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.

Transcriptional immunogenomic analysis reveals distinct immunological clusters in paediatric nervous system tumours.

BACKGROUND: Cancer immunotherapies including immune checkpoint inhibitors and Chimeric Antigen Receptor (CAR) T-cell therapy have shown variable response rates in paediatric patients highlighting the need to establish robust biomarkers for patient selection. While the tumour microenvironment in adults has been widely studied to delineate determinants of immune response, the immune composition of paediatric solid tumours remains relatively uncharacterized calling for investigations to identify potential immune biomarkers. METHODS: To inform immunotherapy approaches in paediatric cancers with embryonal origin, we performed an immunogenomic analysis of RNA-seq data from 925 treatment-naïve paediatric nervous system tumours (pedNST) spanning 12 cancer types from three publicly available data sets. RESULTS: Within pedNST, we uncovered four broad immune clusters: Paediatric Inflamed (10%), Myeloid Predominant (30%), Immune Neutral (43%) and Immune Desert (17%). We validated these clusters using immunohistochemistry, methylation immune inference and segmentation analysis of tissue images. We report shared biology of these immune clusters within and across cancer types, and characterization of specific immune cell frequencies as well as T- and B-cell repertoires. We found no associations between immune infiltration levels and tumour mutational burden, although molecular cancer entities were enriched within specific immune clusters. CONCLUSIONS: Given the heterogeneity of immune infiltration within pedNST, our findings suggest personalized immunogenomic profiling is needed to guide selection of immunotherapeutic strategies.

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.

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.

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.

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.

Integrated Proteogenomic Characterization across Major Histological Types of Pediatric Brain Cancer.

We report a comprehensive proteogenomics analysis, including whole-genome sequencing, RNA sequencing, and proteomics and phosphoproteomics profiling, of 218 tumors across 7 histological types of childhood brain cancer: low-grade glioma (n = 93), ependymoma (32), high-grade glioma (25), medulloblastoma (22), ganglioglioma (18), craniopharyngioma (16), and atypical teratoid rhabdoid tumor (12). Proteomics data identify common biological themes that span histological boundaries, suggesting that treatments used for one histological type may be applied effectively to other tumors sharing similar proteomics features. Immune landscape characterization reveals diverse tumor microenvironments across and within diagnoses. Proteomics data further reveal functional effects of somatic mutations and copy number variations (CNVs) not evident in transcriptomics data. Kinase-substrate association and co-expression network analysis identify important biological mechanisms of tumorigenesis. This is the first large-scale proteogenomics analysis across traditional histological boundaries to uncover foundational pediatric brain tumor biology and inform rational treatment selection.

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.

Immunogenicity and Immune Silence in Human Cancer.

Despite recent advances in cancer immunotherapy, the process of immunoediting early in tumorigenesis remains obscure. Here, we employ a mathematical model that utilizes the Cancer Genome Atlas (TCGA) data to elucidate the contribution of individual mutations and HLA alleles to the immunoediting process. We find that common cancer mutations including BRAF-V600E and KRAS-G12D are predicted to bind none of the common HLA alleles, and are thus "immunogenically silent" in the human population. We identify regions of proteins that are not presented by HLA at a population scale, coinciding with frequently mutated hotspots in cancer, and other protein regions broadly presented across the population in which few mutations occur. We also find that 9/29 common HLA alleles contribute disproportionately to the immunoediting of early oncogenic mutations. These data provide insights into immune evasion of common driver mutations and a molecular basis for the association of particular HLA genotypes with cancer susceptibility.

RET receptor expression and interaction with TRK receptors in neuroblastomas.

Neuroblastomas (NBs) have heterogeneous clinical behavior, from spontaneous regression or differentiation to relentless progression. Evidence from our laboratory and others suggests that neurotrophin receptors contribute to these disparate behaviors. Previously, the role of TRK receptors in NB pathogenesis was investigated. In the present study, the expression of RET and its co­receptors in a panel of NB cell lines was investigated and responses to cognate ligands GDNF, NRTN, and ARTN with GFRα1­3 co­receptor expression, respectively were found to be correlated. RET expression was high in NBLS, moderate in SY5Y, low/absent in NBEBc1 and NLF cells. All cell lines expressed at least one of GFRα co­receptors. In addition, NBLS, SY5Y, NBEBc1 and NLF cells showed different morphological changes in response to ligands. As expected, activation of RET/GFRα3 by ARTN resulted in RET phosphorylation. Interestingly, activation of TrkA by its cognate ligand NGF resulted in RET phosphorylation at Y905, Y1015, and Y1062, and this was inhibited in a dose­dependent manner by the TRK inhibitor (CEP­701). Conversely, RET activation by ARTN in NBLS cells led to phosphorylation of TrkA. This suggests a physical association between RET and TRK proteins, and cross­talk between these two receptor pathways. Finally, RET, GFR and TRK expression in primary tumors was investigated and a significant association between RET, its co­receptors and TRK expression was demonstrated. Thus, the present data support a complex model of interacting neurotrophin receptor pathways in the regulation of cell growth and differentiation in NBs.

Selective inhibition of TGFß1 activation overcomes primary resistance to checkpoint blockade therapy by altering tumor immune landscape.

Despite breakthroughs achieved with cancer checkpoint blockade therapy (CBT), many patients do not respond to anti-programmed cell death-1 (PD-1) due to primary or acquired resistance. Human tumor profiling and preclinical studies in tumor models have recently uncovered transforming growth factor-ß (TGFß) signaling activity as a potential point of intervention to overcome primary resistance to CBT. However, the development of therapies targeting TGFß signaling has been hindered by dose-limiting cardiotoxicities, possibly due to nonselective inhibition of multiple TGFß isoforms. Analysis of mRNA expression data from The Cancer Genome Atlas revealed that TGFΒ1 is the most prevalent TGFß isoform expressed in many types of human tumors, suggesting that TGFß1 may be a key contributor to primary CBT resistance. To test whether selective TGFß1 inhibition is sufficient to overcome CBT resistance, we generated a high-affinity, fully human antibody, SRK-181, that selectively binds to latent TGFß1 and inhibits its activation. Coadministration of SRK-181-mIgG1 and an anti-PD-1 antibody in mice harboring syngeneic tumors refractory to anti-PD-1 treatment induced profound antitumor responses and survival benefit. Specific targeting of TGFß1 was also effective in tumors expressing more than one TGFß isoform. Combined SRK-181-mIgG1 and anti-PD-1 treatment resulted in increased intratumoral CD8+ T cells and decreased immunosuppressive myeloid cells. No cardiac valvulopathy was observed in a 4-week rat toxicology study with SRK-181, suggesting that selectively blocking TGFß1 activation may avoid dose-limiting toxicities previously observed with pan-TGFß inhibitors. These results establish a rationale for exploring selective TGFß1 inhibition to overcome primary resistance to CBT.

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.

Diagnosing Cornelia de Lange syndrome and related neurodevelopmental disorders using RNA sequencing.

PURPOSE: Neurodevelopmental disorders represent a frequent indication for clinical exome sequencing. Fifty percent of cases, however, remain undiagnosed even upon exome reanalysis. Here we show RNA sequencing (RNA-seq) on human B-lymphoblastoid cell lines (LCL) is highly suitable for neurodevelopmental Mendelian gene testing and demonstrate the utility of this approach in suspected cases of Cornelia de Lange syndrome (CdLS). METHODS: Genotype-Tissue Expression project transcriptome data for LCL, blood, and brain were assessed for neurodevelopmental Mendelian gene expression. Detection of abnormal splicing and pathogenic variants in these genes was performed with a novel RNA-seq diagnostic pipeline and using a validation CdLS-LCL cohort (n = 10) and test cohort of patients who carry a clinical diagnosis of CdLS but negative genetic testing (n = 5). RESULTS: LCLs share isoform diversity of brain tissue for a large subset of neurodevelopmental genes and express 1.8-fold more of these genes compared with blood (LCL, n = 1706; whole blood, n = 917). This enables testing of more than 1000 genetic syndromes. The RNA-seq pipeline had 90% sensitivity for detecting pathogenic events and revealed novel diagnoses such as abnormal splice products in NIPBL and pathogenic coding variants in BRD4 and ANKRD11. CONCLUSION: The LCL transcriptome enables robust frontline and/or reflexive diagnostic testing for neurodevelopmental disorders.

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.

Clinical utility of custom-designed NGS panel testing in pediatric tumors.

BACKGROUND: Somatic genetic testing is rapidly becoming the standard of care in many adult and pediatric cancers. Previously, the standard approach was single-gene or focused multigene testing, but many centers have moved towards broad-based next-generation sequencing (NGS) panels. Here, we report the laboratory validation and clinical utility of a large cohort of clinical NGS somatic sequencing results in diagnosis, prognosis, and treatment of a wide range of pediatric cancers. METHODS: Subjects were accrued retrospectively at a single pediatric quaternary-care hospital. Sequence analyses were performed on 367 pediatric cancer samples using custom-designed NGS panels over a 15-month period. Cases were profiled for mutations, copy number variations, and fusions identified through sequencing, and their clinical impact on diagnosis, prognosis, and therapy was assessed. RESULTS: NGS panel testing was incorporated meaningfully into clinical care in 88.7% of leukemia/lymphomas, 90.6% of central nervous system (CNS) tumors, and 62.6% of non-CNS solid tumors included in this cohort. A change in diagnosis as a result of testing occurred in 3.3% of cases. Additionally, 19.4% of all patients had variants requiring further evaluation for potential germline alteration. CONCLUSIONS: Use of somatic NGS panel testing resulted in a significant impact on clinical care, including diagnosis, prognosis, and treatment planning in 78.7% of pediatric patients tested in our institution. Somatic NGS tumor testing should be implemented as part of the routine diagnostic workup of newly diagnosed and relapsed pediatric cancer patients.

Targeting PARP-1 with Alpha-Particles Is Potently Cytotoxic to Human Neuroblastoma in Preclinical Models.

Alpha-emitters can be pharmacologically delivered for irradiation of single cancer cells, but cellular lethality could be further enhanced by targeting alpha-emitters directly to the nucleus. PARP-1 is a druggable protein in the nucleus that is overexpressed in neuroblastoma compared with normal tissues and is associated with decreased survival in high-risk patients. To exploit this, we have functionalized a PARP inhibitor (PARPi) with an alpha-emitter astatine-211. This approach offers enhanced cytotoxicity from conventional PARPis by not requiring enzymatic inhibition of PARP-1 to elicit DNA damage; instead, the alpha-particle directly induces multiple double-strand DNA breaks across the particle track. Here, we explored the efficacy of [211At]MM4 in multiple cancers and found neuroblastoma to be highly sensitive in vitro and in vivo Furthermore, alpha-particles delivered to neuroblastoma show antitumor effects and durable responses in a neuroblastoma xenograft model, especially when administered in a fractionated regimen. This work provides the preclinical proof of concept for an alpha-emitting drug conjugate that directly targets cancer chromatin as a therapeutic approach for neuroblastoma and perhaps other cancers.

An antibody-drug conjugate directed to the ALK receptor demonstrates efficacy in preclinical models of neuroblastoma.

Enthusiasm for the use of antibody-drug conjugates (ADCs) in cancer therapy has risen over the past few years. The success of this therapeutic approach relies on the identification of cell surface antigens that are widely and selectively expressed on tumor cells. Studies have shown that native ALK protein is expressed on the surface of most neuroblastoma cells, providing an opportunity for development of immune-targeting strategies. Clinically relevant antibodies for this target have not yet been developed. Here, we describe the development of an ALK-ADC, CDX-0125-TEI, which selectively targets both wild-type and mutated ALK-expressing neuroblastomas. CDX-0125-TEI exhibited efficient antigen binding and internalization, and cytotoxicity at picomolar concentrations in cells with different expression of ALK on the cell surface. In vivo studies showed that CDX-0125-TEI is effective against ALK wild-type and mutant patient-derived xenograft models. These data demonstrate that ALK is a bona fide immunotherapeutic target and provide a rationale for clinical development of an ALK-ADC approach for neuroblastomas and other ALK-expressing childhood cancers such as rhabdomyosarcomas.