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

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

HTSplotter : an end-to-end data processing, analysis and visualisation tool for chemical and genetic in vitro perturbation screening

In biomedical research, high-throughput screening is often applied as it comes with automatization, higher-efficiency, and more and faster results. High-throughput screening experiments encompass drug, drug combination, genetic perturbagen or a combination of genetic and chemical perturbagen screens. These experiments are conducted in real-time assays over time or in an endpoint assay. The data analysis consists of data cleaning and structuring, as well as further data processing and visualisation, which, due to the amount of data, can easily become laborious, time-consuming and error-prone. Therefore, several tools have been developed to aid researchers in this process, but these typically focus on specific experimental set-ups and are unable to process data of several time points and genetic-chemical perturbagen screens. To meet these needs, we developed HTSplotter, a web tool and Python module that performs automatic data analysis and visualization of visualization of eitherendpoint or real-time assays from different high-throughput screening experiments: drug, drug combination, genetic perturbagen and genetic-chemical perturbagen screens. HTSplotter implements an algorithm based on conditional statements to identify experiment types and controls. After appropriate data normalization, including growth rate normalization, HTSplotter executes downstream analyses such as dose-response relationship and drug synergism assessment by the Bliss independence (BI), Zero Interaction Potency (ZIP) and Highest Single Agent (HSA) methods. All results are exported as a text file and plots are saved in a PDF file. The main advantage of HTSplotter over other available tools is the automatic analysis of genetic-chemical perturbagen screens and real-time assays where growth rate and perturbagen effect results are plotted over time. In conclusion, HTSplotter allows for the automatic end-to-end data processing, analysis and visualisation of various high-throughput in vitro cell culture screens, offering major improvements in terms of versatility, efficiency and time over existing tools

HTSplotter : an end-to-end data processing, analysis and visualisation tool for chemical and genetic in vitro perturbation screening

In biomedical research, high-throughput screening is often applied as it comes with automatization, higher-efficiency, and more and faster results. High-throughput screening experiments encompass drug, drug combination, genetic perturbagen or a combination of genetic and chemical perturbagen screens. These experiments are conducted in real-time assays over time or in an endpoint assay. The data analysis consists of data cleaning and structuring, as well as further data processing and visualisation, which, due to the amount of data, can easily become laborious, time consuming and error-prone. Therefore, several tools have been developed to aid researchers in this process, but these typically focus on specific experimental set-ups and are unable to process data of several time points and genetic-chemical perturbagen screens. To meet these needs, we developed HTSplotter, available as web tool and Python module, which performs automatic data analysis and visualisation of either endpoint or real-time assays from different high-throughput screening experiments: drug, drug combination, genetic perturbagen and genetic-chemical perturbagen screens. HTSplotter implements an algorithm based on conditional statements in order to identify experiment type and controls. After appropriate data normalization, including growth rate normalization, HTSplotter executes downstream analyses such as dose-response relationship and drug synergism assessment by the Bliss independence (BI), Zero Interaction Potency (ZIP) and Highest Single Agent (HAS) methods. All results are exported as a text file and plots are saved in a PDF file. The main advantage of HTSplotter over other available tools is the automatic analysis of genetic-chemical perturbagen screens and real-time assays where growth rate and perturbagen effect results are plotted over time. In conclusion, HTSplotter allows for the automatic end-to-end data processing, analysis and visualisation of various high-throughput in vitro cell culture screens, offering major improvements in terms of versatility, efficiency and time over existing tools

An embryonic stem cell activated FOXM1 transcriptional program marks ultra-high-risk primary neuroblastoma patients for FDI-6 small molecule inhibition

Introduction: Chemotherapy resistance is responsible for high mortality rates in high-risk neuroblastoma patients. MYCN is a major oncogenic driver in these tumors controlling pluripotency genes including LIN28B. Therefore, we hypothesized that enhanced embryonic stem cell (ESC) gene regulatory programs could mark tumors with increased risk for therapy failure enabling the selection of patients for novel targeted therapies. M&M: A microRNA expression ESC-signature was established based on publically available data. In addition, an mRNA ESC-signature of top 500 protein coding genes with highest positive correlation with the microRNA ESC-signature score was generated. Results: High ESC-signature scores were significantly correlated with worse neuroblastoma patient survival, both in the global patient cohort as well as in the subset of stage 4 tumors without MYCN-amplification. In addition, both in neuroblastoma and other embryonal tumors exhibiting MYCN-activation, the scores were significantly higher. This was confirmed in MYCN cell model systems where the scores altered upon MYCN-overexpression/knock-down. Using GSEA, we identified that genes implicated in DNA damage response and cell cycle control were strongly enriched in the signature. One of the genes in the signature is the transcription factor FOXM1, which is a master regulator driving those pathways. The upstream activator of FOXM1, MELK, was also part of the signature. Inhibition of FOXM1 in neuroblastoma cells using the small molecule FDI-6 significantly reduced cell viability. In addition, MELK inhibitors are currently tested in vitro and both FOXM1 and MELK inhibitors are evaluated in MYCN transgenic zebrafish models. Conclusion: A novel ESC-signature score marks neuroblastomas with poor prognosis enabling the identification of ultra-high-risk neuroblastoma patients that may benefit from targeted therapies using FOXM1 or MELK inhibitors

An embryonic stem cell activated FOXM1 transcriptional program marks ultra-high-risk primary neuroblastoma patients for FDI-6 small molecule inhibition

Introduction: Chemotherapy resistance is responsible for high mortality rates in high-risk neuroblastoma patients. MYCN is a major oncogenic driver in these tumors controlling pluripotency genes including LIN28B. Therefore, we hypothesized that enhanced embryonic stem cell (ESC) gene regulatory programs could mark tumors with increased risk for therapy failure enabling the selection of patients for novel targeted therapies. M&M: A microRNA expression ESC-signature was established based on publically available data. In addition, an mRNA ESC-signature of top 500 protein coding genes with highest positive correlation with the microRNA ESC-signature score was generated. Results: High ESC-signature scores were significantly correlated with worse neuroblastoma patient survival, both in the global patient cohort as well as in the subset of stage 4 tumors without MYCN-amplification. In addition, both in neuroblastoma and other embryonal tumors exhibiting MYCN-activation, the scores were significantly higher. This was confirmed in MYCN cell model systems where the scores altered upon MYCN-overexpression/knock-down. Using GSEA, we identified that genes implicated in DNA damage response and cell cycle control were strongly enriched in the signature. One of the genes in the signature is the transcription factor FOXM1, which is a master regulator driving those pathways. The upstream activator of FOXM1, MELK, was also part of the signature. Inhibition of FOXM1 in neuroblastoma cells using the small molecule FDI-6 significantly reduced cell viability. In addition, MELK inhibitors are currently tested in vitro and both FOXM1 and MELK inhibitors are evaluated in MYCN transgenic zebrafish models. Conclusion: A novel ESC-signature score marks neuroblastomas with poor prognosis enabling the identification of ultra-high-risk neuroblastoma patients that may benefit from targeted therapies using FOXM1 or MELK inhibitors

SynergyFinder Plus and HTSplotter heatmap at 72h.

A) HTSplotter heatmap over time and at final time point (72h) of dose-effect combination of prexasertib with MK-1775, maximum BI score of 0.56 at 72h. B) SynergyFinder Plus heatmap of dose-effect combination of prexasertib with MK-1775, with BI score of 17.29, p-value = 1.62x10-07. C) SynergyFinder Plus heatmap of dose-effect combination of BAY1895344 with MK-1775, with BI score of 4.51, with a p-value = 3.35x10-03. D) HTSplotter heatmap over time and at final time point (72h) of dose-effect combination of BAY1895344 with MK-1775, maximum BI score of 0.42 at 72h. HTSplotter has a fixed legend scale from -1 to 1.</p

XY- plot and growth rate plot from the genetic-chemical perturbation, SOX11 overexpression (OE) and celastrol.

A) Relative confluence is the confluence relative to the control. The dash line indicates the predicted combination effect, computed according to the BI method, Eq (4). Relative confluence inhibition over time of celastrol at 576.0 nM combined with SOX11 OE. The BI scores at 24h, 48h and 72h are 0.16, 0.16 and 0.35, respectively. B) The growth is computed according to Eq (7). Growth halt is indicated by the grey dash line. The SOX11 OE and celastrol conditions alone have growth rates lower than the control. The combination of both however, resulted in a almost halted growth rate. SOX11 OE growth rates at 24h, 48h and 72h are 0.65 h-1, 0.86 h-1, 0.79 h-1, respectively, the celastrol (576.0 nM) growth rates at 24h, 48h and 72h are 0.37 h-1, 0.55 h-1, 0.63 h-1, respectively, and the combination growth rates at 24h, 48h and 72h are 0.06 h-1, 0.06 h-1, 0.1 h-1, respectively.</p

The BRIP1/FANCJ DNA helicase is a druggable 17q driver oncogene involved in G-quadruplex induced replicative stress resistance in neuroblastoma

Chromosome 17q gain is by far the most common DNA copy number alteration in aggressive neuroblastoma (NB) but the causal 17q drivers remain to be identified due to the large size of the recurrently involved chromosome segments. Using integrated mRNA/CNV analysis of 211 NBs with the CONEXIC algorithm identified the DNA helicase BRIP1 (alias FANCJ) as top-ranked candidate 17q driver gene. Stable BRIP1 knock down in NB cell lines significantly reduced cell viability and colony forming capacity. In keeping with its role in DNA damage repair, knock down induced DNA damage as evidenced by increased γH2AX. Given that BRIP1 also unwinds G-quadruplex (G4) DNA structures, we hypothesized that increased BRIP1 levels could protect NB cells from MYCN induced replicative stress and install what we call "replicative stress resistance". Knock down increases RPA32 protein levels and decreases sensitivity to hydroxy urea induced replication fork stalling as measured by DNA combing. Next, we assumed that the dependency to G4 unwinding of cancer cells would render them sensitive to G4 stabilizing ligands and indeed observed strong effects on viability upon treatment with TMPYP4. Gene expression profiling after BRIP1 knock down confirmed enrichment for gene sets implicated in DNA replication and repair. Next, overexpression of BRIP1 in dbh-MYCN-eGFP transgenic zebrafish caused accelerated tumor formation. We are now using this model to screen for synergism between G4 stablising ligands such as TMPYP4 and pyridostatin with other small molecules by oral gavage in zebrafish to assess possible synergistic effects as a prelude to novel therapies for high risk NB. In conclusion, we propose BRIP1 as a major 17q cooperative driver oncogene in NB by providing replicative stress resistance to highly replicative NB cells at G4s, offering a new entry point for drugging of aggressive high risk NB