A proteogenomic surfaceome study identifies DLK1 as an immunotherapeutic target in neuroblastoma.

Cancer immunotherapies have produced remarkable results in B-cell malignancies; however, optimal cell surface targets for many solid cancers remain elusive. Here, we present an integrative proteomic, transcriptomic, and epigenomic analysis of tumor specimens along with normal tissues to identify biologically relevant cell surface proteins that can serve as immunotherapeutic targets for neuroblastoma, an often-fatal childhood cancer of the developing nervous system. We apply this approach to human-derived cell lines (N=9) and cell/patient-derived xenograft (N=12) models of neuroblastoma. Plasma membrane-enriched mass spectrometry identified 1,461 cell surface proteins in cell lines and 1,401 in xenograft models, respectively. Additional proteogenomic analyses revealed 60 high-confidence candidate immunotherapeutic targets and we prioritized Delta-like canonical notch ligand 1 (DLK1) for further study. High expression of DLK1 directly correlated with the presence of a super-enhancer spanning the DLK1 locus. Robust cell surface expression of DLK1 was validated by immunofluorescence, flow cytometry, and immunohistochemistry. Short hairpin RNA mediated silencing of DLK1 in neuroblastoma cells resulted in increased cellular differentiation. ADCT-701, a DLK1-targeting antibody-drug conjugate (ADC), showed potent and specific cytotoxicity in DLK1-expressing neuroblastoma xenograft models. Moreover, DLK1 is highly expressed in several adult cancer types, including adrenocortical carcinoma (ACC), pheochromocytoma/paraganglioma (PCPG), hepatoblastoma, and small cell lung cancer (SCLC), suggesting potential clinical benefit beyond neuroblastoma. Taken together, our study demonstrates the utility of comprehensive cancer surfaceome characterization and credentials DLK1 as an immunotherapeutic target. Highlights: Plasma membrane enriched proteomics defines surfaceome of neuroblastomaMulti-omic data integration prioritizes DLK1 as a candidate immunotherapeutic target in neuroblastoma and other cancersDLK1 expression is driven by a super-enhancer DLK1 silencing in neuroblastoma cells results in cellular differentiation ADCT-701, a DLK1-targeting antibody-drug conjugate, shows potent and specific cytotoxicity in DLK1-expressing neuroblastoma preclinical models.

OpenPBTA: The Open Pediatric Brain Tumor Atlas.

Pediatric brain and spinal cancers are collectively the leading disease-related cause of death in children; thus, we urgently need curative therapeutic strategies for these tumors. To accelerate such discoveries, the Children's Brain Tumor Network (CBTN) and Pacific Pediatric Neuro-Oncology Consortium (PNOC) created a systematic process for tumor biobanking, model generation, and sequencing with immediate access to harmonized data. We leverage these data to establish OpenPBTA, an open collaborative project with over 40 scalable analysis modules that genomically characterize 1,074 pediatric brain tumors. Transcriptomic classification reveals universal TP53 dysregulation in mismatch repair-deficient hypermutant high-grade gliomas and TP53 loss as a significant marker for poor overall survival in ependymomas and H3 K28-mutant diffuse midline gliomas. Already being actively applied to other pediatric cancers and PNOC molecular tumor board decision-making, OpenPBTA is an invaluable resource to the pediatric oncology community.

Evaluation of the DLL3-targeting antibody-drug conjugate rovalpituzumab tesirine in preclinical models of neuroblastoma.

Neuroblastomas have neuroendocrine features and often show similar gene expression patterns to small cell lung cancer including high expression of delta-like ligand 3 (DLL3). Here we determine the efficacy of rovalpituzumab tesirine (Rova-T), an antibody drug conjugated (ADC) with a pyrrolobenzodiazepine (PBD) dimer toxin targeting DLL3, in preclinical models of human neuroblastoma. We evaluated DLL3 expression in RNA sequencing data sets and performed immunohistochemistry (IHC) on neuroblastoma patient derived xenograft (PDX), human neuroblastoma primary tumor and normal childhood tissue microarrays (TMAs). We then evaluated the activity of Rova-T against 11 neuroblastoma PDX models using varying doses and schedules and compared anti-tumor activity to expression levels. DLL3 mRNA was differentially overexpressed in neuroblastoma at comparable levels to small cell lung cancer, as well as Wilms and rhabdoid tumors. DLL3 protein was robustly expressed across the neuroblastoma PDX array, but membranous staining was variable. The human neuroblastoma array, however, showed staining in only 44% of cases, whereas no significant staining was observed in the normal childhood tissue array. Rova-T showed a clear dose response effect across the 11 models tested, with a single dose inducing a complete or partial response in 3/11 and stable disease in another 3/11 models. No overt signs of toxicity were observed, and there was no treatment-related mortality. Strong membranous staining was necessary, but not sufficient, for anti-tumor activity. Rova-T has activity in a subset of neuroblastoma preclinical models, but heterogeneous expression in these models and the near absence of expression seen in human tumors suggests that any DLL3-targeting clinical trial should be only performed with a robust companion diagnostic to evaluate DLL3 expression for patient selection.

MYC Levels Regulate Metastatic Heterogeneity in Pancreatic Adenocarcinoma.

The degree of metastatic disease varies widely among patients with cancer and affects clinical outcomes. However, the biological and functional differences that drive the extent of metastasis are poorly understood. We analyzed primary tumors and paired metastases using a multifluorescent lineage-labeled mouse model of pancreatic ductal adenocarcinoma (PDAC)-a tumor type in which most patients present with metastases. Genomic and transcriptomic analysis revealed an association between metastatic burden and gene amplification or transcriptional upregulation of MYC and its downstream targets. Functional experiments showed that MYC promotes metastasis by recruiting tumor-associated macrophages, leading to greater bloodstream intravasation. Consistent with these findings, metastatic progression in human PDAC was associated with activation of MYC signaling pathways and enrichment for MYC amplifications specifically in metastatic patients. Collectively, these results implicate MYC activity as a major determinant of metastatic burden in advanced PDAC. SIGNIFICANCE: Here, we investigate metastatic variation seen clinically in patients with PDAC and murine PDAC tumors and identify MYC as a major driver of this heterogeneity.This article is highlighted in the In This Issue feature, p. 275.

Targeted gene expression profiling of inverted papilloma and squamous cell carcinoma.

BACKGROUND: Inverted papilloma (IP) is a sinonasal tumor with a well-known potential for malignant transformation. The purpose of this study was to identify the genes and pathways associated with IP, with progression to carcinoma-in-situ and invasive carcinoma. METHODS: To determine genes and molecular pathways that may indicate progression and correlate with histologic changes, we analyzed six IP without dysplasia, five IP with carcinoma-in-situ, and 13 squamous cell carcinoma ex-IP by targeted sequencing. The HTG EdgeSeq Oncology Biomarker Panel coupled with next-generation sequencing was used to evaluate 2560 transcripts associated with solid tumors. RESULTS: Progressive upregulation of 11 genes were observed (CALD1, COL1A1, COL3A1, COL4A2, COL5A2, FN1, ITGA5, LGALS1, MMP11, SERPINH1, SPARC) in the order of invasive carcinoma > carcinoma-in-situ > IP without dysplasia. When compared with IP without dysplasia, more genes are differentially expressed in invasive carcinoma than carcinoma-in-situ samples (341 downregulated/333 upregulated vs. 195 downregulated/156 upregulated). Gene set enrichment analysis determined three gene sets in common between the cohorts (epithelial mesenchymal transition, extracellular matrix organization, and coagulation). CONCLUSIONS: Progressive upregulation of genes specific to IP malignant degeneration has significant clinical implications. This panel of 11 genes will improve concordance of histologic classification, which can directly impact treatment and patient outcomes. Additionally, future studies on larger tumor sets may observe upregulation in the gene panel that preceded histologic changes, which may be useful for further risk stratification.

A GPC2 antibody-drug conjugate is efficacious against neuroblastoma and small-cell lung cancer via binding a conformational epitope.

Glypican 2 (GPC2) is a MYCN-regulated, differentially expressed cell-surface oncoprotein and target for immune-based therapies in neuroblastoma. Here, we build on GPC2's immunotherapeutic attributes by finding that it is also a highly expressed, MYCN-driven oncoprotein on small-cell lung cancers (SCLCs), with significantly enriched expression in both the SCLC and neuroblastoma stem cell compartment.By solving the crystal structure of the D3-GPC2-Fab/GPC2 complex at 3.3 Å resolution, we further illustrate that the GPC2-directed antibody-drug conjugate (ADC; D3-GPC2-PBD), that links a human GPC2 antibody (D3) to DNA-damaging pyrrolobenzodiazepine (PBD) dimers, binds a tumor-specific, conformation-dependent epitope of the core GPC2 extracellular domain. We then show that this ADC induces durable neuroblastoma and SCLC tumor regression via induction of DNA damage, apoptosis, and bystander cell killing, notably with no signs of ADC-induced in vivo toxicity. These studies provide preclinical data to support the clinical translation of ADCs targeting GPC2.

Macrophages in SHH subgroup medulloblastoma display dynamic heterogeneity that varies with treatment modality.

Tumor-associated macrophages (TAMs) play an important role in tumor immunity and comprise of subsets that have distinct phenotype, function, and ontology. Transcriptomic analyses of human medulloblastoma, the most common malignant pediatric brain cancer, showed that medulloblastomas (MBs) with activated sonic hedgehog signaling (SHH-MB) have significantly more TAMs than other MB subtypes. Therefore, we examined MB-associated TAMs by single-cell RNA sequencing of autochthonous murine SHH-MB at steady state and under two distinct treatment modalities: molecular-targeted inhibitor and radiation. Our analyses reveal significant TAM heterogeneity, identify markers of ontologically distinct TAM subsets, and show the impact of brain microenvironment on the differentiation of tumor-infiltrating monocytes. TAM composition undergoes dramatic changes with treatment and differs significantly between molecular-targeted and radiation therapy. We identify an immunosuppressive monocyte-derived TAM subset that emerges with radiation therapy and demonstrate its role in regulating T cell and neutrophil infiltration in MB.

GAS7 Deficiency Promotes Metastasis in MYCN-Driven Neuroblastoma.

One of the greatest barriers to curative treatment of neuroblastoma is its frequent metastatic outgrowth prior to diagnosis, especially in cases driven by amplification of the MYCN oncogene. However, only a limited number of regulatory proteins that contribute to this complex MYCN-mediated process have been elucidated. Here we show that the growth arrest-specific 7 (GAS7) gene, located at chromosome band 17p13.1, is preferentially deleted in high-risk MYCN-driven neuroblastoma. GAS7 expression was also suppressed in MYCN-amplified neuroblastoma lacking 17p deletion. GAS7 deficiency led to accelerated metastasis in both zebrafish and mammalian models of neuroblastoma with overexpression or amplification of MYCN. Analysis of expression profiles and the ultrastructure of zebrafish neuroblastoma tumors with MYCN overexpression identified that GAS7 deficiency led to (i) downregulation of genes involved in cell-cell interaction, (ii) loss of contact among tumor cells as critical determinants of accelerated metastasis, and (iii) increased levels of MYCN protein. These results provide the first genetic evidence that GAS7 depletion is a critical early step in the cascade of events culminating in neuroblastoma metastasis in the context of MYCN overexpression. SIGNIFICANCE: Heterozygous deletion or MYCN-mediated repression of GAS7 in neuroblastoma releases an important brake on tumor cell dispersion and migration to distant sites, providing a novel mechanism underlying tumor metastasis in MYCN-driven neuroblastoma.See related commentary by Menard, p. 2815.

Epigenetic regulator BMI1 promotes alveolar rhabdomyosarcoma proliferation and constitutes a novel therapeutic target.

Rhabdomyosarcoma (RMS) is an aggressive pediatric soft tissue sarcoma. There are two main subtypes of RMS, alveolar rhabdomyosarcoma (ARMS) and embryonal rhabdomyosarcoma. ARMS typically encompasses fusion-positive rhabdomyosarcoma, which expresses either PAX3-FOXO1 or PAX7-FOXO1 fusion proteins. There are no targeted therapies for ARMS; however, recent studies have begun to illustrate the cooperation between epigenetic proteins and the PAX3-FOXO1 fusion, indicating that epigenetic proteins may serve as targets in ARMS. Here, we investigate the contribution of BMI1, given the established role of this epigenetic regulator in sustaining aggression in cancer. We determined that BMI1 is expressed across ARMS tumors, patient-derived xenografts, and cell lines. We depleted BMI1 using RNAi and inhibitors (PTC-209 and PTC-028) and found that this leads to a decrease in cell growth/increase in apoptosis in vitro, and delays tumor growth in vivo. Our data suggest that BMI1 inhibition activates the Hippo pathway via phosphorylation of LATS1/2 and subsequent reduction in YAP levels and YAP/TAZ target genes. These results identify BMI1 as a potential therapeutic vulnerability in ARMS and warrant further investigation of BMI1 in ARMS and other sarcomas.

annoFuse: an R Package to annotate, prioritize, and interactively explore putative oncogenic RNA fusions.

BACKGROUND: Gene fusion events are significant sources of somatic variation across adult and pediatric cancers and are some of the most clinically-effective therapeutic targets, yet low consensus of RNA-Seq fusion prediction algorithms makes therapeutic prioritization difficult. In addition, events such as polymerase read-throughs, mis-mapping due to gene homology, and fusions occurring in healthy normal tissue require informed filtering, making it difficult for researchers and clinicians to rapidly discern gene fusions that might be true underlying oncogenic drivers of a tumor and in some cases, appropriate targets for therapy. RESULTS: We developed annoFuse, an R package, and shinyFuse, a companion web application, to annotate, prioritize, and explore biologically-relevant expressed gene fusions, downstream of fusion calling. We validated annoFuse using a random cohort of TCGA RNA-Seq samples (N = 160) and achieved a 96% sensitivity for retention of high-confidence fusions (N = 603). annoFuse uses FusionAnnotator annotations to filter non-oncogenic and/or artifactual fusions. Then, fusions are prioritized if previously reported in TCGA and/or fusions containing gene partners that are known oncogenes, tumor suppressor genes, COSMIC genes, and/or transcription factors. We applied annoFuse to fusion calls from pediatric brain tumor RNA-Seq samples (N = 1028) provided as part of the Open Pediatric Brain Tumor Atlas (OpenPBTA) Project to determine recurrent fusions and recurrently-fused genes within different brain tumor histologies. annoFuse annotates protein domains using the PFAM database, assesses reciprocality, and annotates gene partners for kinase domain retention. As a standard function, reportFuse enables generation of a reproducible R Markdown report to summarize filtered fusions, visualize breakpoints and protein domains by transcript, and plot recurrent fusions within cohorts. Finally, we created shinyFuse for algorithm-agnostic interactive exploration and plotting of gene fusions. CONCLUSIONS: annoFuse provides standardized filtering and annotation for gene fusion calls from STAR-Fusion and Arriba by merging, filtering, and prioritizing putative oncogenic fusions across large cancer datasets, as demonstrated here with data from the OpenPBTA project. We are expanding the package to be widely-applicable to other fusion algorithms and expect annoFuse to provide researchers a method for rapidly evaluating, prioritizing, and translating fusion findings in patient tumors.

A transcriptome-based classifier to determine molecular subtypes in medulloblastoma.

Medulloblastoma is a highly heterogeneous pediatric brain tumor with five molecular subtypes, Sonic Hedgehog TP53-mutant, Sonic Hedgehog TP53-wildtype, WNT, Group 3, and Group 4, defined by the World Health Organization. The current mechanism for classification into these molecular subtypes is through the use of immunostaining, methylation, and/or genetics. We surveyed the literature and identified a number of RNA-Seq and microarray datasets in order to develop, train, test, and validate a robust classifier to identify medulloblastoma molecular subtypes through the use of transcriptomic profiling data. We have developed a GPL-3 licensed R package and a Shiny Application to enable users to quickly and robustly classify medulloblastoma samples using transcriptomic data. The classifier utilizes a large composite microarray dataset (15 individual datasets), an individual microarray study, and an RNA-Seq dataset, using gene ratios instead of gene expression measures as features for the model. Discriminating features were identified using the limma R package and samples were classified using an unweighted mean of normalized scores. We utilized two training datasets and applied the classifier in 15 separate datasets. We observed a minimum accuracy of 85.71% in the smallest dataset and a maximum of 100% accuracy in four datasets with an overall median accuracy of 97.8% across the 15 datasets, with the majority of misclassification occurring between the heterogeneous Group 3 and Group 4 subtypes. We anticipate this medulloblastoma transcriptomic subtype classifier will be broadly applicable to the cancer research and clinical communities.

Somatic structural variation targets neurodevelopmental genes and identifies SHANK2 as a tumor suppressor in neuroblastoma.

Neuroblastoma is a malignancy of the developing sympathetic nervous system that accounts for 12% of childhood cancer deaths. Like many childhood cancers, neuroblastoma shows a relative paucity of somatic single-nucleotide variants (SNVs) and small insertions and deletions (indels) compared to adult cancers. Here, we assessed the contribution of somatic structural variation (SV) in neuroblastoma using a combination of whole-genome sequencing (WGS) of tumor-normal pairs (n = 135) and single-nucleotide polymorphism (SNP) genotyping of primary tumors (n = 914). Our study design allowed for orthogonal validation and replication across platforms. SV frequency, type, and localization varied significantly among high-risk tumors. MYCN nonamplified high-risk tumors harbored an increased SV burden overall, including a significant excess of tandem duplication events across the genome. Genes disrupted by SV breakpoints were enriched in neuronal lineages and associated with phenotypes such as autism spectrum disorder (ASD). The postsynaptic adapter protein-coding gene, SHANK2, located on Chromosome 11q13, was disrupted by SVs in 14% of MYCN nonamplified high-risk tumors based on WGS and 10% in the SNP array cohort. Expression of SHANK2 was low across human-derived neuroblastoma cell lines and high-risk neuroblastoma tumors. Forced expression of SHANK2 in neuroblastoma cells resulted in significant growth inhibition (P = 2.6 × 10-2 to 3.4 × 10-5) and accelerated neuronal differentiation following treatment with all-trans retinoic acid (P = 3.1 × 10-13 to 2.4 × 10-30). These data further define the complex landscape of somatic structural variation in neuroblastoma and suggest that events leading to deregulation of neurodevelopmental processes, such as inactivation of SHANK2, are key mediators of tumorigenesis in this childhood cancer.

LIN28B promotes neuroblastoma metastasis and regulates PDZ binding kinase.

Neuroblastoma is an aggressive pediatric malignancy of the neural crest with suboptimal cure rates and a striking predilection for widespread metastases, underscoring the need to identify novel therapeutic vulnerabilities. We recently identified the RNA binding protein LIN28B as a driver in high-risk neuroblastoma and demonstrated it promotes oncogenic cell proliferation by coordinating a RAN-Aurora kinase A network. Here, we demonstrate that LIN28B influences another key hallmark of cancer, metastatic dissemination. Using a murine xenograft model of neuroblastoma dissemination, we show that LIN28B promotes metastasis. We demonstrate that this is in part due to the effects of LIN28B on self-renewal and migration, providing an understanding of how LIN28B shapes the metastatic phenotype. Our studies reveal that the let-7 family, which LIN28B inhibits, decreases self-renewal and migration. Next, we identify PDZ Binding Kinase (PBK) as a novel LIN28B target. PBK is a serine/threonine kinase that promotes the proliferation and self-renewal of neural stem cells and serves as an oncogenic driver in multiple aggressive malignancies. We demonstrate that PBK is both a novel direct target of let-7i and that MYCN regulates PBK expression, thus elucidating two oncogenic drivers that converge on PBK. Functionally, PBK promotes self-renewal and migration, phenocopying LIN28B. Taken together, our findings define a role for LIN28B in neuroblastoma metastasis and define the targetable kinase PBK as a potential novel vulnerability in metastatic neuroblastoma.

CAMKV Is a Candidate Immunotherapeutic Target in MYCN Amplified Neuroblastoma.

We developed a computational pipeline designed to use RNA sequencing (n = 136) and gene expression profiling (n = 250) data from neuroblastoma tumors to identify cell surface proteins predicted to be highly expressed in MYCN amplified neuroblastomas and with little or no expression in normal human tissues. We then performed ChIP-seq in the MYCN amplified cell lines KELLY, NB-1643, and NGP to identify gene promoters that are occupied by MYCN protein to define the intersection with the differentially-expressed gene list. We initially identified 116 putative immunotherapy targets with predicted transmembrane domains, with the most significant differentially-expressed of these being the calmodulin kinase-like vesicle-associated gene (CAMKV, p = 2 × 10-6). CAMKV encodes a protein that binds calmodulin in the presence of calcium, but lacks the kinase activity of other calmodulin kinase family members. We confirmed that CAMKV is selectively expressed in 7/7 MYCN amplified neuroblastoma cell lines and showed that the transcription of CAMKV is directly controlled by MYCN. From membrane fractionation and immunohistochemistry, we verified that CAMKV is membranous in MYCN amplified neuroblastoma cell lines and patient-derived xenografts. Finally, immunohistochemistry showed that CAMKV is not expressed on normal tissues outside of the central nervous system. Together, these data demonstrate that CAMKV is a differentially-expressed cell surface protein that is transcriptionally regulated by MYCN, making it a candidate for targeting with antibodies or antibody-drug conjugates that do not cross the blood brain barrier.

Mitochondrial DNA Haplogroups and Susceptibility to Neuroblastoma.

BACKGROUND: Neuroblastoma is a childhood malignancy that arises from the developing sympathetic nervous system. Although mitochondrial dysfunctions have been implicated in the pathophysiology of neuroblastoma, the role of mitochondrial DNA (mtDNA) has not been extensively investigated. METHODS: A total of 2404 Caucasian children diagnosed with neuroblastoma and 9310 ancestry-matched controls were recruited at the Children's Hospital of Philadelphia. The mtDNA haplogroups were identified from SNP array data of two independent cohorts. We conducted a case-control study to explore potential associations of mtDNA haplogroups with the susceptibility of neuroblastoma. The genetic effect of neuroblastoma was measured by odds ratios (ORs) of mitochondrial haplogroups. All tests were two-sided. RESULTS: Haplogroup K was statistically significantly associated with reduced risk of neuroblastoma in the discovery cohort consisting of 1474 cases and 5699 controls (OR = 0.72, 95% confidence interval [CI] = 0.57 to 0.90; P = 4.8 × 10-3). The association was replicated in an independent cohort (OR = 0.69, 95% CI = 0.53 to 0.92; P = .01) of 930 cases and 3611 controls. Pooled analysis was performed by combining the two data sets. The association remained highly statistically significant after correction for multiple testing (OR = 0.71, 95% CI = 0.59 to 0.84, P = 1.96 × 10-4, Pcorrected = .002). Further analysis focusing on neuroblastoma subtypes indicated haplogroup K was more associated with high-risk neuroblastoma (OR = 0.57, 95% CI = 0.43 to 0.76; P = 1.46 × 10-4) than low-risk and intermediate-risk neuroblastoma. CONCLUSIONS: Haplogroup K is an independent genetic factor associated with reduced risk of developing neuroblastoma in European descents. These findings provide new insights into the genetic basis of neuroblastoma, implicating mitochondrial DNA encoded proteins in the etiology of neuroblastoma.

NASA GeneLab Platform Utilized for Biological Response to Space Radiation in Animal Models.

Background: Ionizing radiation from galactic cosmic rays (GCR) is one of the major risk factors that will impact the health of astronauts on extended missions outside the protective effects of the Earth's magnetic field. The NASA GeneLab project has detailed information on radiation exposure using animal models with curated dosimetry information for spaceflight experiments. Methods: We analyzed multiple GeneLab omics datasets associated with both ground-based and spaceflight radiation studies that included in vivo and in vitro approaches. A range of ions from protons to iron particles with doses from 0.1 to 1.0 Gy for ground studies, as well as samples flown in low Earth orbit (LEO) with total doses of 1.0 mGy to 30 mGy, were utilized. Results: From this analysis, we were able to identify distinct biological signatures associating specific ions with specific biological responses due to radiation exposure in space. For example, we discovered changes in mitochondrial function, ribosomal assembly, and immune pathways as a function of dose. Conclusions: We provided a summary of how the GeneLab's rich database of omics experiments with animal models can be used to generate novel hypotheses to better understand human health risks from GCR exposures.

YAP1 Mediates Resistance to MEK1/2 Inhibition in Neuroblastomas with Hyperactivated RAS Signaling.

Relapsed neuroblastomas are enriched with activating mutations of the RAS-MAPK signaling pathway. The MEK1/2 inhibitor trametinib delays tumor growth but does not sustain regression in neuroblastoma preclinical models. Recent studies have implicated the Hippo pathway transcriptional coactivator protein YAP1 as an additional driver of relapsed neuroblastomas, as well as a mediator of trametinib resistance in other cancers. Here, we used a highly annotated set of high-risk neuroblastoma cellular models to modulate YAP1 expression and RAS pathway activation to test whether increased YAP1 transcriptional activity is a mechanism of MEK1/2 inhibition resistance in RAS-driven neuroblastomas. In NLF (biallelic NF1 inactivation) and SK-N-AS (NRAS Q61K) cell lines, trametinib caused a near-complete translocation of YAP1 protein into the nucleus. YAP1 depletion sensitized neuroblastoma cells to trametinib, while overexpression of constitutively active YAP1 protein induced trametinib resistance. Mechanistically, significant enhancement of G1-S cell-cycle arrest, mediated by depletion of MYC/MYCN and E2F transcriptional output, sensitized RAS-driven neuroblastomas to trametinib following YAP1 deletion. These findings underscore the importance of YAP activity in response to trametinib in RAS-driven neuroblastomas, as well as the potential for targeting YAP in a trametinib combination. SIGNIFICANCE: High-risk neuroblastomas with hyperactivated RAS signaling escape the selective pressure of MEK inhibition via YAP1-mediated transcriptional reprogramming and may be sensitive to combination therapies targeting both YAP1 and MEK.

Genomic Profiling of Childhood Tumor Patient-Derived Xenograft Models to Enable Rational Clinical Trial Design.

Accelerating cures for children with cancer remains an immediate challenge as a result of extensive oncogenic heterogeneity between and within histologies, distinct molecular mechanisms evolving between diagnosis and relapsed disease, and limited therapeutic options. To systematically prioritize and rationally test novel agents in preclinical murine models, researchers within the Pediatric Preclinical Testing Consortium are continuously developing patient-derived xenografts (PDXs)-many of which are refractory to current standard-of-care treatments-from high-risk childhood cancers. Here, we genomically characterize 261 PDX models from 37 unique pediatric cancers; demonstrate faithful recapitulation of histologies and subtypes; and refine our understanding of relapsed disease. In addition, we use expression signatures to classify tumors for TP53 and NF1 pathway inactivation. We anticipate that these data will serve as a resource for pediatric oncology drug development and will guide rational clinical trial design for children with cancer.

A comparison of survival analysis methods for cancer gene expression RNA-Sequencing data.

Identifying genetic biomarkers of patient survival remains a major goal of large-scale cancer profiling studies. Using gene expression data to predict the outcome of a patient's tumor makes biomarker discovery a compelling tool for improving patient care. As genomic technologies expand, multiple data types may serve as informative biomarkers, and bioinformatic strategies have evolved around these different applications. For categorical variables such as a gene's mutation status, biomarker identification to predict survival time is straightforward. However, for continuous variables like gene expression, the available methods generate highly-variable results, and studies on best practices are lacking. We investigated the performance of eight methods that deal specifically with continuous data. K-means, Cox regression, concordance index, D-index, 25th-75th percentile split, median-split, distribution-based splitting, and KaplanScan were applied to four RNA-sequencing (RNA-seq) datasets from the Cancer Genome Atlas. The reliability of the eight methods was assessed by splitting each dataset into two groups and comparing the overlap of the results. Gene sets that had been identified from the literature for a specific tumor type served as positive controls to assess the accuracy of each biomarker using receiver operating characteristic (ROC) curves. Artificial RNA-Seq data were generated to test the robustness of these methods under fixed levels of gene expression noise. Our results show that methods based on dichotomizing tend to have consistently poor performance while C-index, D-index, and k-means perform well in most settings. Overall, the Cox regression method had the strongest performance based on tests of accuracy, reliability, and robustness.