Showing papers by "Katleen De Preter published in 2018"

Computational deconvolution of transcriptomics data from mixed cell populations.

Abstract: Summary Gene expression analyses of bulk tissues often ignore cell type composition as an important confounding factor, resulting in a loss of signal from lowly abundant cell types. In this review, we highlight the importance and value of computational deconvolution methods to infer the abundance of different cell types and/or cell type-specific expression profiles in heterogeneous samples without performing physical cell sorting. We also explain the various deconvolution scenarios, the mathematical approaches used to solve them and the effect of data processing and different confounding factors on the accuracy of the deconvolution results. Contact katleen.depreter@ugent.be. Supplementary information Supplementary data are available at Bioinformatics online.

Cross-Cohort Analysis Identifies a TEAD4-MYCN Positive Feedback Loop as the Core Regulatory Element of High-Risk Neuroblastoma.

Abstract: High-risk neuroblastomas show a paucity of recurrent somatic mutations at diagnosis. As a result, the molecular basis for this aggressive phenotype remains elusive. Recent progress in regulatory network analysis helped us elucidate disease-driving mechanisms downstream of genomic alterations, including recurrent chromosomal alterations. Our analysis identified three molecular subtypes of high-risk neuroblastomas, consistent with chromosomal alterations, and identified subtype-specific master regulator proteins that were conserved across independent cohorts. A 10-protein transcriptional module-centered around a TEAD4-MYCN positive feedback loop-emerged as the regulatory driver of the high-risk subtype associated with MYCN amplification. Silencing of either gene collapsed MYCN-amplified (MYCNAmp) neuroblastoma transcriptional hallmarks and abrogated viability in vitro and in vivo Consistently, TEAD4 emerged as a robust prognostic marker of poor survival, with activity independent of the canonical Hippo pathway transcriptional coactivators YAP and TAZ. These results suggest novel therapeutic strategies for the large subset of MYCN-deregulated neuroblastomas.Significance: Despite progress in understanding of neuroblastoma genetics, little progress has been made toward personalized treatment. Here, we present a framework to determine the downstream effectors of the genetic alterations sustaining neuroblastoma subtypes, which can be easily extended to other tumor types. We show the critical effect of disrupting a 10-protein module centered around a YAP/TAZ-independent TEAD4-MYCN positive feedback loop in MYCNAmp neuroblastomas, nominating TEAD4 as a novel candidate for therapeutic intervention. Cancer Discov; 8(5); 582-99. ©2018 AACR.This article is highlighted in the In This Issue feature, p. 517.

TBX2 is a neuroblastoma core regulatory circuitry component enhancing MYCN/FOXM1 reactivation of DREAM targets

Abstract: Chromosome 17q gains are almost invariably present in high-risk neuroblastoma cases. Here, we perform an integrative epigenomics search for dosage-sensitive transcription factors on 17q marked by H3K27ac defined super-enhancers and identify TBX2 as top candidate gene. We show that TBX2 is a constituent of the recently established core regulatory circuitry in neuroblastoma with features of a cell identity transcription factor, driving proliferation through activation of p21-DREAM repressed FOXM1 target genes. Combined MYCN/TBX2 knockdown enforces cell growth arrest suggesting that TBX2 enhances MYCN sustained activation of FOXM1 targets. Targeting transcriptional addiction by combined CDK7 and BET bromodomain inhibition shows synergistic effects on cell viability with strong repressive effects on CRC gene expression and p53 pathway response as well as several genes implicated in transcriptional regulation. In conclusion, we provide insight into the role of the TBX2 CRC gene in transcriptional dependency of neuroblastoma cells warranting clinical trials using BET and CDK7 inhibitors.

Cross-Cohort Analysis Identifies a TEAD4–MYCN Positive Feedback Loop as the Core Regulatory Element of High-Risk Neuroblastoma

Abstract: High-risk neuroblastomas show a paucity of recurrent somatic mutations at diagnosis. As a result, the molecular basis for this aggressive phenotype remains elusive. Recent progress in regulatory network analysis helped us elucidate disease-driving mechanisms downstream of genomic alterations, including recurrent chromosomal alterations. Our analysis identified three molecular subtypes of high-risk neuroblastomas, consistent with chromosomal alterations, and identified subtype-specific master regulator proteins that were conserved across independent cohorts. A 10-protein transcriptional module-centered around a TEAD4-MYCN positive feedback loop-emerged as the regulatory driver of the high-risk subtype associated with MYCN amplification. Silencing of either gene collapsed MYCN-amplified (MYCNAmp) neuroblastoma transcriptional hallmarks and abrogated viability in vitro and in vivo Consistently, TEAD4 emerged as a robust prognostic marker of poor survival, with activity independent of the canonical Hippo pathway transcriptional coactivators YAP and TAZ. These results suggest novel therapeutic strategies for the large subset of MYCN-deregulated neuroblastomas.Significance: Despite progress in understanding of neuroblastoma genetics, little progress has been made toward personalized treatment. Here, we present a framework to determine the downstream effectors of the genetic alterations sustaining neuroblastoma subtypes, which can be easily extended to other tumor types. We show the critical effect of disrupting a 10-protein module centered around a YAP/TAZ-independent TEAD4-MYCN positive feedback loop in MYCNAmp neuroblastomas, nominating TEAD4 as a novel candidate for therapeutic intervention. Cancer Discov; 8(5); 582-99. ©2018 AACR.This article is highlighted in the In This Issue feature, p. 517.

Genomic Amplifications and Distal 6q Loss: Novel Markers for Poor Survival in High-risk Neuroblastoma Patients.

Abstract: Background Neuroblastoma is characterized by substantial clinical heterogeneity. Despite intensive treatment, the survival rates of high-risk neuroblastoma patients are still disappointingly low. Somatic chromosomal copy number aberrations have been shown to be associated with patient outcome, particularly in low- and intermediate-risk neuroblastoma patients. To improve outcome prediction in high-risk neuroblastoma, we aimed to design a prognostic classification method based on copy number aberrations.

Network Modeling of microRNA–mRNA Interactions in Neuroblastoma Tumorigenesis Identifies miR-204 as a Direct Inhibitor of MYCN

Abstract: Neuroblastoma is a pediatric cancer of the sympathetic nervous system where MYCN amplification is a key indicator of poor prognosis. However, mechanisms by which MYCN promotes neuroblastoma tumorigenesis are not fully understood. In this study, we analyzed global miRNA and mRNA expression profiles of tissues at different stages of tumorigenesis from TH-MYCN transgenic mice, a model of MYCN-driven neuroblastoma. On the basis of a Bayesian learning network model in which we compared pretumor ganglia from TH-MYCN+/+ mice to age-matched wild-type controls, we devised a predicted miRNA-mRNA interaction network. Among the miRNA-mRNA interactions operating during human neuroblastoma tumorigenesis, we identified miR-204 as a tumor suppressor miRNA that inhibited a subnetwork of oncogenes strongly associated with MYCN-amplified neuroblastoma and poor patient outcome. MYCN bound to the miR-204 promoter and repressed miR-204 transcription. Conversely, miR-204 directly bound MYCN mRNA and repressed MYCN expression. miR-204 overexpression significantly inhibited neuroblastoma cell proliferation in vitro and tumorigenesis in vivo Together, these findings identify novel tumorigenic miRNA gene networks and miR-204 as a tumor suppressor that regulates MYCN expression in neuroblastoma tumorigenesis.Significance: Network modeling of miRNA-mRNA regulatory interactions in a mouse model of neuroblastoma identifies miR-204 as a tumor suppressor and negative regulator of MYCN. Cancer Res; 78(12); 3122-34. ©2018 AACR.

LDHA in Neuroblastoma Is Associated with Poor Outcome and Its Depletion Decreases Neuroblastoma Growth Independent of Aerobic Glycolysis

Abstract: Purpose: To investigate whether lactate dehydrogenase A (LDHA), an important component of the LDH tetramer crucial for aerobic glycolysis, is associated with patient outcome and constitutes a therapeutic target in neuroblastoma (NB). Experimental Design: Expression of LDHA mRNA and protein was determined in 709 and 110 NB patient samples, respectively, and correlated with survival and risk factors. LDHA and LDHB were depleted in human NB cell lines by CRISPR/Cas9 and shRNA, respectively, and aerobic glycolysis, clonogenicity, and tumorigenicity were determined. Expression of LDHA in relation to MYCN was measured in NB cell lines and in the TH-MYCN NB mouse model. Results: Expression of LDHA, both on the mRNA and the protein level, was significantly and independently associated with decreased patient survival. Predominant cytoplasmic localization of LDHA protein was associated with poor outcome. Amplification and expression of MYCN did not correlate with expression of LDHA in NB cell lines or TH-MYCN mice, respectively. Knockout of LDHA inhibited clonogenicity, tumorigenicity, and tumor growth without abolishing LDH activity or significantly decreasing aerobic glycolysis. Concomitant depletion of LDHA and the isoform LDHB ablated clonogenicity while not abrogating LDH activity or decreasing aerobic glycolysis. The isoform LDHC was not expressed. Conclusions: High expression of LDHA is independently associated with outcome of NB, and NB cells can be inhibited by depletion of LDHA or LDHB. This inhibition appears to be unrelated to LDH activity and aerobic glycolysis. Thus, investigations of inhibitory mechanisms beyond attenuation of aerobic glycolysis are warranted, both in NB and normal cells. Clin Cancer Res; 24(22); 5772–83. ©2018 AACR.

Integrated proximal proteomics reveals IRS2 as a determinant of cell survival in ALK-driven neuroblastoma

Abstract: Oncogenic anaplastic lymphoma kinase (ALK) is one of the few druggable targets in neuroblastoma, and therapy resistance to ALK-targeting tyrosine kinase inhibitors (TKIs) comprises an inevitable clinical challenge. Therefore, a better understanding of the oncogenic signaling network rewiring driven by ALK is necessary to improve and guide future therapies. Here, we performed quantitative mass spectrometry-based proteomics on neuroblastoma cells treated with one of three clinically relevant ALK TKIs (crizotinib, LDK378, or lorlatinib) or an experimentally used ALK TKI (TAE684) to unravel aberrant ALK signaling pathways. Our integrated proximal proteomics (IPP) strategy included multiple signaling layers, such as the ALK interactome, phosphotyrosine interactome, phosphoproteome, and proteome. We identified the signaling adaptor protein IRS2 (insulin receptor substrate 2) as a major ALK target and an ALK TKI-sensitive signaling node in neuroblastoma cells driven by oncogenic ALK. TKI treatment decreased the recruitment of IRS2 to ALK and reduced the tyrosine phosphorylation of IRS2. Furthermore, siRNA-mediated depletion of ALK or IRS2 decreased the phosphorylation of the survival-promoting kinase Akt and of a downstream target, the transcription factor FoxO3, and reduced the viability of three ALK-driven neuroblastoma cell lines. Collectively, our IPP analysis provides insight into the proximal architecture of oncogenic ALK signaling by revealing IRS2 as an adaptor protein that links ALK to neuroblastoma cell survival through the Akt-FoxO3 signaling axis.

Circulating microRNA biomarkers for metastatic disease in neuroblastoma patients

Abstract: In this study, the circulating miRNome from diagnostic neuroblastoma serum was assessed for identification of noninvasive biomarkers with potential in monitoring metastatic disease. After determining the circulating neuroblastoma miRNome, 743 miRNAs were screened in 2 independent cohorts of 131 and 54 patients. Evaluation of serum miRNA variance in a model testing for tumor stage, MYCN status, age at diagnosis, and overall survival revealed tumor stage as the most significant factor impacting miRNA abundance in neuroblastoma serum. Differential abundance analysis between patients with metastatic and localized disease revealed 9 miRNAs strongly associated with metastatic stage 4 disease in both patient cohorts. Increasing levels of these miRNAs were also observed in serum from xenografted mice bearing human neuroblastoma tumors. Moreover, murine serum miRNA levels were strongly associated with tumor volume. These findings were validated in longitudinal serum samples from metastatic neuroblastoma patients, where the 9 miRNAs were associated with disease burden and treatment response.

Meta-mining of copy number profiles of high-risk neuroblastoma tumors.

Abstract: Neuroblastoma, a pediatric tumor of the sympathetic nervous system, is predominantly driven by copy number aberrations, which predict survival outcome in global neuroblastoma cohorts and in low-risk cases. For high-risk patients there is still a need for better prognostic biomarkers. Via an international collaboration, we collected copy number profiles of 556 high-risk neuroblastomas generated on different array platforms. This manuscript describes the composition of the dataset, the methods used to process the data, including segmentation and aberration calling, and data validation. t-SNE analysis shows that samples cluster according to MYCN status, and shows a difference between array platforms. 97.3% of samples are characterized by the presence of segmental aberrations, in regions frequently affected in neuroblastoma. Focal aberrations affect genes known to be involved in neuroblastoma, such as ALK and LIN28B. To conclude, we compiled a unique large copy number dataset of high-risk neuroblastoma tumors, available via R2 and a Shiny web application. The availability of patient survival data allows to further investigate the prognostic value of copy number aberrations.

In silico discovery of a FOXM1 driven embryonal signaling pathway in therapy resistant neuroblastoma tumors.

Abstract: Chemotherapy resistance is responsible for high mortality rates in neuroblastoma. MYCN, an oncogenic driver in neuroblastoma, controls pluripotency genes including LIN28B. We hypothesized that enhanced embryonic stem cell (ESC) gene regulatory programs could mark tumors with high pluripotency capacity and subsequently increased risk for therapy failure. An ESC miRNA signature was established based on publicly available data. In addition, an ESC mRNA signature was generated including the 500 protein coding genes with the highest positive expression correlation with the ESC miRNA signature score in 200 neuroblastomas. High ESC m(i)RNA expression signature scores were significantly correlated with poor neuroblastoma patient outcome specifically in the subgroup of MYCN amplified tumors and stage 4 nonamplified tumors. Further data-mining identified FOXM1, as the major predicted driver of this ESC signature, controlling a large set of genes implicated in cell cycle control and DNA damage response. Of further interest, re-analysis of published data showed that MYCN transcriptionally activates FOXM1 in neuroblastoma cells. In conclusion, a novel ESC m(i)RNA signature stratifies neuroblastomas with poor prognosis, enabling the identification of therapy-resistant tumors. The finding that this signature is strongly FOXM1 driven, warrants for drug design targeted at FOXM1 or key components controlling this pathway.

Zipper plot : visualizing transcriptional activity of genomic regions

Abstract: Reconstructing transcript models from RNA-sequencing (RNA-seq) data and establishing these as independent transcriptional units can be a challenging task. Current state-of-the-art tools for long non-coding RNA (lncRNA) annotation are mainly based on evolutionary constraints, which may result in false negatives due to the overall limited conservation of lncRNAs. To tackle this problem we have developed the Zipper plot, a novel visualization and analysis method that enables users to simultaneously interrogate thousands of human putative transcription start sites (TSSs) in relation to various features that are indicative for transcriptional activity. These include publicly available CAGE-sequencing, ChIPsequencing and DNase-sequencing datasets. Our method only requires three tab-separated fields (chromosome, genomic coordinate of the TSS and strand) as input and generates a report that includes a detailed summary table, a Zipper plot and several statistics derived from this plot. Using the Zipper plot, we found evidence of transcription for a set of well-characterized lncRNAs and observed that fewer mono-exonic lncRNAs have CAGE peaks overlapping with their TSSs compared to multi-exonic lncRNAs. Our method is implemented using the statistical programming language R and is freely available as a webtool.

IncGraph: Incremental graphlet counting for topology optimisation.

Abstract: Motivation Graphlets are small network patterns that can be counted in order to characterise the structure of a network (topology). As part of a topology optimisation process, one could use graphlet counts to iteratively modify a network and keep track of the graphlet counts, in order to achieve certain topological properties. Up until now, however, graphlets were not suited as a metric for performing topology optimisation; when millions of minor changes are made to the network structure it becomes computationally intractable to recalculate all the graphlet counts for each of the edge modifications. Results IncGraph is a method for calculating the differences in graphlet counts with respect to the network in its previous state, which is much more efficient than calculating the graphlet occurrences from scratch at every edge modification made. In comparison to static counting approaches, our findings show IncGraph reduces the execution time by several orders of magnitude. The usefulness of this approach was demonstrated by developing a graphlet-based metric to optimise gene regulatory networks. IncGraph is able to quickly quantify the topological impact of small changes to a network, which opens novel research opportunities to study changes in topologies in evolving or online networks, or develop graphlet-based criteria for topology optimisation. Availability IncGraph is freely available as an open-source R package on CRAN (incgraph). The development version is also available on GitHub (rcannood/incgraph).

Circulating microRNA biomarkers for metastatic disease in neuroblastoma patients

Abstract: In this study, the circulating miRNome from diagnostic neuroblastoma serum was assessed for identification of non-invasive biomarkers with potential in monitoring metastatic disease. After determining the circulating neuroblastoma miRNome, 743 miRNAs were screened in two independent cohorts of 131 and 54 patients. Evaluation of serum miRNA variance in a model testing for tumor stage, MYCN status, age at diagnosis and overall survival, revealed tumor stage as the most significant factor impacting miRNA abundance in neuroblastoma serum. Differential expression analysis between patients with metastatic and localized disease revealed 9 miRNAs strongly associated with metastatic stage 4 disease in both patient cohorts. Increasing levels of these miRNAs were also observed in serum from xenografted mice bearing human neuroblastoma tumors. Moreover, murine serum miRNA levels were strongly associated with tumor volume, suggesting this miRNA signature may be applied to monitor disease burden.