A fast, affordable and minimally-invasive diagnostic test for Cancer of Unknown Primary (CUP) using DNA methylation profiling.

Currently, we cannot provide a conclusive diagnosis for 3 to 5% of people who are confronted with cancer. These patients have Cancer of Unknown Primary (CUP), i.e. a metastasized cancer for which the tissue-of-origin cannot be determined. Studies have shown that the DNA methylation profile is a unique 'fingerprint' that can be used to classify tumors. Here we use cfRRBS (cell-free reduced representation bisulfite sequencing), a technique that allows us to identify the methylation profile starting from minimal amounts of highly fragmented DNA, for CUP diagnosis on FFPE tissue and liquid biopsies. We collected 80 primary tumor FFPE samples covering 16 tumor entities together with 15 healthy plasma samples to use as custom cfRRBS reference dataset. Entity specific methylation regions (ESRs) are defined for each entity to build a classifier based on non-negative least squares (NNLS) deconvolution. This classification framework was tested on 30 FFPE, 19 plasma and 40 pleural and peritoneal effusion samples of both known metastatic tumors and clinical CUPs for which pathological investigation finally resulted in a cancer diagnosis. Using this framework, 27/30 FFPE (all CUPs) and 16/19 plasma samples (10/13 CUPs) obtained an accurate diagnosis, with a minimal DNA input of 400 pg. Of the 40 pleural and peritoneal effusion samples, diagnosis is possible in 9/27 samples with negative/inconclusive cytology (6/13 CUPs), showing that cfDNA methylation profiling could complement routine cytological analysis. However, a low "cfDNA - high molecular weight DNA ratio" has a considerable impact on the prediction accuracy. Moreover, the accuracy improves significantly if the predicted tumor percentage is higher than 7%. This proof-of-concept study shows the feasibility of using DNA methylation profiling on FFPE and liquid biopsy samples such as blood, ascites and pleural effusions in a fast and affordable way. Our novel RRBS-based technique requires minimal DNA input, can be performed in less than one week and is highly adaptable to specific diagnostic problems as we only use 5 FFPE references per tumor entity. We believe that cfRRBS methylation profiling could be a valuable addition to the pathologist's toolbox in the diagnosis of CUPs.

Computational deconvolution of DNA methylation data from mixed DNA samples.

In this review, we provide a comprehensive overview of the different computational tools that have been published for the deconvolution of bulk DNA methylation (DNAm) data. Here, deconvolution refers to the estimation of cell-type proportions that constitute a mixed sample. The paper reviews and compares 25 deconvolution methods (supervised, unsupervised or hybrid) developed between 2012 and 2023 and compares the strengths and limitations of each approach. Moreover, in this study, we describe the impact of the platform used for the generation of methylation data (including microarrays and sequencing), the applied data pre-processing steps and the used reference dataset on the deconvolution performance. Next to reference-based methods, we also examine methods that require only partial reference datasets or require no reference set at all. In this review, we provide guidelines for the use of specific methods dependent on the DNA methylation data type and data availability.

Evaluation of single-sample network inference methods for precision oncology.

A major challenge in precision oncology is to detect targetable cancer vulnerabilities in individual patients. Modeling high-throughput omics data in biological networks allows identifying key molecules and processes of tumorigenesis. Traditionally, network inference methods rely on many samples to contain sufficient information for learning, resulting in aggregate networks. However, to implement patient-tailored approaches in precision oncology, we need to interpret omics data at the level of individual patients. Several single-sample network inference methods have been developed that infer biological networks for an individual sample from bulk RNA-seq data. However, only a limited comparison of these methods has been made and many methods rely on 'normal tissue' samples as reference, which are not always available. Here, we conducted an evaluation of the single-sample network inference methods SSN, LIONESS, SWEET, iENA, CSN and SSPGI using transcriptomic profiles of lung and brain cancer cell lines from the CCLE database. The methods constructed functional gene networks with distinct network characteristics. Hub gene analyses revealed different degrees of subtype-specificity across methods. Single-sample networks were able to distinguish between tumor subtypes, as exemplified by node strength clustering, enrichment of known subtype-specific driver genes among hubs and differential node strength. We also showed that single-sample networks correlated better to other omics data from the same cell line as compared to aggregate networks. We conclude that single-sample network inference methods can reflect sample-specific biology when 'normal tissue' samples are absent and we point out peculiarities of each method.

Human iPSC modeling recapitulates in vivo sympathoadrenal development and reveals an aberrant developmental subpopulation in familial neuroblastoma.

Studies defining normal and disrupted human neural crest cell development have been challenging given its early timing and intricacy of development. Consequently, insight into the early disruptive events causing a neural crest related disease such as pediatric cancer neuroblastoma is limited. To overcome this problem, we developed an in vitro differentiation model to recapitulate the normal in vivo developmental process of the sympathoadrenal lineage which gives rise to neuroblastoma. We used human in vitro pluripotent stem cells and single-cell RNA sequencing to recapitulate the molecular events during sympathoadrenal development. We provide a detailed map of dynamically regulated transcriptomes during sympathoblast formation and illustrate the power of this model to study early events of the development of human neuroblastoma, identifying a distinct subpopulation of cell marked by SOX2 expression in developing sympathoblast obtained from patient derived iPSC cells harboring a germline activating mutation in the anaplastic lymphoma kinase (ALK) gene.

MYCN and SNRPD3 cooperate to maintain a balance of alternative splicing events that drives neuroblastoma progression.

Many of the pro-tumorigenic functions of the oncogene MYCN are attributed to its regulation of global gene expression programs. Alternative splicing is another important regulator of gene expression and has been implicated in neuroblastoma development, however, the molecular mechanisms remain unknown. We found that MYCN up-regulated the expression of the core spliceosomal protein, SNRPD3, in models of neuroblastoma initiation and progression. High mRNA expression of SNRPD3 in human neuroblastoma tissues was a strong, independent prognostic factor for poor patient outcome. Repression of SNRPD3 expression correlated with loss of colony formation in vitro and reduced tumorigenicity in vivo. The effect of SNRPD3 on cell viability was in part dependent on MYCN as an oncogenic co-factor. RNA-sequencing revealed a global increase in the number of genes being differentially spliced when MYCN was overexpressed. Surprisingly, depletion of SNRPD3 in the presence of overexpressed MYCN further increased differential splicing, particularly of cell cycle regulators, such as BIRC5 and CDK10. MYCN directly bound SNRPD3, and the protein arginine methyltransferase, PRMT5, consequently increasing SNRPD3 methylation. Indeed, the PRMT5 inhibitor, JNJ-64619178, reduced cell viability and SNRPD3 methylation in neuroblastoma cells with high SNRPD3 and MYCN expression. Our findings demonstrate a functional relationship between MYCN and SNRPD3, which maintains the fidelity of MYCN-driven alternative splicing in the narrow range required for neuroblastoma cell growth. SNRPD3 methylation and its protein-protein interface with MYCN represent novel therapeutic targets. Hypothetical model for SNRPD3 as a co-factor for MYCN oncogenesis. SNRPD3 and MYCN participate in a regulatory loop to balance splicing fidelity in neuroblastoma cells. First MYCN transactivates SNRPD3 to lead to high-level expression. Second, SNRPD3 and MYCN form a protein complex involving PRMT5. Third, this leads to balanced alterative splicing (AS) activitiy that is favorable to neuroblastoma. Together this forms as a therapeutic vulnerability where SNRPD3 perturbation or PRMT5 inhibitors are selectively toxic to neuroblastoma by conditionally disturbing splicing activity.

Mitotic Dysregulation at Tumor Initiation Creates a Therapeutic Vulnerability to Combination Anti-Mitotic and Pro-Apoptotic Agents for MYCN-Driven Neuroblastoma.

MYCN amplification occurs in approximately 20-30% of neuroblastoma patients and correlates with poor prognosis. The TH-MYCN transgenic mouse model mimics the development of human high-risk neuroblastoma and provides strong evidence for the oncogenic function of MYCN. In this study, we identified mitotic dysregulation as a hallmark of tumor initiation in the pre-cancerous ganglia from TH-MYCN mice that persists through tumor progression. Single-cell quantitative-PCR of coeliac ganglia from 10-day-old TH-MYCN mice revealed overexpression of mitotic genes in a subpopulation of premalignant neuroblasts at a level similar to single cells derived from established tumors. Prophylactic treatment using antimitotic agents barasertib and vincristine significantly delayed the onset of tumor formation, reduced pre-malignant neuroblast hyperplasia, and prolonged survival in TH-MYCN mice. Analysis of human neuroblastoma tumor cohorts showed a strong correlation between dysregulated mitosis and features of MYCN amplification, such as MYC(N) transcriptional activity, poor overall survival, and other clinical predictors of aggressive disease. To explore the therapeutic potential of targeting mitotic dysregulation, we showed that genetic and chemical inhibition of mitosis led to selective cell death in neuroblastoma cell lines with MYCN over-expression. Moreover, combination therapy with antimitotic compounds and BCL2 inhibitors exploited mitotic stress induced by antimitotics and was synergistically toxic to neuroblastoma cell lines. These results collectively suggest that mitotic dysregulation is a key component of tumorigenesis in early neuroblasts, which can be inhibited by the combination of antimitotic compounds and pro-apoptotic compounds in MYCN-driven neuroblastoma.

Case series on clinical applications of liquid biopsy in pediatric solid tumors: towards improved diagnostics and disease monitoring.

Background and aims: Solid tumors account for about 30% of all pediatric cancers. The diagnosis is typically based on histological and molecular analysis of a primary tumor biopsy. Liquid biopsies carry several advantages over conventional tissue biopsy. However, their use for genomic analysis and response monitoring of pediatric solid tumors is still in experimental stages and mostly performed retrospectively without direct impact on patient management. In this case series we discuss six clinical cases of children with a solid tumor for whom a liquid biopsy assay was performed and demonstrate the potential of liquid biopsy for future clinical decision making. Methods: We performed quantitative real-time PCR (RT-qPCR), droplet digital PCR (ddPCR) or reduced representation bisulphite sequencing of cell-free DNA (cfRRBS) on liquid biopsies collected from six pediatric patients with a solid tumor treated between 2017 and 2023 at the Princess Máxima Center for Pediatric Oncology in the Netherlands. Results were used to aid in clinical decision making by contribution to establish a diagnosis, by prognostication and response to therapy monitoring. Results: In three patients cfRRBS helped to establish the diagnosis of a rhabdomyosarcoma, an Ewing sarcoma and a neuroblastoma (case 1-3). In two patients, liquid biopsies were used for prognostication, by MYCN ddPCR in a patient with neuroblastoma and by RT-qPCR testing rhabdomyosarcoma-specific mRNA in bone marrow of a patient with a rhabdomyosarcoma (case 4 and 5). In case 6, mRNA testing demonstrated disease progression and assisted clinical decision making. Conclusion: This case series illustrates the value of liquid biopsy. We further demonstrate and recommend the use of liquid biopsies to be used in conjunction with conventional methods for the determination of metastatic status, prognostication and monitoring of treatment response in patients with pediatric solid tumors.

Circulating immune cell dynamics as outcome predictors for immunotherapy in non-small cell lung cancer.

The use of immune checkpoint inhibitors (ICIs) continues to transform the therapeutic landscape of non-small cell lung cancer (NSCLC), with these drugs now being evaluated at every stage of the disease. In contrast to these advances, little progress has been made with respect to reliable predictive biomarkers that can inform clinicians on therapeutic efficacy. All current biomarkers for outcome prediction, including PD-L1, tumor mutational burden or complex immune gene expression signatures, require access to tumor tissue. Besides the invasive nature of the sampling procedure, other disadvantages of tumor tissue biopsies are the inability to capture the complete spatial heterogeneity of the tumor and the difficulty to perform longitudinal follow-up on treatment. A concept emerges in which systemic immune events developing at a distance from the tumor reflect local response or resistance to immunotherapy. The importance of this cancer 'macroenvironment', which can be deciphered by comprehensive analysis of peripheral blood immune cell subsets, has been demonstrated in several cutting-edge preclinical reports, and is corroborated by intriguing data emerging from ICI-treated patients. In this review, we will provide the biological rationale underlying the potential of blood immune cell-based biomarkers in guiding treatment decision in immunotherapy-eligible NSCLC patients. Finally, we will describe new techniques that will facilitate the discovery of more immune cell subpopulations with potential to become predictive biomarkers, and reflect on ways and the remaining challenges to bring this type of analysis to the routine clinical care in the near future.

Memory of stochastic single-cell apoptotic signaling promotes chemoresistance in neuroblastoma.

Gene expression noise is known to promote stochastic drug resistance through the elevated expression of individual genes in rare cancer cells. However, we now demonstrate that chemoresistant neuroblastoma cells emerge at a much higher frequency when the influence of noise is integrated across multiple components of an apoptotic signaling network. Using a JNK activity biosensor with longitudinal high-content and in vivo intravital imaging, we identify a population of stochastic, JNK-impaired, chemoresistant cells that exist because of noise within this signaling network. Furthermore, we reveal that the memory of this initially random state is retained following chemotherapy treatment across a series of in vitro, in vivo, and patient models. Using matched PDX models established at diagnosis and relapse from individual patients, we show that HDAC inhibitor priming cannot erase the memory of this resistant state within relapsed neuroblastomas but improves response in the first-line setting by restoring drug-induced JNK activity within the chemoresistant population of treatment-naïve tumors.

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.

Cell-Free DNA as a Diagnostic and Prognostic Biomarker in Pediatric Rhabdomyosarcoma.

PURPOSE: Total cell-free DNA (cfDNA) and tumor-derived cfDNA (ctDNA) can be used to study tumor-derived genetic aberrations. We analyzed the diagnostic and prognostic potential of cfDNA and ctDNA, obtained from pediatric patients with rhabdomyosarcoma. METHODS: cfDNA was isolated from diagnostic plasma samples from 57 patients enrolled in the EpSSG RMS2005 study. To study the diagnostic potential, shallow whole genome sequencing (shWGS) and cell-free reduced representation bisulphite sequencing (cfRRBS) were performed in a subset of samples and all samples were tested using droplet digital polymerase chain reaction to detect methylated RASSF1A (RASSF1A-M). Correlation with outcome was studied by combining cfDNA RASSF1A-M detection with analysis of our rhabdomyosarcoma-specific RNA panel in paired cellular blood and bone marrow fractions and survival analysis in 56 patients. RESULTS: At diagnosis, ctDNA was detected in 16 of 30 and 24 of 26 patients using shallow whole genome sequencing and cfRRBS, respectively. Furthermore, 21 of 25 samples were correctly classified as embryonal by cfRRBS. RASSF1A-M was detected in 21 of 57 patients. The presence of RASSF1A-M was significantly correlated with poor outcome (the 5-year event-free survival [EFS] rate was 46.2% for 21 RASSF1A-M‒positive patients, compared with 84.9% for 36 RASSF1A-M‒negative patients [P < .001]). RASSF1A-M positivity had the highest prognostic effect among patients with metastatic disease. Patients both negative for RASSF1A-M and the rhabdomyosarcoma-specific RNA panel (28 of 56 patients) had excellent outcome (5-year EFS 92.9%), while double-positive patients (11/56) had poor outcome (5-year EFS 13.6%, P < .001). CONCLUSION: Analyzing ctDNA at diagnosis using various techniques is feasible in pediatric rhabdomyosarcoma and has potential for clinical use. Measuring RASSF1A-M in plasma at initial diagnosis correlated significantly with outcome, particularly when combined with paired analysis of blood and bone marrow using a rhabdomyosarcoma-specific RNA panel.

Opportunities and challenges in interpretable deep learning for drug sensitivity prediction of cancer cells.

In precision oncology, therapy stratification is done based on the patients' tumor molecular profile. Modeling and prediction of the drug response for a given tumor molecular type will further improve therapeutic decision-making for cancer patients. Indeed, deep learning methods hold great potential for drug sensitivity prediction, but a major problem is that these models are black box algorithms and do not clarify the mechanisms of action. This puts a limitation on their clinical implementation. To address this concern, many recent studies attempt to overcome these issues by developing interpretable deep learning methods that facilitate the understanding of the logic behind the drug response prediction. In this review, we discuss strengths and limitations of recent approaches, and suggest future directions that could guide further improvement of interpretable deep learning in drug sensitivity prediction in cancer research.

Digital PCR-based evaluation of nucleic acid extraction kit performance for the co-purification of cell-free DNA and RNA.

BACKGROUND: Blood plasma, one of the most studied liquid biopsies, contains various molecules that have biomarker potential for cancer detection, including cell-free DNA (cfDNA) and cell-free RNA (cfRNA). As the vast majority of cell-free nucleic acids in circulation are non-cancerous, a laboratory workflow with a high detection sensitivity of tumor-derived nucleic acids is a prerequisite for precision oncology. One way to meet this requirement is by the combined analysis of cfDNA and cfRNA from the same liquid biopsy sample. So far, no study has systematically compared the performance of cfDNA and cfRNA co-purification to increase sensitivity. RESULTS: First, we set up a framework using digital PCR (dPCR) technology to quantify cfDNA and cfRNA from human blood plasma in order to compare cfDNA/cfRNA co-purification kit performance. To that end, we optimized two dPCR duplex assays, designed to quantify both cfDNA and cfRNA with the same assays, by ensuring that primers and probes are located within a highly abundant exon. Next, we applied our optimized workflow to evaluate the co-purification performance of two manual and two semi-automated methods over a range of plasma input volumes (0.06-4 mL). Some kits result in higher nucleic acid concentrations in the eluate, while consuming only half of the plasma volume. The combined nucleic acid quantification systematically results in higher nucleic acid concentrations as compared to a parallel quantification of cfDNA and cfRNA in the eluate. CONCLUSIONS: We provide a framework to evaluate the performance of cfDNA/cfRNA co-purification kits and have tested two manual and two semi-automated co-purification kits in function of the available plasma input amount and the intended use of the nucleic acid eluate. We demonstrate that the combined quantification of cfDNA and cfRNA has a benefit compared to separate quantification. We foresee that the results of this study are instrumental for clinical applications to help increase mutation detection sensitivity, allowing improved disease detection and monitoring.

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.

Comprehensive RNA dataset of tissue and plasma from patients with esophageal cancer or precursor lesions.

In the past decades, the incidence of esophageal adenocarcinoma has increased dramatically in Western populations. Better understanding of disease etiology along with the identification of novel prognostic and predictive biomarkers are urgently needed to improve the dismal survival probabilities. Here, we performed comprehensive RNA (coding and non-coding) profiling in various samples from 17 patients diagnosed with esophageal adenocarcinoma, high-grade dysplastic or non-dysplastic Barrett's esophagus. Per patient, a blood plasma sample, and a healthy and disease esophageal tissue sample were included. In total, this comprehensive dataset consists of 102 sequenced libraries from 51 samples. Based on this data, 119 expression profiles are available for three biotypes, including miRNA (51), mRNA (51) and circRNA (17). This unique resource allows for discovery of novel biomarkers and disease mechanisms, comparison of tissue and liquid biopsy profiles, integration of coding and non-coding RNA patterns, and can serve as a validation dataset in other RNA landscaping studies. Moreover, structural RNA differences can be identified in this dataset, including protein coding mutations, fusion genes, and circular RNAs.

miR-99b-5p, miR-380-3p, and miR-485-3p are novel chemosensitizing miRNAs in high-risk neuroblastoma.

Neuroblastoma is a deadly childhood cancer arising in the developing sympathetic nervous system. High-risk patients are currently treated with intensive chemotherapy, which is curative in only 50% of children and leaves some surviving patients with life-long side effects. microRNAs (miRNAs) are critical regulators of neural crest development and are deregulated during neuroblastoma tumorigenesis, making miRNA-based drugs an attractive therapeutic avenue. A functional screen of >1,200 miRNA mimics was conducted in neuroblastoma cell lines to discover miRNAs that sensitized cells to low doses (30% inhibitory concentration [IC30]) of doxorubicin and vincristine chemotherapy used in the treatment of the disease. Three miRNAs, miR-99b-5p, miR-380-3p, and miR-485-3p, had potent chemosensitizing activity with doxorubicin in multiple models of high-risk neuroblastoma. These miRNAs underwent genomic loss in a subset of neuroblastoma patients, and low expression predicted poor survival outcome. In vitro functional assays revealed each of these miRNAs enhanced the anti-proliferative and pro-apoptotic effects of doxorubicin. We used RNA sequencing (RNA-seq) to show that miR-99b-5p represses neuroblastoma dependency genes LIN28B and PHOX2B both in vitro and in patient-derived xenograft (PDX) tumors. Luciferase reporter assays demonstrate that PHOX2B is a direct target of miR-99b-5p. We anticipate that restoring the function of the tumor-suppressive miRNAs discovered here may be a valuable therapeutic strategy for the treatment of neuroblastoma patients.

The feasibility of using liquid biopsies as a complementary assay for copy number aberration profiling in routinely collected paediatric cancer patient samples.

BACKGROUND: Paediatric tumours are often characterised by the presence of recurrent DNA copy number alterations (CNAs). These DNA copy number profiles, obtained from a tissue biopsy, can aid in the correct prognostic classification and therapeutic stratification of several paediatric cancer entities (e.g. MYCN amplification in neuroblastoma) and are part of the routine diagnostic practice. Liquid biopsies (LQBs) offer a potentially safer alternative for such invasive tumour tissue biopsies and can provide deeper insight into tumour heterogeneity. PROCEDURE: The robustness and reliability of LQB CNA analyses was evaluated. We performed retrospective CNA profiling using shallow whole-genome sequencing (sWGS) on paired plasma circulating cell-free DNA (cfDNA) and tissue DNA samples from routinely collected samples from paediatric patients (n = 128) representing different tumour entities, including osteosarcoma, Ewing sarcoma, rhabdomyosarcoma, Wilms tumour, brain tumours and neuroblastoma. RESULTS: Overall, we observed a good concordance between CNAs in tissue DNA and cfDNA. The main cause of CNA discordance was found to be low cfDNA sample quality (i.e. the ratio of cfDNA (<700 bp) and high molecular weight DNA (>700 bp)). Furthermore, CNAs were observed that were present in cfDNA and not in tissue DNA, or vice-versa. In neuroblastoma samples, no false-positives or false-negatives were identified for the detection of the prognostic marker MYCN amplification. CONCLUSION: In future prospective studies, CNA analysis on LQBs that are of sufficient quality can serve as a complementary assay for CNA analysis on tissue biopsies, as either cfDNA or tissue DNA can contain CNAs that cannot be identified in the other biomaterial.

From DNA Copy Number Gains and Tumor Dependencies to Novel Therapeutic Targets for High-Risk Neuroblastoma.

Neuroblastoma is a pediatric tumor arising from the sympatho-adrenal lineage and a worldwide leading cause of childhood cancer-related deaths. About half of high-risk patients die from the disease while survivors suffer from multiple therapy-related side-effects. While neuroblastomas present with a low mutational burden, focal and large segmental DNA copy number aberrations are highly recurrent and associated with poor survival. It can be assumed that the affected chromosomal regions contain critical genes implicated in neuroblastoma biology and behavior. More specifically, evidence has emerged that several of these genes are implicated in tumor dependencies thus potentially providing novel therapeutic entry points. In this review, we briefly review the current status of recurrent DNA copy number aberrations in neuroblastoma and provide an overview of the genes affected by these genomic variants for which a direct role in neuroblastoma has been established. Several of these genes are implicated in networks that positively regulate MYCN expression or stability as well as cell cycle control and apoptosis. Finally, we summarize alternative approaches to identify and prioritize candidate copy-number driven dependency genes for neuroblastoma offering novel therapeutic opportunities.

MEIS2 Is an Adrenergic Core Regulatory Transcription Factor Involved in Early Initiation of TH-MYCN-Driven Neuroblastoma Formation.

Roughly half of all high-risk neuroblastoma patients present with MYCN amplification. The molecular consequences of MYCN overexpression in this aggressive pediatric tumor have been studied for decades, but thus far, our understanding of the early initiating steps of MYCN-driven tumor formation is still enigmatic. We performed a detailed transcriptome landscaping during murine TH-MYCN-driven neuroblastoma tumor formation at different time points. The neuroblastoma dependency factor MEIS2, together with ASCL1, was identified as a candidate tumor-initiating factor and shown to be a novel core regulatory circuit member in adrenergic neuroblastomas. Of further interest, we found a KEOPS complex member (gm6890), implicated in homologous double-strand break repair and telomere maintenance, to be strongly upregulated during tumor formation, as well as the checkpoint adaptor Claspin (CLSPN) and three chromosome 17q loci CBX2, GJC1 and LIMD2. Finally, cross-species master regulator analysis identified FOXM1, together with additional hubs controlling transcriptome profiles of MYCN-driven neuroblastoma. In conclusion, time-resolved transcriptome analysis of early hyperplastic lesions and full-blown MYCN-driven neuroblastomas yielded novel components implicated in both tumor initiation and maintenance, providing putative novel drug targets for MYCN-driven neuroblastoma.