surviving 5 years, comprehensive profiling of these rare patients could elucidate prognostic biomarkers that may confer better patient outcomes. We utilized multiple molecular approaches to characterize the largest patient cohort of isocitrate dehydrogenase (IDH)-wildtype GBM long-term survivors (LTS) to date.

METHODS

Retrospective analysis was performed on 49 archived formalin-fixed paraffin embedded tumor specimens from patients diagnosed with GBM at the Mayo Clinic between December 1995 and September 2013. These patient samples were subdivided into 2 groups based on survival (12 LTS, 37 short-term survivors [STS]) and subsequently examined by mutation sequencing, copy number analysis, methylation profiling, and gene expression.

RESULTS

Of the 49 patients analyzed in this study, LTS were younger at diagnosis (P = 0.016), more likely to be female (P = 0.048), and MGMT promoter methylated (UniD, P = 0.01). IDH-wildtype STS and LTS demonstrated classic GBM mutations and copy number changes. Pathway analysis of differentially expressed genes showed LTS enrichment for sphingomyelin metabolism, which has been linked to decreased GBM growth, invasion, and angiogenesis. STS were enriched for DNA repair and cell cycle control networks.

CONCLUSIONS

While our findings largely report remarkable similarity between these LTS and more typical STS, unique attributes were observed in regard to altered gene expression and pathway enrichment. These attributes may be valuable prognostic markers and are worth further examination. Importantly, this study also underscores the limitations of existing biomarkers and classification methods in predicting patient prognosis.

ILK silencing inhibits migration and invasion of more invasive glioblastoma cells by downregulating ROCK1 and Fascin-1

Glioblastoma multiforme (GBM) is the most aggressive type of brain tumor and it is associated with poor survival. Integrin-linked kinase (ILK) is a serine/threonine protein pseudo-kinase that binds to the cytoplasmic domains of β1 and β3 integrins and has been previously shown to promote invasion and metastasis in many cancer types, including GBM. However, little is known regarding the exact molecular mechanism implicating ILK in GBM aggressiveness. In this study, we used two brain cell lines, the non-invasive neuroglioma H4 cells, and the highly invasive glioblastoma A172 cells, which express ILK in much higher levels than H4. We studied the effect of ILK silencing on the metastatic behavior of glioblastoma cells in vitro and elucidate the underlying molecular mechanism. We showed that siRNA-mediated silencing of ILK inhibits cell migration and invasion of the highly invasive A172 cells while it does not affect the migratory and invasive capacity of H4 cells. These data were also supported by respective changes in the expression of Rho-associated kinase 1 (ROCK1), fascin actin-bundling protein 1 (FSCN1), and matrix metalloproteinase 13 (MMP13), which are known to regulate cell migration and invasion. Our findings were further corroborated by analyzing the Cancer Genome Atlas Glioblastoma Multiforme (TCGA-GBM) dataset. We conclude that ILK promotes glioblastoma cell invasion through activation of ROCK1 and FSCN1 in vitro, providing a more exact molecular mechanism for its action.

Pathogenic mutations in neurofibromin identifies a leucine-rich domain regulating glioma cell invasiveness

Glioblastoma (GBM) is the most aggressive tumor of the brain. NF1, a tumor suppressor gene and RAS-GTPase, is one of the highly mutated genes in GBM. Dysregulated NF1 expression promotes cell invasion, proliferation, and tumorigenesis. Loss of NF1 expression in glioblastoma is associated with increased aggressiveness of the tumor. Here, we show that NF1-loss in patient-derived glioma cells using shRNA increases self-renewal, heightens cell invasion, and promotes mesenchymal subtype and epithelial mesenchymal transition-specific gene expression that enhances tumorigenesis. The neurofibromin protein contains at least four major domains, with the GAP-related domain being the most well-studied. In this study, we report that the leucine-rich domain (LRD) of neurofibromin inhibits invasion of human glioblastoma cells without affecting their proliferation. Moreover, under conditions tested, the NF1-LRD fails to hydrolyze Ras-GTP to Ras-GDP, suggesting that its suppressive function is independent of Ras signaling. We further demonstrate that rare variants within the NF1-LRD domain found in a subset of the patients are pathogenic and reduce NF1-LRD’s invasion suppressive function. Taken together, our results show, for the first time, that NF1-LRD inhibits glioma invasion, and provides evidence of a previously unrecognized function of NF1-LRD in glioma biology.

MGSEA - a multivariate Gene set enrichment analysis

BACKGROUND

Gene Set Enrichment Analysis (GSEA) is a powerful tool to identify enriched functional categories of informative biomarkers. Canonical GSEA takes one-dimensional feature scores derived from the data of one platform as inputs. Numerous extensions of GSEA handling multimodal OMIC data are proposed, yet none of them explicitly captures combinatorial relations of feature scores from multiple platforms.

RESULTS

We propose multivariate GSEA (MGSEA) to capture combinatorial relations of gene set enrichment among multiple platform features. MGSEA successfully captures designed feature relations from simulated data. By applying it to the scores of delineating breast cancer and glioblastoma multiforme (GBM) subtypes from The Cancer Genome Atlas (TCGA) datasets of CNV, DNA methylation and mRNA expressions, we find that breast cancer and GBM data yield both similar and distinct outcomes. Among the enriched functional categories, subtype-specific biomarkers are dominated by mRNA expression in many functional categories in both cancer types and also by CNV in many functional categories in breast cancer. The enriched functional categories belonging to distinct combinatorial patterns are involved different oncogenic processes: cell proliferation (such as cell cycle control, estrogen responses, MYC and E2F targets) for mRNA expression in breast cancer, invasion and metastasis (such as cell adhesion and epithelial-mesenchymal transition (EMT)) for CNV in breast cancer, and diverse processes (such as immune and inflammatory responses, cell adhesion, angiogenesis, and EMT) for mRNA expression in GBM. These observations persist in two external datasets (Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) for breast cancer and Repository for Molecular Brain Neoplasia Data (REMBRANDT) for GBM) and are consistent with knowledge of cancer subtypes. We further compare the characteristics of MGSEA with several extensions of GSEA and point out the pros and cons of each method.

CONCLUSIONS

We demonstrated the utility of MGSEA by inferring the combinatorial relations of multiple platforms for cancer subtype delineation in three multi-OMIC datasets: TCGA, METABRIC and REMBRANDT. The inferred combinatorial patterns are consistent with the current knowledge and also reveal novel insights about cancer subtypes. MGSEA can be further applied to any genotype-phenotype association problems with multimodal OMIC data.

MethCNA: a database for integrating genomic and epigenomic data in human cancer

Background

The integration of DNA methylation and copy number alteration data promises to provide valuable insight into the underlying molecular mechanisms responsible for cancer initiation and progression. However, the generation and processing of these datasets are costly and time-consuming if carried out separately. The Illumina Infinium HumanMethylation450 BeadChip, initially designed for the evaluation of DNA methylation levels, allows copy number variant calling using bioinformatics tools.

Results

A substantial amount of Infinium HumanMethylation450 data across various cancer types has been accumulated in recent years and is a valuable resource for large-scale data analysis. Here we present MethCNA, a comprehensive database for genomic and epigenomic data integration in human cancer. In the current release, MethCNA contains about 10,000 tumor samples representing 37 cancer types. All raw array data were collected from The Cancer Genome Atlas and NCBI Gene Expression Omnibus database and analyzed using a pipeline that integrated multiple computational resources and tools. The normalized copy number aberration data and DNA methylation alterations were obtained. We provide a user-friendly web-interface for data mining and visualization.

Conclusions

The Illumina Infinium HumanMethylation450 BeadChip enables the interrogation and integration of both genomic and epigenomic data from exactly the same DNA specimen, and thus can aid in distinguishing driver from passenger mutations in cancer. We expect MethCNA will enable researchers to explore DNA methylation and copy number alteration patterns, identify key oncogenic drivers in cancer, and assist in the development of targeted therapies. MethCNA is publicly available online at http://cgma.scu.edu.cn/MethCNA.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-4525-0) contains supplementary material, which is available to authorized users.

Expression of microRNAs in tumors of the central nervous system in pediatric patients in México

PURPOSE

MicroRNAs were identified as molecules that participate in gene regulation; alterations in their expression characterize central nervous system (CNS). Information in pediatrics is scarce, so the objective of this work was to determine and then compare the patterns of expression of microRNAs in astrocytomas, ependymomas, and medulloblastomas, as well as in non-neoplastic brain.

METHODS

Low-density arrays were utilized to evaluate 756 microRNAs in three samples of each type of tumor and non-neoplastic brain. The relative expression was calculated in order to identify the three microRNAs whose expression was modified notably. This was verified using RT-qPCR in more number of tumor samples.

RESULTS

The microRNAs selected for testing were miR-100-5p, miR-195-5p, and miR-770-5p. A higher expression of miR-100-5p was observed in the astrocytomas and ependymomas compared to the medulloblastomas: on average 3.8 times (p < 0.05). MiR-770-5p was expressed less in medulloblastomas compared to astrocytomas four times (p = 0.0162). MiR-195-5p had a low expression in medulloblastomas compared to non-neoplastic cerebellum (p = 0.049). In all three tumor types, expression of miR-770-5p was lower than in non-neoplastic brain (p < 0.001).

CONCLUSIONS

These microRNAs may represent potential markers in these tumors.

Pseudogenes of annexin A2, novel prognosis biomarkers for diffuse gliomas

Diffuse gliomas is a kind of common malignant primary brain tumor. Pseudogenes have multilayered biological function in the progression of human cancers. In this study, Differentially Expressed Pseudogenes (DEPs) between glioblastomas and non-tumor controls were found by bioinformatics analysis, of which the annexin A2 pseudogenes (ANXA2P1, ANXA2P2 and ANXA2P3) were significantly up-regulated, along with the parent gene annexin A2 (ANXA2). Among four glioblastoma subtypes, ANXA2P1 and ANXA2P2 were preferentially expressed in mesenchymal subtype and less expressed in proneural subtype. Meanwhile, Pearson’s correlation analysis revealed that the expression level of ANXA2 was positively correlated with ANXA2 pseudogenes expression. Then, the expression patterns of ANXA2 and its pseudogenes were validated in diffuse glioma specimens (n=99) and non-tumor tissues (n=12) by quantitative real-time PCR (qRT-PCR). Additionally, Kaplan–Meier analysis revealed that highly expressed ANXA2 and annexin A2 pseudogenes were associated with the poor survival outcome of glioma patients. Cox regression analyses suggested that ANXA2, ANXA2P1 and ANXA2P2 were the independent prognosis factors for gliomas. Furthermore, down-regulation of ANXA2 and ANXA2 pseudogenes might contribute to the improvement of patients’ survival who received chemotherapy and radiotherapy. These results demonstrated that ANXA2 pseudogenes and ANXA2 could be used as the novel biomarkers for diagnosis, prognosis and target therapy of gliomas.

lncRNAs PVT1 and HAR1A are prognosis biomarkers and indicate therapy outcome for diffuse glioma patients

Diffuse gliomas are well known malignant brain tumors. Long non-coding RNAs (lncRNAs), a type of RNA transcript with more than 200 nucleotides, involve in tumorigenesis and development of various cancers. This study focused on identifying differentially expressed lncRNAs in gliomas based on gene expression profiling, and chose certain lncRNAs PVT1, CYTOR, HAR1A and MIAT, which changed with significant differences. Further analysis of TCGA and GEO data revealed that the expressions of PVT1 and CYTOR were up-regulated, while HAR1A and MIAT expressions were down-regulated in gliomas. Their expression patterns were validated in an independent cohort containing 98 glioma specimens and 12 non-tumor tissue controls. High expression of PVT1 and CYTOR as well as low HAR1A and MIAT expression were associated with high Ki-67 level and more TP53 mutation. Kaplan-Meier survival curve and Cox regression analyses showed that glioma patients with high PVT1 expression or low HAR1A expression had poor survival outcome, aberrantly expressed PVT1 and HAR1A could be the independent prognosis biomarkers for glioma patients. Moreover, down-regulation of PVT1 and up-regulation of HAR1A contributed to improve the survival of patients who received chemotherapy and radiotherapy. These results implied that these four lncRNAs might play important role in diffuse gliomas progression, particularly, PVT1 and HAR1A could be explored as promising biomarkers for diagnosis, prognosis and target therapy of diffuse gliomas.

CRMP2 Phosphorylation Drives Glioblastoma Cell Proliferation

Glioblastoma (GBM) is an aggressive primary brain tumor. The rapid growth and the privileged provenance of the tumor within the brain contribute to its aggressivity and poor therapeutic targeting. A poor prognostic factor in glioblastoma is the deletion or mutation of the Nf1 gene. This gene codes for the protein neurofibromin, a tumor suppressor gene that is known to interact with the collapsin response mediator protein 2 (CRMP2). CRMP2 expression and elevated expression of nuclear phosphorylated CRMP2 have recently been implicated in cancer progression. The CRMP2-neurofibromin interaction protects CRMP2 from its phosphorylation by cyclin-dependent kinase 5 (Cdk5), an event linked to cancer progression. In three human glioblastoma cell lines (GL15, A172, and U87), we observed an inverse correlation between neurofibromin expression and CRMP2 phosphorylation levels. Glioblastoma cell proliferation was dependent on CRMP2 expression and phosphorylation by Cdk5 and glycogen synthase kinase 3 beta (GSK3β). The CRMP2 phosphorylation inhibitor (S)-lacosamide reduces, in a concentration-dependent manner, glioblastoma cell proliferation and induced apoptosis in all three GBM cell lines tested. Since (S)-lacosamide is bioavailable in the brain, we tested its utility in an in vivo orthotopic model of GBM using GL261-LucNeo glioma cells. (S)-lacosamide decreased tumor size, as measured via in vivo bioluminescence imaging, by ~54% compared to vehicle control. Our results introduce CRMP2 expression and phosphorylation as a novel player in GBM proliferation and survival, which is enhanced by loss of Nf1.

Host mediated inflammatory influence on glioblastoma multiforme recurrence following high-dose ionizing radiation

Despite optimal clinical treatment, glioblastoma multiforme (GBM) inevitably recurs. Standard treatment of GBM, exposes patients to radiation which kills tumor cells, but also modulates the molecular fingerprint of any surviving tumor cells and the cross-talk between those cells and the host. Considerable investigation of short-term (hours to days) post-irradiation tumor cell response has been undertaken, yet long-term responses (weeks to months) which are potentially even more informative of recurrence, have been largely overlooked. To better understand the potential of these processes to reshape tumor regrowth, molecular studies in conjunction with in silico modeling were used to examine short- and long-term growth dynamics. Despite survival of 2.55% and 0.009% following 8 or 16Gy, GBM cell populations in vitro showed a robust escape from cellular extinction and a return to pre-irradiated growth rates with no changes in long-term population doublings. In contrast, these same irradiated GBM cell populations injected in vivo elicited tumors which displayed significantly suppressed growth rates compared to their pre-irradiated counterparts. Transcriptome analysis days to weeks after irradiation revealed, 281 differentially expressed genes with a robust increase for cytokines, histones and C-C or C-X-C motif chemokines in irradiated cells. Strikingly, this same inflammatory signature in vivo for IL1A, CXCL1, IL6 and IL8 was increased in xenografts months after irradiation. Computational modeling of tumor cell dynamics indicated a host-mediated negative pressure on the surviving cells was a source of inhibition consistent with the findings resulting in suppressed tumor growth. Thus, tumor cells surviving irradiation may shift the landscape of population doubling through inflammatory mediators interacting with the host in a way that impacts tumor recurrence and affects the efficacy of subsequent therapies. Clues to more effective therapies may lie in the development and use of pre-clinical models of post-treatment response to target the source of inflammatory mediators that significantly alter cellular dynamics and molecular pathways in the early stages of tumor recurrence.

Putative effectors for prognosis in lung adenocarcinoma are ethnic and gender specific

Lung adenocarcinoma possesses distinct patterns of EGFR/KRAS mutations between East Asian and Western, male and female patients. However, beyond the well-known EGFR/KRAS distinction, gender and ethnic specific molecular aberrations and their effects on prognosis remain largely unexplored. Association modules capture the dependency of an effector molecular aberration and target gene expressions. We established association modules from the copy number variation (CNV), DNA methylation and mRNA expression data of a Taiwanese female cohort. The inferred modules were validated in four external datasets of East Asian and Caucasian patients by examining the coherence of the target gene expressions and their associations with prognostic outcomes. Modules 1 (cis-acting effects with chromosome 7 CNV) and 3 (DNA methylations of UBIAD1 and VAV1) possessed significantly negative associations with survival times among two East Asian patient cohorts. Module 2 (cis-acting effects with chromosome 18 CNV) possessed significantly negative associations with survival times among the East Asian female subpopulation alone. By examining the genomic locations and functions of the target genes, we identified several putative effectors of the two cis-acting CNV modules: RAC1, EGFR, CDK5 and RALBP1. Furthermore, module 3 targets were enriched with genes involved in cell proliferation and division and hence were consistent with the negative associations with survival times. We demonstrated that association modules in lung adenocarcinoma with significant links of prognostic outcomes were ethnic and/or gender specific. This discovery has profound implications in diagnosis and treatment of lung adenocarcinoma and echoes the fundamental principles of the personalized medicine paradigm.

Mir-21-Sox2 Axis Delineates Glioblastoma Subtypes with Prognostic Impact

Glioblastoma (GBM) is the most aggressive human brain tumor. Although several molecular subtypes of GBM are recognized, a robust molecular prognostic marker has yet to be identified. Here, we report that the stemness regulator Sox2 is a new, clinically important target of microRNA-21 (miR-21) in GBM, with implications for prognosis. Using the MiR-21-Sox2 regulatory axis, approximately half of all GBM tumors present in the Cancer Genome Atlas (TCGA) and in-house patient databases can be mathematically classified into high miR-21/low Sox2 (Class A) or low miR-21/high Sox2 (Class B) subtypes. This classification reflects phenotypically and molecularly distinct characteristics and is not captured by existing classifications. Supporting the distinct nature of the subtypes, gene set enrichment analysis of the TCGA dataset predicted that Class A and Class B tumors were significantly involved in immune/inflammatory response and in chromosome organization and nervous system development, respectively. Patients with Class B tumors had longer overall survival than those with Class A tumors. Analysis of both databases indicated that the Class A/Class B classification is a better predictor of patient survival than currently used parameters. Further, manipulation of MiR-21-Sox2 levels in orthotopic mouse models supported the longer survival of the Class B subtype. The MiR-21-Sox2 association was also found in mouse neural stem cells and in the mouse brain at different developmental stages, suggesting a role in normal development. Therefore, this mechanism-based classification suggests the presence of two distinct populations of GBM patients with distinguishable phenotypic characteristics and clinical outcomes.

SIGNIFICANCE STATEMENT

Molecular profiling-based classification of glioblastoma (GBM) into four subtypes has substantially increased our understanding of the biology of the disease and has pointed to the heterogeneous nature of GBM. However, this classification is not mechanism based and its prognostic value is limited. Here, we identify a new mechanism in GBM (the miR-21-Sox2 axis) that can classify ∼50% of patients into two subtypes with distinct molecular, radiological, and pathological characteristics. Importantly, this classification can predict patient survival better than the currently used parameters. Further, analysis of the miR-21-Sox2 relationship in mouse neural stem cells and in the mouse brain at different developmental stages indicates that miR-21 and Sox2 are predominantly expressed in mutually exclusive patterns, suggesting a role in normal neural development.

Analysis of spatial-temporal gene expression patterns reveals dynamics and regionalization in developing mouse brain

Allen Brain Atlas (ABA) provides a valuable resource of spatial/temporal gene expressions in mammalian brains. Despite rich information extracted from this database, current analyses suffer from several limitations. First, most studies are either gene-centric or region-centric, thus are inadequate to capture the superposition of multiple spatial-temporal patterns. Second, standard tools of expression analysis such as matrix factorization can capture those patterns but do not explicitly incorporate spatial dependency. To overcome those limitations, we proposed a computational method to detect recurrent patterns in the spatial-temporal gene expression data of developing mouse brains. We demonstrated that regional distinction in brain development could be revealed by localized gene expression patterns. The patterns expressed in the forebrain, medullary and pontomedullary, and basal ganglia are enriched with genes involved in forebrain development, locomotory behavior, and dopamine metabolism respectively. In addition, the timing of global gene expression patterns reflects the general trends of molecular events in mouse brain development. Furthermore, we validated functional implications of the inferred patterns by showing genes sharing similar spatial-temporal expression patterns with Lhx2 exhibited differential expression in the embryonic forebrains of Lhx2 mutant mice. These analysis outcomes confirm the utility of recurrent expression patterns in studying brain development.

An Integrative Analysis to Identify Driver Genes in Esophageal Squamous Cell Carcinoma

Background

Few driver genes have been well established in esophageal squamous cell carcinoma (ESCC). Identification of the genomic aberrations that contribute to changes in gene expression profiles can be used to predict driver genes.

Methods

We searched for driver genes in ESCC by integrative analysis of gene expression microarray profiles and copy number data. To narrow down candidate genes, we performed survival analysis on expression data and tested the genetic vulnerability of each genes using public RNAi screening data. We confirmed the results by performing RNAi experiments and evaluating the clinical relevance of candidate genes in an independent ESCC cohort.

Results

We found 10 significantly recurrent copy number alterations accompanying gene expression changes, including loci 11q13.2, 7p11.2, 3q26.33, and 17q12, which harbored CCND1, EGFR, SOX2, and ERBB2, respectively. Analysis of survival data and RNAi screening data suggested that GRB7, located on 17q12, was a driver gene in ESCC. In ESCC cell lines harboring 17q12 amplification, knockdown of GRB7 reduced the proliferation, migration, and invasion capacities of cells. Moreover, siRNA targeting GRB7 had a synergistic inhibitory effect when combined with trastuzumab, an anti-ERBB2 antibody. Survival analysis of the independent cohort also showed that high GRB7 expression was associated with poor prognosis in ESCC.

Conclusion

Our integrative analysis provided important insights into ESCC pathogenesis. We identified GRB7 as a novel ESCC driver gene and potential new therapeutic target.

Comparative genomic and genetic analysis of glioblastoma-derived brain tumor-initiating cells and their parent tumors

BACKGROUND

Glioblastoma (GBM) is a fatal cancer that has eluded major therapeutic advances. Failure to make progress may reflect the absence of a human GBM model that could be used to test compounds for anti-GBM activity. In this respect, the development of brain tumor-initiating cell (BTIC) cultures is a step forward because BTICs appear to capture the molecular diversity of GBM better than traditional glioma cell lines. Here, we perform a comparative genomic and genetic analysis of BTICs and their parent tumors as preliminary evaluation of the BTIC model.

METHODS

We assessed single nucleotide polymorphisms (SNPs), genome-wide copy number variations (CNVs), gene expression patterns, and molecular subtypes of 11 established BTIC lines and matched parent tumors.

RESULTS

Although CNV differences were noted, BTICs retained the major genomic alterations characteristic of GBM. SNP patterns were similar between BTICs and tumors. Importantly, recurring SNP or CNV alterations specific to BTICs were not seen. Comparative gene expression analysis and molecular subtyping revealed differences between BTICs and GBMs. These differences formed the basis of a 63-gene expression signature that distinguished cells from tumors; differentially expressed genes primarily involved metabolic processes. We also derived a set of 73 similarly expressed genes; these genes were not associated with specific biological functions.

CONCLUSIONS

Although not identical, established BTIC lines preserve the core molecular alterations seen in their parent tumors, as well as the genomic hallmarks of GBM, without acquiring recurring BTIC-specific changes.

Genome-wide mutational spectra analysis reveals significant cancer-specific heterogeneity

Cancer is widely recognized as a genetic disease in which somatic mutations are sequentially accumulated to drive tumor progression. Although genomic landscape studies are informative for individual cancer types, a comprehensive comparative study of tumorigenic mutations across cancer types based on integrative data sources is still a pressing need. We systematically analyzed ~10(6) non-synonymous mutations extracted from COSMIC, involving ~8000 genome-wide screened samples across 23 major human cancers at both the amino acid and gene levels. Our analysis identified cancer-specific heterogeneity that traditional nucleotide variation analysis alone usually overlooked. Particularly, the amino acid arginine (R) turns out to be the most favorable target of amino acid alteration in most cancer types studied (P < 10(-9), binomial test), reflecting its important role in cellular physiology. The tumor suppressor gene TP53 is mutated exclusively with the HYDIN, KRAS, and PTEN genes in large intestine, lung, and endometrial cancers respectively, indicating that TP53 takes part in different signaling pathways in different cancers. While some of our analyses corroborated previous observations, others indicated relevant candidates with high priority for further experimental validation. Our findings have many ramifications in understanding the etiology of cancer and the underlying molecular mechanisms in particular cancers.

Insights from Chromosome-Centric Mapping of Disease-Associated Genes: Chromosome 12 Perspective

In line with the aims of the Chromosome-based Human Proteome Project and the Biology/Disease-based Human Proteome Project, we have been studying differentially expressed transcripts and proteins in gliomas—the most prevalent primary brain tumors. Here, we present a perspective on important insights from this analysis in terms of their co-expression, co-regulation/de-regulation, and co-localization on chromosome 12 (Chr. 12). We observe the following: (1) Over-expression of genes mapping onto amplicon regions of chromosomes may be considered as a biological validation of mass spectrometry data. (2) Their co-localization further suggests common determinants of co-expression and co-regulation of these clusters. (3) Co-localization of "missing" protein genes of Chr. 12 in close proximity to functionally related genes may help in predicting their functions. (4) Further, integrating differentially expressed gene-protein sets and their ontologies with medical terms associated with clinical phenotypes in a chromosome-centric manner reveals a network of genes, diseases, and pathways—a diseasome network. Thus, chromosomal mapping of disease data sets can help uncover important regulatory and functional links that may offer new insights for biomarker development.

Sunitinib impedes brain tumor progression and reduces tumor-induced neurodegeneration in the microenvironment

Malignant gliomas can be counted to the most devastating tumors in humans. Novel therapies do not achieve significant prolonged survival rates. The cancer cells have an impact on the surrounding vital tissue and form tumor zones, which make up the tumor microenvironment. We investigated the effects of sunitinib, a small molecule multitargeted receptor tyrosine kinase inhibitor, on constituents of the tumor microenvironment such as gliomas, astrocytes, endothelial cells, and neurons. Sunitinib has a known anti-angiogenic effect. We found that sunitinib normalizes the aberrant tumor-derived vasculature and reduces tumor vessel pathologies (i.e. auto-loops). Sunitinib has only minor effects on the normal, physiological, non-proliferating vasculature. We found that neurons and astrocytes are protected by sunitinib against glutamate-induced cell death, whereas sunitinib acts as a toxin towards proliferating endothelial cells and tumor vessels. Moreover, sunitinib is effective in inducing glioma cell death. We determined the underlying pathways by which sunitinib operates as a toxin on gliomas and found vascular endothelial growth factor receptor 2 (VEGFR2, KDR/Flk1) as the main target to execute gliomatoxicity. The apoptosis-inducing effect of sunitinib can be mimicked by inhibition of VEGFR2. Knockdown of VEGFR2 can, in part, foster the resistance of glioma cells to receptor tyrosine kinase inhibitors. Furthermore, sunitinib alleviates tumor-induced neurodegeneration. Hence, we tested whether temozolomide treatment could be potentiated by sunitinib application. Here we show that sunitinib can amplify the effects of temozolomide in glioma cells. Thus, our data indicate that combined treatment with temozolomide does not abrogate the effects of sunitinib. In conclusion, we found that sunitinib acts as a gliomatoxic agent and at the same time carries out neuroprotective effects, reducing tumor-induced neurodegeneration. Thus, this report uncovered sunitinib's actions on the brain tumor microenvironment, revealing novel aspects for adjuvant approaches and new clinical assessment criteria when applied to brain tumor patients.

PIPs in neurological diseases

Phosphoinositide (PIP) lipids regulate many aspects of cell function in the nervous system including receptor signalling, secretion, endocytosis, migration and survival. Levels of PIPs such as PI4P, PI(4,5)P2 and PI(3,4,5)P3 are normally tightly regulated by phosphoinositide kinases and phosphatases. Deregulation of these biochemical pathways leads to lipid imbalances, usually on intracellular endosomal membranes, and these changes have been linked to a number of major neurological diseases including Alzheimer's, Parkinson's, epilepsy, stroke, cancer and a range of rarer inherited disorders including brain overgrowth syndromes, Charcot-Marie-Tooth neuropathies and neurodevelopmental conditions such as Lowe's syndrome. This article analyses recent progress in this area and explains how PIP lipids are involved, to varying degrees, in almost every class of neurological disease. This article is part of a Special Issue entitled Brain Lipids.

Neurotensin promotes the progression of malignant glioma through NTSR1 and impacts the prognosis of glioma patients

Background

The poor prognosis and minimally successful treatments of malignant glioma indicate a challenge to identify new therapeutic targets which impact glioma progression. Neurotensin (NTS) and its high affinity receptor (NTSR1) overexpression induces neoplastic growth and predicts the poor prognosis in various malignancies. Whether NTS can promote the glioma progression and its prognostic significance for glioma patients remains unclear.

Methods

NTS precursor (ProNTS), NTS and NTSR1 expression levels in glioma were detected by immunobloting Elisa and immunohistochemistry assay. The prognostic analysis was conducted from internet by R2 microarray platform. Glioma cell proliferation was evaluated by CCK8 and BrdU incorporation assay. Wound healing model and Matrigel transwell assay were utilized to test cellular migration and invasion. The orthotopic glioma implantations were established to analyze the role of NTS and NTSR1 in glioma progression in vivo.

Results

Positive correlations were shown between the expression levels of NTS and NTSR1 with the pathological grade of gliomas. The high expression levels of NTS and NTSR1 indicate a worse prognosis in glioma patients. The proliferation and invasiveness of glioma cells could be enhanced by NTS stimulation and impaired by the inhibition of NTSR1. NTS stimulated Erk1/2 phosphorylation in glioma cells, which could be reversed by SR48692 or NTSR1-siRNA. In vivo experiments showed that SR48692 significantly prolonged the survival length of glioma-bearing mice and inhibited glioma cell invasiveness.

Conclusion

NTS promotes the proliferation and invasion of glioma via the activation of NTSR1. High expression levels of NTS and NTSR1 predict a poor prognosis in glioma patients.

Electronic supplementary material

The online version of this article (doi:10.1186/s12943-015-0290-8) contains supplementary material, which is available to authorized users.

Chromosomal Instability and Phosphoinositide Pathway Gene Signatures in Glioblastoma Multiforme

Structural rearrangements of chromosome 10 are frequently observed in glioblastoma multiforme and over 80 % of tumour samples archived in the catalogue of somatic mutations in cancer database had gene copy number loss for PI4K2A which encodes phosphatidylinositol 4-kinase type IIalpha. PI4K2A loss of heterozygosity mirrored that of PTEN, another enzyme that regulates phosphoinositide levels and also PIK3AP1, MINPP1, INPP5A and INPP5F. These results indicated a reduction in copy number for a set of phosphoinositide signalling genes that co-localise to chromosome 10q. This analysis was extended to a panel of phosphoinositide pathway genes on other chromosomes and revealed a number of previously unreported associations with glioblastoma multiforme. Of particular note were highly penetrant copy number losses for a group of X-linked phosphoinositide phosphatase genes OCRL, MTM1 and MTMR8; copy number amplifications for the chromosome 19 genes PIP5K1C, AKT2 and PIK3R2, and also for the phospholipase C genes PLCB1, PLCB4 and PLCG1 on chromosome 20. These mutations are likely to affect signalling and trafficking functions dependent on the PI(4,5)P2, PI(3,4,5)P3 and PI(3,5)P2 lipids as well as the inositol phosphates IP3, IP5 and IP6. Analysis of flanking genes with functionally unrelated products indicated that chromosomal instability as opposed to a phosphoinositide-specific process underlay this pattern of copy number variation. This in silico study suggests that in glioblastoma multiforme, karyotypic changes have the potential to cause multiple abnormalities in sets of genes involved in phosphoinositide metabolism and this may be important for understanding drug resistance and phosphoinositide pathway redundancy in the advanced disease state.

Genetic and epigenetic regulation of gene expression in fetal and adult human livers

Background

The liver plays a central role in the maintenance of homeostasis and health in general. However, there is substantial inter-individual variation in hepatic gene expression, and although numerous genetic factors have been identified, less is known about the epigenetic factors.

Results

By analyzing the methylomes and transcriptomes of 14 fetal and 181 adult livers, we identified 657 differentially methylated genes with adult-specific expression, these genes were enriched for transcription factor binding sites of HNF1A and HNF4A. We also identified 1,000 genes specific to fetal liver, which were enriched for GATA1, STAT5A, STAT5B and YY1 binding sites. We saw strong liver-specific effects of single nucleotide polymorphisms on both methylation levels (28,447 unique CpG sites (meQTL)) and gene expression levels (526 unique genes (eQTL)), at a false discovery rate (FDR) < 0.05. Of the 526 unique eQTL associated genes, 293 correlated significantly not only with genetic variation but also with methylation levels. The tissue-specificities of these associations were analyzed in muscle, subcutaneous adipose tissue and visceral adipose tissue. We observed that meQTL were more stable between tissues than eQTL and a very strong tissue-specificity for the identified associations between CpG methylation and gene expression.

Conclusions

Our analyses generated a comprehensive resource of factors involved in the regulation of hepatic gene expression, and allowed us to estimate the proportion of variation in gene expression that could be attributed to genetic and epigenetic variation, both crucial to understanding differences in drug response and the etiology of liver diseases.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-860) contains supplementary material, which is available to authorized users.

Informatic system for a global tissue-fluid biorepository with a graph theory-oriented graphical user interface

The Richard Floor Biorepository supports collaborative studies of extracellular vesicles (EVs) found in human fluids and tissue specimens. The current emphasis is on biomarkers for central nervous system neoplasms but its structure may serve as a template for collaborative EV translational studies in other fields. The informatic system provides specimen inventory tracking with bar codes assigned to specimens and containers and projects, is hosted on globalized cloud computing resources, and embeds a suite of shared documents, calendars, and video-conferencing features. Clinical data are recorded in relation to molecular EV attributes and may be tagged with terms drawn from a network of externally maintained ontologies thus offering expansion of the system as the field matures. We fashioned the graphical user interface (GUI) around a web-based data visualization package. This system is now in an early stage of deployment, mainly focused on specimen tracking and clinical, laboratory, and imaging data capture in support of studies to optimize detection and analysis of brain tumour-specific mutations. It currently includes 4,392 specimens drawn from 611 subjects, the majority with brain tumours. As EV science evolves, we plan biorepository changes which may reflect multi-institutional collaborations, proteomic interfaces, additional biofluids, changes in operating procedures and kits for specimen handling, novel procedures for detection of tumour-specific EVs, and for RNA extraction and changes in the taxonomy of EVs. We have used an ontology-driven data model and web-based architecture with a graph theory-driven GUI to accommodate and stimulate the semantic web of EV science.

Integrative bayesian network analysis of genomic data

Rapid development of genome-wide profiling technologies has made it possible to conduct integrative analysis on genomic data from multiple platforms. In this study, we develop a novel integrative Bayesian network approach to investigate the relationships between genetic and epigenetic alterations as well as how these mutations affect a patient's clinical outcome. We take a Bayesian network approach that admits a convenient decomposition of the joint distribution into local distributions. Exploiting the prior biological knowledge about regulatory mechanisms, we model each local distribution as linear regressions. This allows us to analyze multi-platform genome-wide data in a computationally efficient manner. We illustrate the performance of our approach through simulation studies. Our methods are motivated by and applied to a multi-platform glioblastoma dataset, from which we reveal several biologically relevant relationships that have been validated in the literature as well as new genes that could potentially be novel biomarkers for cancer progression.