microRNA neural networks improve diagnosis of acute coronary syndrome (ACS).

BACKGROUND: Cardiac troponins are the preferred biomarkers of acute myocardial infarction. Despite superior sensitivity, serial testing of Troponins to identify patients suffering acute coronary syndromes is still required in many cases to overcome limited specificity. Moreover, unstable angina pectoris relies on reported symptoms in the troponin-negative group. In this study, we investigated genome-wide miRNA levels in a prospective cohort of patients with clinically suspected ACS and determined their diagnostic value by applying an in silico neural network. METHODS: PAXgene blood and serum samples were drawn and hsTnT was measured in patients at initial presentation to our Chest-Pain Unit. After clinical and diagnostic workup, patients were adjudicated by senior cardiologists in duty to their final diagnosis: STEMI, NSTEMI, unstable angina pectoris and non-ACS patients. ACS patients and a cohort of healthy controls underwent deep transcriptome sequencing. Machine learning was implemented to construct diagnostic miRNA classifiers. RESULTS: We developed a neural network model which incorporates 34 validated ACS miRNAs, showing excellent classification results. By further developing additional machine learning models and selecting the best miRNAs, we achieved an accuracy of 0.96 (95% CI 0.96-0.97), sensitivity of 0.95, specificity of 0.96 and AUC of 0.99. The one-point hsTnT value reached an accuracy of 0.89, sensitivity of 0.82, specificity of 0.96, and AUC of 0.96. CONCLUSIONS: Here we show the concept of neural network based biomarkers for ACS. This approach also opens the possibility to include multi-modal data points to further increase precision and perform classification of other ACS differential diagnoses.

Energy Metabolites as Biomarkers in Ischemic and Dilated Cardiomyopathy.

With more than 25 million people affected, heart failure (HF) is a global threat. As energy production pathways are known to play a pivotal role in HF, we sought here to identify key metabolic changes in ischemic- and non-ischemic HF by using a multi-OMICS approach. Serum metabolites and mRNAseq and epigenetic DNA methylation profiles were analyzed from blood and left ventricular heart biopsy specimens of the same individuals. In total we collected serum from n = 82 patients with Dilated Cardiomyopathy (DCM) and n = 51 controls in the screening stage. We identified several metabolites involved in glycolysis and citric acid cycle to be elevated up to 5.7-fold in DCM (p = 1.7 × 10-6). Interestingly, cardiac mRNA and epigenetic changes of genes encoding rate-limiting enzymes of these pathways could also be found and validated in our second stage of metabolite assessment in n = 52 DCM, n = 39 ischemic HF and n = 57 controls. In conclusion, we identified a new set of metabolomic biomarkers for HF. We were able to identify underlying biological cascades that potentially represent suitable intervention targets.

Mutation of the Na+/K+-ATPase Atp1a1a.1 causes QT interval prolongation and bradycardia in zebrafish.

The genetic underpinnings that orchestrate the vertebrate heart rate are not fully understood yet, but of high clinical importance, since diseases of cardiac impulse formation and propagation are common and severe human arrhythmias. To identify novel regulators of the vertebrate heart rate, we deciphered the pathogenesis of the bradycardia in the homozygous zebrafish mutant hiphop (hip) and identified a missense-mutation (N851K) in Na+/K+-ATPase α1-subunit (atp1a1a.1). N851K affects zebrafish Na+/K+-ATPase ion transport capacity, as revealed by in vitro pump current measurements. Inhibition of the Na+/K+-ATPase in vivo indicates that hip rather acts as a hypomorph than being a null allele. Consequently, reduced Na+/K+-ATPase function leads to prolonged QT interval and refractoriness in the hip mutant heart, as shown by electrocardiogram and in vivo electrical stimulation experiments. We here demonstrate for the first time that Na+/K+-ATPase plays an essential role in heart rate regulation by prolonging myocardial repolarization.

Epigenome-Wide Association Study Identifies Cardiac Gene Patterning and a Novel Class of Biomarkers for Heart Failure.

BACKGROUND: Biochemical DNA modification resembles a crucial regulatory layer among genetic information, environmental factors, and the transcriptome. To identify epigenetic susceptibility regions and novel biomarkers linked to myocardial dysfunction and heart failure, we performed the first multi-omics study in myocardial tissue and blood of patients with dilated cardiomyopathy and controls. METHODS: Infinium human methylation 450 was used for high-density epigenome-wide mapping of DNA methylation in left-ventricular biopsies and whole peripheral blood of living probands. RNA deep sequencing was performed on the same samples in parallel. Whole-genome sequencing of all patients allowed exclusion of promiscuous genotype-induced methylation calls. RESULTS: In the screening stage, we detected 59 epigenetic loci that are significantly associated with dilated cardiomyopathy (false discovery corrected P≤0.05), with 3 of them reaching epigenome-wide significance at P≤5×10-8. Twenty-seven (46%) of these loci could be replicated in independent cohorts, underlining the role of epigenetic regulation of key cardiac transcription regulators. Using a staged multi-omics study design, we link a subset of 517 epigenetic loci with dilated cardiomyopathy and cardiac gene expression. Furthermore, we identified distinct epigenetic methylation patterns that are conserved across tissues, rendering these CpGs novel epigenetic biomarkers for heart failure. CONCLUSIONS: The present study provides to our knowledge the first epigenome-wide association study in living patients with heart failure using a multi-omics approach.

Clinical genetics and outcome of left ventricular non-compaction cardiomyopathy.

AIMS: In this study, we aimed to clinically and genetically characterize LVNC patients and investigate the prevalence of variants in known and novel LVNC disease genes. INTRODUCTION: Left ventricular non-compaction cardiomyopathy (LVNC) is an increasingly recognized cause of heart failure, arrhythmia, thromboembolism, and sudden cardiac death. We sought here to dissect its genetic causes, phenotypic presentation and outcome. METHODS AND RESULTS: In our registry with follow-up of in the median 61 months, we analysed 95 LVNC patients (68 unrelated index patients and 27 affected relatives; definite familial LVNC = 23.5%) by cardiac phenotyping, molecular biomarkers and exome sequencing. Cardiovascular events were significantly more frequent in LVNC patients compared with an age-matched group of patients with non-ischaemic dilated cardiomyopathy (hazard ratio = 2.481, P = 0.002). Stringent genetic classification according to ACMG guidelines revealed that TTN, LMNA, and MYBPC3 are the most prevalent disease genes (13 patients are carrying a pathogenic truncating TTN variant, odds ratio = 40.7, Confidence interval = 21.6-76.6, P < 0.0001, percent spliced in 76-100%). We also identified novel candidate genes for LVNC. For RBM20, we were able to perform detailed familial, molecular and functional studies. We show that the novel variant p.R634L in the RS domain of RBM20 co-segregates with LVNC, leading to titin mis-splicing as revealed by RNA sequencing of heart tissue in mutation carriers, protein analysis, and functional splice-reporter assays. CONCLUSION: Our data demonstrate that the clinical course of symptomatic LVNC can be severe. The identified pathogenic variants and distribution of disease genes-a titin-related pathomechanism is found in every fourth patient-should be considered in genetic counselling of patients. Pathogenic variants in the nuclear proteins Lamin A/C and RBM20 were associated with worse outcome.

RNA splicing regulated by RBFOX1 is essential for cardiac function in zebrafish.

Alternative splicing is one of the major mechanisms through which the proteomic and functional diversity of eukaryotes is achieved. However, the complex nature of the splicing machinery, its associated splicing regulators and the functional implications of alternatively spliced transcripts are only poorly understood. Here, we investigated the functional role of the splicing regulator rbfox1 in vivo using the zebrafish as a model system. We found that loss of rbfox1 led to progressive cardiac contractile dysfunction and heart failure. By using deep-transcriptome sequencing and quantitative real-time PCR, we show that depletion of rbfox1 in zebrafish results in an altered isoform expression of several crucial target genes, such as actn3a and hug. This study underlines that tightly regulated splicing is necessary for unconstrained cardiac function and renders the splicing regulator rbfox1 an interesting target for investigation in human heart failure and cardiomyopathy.

Bias in High-Throughput Analysis of miRNAs and Implications for Biomarker Studies.

A certain degree of bias in high-throughput molecular technologies including microarrays and next-generation sequencing (NGS) is known. To quantify the actual impact of the biomarker discovery platform on miRNA profiles, we first performed a meta-analysis: raw data of 1 539 microarrays and 705 NGS blood-borne miRNomes were statistically evaluated, suggesting a substantial influence of the technology on biomarker profiles. We observed highly significant dependency of the miRNA nucleotide composition on the expression level. Higher expression in NGS was discovered for uracil-rich miRNAs (p = 7 × 10(-37)), while high expression in microarrays was found predominantly for guanine-rich miRNAs (p = 3 × 10(-33)). To verify the findings, 10 identical replicates of one individual were measured using NGS and microarrays (2 525 miRNAs from miRBase version 21). Overall, we calculated a correlation coefficient of 0.414 for both technologies. Detailed analysis however revealed that the correlation was observed only for miRNAs in the early miRBase versions (<8). The majority of miRNAs (2 013 from miRBase version 8 onward) was not correlated between microarray and NGS. Specifically, we observed 67 miRNAs with a median read count above 10 in NGS, while they were not detected in any of the 10 replicated array experiments. In contrast, 234 miRNAs were discovered in all 10 replicated array measurements but were not found in any of the NGS experiments of the same individual. While the first group had average guanine content of 22%, the latter group consisted of 41% of this nucleotide. Selected concordant and discordant miRNAs were tested in quantitative real-time-polymerase chain reaction (RT-qPCR) experiments again of the same individual, providing further evidence for the substantial bias depending on the base composition. As a consequence, biomarkers that have been discovered by specific high-throughout technologies have to be carefully considered. Especially for validation of the platform, the selection of reasonable candidates is essential.

Atlas of the clinical genetics of human dilated cardiomyopathy.

AIM: Numerous genes are known to cause dilated cardiomyopathy (DCM). However, until now technological limitations have hindered elucidation of the contribution of all clinically relevant disease genes to DCM phenotypes in larger cohorts. We now utilized next-generation sequencing to overcome these limitations and screened all DCM disease genes in a large cohort. METHODS AND RESULTS: In this multi-centre, multi-national study, we have enrolled 639 patients with sporadic or familial DCM. To all samples, we applied a standardized protocol for ultra-high coverage next-generation sequencing of 84 genes, leading to 99.1% coverage of the target region with at least 50-fold and a mean read depth of 2415. In this well characterized cohort, we find the highest number of known cardiomyopathy mutations in plakophilin-2, myosin-binding protein C-3, and desmoplakin. When we include yet unknown but predicted disease variants, we find titin, plakophilin-2, myosin-binding protein-C 3, desmoplakin, ryanodine receptor 2, desmocollin-2, desmoglein-2, and SCN5A variants among the most commonly mutated genes. The overlap between DCM, hypertrophic cardiomyopathy (HCM), and channelopathy causing mutations is considerably high. Of note, we find that >38% of patients have compound or combined mutations and 12.8% have three or even more mutations. When comparing patients recruited in the eight participating European countries we find remarkably little differences in mutation frequencies and affected genes. CONCLUSION: This is to our knowledge, the first study that comprehensively investigated the genetics of DCM in a large-scale cohort and across a broad gene panel of the known DCM genes. Our results underline the high analytical quality and feasibility of Next-Generation Sequencing in clinical genetic diagnostics and provide a sound database of the genetic causes of DCM.

miFRame: analysis and visualization of miRNA sequencing data in neurological disorders.

BACKGROUND: While in the past decades nucleic acid analysis has been predominantly carried out using quantitative low- and high-throughput approaches such as qRT-PCR and microarray technology, next-generation sequencing (NGS) with its single base resolution is now frequently applied in DNA and RNA testing. Especially for small non-coding RNAs such as microRNAs there is a need for analysis and visualization tools that facilitate interpretation of the results also for clinicians. METHODS: We developed miFRame, which supports the analysis of human small RNA NGS data. Our tool carries out different data analyses for known as well as predicted novel mature microRNAs from known precursors and presents the results in a well interpretable manner. Analyses include among others expression analysis of precursors and mature miRNAs, detection of novel precursors and detection of potential iso-microRNAs. Aggregation of results from different users moreover allows for evaluation whether remarkable results, such as novel mature miRNAs, are indeed specific for the respective experimental set-up or are frequently detected across a broad range of experiments. RESULTS: We demonstrate the capabilities of miFRame, which is freely available at http://www.ccb.uni-saarland.de/miframe on two studies, circulating biomarker screening for Multiple Sclerosis (cohort includes clinically isolated syndrome, relapse remitting MS, matched controls) as well as Alzheimer Disease (cohort includes Alzheimer Disease, Mild Cognitive Impairment, matched controls). Here, our tool allowed for an improved biomarker discovery by identifying likely false positive marker candidates.

A genome-wide association study identifies 6p21 as novel risk locus for dilated cardiomyopathy.

AIMS: Dilated cardiomyopathy (DCM) is one of the leading causes for cardiac transplantations and accounts for up to one-third of all heart failure cases. Since extrinsic and monogenic causes explain only a fraction of all cases, common genetic variants are suspected to contribute to the pathogenesis of DCM, its age of onset, and clinical progression. By a large-scale case-control genome-wide association study we aimed here to identify novel genetic risk loci for DCM. METHODS AND RESULTS: Applying a three-staged study design, we analysed more than 4100 DCM cases and 7600 controls. We identified and successfully replicated multiple single nucleotide polymorphism on chromosome 6p21. In the combined analysis, the most significant association signal was obtained for rs9262636 (P = 4.90 × 10(-9)) located in HCG22, which could again be replicated in an independent cohort. Taking advantage of expression quantitative trait loci (eQTL) as molecular phenotypes, we identified rs9262636 as an eQTL for several closely located genes encoding class I and class II major histocompatibility complex heavy chain receptors. CONCLUSION: The present study reveals a novel genetic susceptibility locus that clearly underlines the role of genetically driven, inflammatory processes in the pathogenesis of idiopathic DCM.

Systematic permutation testing in GWAS pathway analyses: identification of genetic networks in dilated cardiomyopathy and ulcerative colitis.

BACKGROUND: Genome wide association studies (GWAS) are applied to identify genetic loci, which are associated with complex traits and human diseases. Analogous to the evolution of gene expression analyses, pathway analyses have emerged as important tools to uncover functional networks of genome-wide association data. Usually, pathway analyses combine statistical methods with a priori available biological knowledge. To determine significance thresholds for associated pathways, correction for multiple testing and over-representation permutation testing is applied. RESULTS: We systematically investigated the impact of three different permutation test approaches for over-representation analysis to detect false positive pathway candidates and evaluate them on genome-wide association data of Dilated Cardiomyopathy (DCM) and Ulcerative Colitis (UC). Our results provide evidence that the gold standard - permuting the case-control status - effectively improves specificity of GWAS pathway analysis. Although permutation of SNPs does not maintain linkage disequilibrium (LD), these permutations represent an alternative for GWAS data when case-control permutations are not possible. Gene permutations, however, did not add significantly to the specificity. Finally, we provide estimates on the required number of permutations for the investigated approaches. CONCLUSIONS: To discover potential false positive functional pathway candidates and to support the results from standard statistical tests such as the Hypergeometric test, permutation tests of case control data should be carried out. The most reasonable alternative was case-control permutation, if this is not possible, SNP permutations may be carried out. Our study also demonstrates that significance values converge rapidly with an increasing number of permutations. By applying the described statistical framework we were able to discover axon guidance, focal adhesion and calcium signaling as important DCM-related pathways and Intestinal immune network for IgA production as most significant UC pathway.

Influence of the confounding factors age and sex on microRNA profiles from peripheral blood.

BACKGROUND: MicroRNAs (miRNAs) measured from blood samples are promising minimally invasive biomarker candidates that have been extensively studied in several case-control studies. However, the influence of age and sex as confounding variables remains largely unknown. METHODS: We systematically explored the impact of age and sex on miRNAs in a cohort of 109 physiologically unaffected individuals whose blood was characterized by microarray technology (stage 1). We also investigated an independent cohort from a different institution consisting of 58 physiologically unaffected individuals having a similar mean age but with a smaller age distribution. These samples were measured by use of high-throughput sequencing (stage 2). RESULTS: We detected 318 miRNAs that were significantly correlated with age in stage 1 and, after adjustment for multiple testing of 35 miRNAs, remained statistically significant. Regarding sex, 144 miRNAs showed significant dysregulation. Here, no miRNA remained significant after adjustment for multiple testing. In the high-throughput datasets of stage 2, we generally observed a smaller number of significant associations, mainly as an effect of the smaller cohort size and age distribution. Nevertheless, we found 7 miRNAs that were correlated with age, of which 5 were concordant with stage 1. CONCLUSIONS: The age distribution of individuals recruited for case-control studies needs to be carefully considered, whereas sex may be less confounding. To support the translation of miRNAs into clinical application, we offer a web-based application (http://www.ccb.uni-saarland.de/mirnacon) to test individual miRNAs or miRNA signatures for their likelihood of being influenced.

Multivariate miRNA signatures as biomarkers for non-ischaemic systolic heart failure.

AIMS: Non-ischaemic heart failure is one of the today's most prevalent cardiovascular disorders. Since modern pharmacotherapy has proved to be very effective in delaying disease progression and preventing death, imaging modalities and molecular biomarkers play an important role in early identification and clinical management as well as risk assessment of patients. The present study evaluated for the first time whole peripheral blood miRNAs as novel biomarker candidates for non-ischaemic heart failure with reduced ejection fraction (HF-REF). METHODS AND RESULTS: We assessed genome-wide miRNA expression profiles in 53 HF-REF patients and 39 controls. We could identify and validate several miRNAs that show altered expression levels in non-ischaemic HF-REF, discriminating cases from controls both as single markers or when combined in a multivariate signature. In addition, we demonstrate that the miRNAs of this signature significantly correlate with disease severity as indicated by left ventricular ejection fraction. CONCLUSION: Our data further denote that miRNAs are potential biomarkers for systolic heart failure. Since their detection levels in whole blood are also related to the degree of left ventricular dysfunction, they may serve as objective molecular tools to assess disease severity and prognosis.

Improving sudden cardiac death risk stratification in hypertrophic cardiomyopathy using established clinical variables and genetic information.

BACKGROUND AND AIMS: The cardiac societies of Europe and the United States have established different risk models for preventing sudden cardiac death (SCD) in hypertrophic cardiomyopathy (HCM). The aim of this study is to validate current SCD risk prediction methods in a German HCM cohort and to improve them by the addition of genotype information. METHODS: HCM patients without prior SCD or equivalent arrhythmic events ≥ 18 years of age were enrolled in an expert cardiomyopathy center in Germany. The primary endpoint was defined as SCD/-equivalent within 5 years of baseline evaluation. 5-year SCD-risk estimates and recommendations for ICD implantations, as defined by the ESC and AHA/ACC guidelines, were analyzed. Multivariate cox proportional hazards analyses were integrated with genetic findings as additive SCD risk. RESULTS: 283 patients were included and followed for in median 5.77 years (2.92; 8.85). A disease-causing variant was found in 138 (49%) patients. 14 (5%) patients reached the SCD endpoint (5-year incidence 4.9%). Kaplan-Meier survival analysis shows significantly lower overall SCD event-free survival for patients with an identified disease-causing variant (p < 0.05). The ESC HCM Risk-SCD model showed an area-under-the-curve (AUC) of 0.74 (95% CI 0.68-0.79; p < 0.0001) with a sensitivity of 0.29 (95% CI 0.08-0.58) and specificity of 0.83 (95% CI 0.78-0.88) for a risk estimate ≥ 6%/5-years. By comparison, the AHA/ACC HCM SCD risk stratification model showed an AUC of 0.70 (95% CI 0.65-0.76; p = 0.003) with a sensitivity of 0.93 (95% CI, 0.66-0.998) and specificity of 0.28 (95% CI 0.23-0.34) at the respective cut-off. The modified SCD Risk Score with genetic information yielded an AUC of 0.76 (95% CI 0.71-0.81; p < 0.0001) with a sensitivity of 0.86 (95% CI 0.57-0.98) and specificity of 0.69 (95% CI 0.63-0.74). The number-needed-to-treat (NNT) to prevent 1 SCD event by prophylactic ICD-implantation is 13 for the ESC model, 28 for AHA/ACC and 9 for the modified Genotype-model. CONCLUSION: This study confirms the performance of current risk models in clinical decision making. The integration of genetic findings into current SCD risk stratification methods seem feasible and can add in decision making, especially in borderline risk-groups. A subgroup of patients with high SCD risk remains unidentified by current risk scores.

Refining diagnostic microRNA signatures by whole-miRNome kinetic analysis in acute myocardial infarction.

BACKGROUND: Alterations in microRNA (miRNA) expression patterns in whole blood may be useful biomarkers of diverse cardiovascular disorders. We previously reported that miRNAs are significantly dysregulated in acute myocardial infarction (AMI) and applied machine-learning techniques to define miRNA subsets with high diagnostic power for AMI diagnosis. However, the kinetics of the time-dependent sensitivity of these novel miRNA biomarkers remained unknown. METHODS: To characterize temporal changes in the expressed human miRNAs (miRNome), we performed here the first whole-genome miRNA kinetic study in AMI patients. We measured miRNA expression levels at multiple time points (0, 2, 4, 12, 24 h after initial presentation) in patients with acute ST-elevation myocardial infarction by using microfluidic primer extension arrays and quantitative real-time PCR. As a prerequisite, all patients enrolled had to have cardiac troponin T concentrations <50 ng/L on admission as measured with a high-sensitivity assay. RESULTS: We found a subset of miRNAs to be significantly dysregulated both at initial presentation and during the course of AMI. Additionally, we identified novel miRNAs that are dysregulated early during myocardial infarction, such as miR-1915 and miR-181c*. CONCLUSIONS: The present proof-of-concept study provides novel insights into the dynamic changes of the human miRNome during AMI.

Protein kinase D2 controls cardiac valve formation in zebrafish by regulating histone deacetylase 5 activity.

BACKGROUND: The molecular mechanisms that guide heart valve formation are not well understood. However, elucidation of the genetic basis of congenital heart disease is one of the prerequisites for the development of tissue-engineered heart valves. METHODS AND RESULTS: We isolated here a mutation in zebrafish, bungee (bng(jh177)), which selectively perturbs valve formation in the embryonic heart by abrogating endocardial Notch signaling in cardiac cushions. We found by positional cloning that the bng phenotype is caused by a missense mutation (Y849N) in zebrafish protein kinase D2 (pkd2). The bng mutation selectively impairs PKD2 kinase activity and hence Histone deacetylase 5 phosphorylation, nuclear export, and inactivation. As a result, the expression of Histone deacetylase 5 target genes Krüppel-like factor 2a and 4a, transcription factors known to be pivotal for heart valve formation and to act upstream of Notch signaling, is severely downregulated in bungee (bng) mutant embryos. Accordingly, the expression of Notch target genes, such as Hey1, Hey2, and HeyL, is severely decreased in bng mutant embryos. Remarkably, downregulation of Histone deacetylase 5 activity in homozygous bng mutant embryos can rescue the mutant phenotype and reconstitutes notch1b expression in atrioventricular endocardial cells. CONCLUSIONS: We demonstrate for the first time that proper heart valve formation critically depends on Protein kinase D2-Histone deacetylase 5-Krüppel-like factor signaling.

Controlling my genome with my smartphone: first clinical experiences of the PROMISE system.

BACKGROUND: The development of Precision Medicine strategies requires high-dimensional phenotypic and genomic data, both of which are highly privacy-sensitive data types. Conventional data management systems lack the capabilities to sufficiently handle the expected large quantities of such sensitive data in a secure manner. PROMISE is a genetic data management concept that implements a highly secure platform for data exchange while preserving patient interests, privacy, and autonomy. METHODS: The concept of PROMISE to democratize genetic data was developed by an interdisciplinary team. It integrates a sophisticated cryptographic concept that allows only the patient to grant selective access to defined parts of his genetic information with single DNA base-pair resolution cryptography. The PROMISE system was developed for research purposes to evaluate the concept in a pilot study with nineteen cardiomyopathy patients undergoing genotyping, questionnaires, and longitudinal follow-up. RESULTS: The safety of genetic data was very important to 79%, and patients generally regarded the data as highly sensitive. More than half the patients reported that their attitude towards the handling of genetic data has changed after using the PROMISE app for 4 months (median). The patients reported higher confidence in data security and willingness to share their data with commercial third parties, including pharmaceutical companies (increase from 5 to 32%). CONCLUSION: PROMISE democratizes genomic data by a transparent, secure, and patient-centric approach. This clinical pilot study evaluating a genetic data infrastructure is unique and shows that patient's acceptance of data sharing can be increased by patient-centric decision-making.

Functional Therapeutic Target Validation Using Pediatric Zebrafish Xenograft Models.

The survival rate among children with relapsed tumors remains poor, due to tumor heterogeneity, lack of directly actionable tumor drivers and multidrug resistance. Novel personalized medicine approaches tailored to each tumor are urgently needed to improve cancer treatment. Current pediatric precision oncology platforms, such as the INFORM (INdividualized Therapy FOr Relapsed Malignancies in Childhood) study, reveal that molecular profiling of tumor tissue identifies targets associated with clinical benefit in a subgroup of patients only and should be complemented with functional drug testing. In such an approach, patient-derived tumor cells are exposed to a library of approved oncological drugs in a physiological setting, e.g., in the form of animal avatars injected with patient tumor cells. We used molecularly fully characterized tumor samples from the INFORM study to compare drug screen results of individual patient-derived cell models in functional assays: (i) patient-derived spheroid cultures within a few days after tumor dissociation; (ii) tumor cells reisolated from the corresponding mouse PDX; (iii) corresponding long-term organoid-like cultures and (iv) drug evaluation with the corresponding zebrafish PDX (zPDX) model. Each model had its advantage and complemented the others for drug hit and drug combination selection. Our results provide evidence that in vivo zPDX drug screening is a promising add-on to current functional drug screening in precision medicine platforms.

NIMA-related kinase 9 regulates the phosphorylation of the essential myosin light chain in the heart.

To adapt to changing hemodynamic demands, regulatory mechanisms modulate actin-myosin-kinetics by calcium-dependent and -independent mechanisms. We investigate the posttranslational modification of human essential myosin light chain (ELC) and identify NIMA-related kinase 9 (NEK9) to interact with ELC. NEK9 is highly expressed in the heart and the interaction with ELC is calcium-dependent. Silencing of NEK9 results in blunting of calcium-dependent ELC-phosphorylation. CRISPR/Cas9-mediated disruption of NEK9 leads to cardiomyopathy in zebrafish. Binding to ELC is mediated via the protein kinase domain of NEK9. A causal relationship between NEK9 activity and ELC-phosphorylation is demonstrated by genetic sensitizing in-vivo. Finally, we observe significantly upregulated ELC-phosphorylation in dilated cardiomyopathy patients and provide a unique map of human ELC-phosphorylation-sites. In summary, NEK9-mediated ELC-phosphorylation is a calcium-dependent regulatory system mediating cardiac contraction and inotropy.

Broad-Spectrum HDAC Inhibitors Promote Autophagy through FOXO Transcription Factors in Neuroblastoma.

Depending on context and tumor stage, deregulation of autophagy can either suppress tumorigenesis or promote chemoresistance and tumor survival. Histone deacetylases (HDACs) can modulate autophagy; however, the exact mechanisms are not fully understood. Here, we analyze the effects of the broad-spectrum HDAC inhibitors (HDACi) panobinostat and vorinostat on the transcriptional regulation of autophagy with respect to autophagy transcription factor activity (Transcription factor EB-TFEB, forkhead boxO-FOXO) and autophagic flux in neuroblastoma cells. In combination with the late-stage autophagic flux inhibitor bafilomycin A1, HDACis increase the number of autophagic vesicles, indicating an increase in autophagic flux. Both HDACi induce nuclear translocation of the transcription factors FOXO1 and FOXO3a, but not TFEB and promote the expression of pro-autophagic FOXO1/3a target genes. Moreover, FOXO1/3a knockdown experiments impaired HDACi treatment mediated expression of autophagy related genes. Combination of panobinostat with the lysosomal inhibitor chloroquine, which blocks autophagic flux, enhances neuroblastoma cell death in culture and hampers tumor growth in vivo in a neuroblastoma zebrafish xenograft model. In conclusion, our results indicate that pan-HDACi treatment induces autophagy in neuroblastoma at a transcriptional level. Combining HDACis with autophagy modulating drugs suppresses tumor growth of high-risk neuroblastoma cells. These experimental data provide novel insights for optimization of treatment strategies in neuroblastoma.