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.

SOX11 regulates SWI/SNF complex components as member of the adrenergic neuroblastoma core regulatory circuitry.

The pediatric extra-cranial tumor neuroblastoma displays a low mutational burden while recurrent copy number alterations are present in most high-risk cases. Here, we identify SOX11 as a dependency transcription factor in adrenergic neuroblastoma based on recurrent chromosome 2p focal gains and amplifications, specific expression in the normal sympatho-adrenal lineage and adrenergic neuroblastoma, regulation by multiple adrenergic specific (super-)enhancers and strong dependency on high SOX11 expression in adrenergic neuroblastomas. SOX11 regulated direct targets include genes implicated in epigenetic control, cytoskeleton and neurodevelopment. Most notably, SOX11 controls chromatin regulatory complexes, including 10 SWI/SNF core components among which SMARCC1, SMARCA4/BRG1 and ARID1A. Additionally, the histone deacetylase HDAC2, PRC1 complex component CBX2, chromatin-modifying enzyme KDM1A/LSD1 and pioneer factor c-MYB are regulated by SOX11. Finally, SOX11 is identified as a core transcription factor of the core regulatory circuitry (CRC) in adrenergic high-risk neuroblastoma with a potential role as epigenetic master regulator upstream of the CRC.

Targeted AURKA degradation: Towards new therapeutic agents for neuroblastoma.

Aurora kinase A (AURKA) is a well-established target in neuroblastoma (NB) due to both its catalytic functions during mitosis and its kinase-independent functions, including stabilization of the key oncoprotein MYCN. We present a structure-activity relationship (SAR) study of MK-5108-derived PROTACs against AURKA by exploring different linker lengths and exit vectors on the thalidomide moiety. PROTAC SK2188 induces the most potent AURKA degradation (DC50,24h 3.9 nM, Dmax,24h 89%) and shows an excellent binding and degradation selectivity profile. Treatment of NGP neuroblastoma cells with SK2188 induced concomitant MYCN degradation, high replication stress/DNA damage levels and apoptosis. Moreover, SK2188 significantly outperforms the parent inhibitor MK-5108 in a cell proliferation screen and patient-derived organoids. Furthermore, altering the attachment point of the PEG linker to the 5-position of thalidomide allowed us to identify a potent AURKA degrader with a linker as short as 2 PEG units. With this, our SAR-study provides interesting lead structures for further optimization and validation of AURKA degradation as a potential therapeutic strategy in neuroblastoma.

RRM2 enhances MYCN-driven neuroblastoma formation and acts as a synergistic target with CHK1 inhibition.

High-risk neuroblastoma, a pediatric tumor originating from the sympathetic nervous system, has a low mutation load but highly recurrent somatic DNA copy number variants. Previously, segmental gains and/or amplifications allowed identification of drivers for neuroblastoma development. Using this approach, combined with gene dosage impact on expression and survival, we identified ribonucleotide reductase subunit M2 (RRM2) as a candidate dependency factor further supported by growth inhibition upon in vitro knockdown and accelerated tumor formation in a neuroblastoma zebrafish model coexpressing human RRM2 with MYCN. Forced RRM2 induction alleviates excessive replicative stress induced by CHK1 inhibition, while high RRM2 expression in human neuroblastomas correlates with high CHK1 activity. MYCN-driven zebrafish tumors with RRM2 co-overexpression exhibit differentially expressed DNA repair genes in keeping with enhanced ATR-CHK1 signaling activity. In vitro, RRM2 inhibition enhances intrinsic replication stress checkpoint addiction. Last, combinatorial RRM2-CHK1 inhibition acts synergistic in high-risk neuroblastoma cell lines and patient-derived xenograft models, illustrating the therapeutic potential.

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.

Measurable impact of RNA quality on gene expression results from quantitative PCR.

Compromised RNA quality is suggested to lead to unreliable results in gene expression studies. Therefore, assessment of RNA integrity and purity is deemed essential prior to including samples in the analytical pipeline. This may be of particular importance when diagnostic, prognostic or therapeutic conclusions depend on such analyses. In this study, the comparative value of six RNA quality parameters was determined using a large panel of 740 primary tumour samples for which real-time quantitative PCR gene expression results were available. The tested parameters comprise of microfluidic capillary electrophoresis based 18S/28S rRNA ratio and RNA Quality Index value, HPRT1 5'-3' difference in quantification cycle (Cq) and HPRT1 3' Cq value based on a 5'/3' ratio mRNA integrity assay, the Cq value of expressed Alu repeat sequences and a normalization factor based on the mean expression level of four reference genes. Upon establishment of an innovative analytical framework to assess impact of RNA quality, we observed a measurable impact of RNA quality on the variation of the reference genes, on the significance of differential expression of prognostic marker genes between two cancer patient risk groups, and on risk classification performance using a multigene signature. This study forms the basis for further rational assessment of reverse transcription quantitative PCR based results in relation to RNA quality.