Association of blood cell-based inflammatory markers with gut microbiota and cancer incidence in the Rotterdam study

The immune response-gut microbiota interaction is implicated in various human diseases, including cancer. Identifying the link between the gut microbiota and systemic inflammatory markers and their association with cancer will be important for our understanding of cancer etiology. The current study was performed on 8090 participants from the population-based Rotterdam study. We found a significant association (false discovery rate [FDR] ≤0.05) between lymphocytes and three gut microbial taxa, namely the family Streptococcaceae, genus Streptococcus, and order Lactobacillales. In addition, we identified 95 gut microbial taxa that were associated with inflammatory markers (p < 0.05). Analyzing the cancer data, we observed a significant association between higher systemic immune-inflammation index (SII) levels at baseline (hazard ratio (HR): 1.65 [95% confidence interval (CI); 1.10-2.46, p ≤ 0.05]) and a higher count of lymphocytes (HR: 1.38 [95% CI: 1.15-1.65, p ≤ 0.05]) and granulocytes (HR: 1.69 [95% CI: 1.40-2.03, p ≤ 0.05]) with increased risk of lung cancer after adjusting for age, sex, body mass index (BMI), and study cohort. This association was lost for SII and lymphocytes after additional adjustment for smoking (SII = HR:1.46 [95% CI: 0.96-2.22, p = 0.07] and lymphocytes = HR: 1.19 [95% CI: 0.97-1.46, p = 0.08]). In the stratified analysis, higher count of lymphocyte and granulocytes at baseline were associated with an increased risk of lung cancer in smokers after adjusting for age, sex, BMI, and study cohort (HR: 1.33 [95% CI: 1.09-1.62, p ≤0.05] and HR: 1.57 [95% CI: 1.28-1.92, p ≤0.05], respectively). Our study revealed a positive association between gut microbiota, higher SII levels, and higher lymphocyte and granulocyte counts, with an increased risk of developing lung cancer.

Local delivery of hrBMP4 as an anticancer therapy in patients with recurrent glioblastoma: a first-in-human phase 1 dose escalation trial

BACKGROUND

This Phase 1 study evaluates the intra- and peritumoral administration by convection enhanced delivery (CED) of human recombinant Bone Morphogenetic Protein 4 (hrBMP4) - an inhibitory regulator of cancer stem cells (CSCs) - in recurrent glioblastoma.

METHODS

In a 3 + 3 dose escalation design, over four to six days, fifteen recurrent glioblastoma patients received, by CED, one of five doses of hrBMP4 ranging from 0·5 to 18 mg. Patients were followed by periodic physical, neurological, blood testing, magnetic resonance imaging (MRI) and quality of life evaluations. The primary objective of this first-in-human study was to determine the safety, dose-limiting toxicities (DLT) and maximum tolerated dose (MTD) of hrBMP4. Secondary objectives were to assess potential efficacy and systemic exposure to hrBMP4 upon intracerebral infusion.

RESULTS

Intra- and peritumoral infusion of hrBMP4 was safe and well-tolerated. We observed no serious adverse events related to this drug. Neither MTD nor DLT were reached. Three patients had increased hrBMP4 serum levels at the end of infusion, which normalized within 4 weeks, without sign of toxicity. One patient showed partial response and two patients a complete (local) tumor response, which was maintained until the most recent follow-up, 57 and 30 months post-hrBMP4. Tumor growth was inhibited in areas permeated by hrBMP4.

CONCLUSION

Local delivery of hrBMP4 in and around recurring glioblastoma is safe and well-tolerated. Three patients responded to the treatment. A complete response and long-term survival occurred in two of them. This warrants further clinical studies on this novel treatment targeting glioblastoma CSCs.

TRIAL REGISTRATION

ClinicaTrials.gov identifier: NCT02869243.

TAMI-10. CIRCULATING ANGIOGENIC CELLS (CACS) IN GLIOBLASTOMA: TOWARDS DEFINING CRUCIAL FUNCTIONAL DIFFERENCES IN CAC-INDUCED NEOPLASTIC VERSUS REACTIVE NEOVASCULARIZATION

In order to identify suitable therapeutic targets for glioma anti-angiogenic therapy, the process of neovascularization mediated by circulating angiogenic cells (CACs) needs to be scrutinized. In the present study we compared the expression of neovascularization-related genes by three circulating CAC subsets (HPCs, CD34+ and KDR+ cells; internal controls: PBMCs and circulating endothelial cells) of treatment-naïve patients with glioblastoma (GBM) to those of patients undergoing reactive neovascularization (myocardial infarction (MI). CACs from umbilical cord (representing developmental neovascularization) and healthy subjects served as controls. Fluorescent activated cell sorting was used to isolate CACs, RT-PCR to determine the expression levels of a panel of 48 neovascularization-related genes, Luminex assays to measure plasma levels of 21 CAC-related circulating molecules. We found essential differences in gene expression between GBM and MI CACs. GBM CACs had a higher expression of pro-angiogenic factors (esp. KITL, CXCL12 and JAG1); growth factor and chemotactic receptors (IGF1R, TGFbR2, CXCR4 and CCR2); adhesion receptor monomers (ITGA5 and ITGA6) and matricellular factor POSTN. In addition, we found major differences in the levels of neovascularization-related plasma factors. A strong positive correlation between plasma MMP9 levels and expression of CXCR4 in the CAC subset of hematopoietic progenitor cells (HPCs) was found in GBM patients. Our findings indicate that CAC-mediated neovascularization in GBM is characterized by more efficient CAC homing to target tissue and a more potent pro-angiogenic response than in physiologic tissue repair in MI. Our findings can aid in selecting targets for therapeutic strategies acting against GBM-specific CACs.

Enabling Analytics on Sensitive Medical Data with Secure Multi-Party Computation

While there is a clear need to apply data analytics in the healthcare sector, this is often difficult because it requires combining sensitive data from multiple data sources. In this paper, we show how the cryptographic technique of secure multi-party computation can enable such data analytics by performing analytics without the need to share the underlying data. We discuss the issue of compliance to European privacy legislation; report on three pilots bringing these techniques closer to practice; and discuss the main challenges ahead to make fully privacy-preserving data analytics in the medical sector commonplace.

Identification of Patients with Recurrent Glioblastoma Who May Benefit from Combined Bevacizumab and CCNU Therapy: A Report from the BELOB Trial

The results from the randomized phase II BELOB trial provided evidence for a potential benefit of bevacizumab (beva), a humanized monoclonal antibody against circulating VEGF-A, when added to CCNU chemotherapy in patients with recurrent glioblastoma (GBM). In this study, we performed gene expression profiling (DASL and RNA-seq) of formalin-fixed, paraffin-embedded tumor material from participants of the BELOB trial to identify patients with recurrent GBM who benefitted most from beva+CCNU treatment. We demonstrate that tumors assigned to the IGS-18 or "classical" subtype and treated with beva+CCNU showed a significant benefit in progression-free survival and a trend toward benefit in overall survival, whereas other subtypes did not exhibit such benefit. In particular, expression of FMO4 and OSBPL3 was associated with treatment response. Importantly, the improved outcome in the beva+CCNU treatment arm was not explained by an uneven distribution of prognostically favorable subtypes as all molecular glioma subtypes were evenly distributed along the different study arms. The RNA-seq analysis also highlighted genetic alterations, including mutations, gene fusions, and copy number changes, within this well-defined cohort of tumors that may serve as useful predictive or prognostic biomarkers of patient outcome. Further validation of the identified molecular markers may enable the future stratification of recurrent GBM patients into appropriate treatment regimens.

Discriminating somatic and germline mutations in tumor DNA samples without matching normals

Tumor analyses commonly employ a correction with a matched normal (MN), a sample from healthy tissue of the same individual, in order to distinguish germline mutations from somatic mutations. Since the majority of variants found in an individual are thought to be common within the population, we constructed a set of 931 samples from healthy, unrelated individuals, originating from two different sequencing platforms, to serve as a virtual normal (VN) in the absence of such an associated normal sample. Our approach removed (1) >96% of the germline variants also removed by the MN sample and (2) a large number (2%–8%) of additional variants not corrected for by the associated normal. The combination of the VN with the MN improved the correction for polymorphisms significantly, with up to ∼30% compared with MN and ∼15% compared with VN only. We determined the number of unrelated genomes needed in order to correct at least as efficiently as the MN is about 200 for structural variations (SVs) and about 400 for single-nucleotide variants (SNVs) and indels. In addition, we propose that the removal of common variants with purely position-based methods is inaccurate and incurs additional false-positive somatic variants, and more sophisticated algorithms, which are capable of leveraging information about the area surrounding variants, are needed for optimal accuracy. Our VN correction method can be used to analyze any list of variants, regardless of sequencing platform of origin. This VN methodology is available for use on our public Galaxy server.

Identification of cancer predisposition variants in apparently healthy individuals using a next-generation sequencing-based family genomics approach

Cancer, like many common disorders, has a complex etiology, often with a strong genetic component and with multiple environmental factors contributing to susceptibility. A considerable number of genomic variants have been previously reported to be causative of, or associated with, an increased risk for various types of cancer. Here, we adopted a next-generation sequencing approach in 11 members of two families of Greek descent to identify all genomic variants with the potential to predispose family members to cancer. Cross-comparison with data from the Human Gene Mutation Database identified a total of 571 variants, from which 47 % were disease-associated polymorphisms, 26 % disease-associated polymorphisms with additional supporting functional evidence, 19 % functional polymorphisms with in vitro/laboratory or in vivo supporting evidence but no known disease association, 4 % putative disease-causing mutations but with some residual doubt as to their pathological significance, and 3 % disease-causing mutations. Subsequent analysis, focused on the latter variant class most likely to be involved in cancer predisposition, revealed two variants of prime interest, namely MSH2 c.2732T>A (p.L911R) and BRCA1 c.2955delC, the first of which is novel. KMT2D c.13895delC and c.1940C>A variants are additionally reported as incidental findings. The next-generation sequencing-based family genomics approach described herein has the potential to be applied to other types of complex genetic disorder in order to identify variants of potential pathological significance.

iReport: a generalised Galaxy solution for integrated experimental reporting

Background

Galaxy offers a number of visualisation options with components, such as Trackster, Circster and Galaxy Charts, but currently lacks the ability to easily combine outputs from different tools into a single view or report. A number of tools produce HTML reports as output in order to combine the various output files from a single tool; however, this requires programming and knowledge of HTML, and the reports must be custom-made for each new tool.

Findings

We have developed a generic and flexible reporting tool for Galaxy, iReport, that allows users to create interactive HTML reports directly from the Galaxy UI, with the ability to combine an arbitrary number of outputs from any number of different tools. Content can be organised into different tabs, and interactivity can be added to components. To demonstrate the capability of iReport we provide two publically available examples, the first is an iReport explaining about iReports, created for, and using content from the recent Galaxy Community Conference 2014. The second is a genetic report based on a trio analysis to determine candidate pathogenic variants which uses our previously developed Galaxy toolset for whole-genome NGS analysis, CGtag. These reports may be adapted for outputs from any sequencing platform and any results, such as omics data, non-high throughput results and clinical variables.

Conclusions

iReport provides a secure, collaborative, and flexible web-based reporting system that is compatible with Galaxy (and non-Galaxy) generated content. We demonstrate its value with a real-life example of reporting genetic trio-analysis.

CGtag: complete genomics toolkit and annotation in a cloud-based Galaxy

BACKGROUND

Complete Genomics provides an open-source suite of command-line tools for the analysis of their CG-formatted mapped sequencing files. Determination of; for example, the functional impact of detected variants, requires annotation with various databases that often require command-line and/or programming experience; thus, limiting their use to the average research scientist. We have therefore implemented this CG toolkit, together with a number of annotation, visualisation and file manipulation tools in Galaxy called CGtag (Complete Genomics Toolkit and Annotation in a Cloud-based Galaxy).

FINDINGS

In order to provide research scientists with web-based, simple and accurate analytical and visualisation applications for the selection of candidate mutations from Complete Genomics data, we have implemented the open-source Complete Genomics tool set, CGATools, in Galaxy. In addition we implemented some of the most popular command-line annotation and visualisation tools to allow research scientists to select candidate pathological mutations (SNV, and indels). Furthermore, we have developed a cloud-based public Galaxy instance to host the CGtag toolkit and other associated modules.

CONCLUSIONS

CGtag provides a user-friendly interface to all research scientists wishing to select candidate variants from CG or other next-generation sequencing platforms' data. By using a cloud-based infrastructure, we can also assure sufficient and on-demand computation and storage resources to handle the analysis tasks. The tools are freely available for use from an NBIC/CTMM-TraIT (The Netherlands Bioinformatics Center/Center for Translational Molecular Medicine) cloud-based Galaxy instance, or can be installed to a local (production) Galaxy via the NBIC Galaxy tool shed.

Circulating cells as predictors of secondary manifestations of cardiovascular disease: design of the CIRCULATING CELLS study

Biomarkers for primary or secondary risk prediction of cardiovascular disease (CVD) are urgently needed to improve individual treatment and clinical trial design. The vast majority of biomarker discovery studies has concentrated on plasma/serum as an easily accessible source. Although numerous markers have been identified, their added predictive value on top of traditional risk factors has been limited, as the biological specimen does not specifically reflect expression profiles related with CVD progression and because the signal is often diluted by marker release from other organs. In contrast to serum markers, circulating cells serve as indicators of the actual disease state due to their active role in the pathogenesis of CVD and are responsible for the majority of secreted biomarkers. Therefore, the CIRCULATING CELLS study was initiated, focusing on the cellular effectors of atherosclerosis in the circulation. In total, 714 patients with coronary artery disease (CAD) symptoms were included. Blood cell fractions (monocytes, T-lymphocytes, platelets, granulocytes, PBMC) of all individual patients were isolated and stored for analysis. Concomitantly, extensive flow cytometric characterization of these populations was performed. From each patient, a detailed clinical profile together with extensive questionnaires about medical history and life style was obtained. Various high-throughput -omics approaches (protein, mRNA, miRNA) are currently being undertaken. Data will be integrated with advanced bioinformatics for discovery and validation of secondary risk markers for adverse events. Overall, the CIRCULATING CELLS study grants the interesting possibility that it will both identify novel biomarkers and provide useful insights into the pathophysiology of CAD in patients.

iFUSE: integrated fusion gene explorer

We present iFUSE (integrated fusion gene explorer), an online visualization tool that provides a fast and informative view of structural variation data and prioritizes those breaks likely representing fusion genes. This application uses calculated break points to determine fusion genes based on the latest annotation for genomic sequence information, and where relevant the structural variation (SV) events are annotated with predicted RNA and protein sequences. iFUSE takes as input a Complete Genomics (CG) junction file, a FusionMap fusion detection report file or a file already analysed and annotated by the iFUSE application on a previous occasion.

RESULTS

We demonstrate the use of iFUSE with case studies from tumour-normal SV detection derived from Complete Genomics whole-genome sequencing results.

AVAILABILITY

iFUSE is available as a web service at http://ifuse.erasmusmc.nl.

Gene fusions by chromothripsis of chromosome 5q in the VCaP prostate cancer cell line

The VCaP cell line is widely used in prostate cancer research as it is a unique model to study castrate resistant disease expressing high levels of the wild type androgen receptor and the TMPRSS2-ERG fusion transcript. Using next generation sequencing, we assembled the structural variations in VCaP genomic DNA and observed a massive number of genomic rearrangements along the q arm of chromosome 5, characteristic of chromothripsis. Chromothripsis is a recently recognized phenomenon characterized by extensive chromosomal shattering in a single catastrophic event, mainly detected in cancer cells. Various structural events identified on chromosome 5q of VCaP resulted in gene fusions. Out of the 18 gene fusion candidates tested, 15 were confirmed on genomic level. In our set of gene fusions, only rarely we observe microhomology flanking the breakpoints. On RNA level, only five transcripts were detected and NDUFAF2-MAST4 was the only resulting in an in-frame fusion transcript. Our data indicate that although a marker of genomic instability, chromothripsis might lead to only a limited number of functionally relevant fusion genes.

Comprehensive investigation of parameter choice in viral integration site analysis and its effects on the gene annotations produced

Introducing therapeutic genes into hematopoietic stem cells using retroviral vector-mediated gene transfer is an effective treatment for monogenic diseases. The risks of therapeutic gene integration include aberrant expression of a neighboring gene, resulting in oncogenesis at low frequencies (10(-7)-10(-6)/transduced cell). Mechanisms governing insertional mutagenesis are the subject of intensive ongoing studies that produce large amounts of sequencing data representing genomic regions flanking viral integration sites (IS). Validating and analyzing these data require automated bioinformatics applications. The exact methods used vary between applications, based on the requirements and preferences of the designer. The parameters used to analyze sequence data are capable of shaping the resulting integration site annotations, but a comprehensive examination of these effects is lacking. Here we present a web-based tool for integration site analysis, called Methods for Analyzing ViRal Integration Collections (MAVRIC), and use its highly customizable interface to look at how IS annotations can vary based on the analysis parameters. We used the integration data of the previously published adenosine deaminase severe combined immunodeficiency (ADA-SCID) gene therapy trials for evaluation of MAVRIC. The output illustrates how MAVRIC allows for direct multiparameter comparison of integration patterns. Careful analysis of the SCID data and reanalyses using different parameters for trimming, alignment, and repeat masking revealed the degree of variation that can be expected to arise due to changes in these parameters. We observed mainly small differences in annotation, with the largest effects caused by masking repeat sequences and by changing the size of the window around the IS.

Hypoxia-inducible factor 2α plays a critical role in the formation of alveoli and surfactant

Alveolarization of the developing lung is an important step toward the switch from intrauterine life to breathing oxygen-rich air after birth. The distal airways structurally change to minimize the gas exchange path, and Type II pneumocytes increase the production of surfactants, which are required to reduce surface tension at the air-liquid interface in the alveolus. Hypoxia-inducible factor 2α (Hif2α) is an oxygen-regulated transcription factor expressed in endothelial and Type II cells, and its expression increases toward the end of gestation. We investigated the role of Hif2α in Type II cells by conditionally expressing an oxygen-insensitive mutant of Hif2α in airway epithelial cells during development. Newborn mice expressing the mutant Hif2α were born alive but quickly succumbed to respiratory distress. Subsequent analysis of the lungs revealed dilated alveoli covered with enlarged, aberrant Type II cells and a diminished number of Type I cells. The Type II cells accumulated glycogen in part by increased glucose uptake via the up-regulation of the glucose transporter 1. Furthermore, the cells lacked two crucial enzymes involved in the metabolism of glycogen into surfactant lipids, lysophosphatidylcholine acyltransferase and ATP-binding cassette sub-family A member 3. We conclude that Hif2α is a key regulator in alveolar maturation and the production of phospholipids by Type II cells.

Functional gene-expression analysis shows involvement of schizophrenia-relevant pathways in patients with 22q11 deletion syndrome

22q11 Deletion Syndrome (22q11DS) is associated with dysmorphology and a high prevalence of schizophrenia-like symptoms. Several genes located on chromosome 22q11 have been linked to schizophrenia. The deletion is thought to disrupt the expression of multiple genes involved in maturation and development of neurons and neuronal circuits, and neurotransmission. We investigated whole-genome gene expression of Peripheral Blood Mononuclear Cells (PBMC's) of 8 22q11DS patients and 8 age- and gender-matched controls, to (1) investigate the expression levels of 22q11 genes and (2) to investigate whether 22q11 genes participate in functional genetic networks relevant to schizophrenia. Functional relationships between genes differentially expressed in patients (as identified by Locally Adaptive Statistical procedure (LAP) or satisfying p<0.05 and fold-change >1.5) were investigated with the Ingenuity Pathways Analysis (IPA). 14 samples (7 patients, 7 controls) passed quality controls. LAP identified 29 deregulated genes. Pathway analysis showed 262 transcripts differentially expressed between patients and controls. Functional pathways most disturbed were cell death, cell morphology, cellular assembly and organization, and cell-to-cell signaling. In addition, 10 canonical pathways were identified, among which the signal pathways for Natural Killer-cells, neurotrophin/Trk, neuregulin, axonal guidance, and Huntington's disease. Our findings support the use of 22q11DS as a research model for schizophrenia. We identified decreased expression of several genes (among which COMT, Ufd1L, PCQAP, and GNB1L) previously linked to schizophrenia as well as involvement of signaling pathways relevant to schizophrenia, of which Neurotrophin/Trk and neuregulin signaling seems to be especially notable.

Marked reduction of AKT1 expression and deregulation of AKT1-associated pathways in peripheral blood mononuclear cells of schizophrenia patients

Background

Recent studies have suggested that deregulated AKT1 signaling is associated with schizophrenia. We hypothesized that if this is indeed the case, we should observe both decreased AKT1 expression as well as deregulation of AKT1 regulated pathways in Peripheral Blood Mononuclear Cells (PBMCs) of schizophrenia patients.

Objectives

To examine PBMC expression levels of AKT1 in schizophrenia patients versus controls, and to examine whether functional biological processes in which AKT1 plays an important role are deregulated in schizophrenia patients.

Methods/Results

A case-control study, investigating whole-genome PBMC gene expression in male, recent onset (<5 years) schizophrenia patients (N = 41) as compared to controls (N = 29). Genes, differentially expressed between patients and controls were identified using ANOVA with Benjamini-Hochberg correction (false discovery rate (FDR) = 0.05). Functional aspects of the deregulated set of genes were investigated with the Ingenuity Pathway Analysis (IPA) Software Tool. We found significantly decreased PBMC expression of AKT1 (p<0.001, t = −4.25) in the patients. AKT1 expression was decreased in antipsychotic-free or -naive patients (N = 11), in florid psychotic (N = 20) and in remitted (N = 21) patients. A total of 1224 genes were differentially expressed between patients and controls (FDR = 0.05). Functional analysis of the entire deregulated gene set indicated deregulated canonical pathways involved in a large number of cellular processes: immune system, cell adhesion and neuronal guidance, neurotrophins and (neural) growth factors, oxidative stress and glucose metabolism, and apoptosis and cell-cycle regulation. Many of these processes are associated with AKT1.

Conclusions

We show significantly decreased PBMC gene expression of AKT1 in male, recent-onset schizophrenia patients. Our observations suggest that decreased PBMC AKT1 expression is a stable trait in recent onset, male schizophrenia patients. We identified several AKT related cellular processes which are potentially affected in these patients, a majority of which play a prominent role in current schizophrenia hypotheses.

Absence of common somatic alterations in genes on 1p and 19q in oligodendrogliomas

A common and histologically well defined subtype of glioma are the oligodendroglial brain tumors. Approximately 70% of all oligodendrogliomas have a combined loss of the entire 1p and 19q chromosomal arms. This remarkably high frequency suggests that the remaining arms harbor yet to be identified tumor suppressor genes. Identification of these causal genetic changes in oligodendrogliomas is important because they form direct targets for treatment. In this study we therefore performed targeted resequencing of all exons, microRNAs, splice sites and promoter regions residing on 1p and 19q on 7 oligodendrogliomas and 4 matched controls. Only one missense mutation was identified in a single sample in the ARHGEF16 gene. This mutation lies within- and disrupts the conserved PDZ binding domain. No similar ARHGEF16 mutations or deletions were found in a larger set of oligodendrogliomas. The absence of common somatic changes within genes located on 1p and 19q in three out of four samples indicates that no additional "second hit" is required to drive oncogenic transformation on either chromosomal arm.

Enhanced RAD21 cohesin expression confers poor prognosis and resistance to chemotherapy in high grade luminal, basal and HER2 breast cancers

INTRODUCTION

RAD21 is a component of the cohesin complex, which is essential for chromosome segregation and error-free DNA repair. We assessed its prognostic and predictive power in a cohort of in situ and invasive breast cancers, and its effect on chemosensitivity in vitro.

METHODS

RAD21 immunohistochemistry was performed on 345 invasive and 60 pure in situ carcinomas. Integrated genomic and transcriptomic analyses were performed on a further 48 grade 3 invasive cancers. Chemosensitivity was assessed in breast cancer cell lines with an engineered spectrum of RAD21 expression.

RESULTS

RAD21 expression correlated with early relapse in all patients (hazard ratio (HR) 1.74, 95% confidence interval (CI) 1.06 to 2.86, P = 0.029). This was due to the effect of grade 3 tumors (but not grade 1 or 2) in which RAD21 expression correlated with early relapse in luminal (P = 0.040), basal (P = 0.018) and HER2 (P = 0.039) groups. In patients treated with chemotherapy, RAD21 expression was associated with shorter overall survival (P = 0.020). RAD21 mRNA expression correlated with DNA copy number, with amplification present in 32% (7/22) of luminal, 31% (4/13) of basal and 22% (2/9) of HER2 grade 3 cancers. Variations in RAD21 mRNA expression in the clinical samples were reflected in the gene expression data from 36 breast cancer cell lines. Knockdown of RAD21 in the MDA-MB-231 breast cancer cell line significantly enhanced sensitivity to cyclophosphamide, 5-fluorouracil and etoposide. The findings for the former two drugs recapitulated the clinical findings.

CONCLUSIONS

RAD21 expression confers poor prognosis and resistance to chemotherapy in high grade luminal, basal and HER2 breast cancers. RAD21 may be a novel therapeutic target.

Gene expression-based classification of non-small cell lung carcinomas and survival prediction

Background

Current clinical therapy of non-small cell lung cancer depends on histo-pathological classification. This approach poorly predicts clinical outcome for individual patients. Gene expression profiling holds promise to improve clinical stratification, thus paving the way for individualized therapy.

Methodology and Principal Findings

A genome-wide gene expression analysis was performed on a cohort of 91 patients. We used 91 tumor- and 65 adjacent normal lung tissue samples. We defined sets of predictor genes (probe sets) with the expression profiles. The power of predictor genes was evaluated using an independent cohort of 96 non-small cell lung cancer- and 6 normal lung samples. We identified a tumor signature of 5 genes that aggregates the 156 tumor and normal samples into the expected groups. We also identified a histology signature of 75 genes, which classifies the samples in the major histological subtypes of non-small cell lung cancer. Correlation analysis identified 17 genes which showed the best association with post-surgery survival time. This signature was used for stratification of all patients in two risk groups. Kaplan-Meier survival curves show that the two groups display a significant difference in post-surgery survival time (p = 5.6E-6). The performance of the signatures was validated using a patient cohort of similar size (Duke University, n = 96). Compared to previously published prognostic signatures for NSCLC, the 17 gene signature performed well on these two cohorts.

Conclusions

The gene signatures identified are promising tools for histo-pathological classification of non-small cell lung cancer, and may improve the prediction of clinical outcome.

Abstract 808: Intrinsic gene expression profiles of gliomas are a better predictor of survival than histology

Gliomas are the most common primary brain tumors with heterogeneous morphology and variable prognosis. Treatment decisions in patients rely mainly on histological classification and clinical parameters. However, differences between histological subclasses and grades are subtle, and classifying gliomas is subject to a large inter-observer variability. To improve current classification standards, we have performed gene expression profiling on a large cohort of glioma samples of all histological subtypes and grades. We identified seven distinct molecular subgroups that correlate with survival. These include two favorable prognostic subgroups (median survival &gt;4.7 years), two with intermediate prognosis (median survival 1-4 years), two with poor prognosis (median survival &lt;1 year), and one control group. The intrinsic molecular subtypes of glioma are different from histological subgroups and correlate better to patient survival. The prognostic value of molecular subgroups was validated on five independent sample cohorts (TCGA, REMBRANDT, GSE12907, GSE4271, and Li et al.). The power of intrinsic subtyping is demonstrated by its ability to identify a subset of prognostically favorable tumors within an external dataset that contains only histologically confirmed glioblastomas. Specific genetic changes (EGFR amplification, IDH1 mutation, 1p/19q LOH) segregate in distinct molecular subgroups. We identified a subgroup with molecular features associated with secondary glioblastoma, suggesting that different genetic changes drive gene expression profiles. Finally, we assessed response to treatment in molecular subgroups. Our data provides compelling evidence that expression profiling is a more accurate and objective method to classify gliomas than histological classification. Molecular classification therefore may aid diagnosis and can guide clinical decision making.

Note: This abstract was not presented at the AACR 101st Annual Meeting 2010 because the presenter was unable to attend.

Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 808.

Transcription and chromatin organization of a housekeeping gene cluster containing an integrated beta-globin locus control region

The activity of locus control regions (LCR) has been correlated with chromatin decondensation, spreading of active chromatin marks, locus repositioning away from its chromosome territory (CT), increased association with transcription factories, and long-range interactions via chromatin looping. To investigate the relative importance of these events in the regulation of gene expression, we targeted the human β-globin LCR in two opposite orientations to a gene-dense region in the mouse genome containing mostly housekeeping genes. We found that each oppositely oriented LCR influenced gene expression on both sides of the integration site and over a maximum distance of 150 kilobases. A subset of genes was transcriptionally enhanced, some of which in an LCR orientation-dependent manner. The locus resides mostly at the edge of its CT and integration of the LCR in either orientation caused a more frequent positioning of the locus away from its CT. Locus association with transcription factories increased moderately, both for loci at the edge and outside of the CT. These results show that nuclear repositioning is not sufficient to increase transcription of any given gene in this region. We identified long-range interactions between the LCR and two upregulated genes and propose that LCR-gene contacts via chromatin looping determine which genes are transcriptionally enhanced.

Identification of differentially regulated splice variants and novel exons in glial brain tumors using exon expression arrays

Aberrant splice variants are involved in the initiation and/or progression of glial brain tumors. We therefore set out to identify splice variants that are differentially expressed between histologic subgroups of gliomas. Splice variants were identified using a novel platform that profiles the expression of virtually all known and predicted exons present in the human genome. Exon-level expression profiling was done on 26 glioblastomas, 22 oligodendrogliomas, and 6 control brain samples. Our results show that Human Exon arrays can identify subgroups of gliomas based on their histologic appearance and genetic aberrations. We next used our expression data to identify differentially expressed splice variants. In two independent approaches, we identified 49 and up to 459 exons that are differentially spliced between glioblastomas and oligodendrogliomas, a subset of which (47% and 33%) were confirmed by reverse transcription-PCR (RT-PCR). In addition, exon level expression profiling also identified >700 novel exons. Expression of approximately 67% of these candidate novel exons was confirmed by RT-PCR. Our results indicate that exon level expression profiling can be used to molecularly classify brain tumor subgroups, can identify differentially regulated splice variants, and can identify novel exons. The splice variants identified by exon level expression profiling may help to detect the genetic changes that cause or maintain gliomas and may serve as novel treatment targets.

Exon expression arrays as a tool to identify new cancer genes

Background

Identification of genes that are causally implicated in oncogenesis is a major goal in cancer research. An estimated 10–20% of cancer-related gene mutations result in skipping of one or more exons in the encoded transcripts. Here we report on a strategy to screen in a global fashion for such exon-skipping events using PAttern based Correlation (PAC). The PAC algorithm has been used previously to identify differentially expressed splice variants between two predefined subgroups. As genetic changes in cancer are sample specific, we tested the ability of PAC to identify aberrantly expressed exons in single samples.

Principal Findings

As a proof-of-principle, we tested the PAC strategy on human cancer samples of which the complete coding sequence of eight cancer genes had been screened for mutations. PAC detected all seven exon-skipping mutants among 12 cancer cell lines. PAC also identified exon-skipping mutants in clinical cancer specimens although detection was compromised due to heterogeneous (wild-type) transcript expression. PAC reduced the number of candidate genes/exons for subsequent mutational analysis by two to three orders of magnitude and had a substantial true positive rate. Importantly, of 112 randomly selected outlier exons, sequence analysis identified two novel exon skipping events, two novel base changes and 21 previously reported base changes (SNPs).

Conclusions

The ability of PAC to enrich for mutated transcripts and to identify known and novel genetic changes confirms its suitability as a strategy to identify candidate cancer genes.

TF Target Mapper: a BLAST search tool for the identification of Transcription Factor target genes

BACKGROUND

In the current era of high throughput genomics a major challenge is the genome-wide identification of target genes for specific transcription factors. Chromatin immunoprecipitation (ChIP) allows the isolation of in vivo binding sites of transcription factors and provides a powerful tool for examining gene regulation. Crosslinked chromatin is immunoprecipitated with antibodies against specific transcription factors, thus enriching for sequences bound in vivo by these factors in the immunoprecipitated DNA. Cloning and sequencing the immunoprecipitated sequences allows identification of transcription factor target genes. Routinely, thousands of such sequenced clones are used in BLAST searches to map their exact location in the genome and the genes located in the vicinity. These genes represent potential targets of the transcription factor of interest. Such bioinformatics analysis is very laborious if performed manually and for this reason there is a need for developing bioinformatic tools to automate and facilitate it.

RESULTS

In order to facilitate this analysis we generated TF Target Mapper (Transcription Factor Target Mapper). TF Target Mapper is a BLAST search tool allowing rapid extraction of annotated information on genes around each hit. It combines sequence cleaning/filtering, pattern searching and BLAST searches with extraction of information on genes located around each BLAST hit and comparisons of the output list of genes or gene ontology IDs with user-implemented lists. We successfully applied and tested TF Target Mapper to analyse sequences bound in vivo by the transcription factor GATA-1. We show that TF Target Mapper efficiently extracted information on genes around ChIPed sequences, thus identifying known (e.g. alpha-globin and zeta-globin) and potentially novel GATA-1 gene targets.

CONCLUSION

TF Target Mapper is a very efficient BLAST search tool that allows the rapid extraction of annotated information on the genes around each hit. It can contribute to the comprehensive bioinformatic transcriptome/regulome analysis, by providing insight into the mechanisms of action of specific transcription factors, thus helping to elucidate the pathways these factors regulate.

Gene expression profiles associated with treatment response in oligodendrogliomas

Oligodendrogliomas are a specific subtype of brain tumor of which the majority responds favorably to chemotherapy. In this study, we made use of expression profiling to identify chemosensitive oligodendroglial tumors. Correlation of expression profiles to loss of heterozygosity on 1p and 19q, common chromosomal aberrations associated with response to treatment, identified 376, 64, and 60 differentially expressed probe sets associated with loss of 1p, 19q or 1p, and 19q, respectively. Correlation of expression profiles to the tumors' response to treatment identified 16 differentially expressed probe sets. Because transcripts associated with chemotherapeutic response were identified independent of common chromosomal aberrations, expression profiling may be used as an alternative approach to the tumors' 1p status to identify chemosensitive oligodendroglial tumors. Finally, we correlated expression profiles to survival of the patient after diagnosis and identified 103 differentially expressed probe sets. The observation that many genes are differentially expressed between long and short survivors indicates that the genetic background of the tumor is an important factor in determining the prognosis of the patient. Furthermore, these transcripts can help identify patient subgroups that are associated with favorable prognosis. Our study is the first to correlate gene expression with chromosomal aberrations and clinical performance (response to treatment and survival) in oligodendrogliomas. The differentially expressed transcripts can help identify patient subgroups with good prognosis and those that will benefit from chemotherapeutic treatments.

Genomic and Expression Profiling of Human Spermatocytic Seminomas: Primary Spermatocyte as Tumorigenic Precursor and DMRT1 as Candidate Chromosome 9 Gene

Spermatocytic seminomas are solid tumors found solely in the testis of predominantly elderly individuals. We investigated these tumors using a genome-wide analysis for structural and numerical chromosomal changes through conventional karyotyping, spectral karyotyping, and array comparative genomic hybridization using a 32 K genomic tiling-path resolution BAC platform (confirmed by in situ hybridization). Our panel of five spermatocytic seminomas showed a specific pattern of chromosomal imbalances, mainly numerical in nature (range, 3-24 per tumor). Gain of chromosome 9 was the only consistent anomaly, which in one case also involved amplification of the 9p21.3-pter region. Parallel chromosome level expression profiling as well as microarray expression analyses (Affymetrix U133 plus 2.0) was also done. Unsupervised cluster analysis showed that a profile containing transcriptional data on 373 genes (difference of > or = 3.0-fold) is suitable for distinguishing these tumors from seminomas/dysgerminomas. The diagnostic markers SSX2-4 and POU5F1 (OCT3/OCT4), previously identified by us, were among the top discriminatory genes, thereby validating the experimental set-up. In addition, novel discriminatory markers suitable for diagnostic purposes were identified, including Deleted in Azospermia (DAZ). Although the seminomas/dysgerminomas were characterized by expression of stem cell-specific genes (e.g., POU5F1, PROM1/CD133, and ZFP42), spermatocytic seminomas expressed multiple cancer testis antigens, including TSP50 and CTCFL (BORIS), as well as genes known to be expressed specifically during prophase meiosis I (TCFL5, CLGN, and LDHc). This is consistent with different cells of origin, the primordial germ cell and primary spermatocyte, respectively. Based on the region of amplification defined on 9p and the associated expression plus confirmatory immunohistochemistry, DMRT1 (a male-specific transcriptional regulator) was identified as a likely candidate gene for involvement in the development of spermatocytic seminomas.

Sialin, an anion transporter defective in sialic acid storage diseases, shows highly variable expression in adult mouse brain, and is developmentally regulated

Sialin is a lysosomal membrane protein encoded by the SLC17A5 gene, which is mutated in patients with sialic acid storage diseases (SASD). To further understand the role of sialin in normal CNS development and in the progressive neuronal atrophy and dysmyelination seen in SASD, we investigated its normal cellular distribution in adult and developing mice. Overall, sialin showed granular immunoreactivity, consistent with a vesicular protein. Adult mice showed widespread sialin expression, including in the brain, heart, lung, and liver. High-level immunoreactivity was seen in the neuropil of the hippocampus, striatum, and cerebral cortex, as well as in the perikarya of cerebellar Purkinje cells, globus pallidus, and certain thalamic and brainstem nuclei. In mouse embryos, the highest levels of expression were observed in the nervous system. We discuss the possible role of sialin in normal development and in SASD pathogenesis, as a framework for further investigation of its function in these contexts.

New insights on human T cell development by quantitative T cell receptor gene rearrangement studies and gene expression profiling

To gain more insight into initiation and regulation of T cell receptor (TCR) gene rearrangement during human T cell development, we analyzed TCR gene rearrangements by quantitative PCR analysis in nine consecutive T cell developmental stages, including CD34⁺ lin⁻ cord blood cells as a reference. The same stages were used for gene expression profiling using DNA microarrays. We show that TCR loci rearrange in a highly ordered way (TCRD-TCRG-TCRB-TCRA) and that the initiating Dδ2-Dδ3 rearrangement occurs at the most immature CD34⁺CD38⁻CD1a⁻ stage. TCRB rearrangement starts at the CD34⁺CD38⁺CD1a⁻ stage and complete in-frame TCRB rearrangements were first detected in the immature single positive stage. TCRB rearrangement data together with the PTCRA (pTα) expression pattern show that human TCRβ-selection occurs at the CD34⁺CD38⁺CD1a⁺ stage. By combining the TCR rearrangement data with gene expression data, we identified candidate factors for the initiation/regulation of TCR recombination. Our data demonstrate that a number of key events occur earlier than assumed previously; therefore, human T cell development is much more similar to murine T cell development than reported before.

Detailed gene copy number and RNA expression analysis of the 17q12-23 region in primary breast cancers

Chromosome region 17q12-23 commonly shows an increase in DNA copy number in breast cancers, suggesting that several oncogenes are located at this site. We performed a high-resolution expression array and comparative genomic hybridization analysis of genes mapped to the entire 17q12-23 region, to identify novel candidate oncogenes. We identified 24 genes that showed significant overexpression in breast cancers with gain of 17q12-23, compared to cancers without gain. These genes included previously identified oncogenes, together with several novel candidate oncogenes. FISH analysis using specific gene probes hybridized to tissue arrays confirmed the underlying amplification of overexpressed genes. This high-resolution analysis of the 17q12-23 region indicates that several established and novel candidate oncogenes, including a Wnt-signaling pathway member, are amplified and overexpressed within individual primary breast cancer samples. We were also able to confirm the presence of two apparently separate and reciprocally amplified groups of genes within this region. Investigation of these genes and their functional interactions will facilitate our understanding of breast oncogenesis and optimal management of this disease.