Pan-cancer genome and transcriptome analyses of 1,699 paediatric leukaemias and solid tumours

FLT3 overexpression in acute leukaemias: New insights into the search for molecular mechanisms

FLT3 overexpression is a recurrent event in various acute leukaemia subtypes. This transcriptional deregulation is important to define the prognostic risk for many patients. Of note, the molecular mechanisms leading to this gene upregulation are unknown for a substantial number of cases. In this Mini-Review, we highlight the role of FLT3 overexpression in acute leukaemia and discuss emerging mechanisms accounting for this upregulation. The benefits of using targeted therapy are also addressed in the overexpression context, posing other therapeutic possibilities based on state-of-the-art knowledge that could be considered for future research.

Using singscore to predict mutation status in acute myeloid leukemia from transcriptomic signatures

Advances in RNA sequencing (RNA-seq) technologies that measure the transcriptome of biological samples have revolutionised our ability to understand transcriptional regulatory programs that underpin diseases such as cancer. We recently published singscore - a single sample, rank-based gene set scoring method which quantifies how concordant the transcriptional profile of individual samples are relative to specific gene sets of interest. Here we demonstrate the application of singscore to investigate transcriptional profiles associated with specific mutations or genetic lesions in acute myeloid leukemia. Using matched genomic and transcriptomic data available through the TCGA we show that scoring of appropriate signatures can distinguish samples with corresponding mutations, reflecting the ability of these mutations to drive aberrant transcriptional programs involved in leukemogenesis. We believe the singscore method is particularly useful for studying heterogeneity within a specific subsets of cancers, and as demonstrated, we show the ability of singscore to identify where alternative mutations appear to drive similar transcriptional programs.

Acute myeloid leukemia driven by the CALM-AF10 fusion gene is dependent on BMI1

A subset of acute myeloid and lymphoid leukemia cases harbor a t(10;11)(p13;q14) translocation resulting in the CALM-AF10 fusion gene. Standard chemotherapeutic strategies are often ineffective in treating patients with CALM-AF10 fusions. Hence, there is an urgent need to identify molecular pathways dysregulated in CALM-AF10-positive leukemias which may lay the foundation for novel targeted therapies. Here we demonstrate that the Polycomb Repressive Complex 1 gene BMI1 is consistently overexpressed in adult and pediatric CALM-AF10-positive leukemias. We demonstrate that genetic Bmi1 depletion abrogates CALM-AF10-mediated transformation of murine hematopoietic stem and progenitor cells (HSPCs). Furthermore, CALM-AF10-positive murine and human AML cells are sensitive to the small-molecule BMI1 inhibitor PTC-209 as well as to PTC-596, a compound in clinical development that has been shown to result in downstream degradation of BMI1 protein. PTC-596 significantly prolongs survival of mice injected with a human CALM-AF10 cell line in a xenograft assay. In summary, these results validate BMI1 as a bona fide candidate for therapeutic targeting in AML with CALM-AF10 rearrangements.

Healthcare professionals' attitudes toward cancer precision medicine: A systematic review

Use of precision medicine in oncology is burgeoning and can provide patients with new treatment options. However, it is not clear how precision medicine is impacting healthcare professionals (HCPs), particularly with regards to their concerns about this new approach. We therefore synthesized the existing literature on HCPs' attitudes toward cancer precision medicine. We searched four databases for relevant articles. Two reviewers screened eligible articles and extracted data. We assessed the quality of each article using the QualSyst tool. We found 22 articles, representing 4,321 HCPs (63.7% cancer specialists). HCPs held largely positive attitudes toward cancer precision medicine, including their capacity to facilitate treatment decisions and provide prognostic information. However, they also had concerns regarding costs, insurance coverage, limited HCP knowledge about precision medicine, potential misuse, difficulties accessing the tests, and delays in receiving test results. Most HCPs felt that test-related decisions should be shared between families and HCPs. HCPs intended to disclose actionable results but were less inclined to disclose negative/secondary findings. HCPs had a strong preference for genetic counselor involvement when disclosing germline findings. Most HCPs intended to use somatic and germline tests in their future practice but the extent to which pharmacogenomic tests will be used is uncertain. HCPs indicated that additional evidence supporting test utility and increased availability of treatment guidelines could facilitate the use of testing. HCPs held generally positive attitudes toward cancer precision medicine, however there were some key concerns. Addressing concerns early, devising educational support for HCPs and developing guidelines may facilitate the successful implementation of precision medicine trials in the future.

Pediatric leukemia: Moving toward more accurate models

Leukemia is a complex genetic disease caused by errors in differentiation, growth, and apoptosis of hematopoietic cells in either lymphoid or myeloid lineages. Large-scale genomic characterization of thousands of leukemia patients has produced a tremendous amount of data that have enabled a better understanding of the differences between adult and pediatric patients. For instance, although phenotypically similar, pediatric and adult myeloid leukemia patients differ in their mutational profiles, typically involving either chromosomal translocations or recurrent single-base-pair mutations, respectively. To elucidate the molecular mechanisms underlying the biology of this cancer, continual efforts have been made to develop more contextually and biologically relevant experimental models. Leukemic cell lines, for example, provide an inexpensive and tractable model but often fail to recapitulate critical aspects of tumor biology. Likewise, murine leukemia models of leukemia have been highly informative but also do not entirely reproduce the human disease. More recent advances in the development of patient-derived xenografts (PDXs) or human models of leukemias are poised to provide a more comprehensive, and biologically relevant, approach to directly assess the impact of the in vivo environment on human samples. In this review, the advantages and limitations of the various current models used to functionally define the genetic requirements of leukemogenesis are discussed.

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.

Electronic supplementary material

The online version of this article (10.1186/s13073-019-0644-8) contains supplementary material, which is available to authorized users.

Predisposing germline mutations in high hyperdiploid acute lymphoblastic leukemia in children

High hyperdiploidy (HD) is the most common cytogenetic subtype of childhood acute lymphoblastic leukemia (ALL), and a higher incidence of HD has been reported in ALL patients with congenital cancer syndromes. We assessed the frequency of predisposing germline mutations in 57 HD-ALL patients from the California Childhood Leukemia Study via targeted sequencing of cancer-relevant genes. Three out of 57 patients (5.3%) harbored confirmed germline mutations that were likely causal, in NBN, ETV6, and FLT3, with an additional six patients (10.5%) harboring putative predisposing mutations that were rare in unselected individuals (<0.01% allele frequency in the Exome Aggregation Consortium, ExAC) and predicted functional (scaled CADD score ≥ 20) in known or potential ALL predisposition genes (SH2B3, CREBBP, PMS2, MLL, ABL1, and MYH9). Three additional patients carried rare and predicted damaging germline mutations in GAB2, a known activator of the ERK/MAPK and PI3K/AKT pathways and binding partner of PTPN11-encoded SHP2. The frequency of rare and predicted functional germline GAB2 mutations was significantly higher in our patients (2.6%) than in ExAC (0.28%, P = 4.4 × 10^-3 ), an observation that was replicated in ALL patients from the TARGET project (P = .034). We cloned patient GAB2 mutations and expressed mutant proteins in HEK293 cells and found that frameshift mutation P621fs led to reduced SHP2 binding and ERK1/2 phosphorylation but significantly increased AKT phosphorylation, suggesting possible RAS-independent leukemogenic effects. Our results support a significant contribution of rare, high penetrance germline mutations to HD-ALL etiology, and pinpoint GAB2 as a putative novel ALL predisposition gene.

Dean Flow Assisted Single Cell and Bead Encapsulation for High Performance Single Cell Expression Profiling

Droplet microfluidics-based platform (Drop-seq) has been shown to be a powerful tool for single cell expression profiling. Nevertheless, this platform required the simultaneous encapsulation of single cell and single barcoded bead, the incidence of which was very low, limiting its efficiency. Spiral channels were reported to focus the barcoded beads and thus increased the efficiency, but focusing of cells was not demonstrated, which could potentially further enhance the performance. Here, we designed spiral and serpentine channels to focus both bead and cell solutions and implemented this microfluidic design on Drop-seq. We characterized the effect of cell/bead concentration on encapsulation results and tested the performance by coencapsulating barcoded beads and human-mouse cell mixtures followed by sequencing. The results showed ∼300% and ∼40% increase in cell utilization rate compared to the traditional Drop-seq device and the device focusing beads alone, respectively. This chip design showed great potential for high efficiency single cell expression profiling.

Dangerous liaisons: interplay between SWI/SNF, NuRD, and Polycomb in chromatin regulation and cancer

In this review, Bracken et al. discuss the functional organization and biochemical activities of remodelers and Polycomb and explore how they work together to control cell differentiation and the maintenance of cell identity. They also discuss how mutations in the genes encoding these various chromatin regulators contribute to oncogenesis by disrupting the chromatin equilibrium.

Changes in chromatin structure mediated by ATP-dependent nucleosome remodelers and histone modifying enzymes are integral to the process of gene regulation. Here, we review the roles of the SWI/SNF (switch/sucrose nonfermenting) and NuRD (nucleosome remodeling and deacetylase) and the Polycomb system in chromatin regulation and cancer. First, we discuss the basic molecular mechanism of nucleosome remodeling, and how this controls gene transcription. Next, we provide an overview of the functional organization and biochemical activities of SWI/SNF, NuRD, and Polycomb complexes. We describe how, in metazoans, the balance of these activities is central to the proper regulation of gene expression and cellular identity during development. Whereas SWI/SNF counteracts Polycomb, NuRD facilitates Polycomb repression on chromatin. Finally, we discuss how disruptions of this regulatory equilibrium contribute to oncogenesis, and how new insights into the biological functions of remodelers and Polycombs are opening avenues for therapeutic interventions on a broad range of cancer types.

Portrait of a cancer: mutational signature analyses for cancer diagnostics

BACKGROUND

In the past decade, systematic and comprehensive analyses of cancer genomes have identified cancer driver genes and revealed unprecedented insight into the molecular mechanisms underlying the initiation and progression of cancer. These studies illustrate that although every cancer has a unique genetic make-up, there are only a limited number of mechanisms that shape the mutational landscapes of cancer genomes, as reflected by characteristic computationally-derived mutational signatures. Importantly, the molecular mechanisms underlying specific signatures can now be dissected and coupled to treatment strategies. Systematic characterization of mutational signatures in a cancer patient's genome may thus be a promising new tool for molecular tumor diagnosis and classification.

RESULTS

In this review, we describe the status of mutational signature analysis in cancer genomes and discuss the opportunities and relevance, as well as future challenges, for further implementation of mutational signatures in clinical tumor diagnostics and therapy guidance.

CONCLUSIONS

Scientific studies have illustrated the potential of mutational signature analysis in cancer research. As such, we believe that the implementation of mutational signature analysis within the diagnostic workflow will improve cancer diagnosis in the future.

-Omics biomarker identification pipeline for translational medicine

BACKGROUND

Translational medicine (TM) is an emerging domain that aims to facilitate medical or biological advances efficiently from the scientist to the clinician. Central to the TM vision is to narrow the gap between basic science and applied science in terms of time, cost and early diagnosis of the disease state. Biomarker identification is one of the main challenges within TM. The identification of disease biomarkers from -omics data will not only help the stratification of diverse patient cohorts but will also provide early diagnostic information which could improve patient management and potentially prevent adverse outcomes. However, biomarker identification needs to be robust and reproducible. Hence a robust unbiased computational framework that can help clinicians identify those biomarkers is necessary.

METHODS

We developed a pipeline (workflow) that includes two different supervised classification techniques based on regularization methods to identify biomarkers from -omics or other high dimension clinical datasets. The pipeline includes several important steps such as quality control and stability of selected biomarkers. The process takes input files (outcome and independent variables or -omics data) and pre-processes (normalization, missing values) them. After a random division of samples into training and test sets, Least Absolute Shrinkage and Selection Operator and Elastic Net feature selection methods are applied to identify the most important features representing potential biomarker candidates. The penalization parameters are optimised using 10-fold cross validation and the process undergoes 100 iterations and a combinatorial analysis to select the best performing multivariate model. An empirical unbiased assessment of their quality as biomarkers for clinical use is performed through a Receiver Operating Characteristic curve and its Area Under the Curve analysis on both permuted and real data for 1000 different randomized training and test sets. We validated this pipeline against previously published biomarkers.

RESULTS

We applied this pipeline to three different datasets with previously published biomarkers: lipidomics data by Acharjee et al. (Metabolomics 13:25, 2017) and transcriptomics data by Rajamani and Bhasin (Genome Med 8:38, 2016) and Mills et al. (Blood 114:1063-1072, 2009). Our results demonstrate that our method was able to identify both previously published biomarkers as well as new variables that add value to the published results.

CONCLUSIONS

We developed a robust pipeline to identify clinically relevant biomarkers that can be applied to different -omics datasets. Such identification reveals potentially novel drug targets and can be used as a part of a machine-learning based patient stratification framework in the translational medicine settings.

5-Methylcytosine and 5-Hydroxymethylcytosine Signatures Underlying Pediatric Cancers

In addition to the genetic variations, recent evidence has shown that DNA methylation of both 5-methylcytosine (5mC) and 5-hydroxymethylcytosine (5hmC) underlies the pathogenesis of pediatric cancer. Given the high mortality rate, there is an urgent need to study the mechanisms contributing to the pathogenicity of pediatric cancer. Over the past decades, next-generation sequencing (NGS) has enabled us to perform genome-wide screening to study the complex regulatory mechanisms of 5mC and 5hmC underlying pediatric tumorigenesis. To shed light on recent developments on pediatric cancer predisposition and tumor progression, here we discuss the role of both genome-wide and locus-specific dysregulation of 5mC and 5hmC in hematopoiesis malignancy and neuroblastoma, the most common types of pediatric cancer, together with their therapeutic potential.

Assessment of circulating tumor DNA in pediatric solid tumors: The promise of liquid biopsies

Circulating tumor DNA can be detected in the blood and body fluids of patients using ultrasensitive technologies, which have the potential to improve cancer diagnosis, risk stratification, noninvasive tumor profiling, and tracking of treatment response and disease recurrence. As we begin to apply "liquid biopsy" strategies in children with cancer, it is important to tailor our efforts to the unique genomic features of these tumors and address the technical and logistical challenges of integrating biomarker testing. This article reviews the literature demonstrating the feasibility of applying liquid biopsy to pediatric solid malignancies and suggests new directions for future studies.

Genome sequencing analysis of blood cells identifies germline haplotypes strongly associated with drug resistance in osteosarcoma patients

BACKGROUND

Osteosarcoma is the most common malignant bone tumor in children. Survival remains poor among histologically poor responders, and there is a need to identify them at diagnosis to avoid delivering ineffective therapy. Genetic variation contributes to a wide range of response and toxicity related to chemotherapy. The aim of this study is to use sequencing of blood cells to identify germline haplotypes strongly associated with drug resistance in osteosarcoma patients.

METHODS

We used sequencing data from two patient datasets, from Inova Hospital and the NCI TARGET. We explored the effect of mutation hotspots, in the form of haplotypes, associated with relapse outcome. We then mapped the single nucleotide polymorphisms (SNPs) in these haplotypes to genes and pathways. We also performed a targeted analysis of mutations in Drug Metabolizing Enzymes and Transporter (DMET) genes associated with tumor necrosis and survival.

RESULTS

We found intronic and intergenic hotspot regions from 26 genes common to both the TARGET and INOVA datasets significantly associated with relapse outcome. Among significant results were mutations in genes belonging to AKR enzyme family, cell-cell adhesion biological process and the PI3K pathways; as well as variants in SLC22 family associated with both tumor necrosis and overall survival. The SNPs from our results were confirmed using Sanger sequencing. Our results included known as well as novel SNPs and haplotypes in genes associated with drug resistance.

CONCLUSION

We show that combining next generation sequencing data from multiple datasets and defined clinical data can better identify relevant pathway associations and clinically actionable variants, as well as provide insights into drug response mechanisms.

The Pediatric Cell Atlas: Defining the Growth Phase of Human Development at Single-Cell Resolution

Single-cell gene expression analyses of mammalian tissues have uncovered profound stage-specific molecular regulatory phenomena that have changed the understanding of unique cell types and signaling pathways critical for lineage determination, morphogenesis, and growth. We discuss here the case for a Pediatric Cell Atlas as part of the Human Cell Atlas consortium to provide single-cell profiles and spatial characterization of gene expression across human tissues and organs. Such data will complement adult and developmentally focused HCA projects to provide a rich cytogenomic framework for understanding not only pediatric health and disease but also environmental and genetic impacts across the human lifespan.

Therapeutic Targeting of Non-oncogene Dependencies in High-risk Neuroblastoma

PURPOSE

Neuroblastoma is a pediatric malignancy of the sympathetic nervous system with diverse clinical behaviors. Genomic amplification of MYCN oncogene has been shown to drive neuroblastoma pathogenesis and correlate with aggressive disease, but the survival rates for those high-risk tumors carrying no MYCN amplification remain equally dismal. The paucity of mutations and molecular heterogeneity has hindered the development of targeted therapies for most advanced neuroblastomas. We use an alternative method to identify potential drugs that target nononcogene dependencies in high-risk neuroblastoma.

EXPERIMENTAL DESIGN

By using a gene expression-based integrative approach, we identified prognostic signatures and potentially effective single agents and drug combinations for high-risk neuroblastoma.

RESULTS

Among these predictions, we validated in vitro efficacies of some investigational and marketed drugs, of which niclosamide, an anthelmintic drug approved by the FDA, was further investigated in vivo. We also quantified the proteomic changes during niclosamide treatment to pinpoint nucleoside diphosphate kinase 3 (NME3) downregulation as a potential mechanism for its antitumor activity.

CONCLUSIONS

Our results establish a gene expression-based strategy to interrogate cancer biology and inform drug discovery and repositioning for high-risk neuroblastoma.

Targeting anaplastic lymphoma kinase in neuroblastoma

Over the last decade, anaplastic lymphoma kinase (ALK), a receptor tyrosine kinase (RTK), has been identified as a fusion partner in a diverse variety of translocation events resulting in oncogenic signaling in many different cancer types. In tumors where the full‐length ALK RTK itself is mutated, such as neuroblastoma, the picture regarding the role of ALK as an oncogenic driver is less clear. Neuroblastoma is a complex and heterogeneous tumor that arises from the neural crest derived peripheral nervous system. Although high‐risk neuroblastoma is rare, it often relapses and becomes refractory to treatment. Thus, neuroblastoma accounts for 10–15% of all childhood cancer deaths. Since most cases are in children under the age of 2, understanding the role and regulation of ALK during neural crest development is an important goal in addressing neuroblastoma tumorigenesis. An impressive array of tyrosine kinase inhibitors (TKIs) that act to inhibit ALK have been FDA approved for use in ALK‐driven cancers. ALK TKIs bind differently within the ATP‐binding pocket of the ALK kinase domain and have been associated with different resistance mutations within ALK itself that arise in response to therapeutic use, particularly in ALK‐fusion positive non‐small cell lung cancer (NSCLC). This patient population has highlighted the importance of considering the relevant ALK TKI to be used for a given ALK mutant variant. In this review, we discuss ALK in neuroblastoma, as well as the use of ALK TKIs and other strategies to inhibit tumor growth. Current efforts combining novel approaches and increasing our understanding of the oncogenic role of ALK in neuroblastoma are aimed at improving the efficacy of ALK TKIs as precision medicine options in the clinic.

The genetic changes of Wilms tumour

Wilms tumour is the most common renal malignancy of childhood. The disease is curable in the majority of cases, albeit at considerable cost in terms of late treatment-related effects in some children. However, one in ten children with Wilms tumour will die of their disease despite modern treatment approaches. The genetic changes that underpin Wilms tumour have been defined by studies of familial cases and by unbiased DNA sequencing of tumour genomes. Together, these approaches have defined the landscape of cancer genes that are operative in Wilms tumour, many of which are intricately linked to the control of fetal nephrogenesis. Advances in our understanding of the germline and somatic genetic changes that underlie Wilms tumour may translate into better patient outcomes. Improvements in risk stratification have already been seen through the introduction of molecular biomarkers into clinical practice. A host of additional biomarkers are due to undergo clinical validation. Identifying actionable mutations has led to potential new targets, with some novel compounds undergoing testing in early phase trials. Avenues that warrant further exploration include targeting Wilms tumour cancer genes with a non-redundant role in nephrogenesis and targeting the fetal renal transcriptome.

Landscape of Germline and Somatic Mitochondrial DNA Mutations in Pediatric Malignancies

Little is known about the spectrum of mitochondrial DNA (mtDNA) mutations across pediatric malignancies. In this study, we analyzed matched tumor and normal whole genome sequencing data from 616 pediatric patients with hematopoietic malignancies, solid tumors, and brain tumors. We identified 391 mtDNA mutations in 284 tumors including 45 loss-of-function mutations, which clustered at four statistically significant hotspots in MT-COX3, MT-ND4, and MT-ND5, and at a mutation hotspot in MT-tRNA-MET. A skewed ratio (4.83) of nonsynonymous versus synonymous (dN/dS) mtDNA mutations with high statistical significance was identified on the basis of Monte Carlo simulations in the tumors. In comparison, opposite ratios of 0.44 and 0.93 were observed in 616 matched normal tissues and in 249 blood samples from children without cancer, respectively. mtDNA mutations varied by cancer type and mtDNA haplogroup. Collectively, these results suggest that deleterious mtDNA mutations play a role in the development and progression of pediatric cancers. SIGNIFICANCE: This pan-cancer mtDNA study establishes the landscape of germline and tumor mtDNA mutations and identifies hotspots of tumor mtDNA mutations to pinpoint key mitochondrial functions in pediatric malignancies.

Timing of first-in-child trials of FDA-approved oncology drugs

AIM

The lag time between initial human studies of oncology agents and the first-in-child clinical trials of these agents has not been defined.

METHODS

We conducted a systematic analysis of time from first-in-human trials to first-in-child trials (age of eligibility <18 years) of agents first approved by the US Food and Drug Administration (FDA) for any oncology indication from 1997 to 2017. We used clinical trial registry data, published literature and oncology abstracts to identify relevant trials and start dates.

RESULTS

From 1997 to 2017, 126 drugs received initial FDA approval for an oncology indication. Of these, 117 were non-hormonal agents used in subsequent analyses. Fifteen of 117 drugs (12.8%) did not yet have a paediatric trial, and six of 117 drugs (5.1%) had an initial approval that included children. The median time between the first-in-human trial and first-in-child trial was 6.5 years (range 0-27.7 years). The median time from initial FDA approval to the first-in-child clinical trial was -0.66 years (range -43 to +19 years). These values were stable regardless of year of initial FDA approval, drug class and initial approved disease indication.

CONCLUSION

The median lag time from first-in-human to first-in-child trials of oncology agents that were ultimately approved by FDA was 6.5 years. These results provide a benchmark against which to evaluate recent initiatives designed to hasten drug development relevant to children with cancer.

The genomic landscape of pediatric cancers: Implications for diagnosis and treatment

The past decade has witnessed a major increase in our understanding of the genetic underpinnings of childhood cancer. Genomic sequencing studies have highlighted key differences between pediatric and adult cancers. Whereas many adult cancers are characterized by a high number of somatic mutations, pediatric cancers typically have few somatic mutations but a higher prevalence of germline alterations in cancer predisposition genes. Also noteworthy is the remarkable heterogeneity in the types of genetic alterations that likely drive the growth of pediatric cancers, including copy number alterations, gene fusions, enhancer hijacking events, and chromoplexy. Because most studies have genetically profiled pediatric cancers only at diagnosis, the mechanisms underlying tumor progression, therapy resistance, and metastasis remain poorly understood. We discuss evidence that points to a need for more integrative approaches aimed at identifying driver events in pediatric cancers at both diagnosis and relapse. We also provide an overview of key aspects of germline predisposition for cancer in this age group.

Cancer mutational burden is shaped by G4 DNA, replication stress and mitochondrial dysfunction

A hallmark of cancer is genomic instability, which can enable cancer cells to evade therapeutic strategies. Here we employed a computational approach to uncover mechanisms underlying cancer mutational burden by focusing upon relationships between 1) translocation breakpoints and the thousands of G4 DNA-forming sequences within retrotransposons impacting transcription and exemplifying probable non-B DNA structures and 2) transcriptome profiling and cancer mutations. We determined the location and number of G4 DNA-forming sequences in the Genome Reference Consortium Human Build 38 and found a total of 358,605 covering ∼13.4 million bases. By analyzing >97,000 unique translocation breakpoints from the Catalogue Of Somatic Mutations In Cancer (COSMIC), we found that breakpoints are overrepresented at G4 DNA-forming sequences within hominid-specific SVA retrotransposons, and generally occur in tumors with mutations in tumor suppressor genes, such as TP53. Furthermore, correlation analyses between mRNA levels and exome mutational loads from The Cancer Genome Atlas (TCGA) encompassing >450,000 gene-mutation regressions revealed strong positive and negative associations, which depended upon tissue of origin. The strongest positive correlations originated from genes not listed as cancer genes in COSMIC; yet, these show strong predictive power for survival in most tumor types by Kaplan-Meier estimation. Thus, correlation analyses of DNA structure and gene expression with mutation loads complement and extend more traditional approaches to elucidate processes shaping genomic instability in cancer. The combined results point to G4 DNA, activation of cell cycle/DNA repair pathways, and mitochondrial dysfunction as three major factors driving the accumulation of somatic mutations in cancer cells.

Analysis of error profiles in deep next-generation sequencing data

BACKGROUND

Sequencing errors are key confounding factors for detecting low-frequency genetic variants that are important for cancer molecular diagnosis, treatment, and surveillance using deep next-generation sequencing (NGS). However, there is a lack of comprehensive understanding of errors introduced at various steps of a conventional NGS workflow, such as sample handling, library preparation, PCR enrichment, and sequencing. In this study, we use current NGS technology to systematically investigate these questions.

RESULTS

By evaluating read-specific error distributions, we discover that the substitution error rate can be computationally suppressed to 10-5 to 10-4, which is 10- to 100-fold lower than generally considered achievable (10-3) in the current literature. We then quantify substitution errors attributable to sample handling, library preparation, enrichment PCR, and sequencing by using multiple deep sequencing datasets. We find that error rates differ by nucleotide substitution types, ranging from 10-5 for A>C/T>G, C>A/G>T, and C>G/G>C changes to 10-4 for A>G/T>C changes. Furthermore, C>T/G>A errors exhibit strong sequence context dependency, sample-specific effects dominate elevated C>A/G>T errors, and target-enrichment PCR led to ~ 6-fold increase of overall error rate. We also find that more than 70% of hotspot variants can be detected at 0.1 ~ 0.01% frequency with the current NGS technology by applying in silico error suppression.

CONCLUSIONS

We present the first comprehensive analysis of sequencing error sources in conventional NGS workflows. The error profiles revealed by our study highlight new directions for further improving NGS analysis accuracy both experimentally and computationally, ultimately enhancing the precision of deep sequencing.

Ushering in the next generation of precision trials for pediatric cancer

Cancer treatment decisions are increasingly based on the genomic profile of the patient’s tumor, a strategy called “precision oncology.” Over the past few years, a growing number of clinical trials and case reports have provided evidence that precision oncology is an effective approach for at least some children with cancer. Here, we review key factors influencing pediatric drug development in the era of precision oncology. We describe an emerging regulatory framework that is accelerating the pace of clinical trials in children as well as design challenges that are specific to trials that involve young cancer patients. Last, we discuss new drug development approaches for pediatric cancers whose growth relies on proteins that are difficult to target therapeutically, such as transcription factors.

Renal medullary carcinomas depend upon SMARCB1 loss and are sensitive to proteasome inhibition

Renal medullary carcinoma (RMC) is a rare and deadly kidney cancer in patients of African descent with sickle cell trait. We have developed faithful patient-derived RMC models and using whole-genome sequencing, we identified loss-of-function intronic fusion events in one SMARCB1 allele with concurrent loss of the other allele. Biochemical and functional characterization of these models revealed that RMC requires the loss of SMARCB1 for survival. Through integration of RNAi and CRISPR-Cas9 loss-of-function genetic screens and a small-molecule screen, we found that the ubiquitin-proteasome system (UPS) was essential in RMC. Inhibition of the UPS caused a G2/M arrest due to constitutive accumulation of cyclin B1. These observations extend across cancers that harbor SMARCB1 loss, which also require expression of the E2 ubiquitin-conjugating enzyme, UBE2C. Our studies identify a synthetic lethal relationship between SMARCB1-deficient cancers and reliance on the UPS which provides the foundation for a mechanism-informed clinical trial with proteasome inhibitors.

Renal medullary carcinoma (RMC for short) is a rare type of kidney cancer that affects teenagers and young adults. These patients are usually of African descent and carry one of the two genetic changes that cause sickle cell anemia. RMC is an aggressive disease without effective treatments and patients survive, on average, for only six to eight months after their diagnosis.

Recent genetic studies found that most RMC cells have mutations that prevent them from producing a protein called SMARCB1. SMARCB1 normally acts as a so-called tumor suppressor, preventing cells from becoming cancerous. However, it was not clear whether RMCs always have to lose SMARCB1 if they are to survive and grow.

Often, diseases are studied using laboratory-grown cells and tissues that have certain features of the disease. No such models had been created for RMC, which has slowed efforts to understand how the disease develops and find new treatments for it. Hong et al. therefore worked with patients to develop new lines of cells that can be used to study RMC in the laboratory. These RMC cells started dying when they were given copies of the SMARCB1 gene, which supports the theory that RMCs have to lose SMARCB1 in order to grow.

Hong et al. then used a set of genetic reagents that can suppress or delete genes that are targeted by drugs, and followed this by testing a range of drugs on the RMC cells. Drugs and genetic reagents that reduced the activity of the proteasome – the structure inside cells that gets rid of old or unwanted proteins – caused the RMC cells to die. These proteasome inhibitor drugs also killed other kinds of cancer cells with SMARCB1 mutations.

Proteasome inhibitors are already used to treat different types of cancer. Potentially, a clinical trial could be run to see if they will treat patients whose cancers lack SMARCB1. Further work is also needed to determine the exact link between SMARCB1 and the proteasome.

Dual-Specificity Phosphatases in Neuroblastoma Cell Growth and Differentiation

Dual-specificity phosphatases (DUSPs) are important regulators of neuronal cell growth and differentiation by targeting proteins essential to neuronal survival in signaling pathways, among which the MAP kinases (MAPKs) stand out. DUSPs include the MAPK phosphatases (MKPs), a family of enzymes that directly dephosphorylate MAPKs, as well as the small-size atypical DUSPs, a group of low molecular-weight enzymes which display more heterogeneous substrate specificity. Neuroblastoma (NB) is a malignancy intimately associated with the course of neuronal and neuroendocrine cell differentiation, and constitutes the source of more common extracranial solid pediatric tumors. Here, we review the current knowledge on the involvement of MKPs and small-size atypical DUSPs in NB cell growth and differentiation, and discuss the potential of DUSPs as predictive biomarkers and therapeutic targets in human NB.

Developmental origins and emerging therapeutic opportunities for childhood cancer

Cancer is the leading disease-related cause of death in children in developed countries. Arising in the context of actively growing tissues, childhood cancers are fundamentally diseases of dysregulated development. Childhood cancers exhibit a lower overall mutational burden than adult cancers, and recent sequencing studies have revealed that the genomic events central to childhood oncogenesis include mutations resulting in broad epigenetic changes or translocations that result in fusion oncoproteins. Here, we will review the developmental origins of childhood cancers, epigenetic dysregulation in tissue stem/precursor cells in numerous examples of childhood cancer oncogenesis and emerging therapeutic opportunities aimed at both cell-intrinsic and microenvironmental targets together with new insights into the mechanisms underlying long-term sequelae of childhood cancer therapy.

Emerging Therapies for Acute Myelogenus Leukemia Patients Targeting Apoptosis and Mitochondrial Metabolism

Acute Myelogenous Leukemia (AML) is a malignant disease of the hematopoietic cells, characterized by impaired differentiation and uncontrolled clonal expansion of myeloid progenitors/precursors, resulting in bone marrow failure and impaired normal hematopoiesis. AML comprises a heterogeneous group of malignancies, characterized by a combination of different somatic genetic abnormalities, some of which act as events driving leukemic development. Studies carried out in the last years have shown that AML cells invariably have abnormalities in one or more apoptotic pathways and have identified some components of the apoptotic pathway that can be targeted by specific drugs. Clinical results deriving from studies using B-cell lymphoma 2 (BCL-2) inhibitors in combination with standard AML agents, such as azacytidine, decitabine, low-dose cytarabine, provided promising results and strongly support the use of these agents in the treatment of AML patients, particularly of elderly patients. TNF-related apoptosis-inducing ligand (TRAIL) and its receptors are frequently deregulated in AML patients and their targeting may represent a promising strategy for development of new treatments. Altered mitochondrial metabolism is a common feature of AML cells, as supported through the discovery of mutations in the isocitrate dehydrogenase gene and in mitochondrial electron transport chain and of numerous abnormalities of oxidative metabolism existing in AML subgroups. Overall, these observations strongly support the view that the targeting of mitochondrial apoptotic or metabolic machinery is an appealing new therapeutic perspective in AML.

Origins and clinical relevance of proteoforms in pediatric malignancies

INTRODUCTION

Cancer changes the proteome in complex ways that reach well beyond simple changes in protein abundance. Genomic and transcriptional variations and post-translational protein modification create functional variants of a protein, known as proteoforms. Childhood cancers have fewer genomic alterations but show equally dramatic phenotypic changes as malignant cells in adults. Therefore, unraveling the complexities of the proteome is even more important in pediatric malignancies. Areas covered: In this review, the biological origins of proteoforms and technological advancements in the study of proteoforms are discussed. Particular emphasis is given to their implication in childhood malignancies and the critical role of cancer-specific proteoforms for the next generation of cancer therapies and diagnostics. Expert opinion: Recent advancements in technology have led to a better understanding of the underlying mechanisms of tumorigenesis. This has been critical for the development of more effective and less harmful treatments that are based on direct targeting of altered proteins and deregulated pathways. As proteome coverage and the ability to detect complex proteoforms increase, the most need for change is in data compilation and database availability to mediate high-level data analysis and allow for better functional annotation of proteoforms.

Integrative analysis reveals driver long non-coding RNAs in osteosarcoma

Transcriptome profiling of osteosarcoma (OS) by next generation sequencing technology (NGS) has been broadly performed by previous researches, which uncovers a large number protein-coding driver genes, facilitates our understanding of the molecular mechanisms of OS formation, progression and metastasis. Recently, more and more researchers realize the importance of long non-coding RNAs (lncRNAs) on the development of OS. However, few studies focus on discovering driver lncRNAs.Here we collected somatic copy number alterations (SCNAs) and gene expression profiles of 84 samples from Therapeutically Applicable Research to Generate Effective Treatments (TARGET) project. The RNA sequencing data detected 13,903 expressed lncRNAs, 157 of which were previously reported to be associated with cancer based on the annotations from Lnc2Cancer database.By analyzing the SNP array data, several significant SCNAs were detected, such as the amplifications on chromosomes 1q, 4q, 17p, 17q, and 19q, and deletions on 1q, 3q, 9p, 10q, and 15q. With the SCNA and gene expression profiles, we identified 167 driver genes by integrative analysis, including 162 novel driver lncRNAs, 2 lncRNAs reported to be associated with OS, and another 3 associated with other cancers. Furthermore, functional characterization and survival analysis revealed that RP11-241F15.10 may function as a tumor suppressor in OS, and loss of function may contribute to activation of Wnt signaling pathway.This study not only facilitates our understanding of the oncogenic or tumor-suppressor role of lncRNAs in OS, but also provides potential therapies for the patients with OS with metastasis or relapse.

Tumor Variant Identification That Accounts for the Unique Molecular Landscape of Pediatric Malignancies

Precision oncology trials for pediatric cancers require rapid and accurate detection of genetic alterations. Tumor variant identification should interrogate the distinctive driver genes and more frequent copy number variants and gene fusions that are characteristics of pediatric tumors. Here, we evaluate tumor variant identification using whole genome sequencing (n = 12 samples) and two amplification-based next-generation sequencing assays (n = 28 samples), including one assay designed to rapidly assess common diagnostic, prognostic, and therapeutic biomarkers found in pediatric tumors. Variant identification by the three modalities was comparable when filtered for 151 pediatric driver genes. Across the 28 samples, the pediatric cancer-focused assay detected more tumor variants per sample (two-sided, P < .05), which improved the identification of potentially druggable events and matched pathway inhibitors. Overall, our data indicate that an assay designed to evaluate pediatric cancer-specific variants, including gene fusions, may improve the detection of target-agent pairs for precision oncology.

The Clonal Evolution of Metastatic Osteosarcoma as Shaped by Cisplatin Treatment

To investigate the genomic evolution of metastatic pediatric osteosarcoma, we performed whole-genome and targeted deep sequencing on 14 osteosarcoma metastases and two primary tumors from four patients (two to eight samples per patient). All four patients harbored ancestral (truncal) somatic variants resulting in TP53 inactivation and cell-cycle aberrations, followed by divergence into relapse-specific lineages exhibiting a cisplatin-induced mutation signature. In three of the four patients, the cisplatin signature accounted for >40% of mutations detected in the metastatic samples. Mutations potentially acquired during cisplatin treatment included NF1 missense mutations of uncertain significance in two patients and a KIT G565R activating mutation in one patient. Three of four patients demonstrated widespread ploidy differences between samples from the sample patient. Single-cell seeding of metastasis was detected in most metastatic samples. Cross-seeding between metastatic sites was observed in one patient, whereas in another patient a minor clone from the primary tumor seeded both metastases analyzed. These results reveal extensive clonal heterogeneity in metastatic osteosarcoma, much of which is likely cisplatin-induced. IMPLICATIONS: The extent and consequences of chemotherapy-induced damage in pediatric cancers is unknown. We found that cisplatin treatment can potentially double the mutational burden in osteosarcoma, which has implications for optimizing therapy for recurrent, chemotherapy-resistant disease.

Kinetic analysis of multistep USP7 mechanism shows critical role for target protein in activity

USP7 is a highly abundant deubiquitinating enzyme (DUB), involved in cellular processes including DNA damage response and apoptosis. USP7 has an unusual catalytic mechanism, where the low intrinsic activity of the catalytic domain (CD) increases when the C-terminal Ubl domains (Ubl45) fold onto the CD, allowing binding of the activating C-terminal tail near the catalytic site. Here we delineate how the target protein promotes the activation of USP7. Using NMR analysis and biochemistry we describe the order of activation steps, showing that ubiquitin binding is an instrumental step in USP7 activation. Using chemically synthesised p53-peptides we also demonstrate how the correct ubiquitinated substrate increases catalytic activity. We then used transient reaction kinetic modelling to define how the USP7 multistep mechanism is driven by target recognition. Our data show how this pleiotropic DUB can gain specificity for its cellular targets.

Deubiquitinating enzymes (DUBs) are critical regulators of cellular processes by removing ubiquitin from specific targets. Here global kinetic modelling reveals the mechanism by which the low intrinsic activity of USP7 is substantially enhanced on a specific physiological target.

Nouvelles perspectives dans l’immunothérapie des cancers pédiatriques

NEW PERSPECTIVES IN IMMUNOTHERAPIES FOR PEDIATRIC MALIGNANCIES

New therapeutic paradigms are needed to improve the survival of children and adolescents with high-risk malignancies, and to reduce the sequelae associated with treatment. Immunotherapies, targeting tumor cells and/or the immune system to enhance existing anti-tumor immunity or induce novel anti-tumor immune responses, are becoming increasingly successful in adult oncology. Based on the results obtained with anti-ganglioside2 antibodies in neuroblastoma, rituximab in mature B malignancies, immune checkpoint inhibitors in lymphoma and especially in Hodgkin lymphoma, blinatumomab and CAR-T CD19 cells for B-cell acute lymphoblastic leukemia, immunotherapy has demonstrated irrefutable benefits in pediatric patients. However, these results are currently limited to a minority of patients and histologies. Current and ongoing trials tend to focus on a single type of immunotherapy, but it is likely that combinations of immunotherapies with different mechanisms of action or combination with other classes of anti-cancer treatments will be additives or even synergistic. The development of this new class of drugs in the treatment of pediatric cancers has multiple challenges: to better evaluate the response to treatment, to define the optimal doses and schedules, to manage immuno-mediated toxicities, to identify its specific sequelae, and, finally, to better understand the strategies of immune evasion of pediatric cancers in order to develop efficient immunotherapies.

Comparison of three variant callers for human whole genome sequencing

Testing of patients with genetics-related disorders is in progress of shifting from single gene assays to gene panel sequencing, whole-exome sequencing (WES) and whole-genome sequencing (WGS). Since WGS is unquestionably becoming a new foundation for molecular analyses, we decided to compare three currently used tools for variant calling of human whole genome sequencing data. We tested DeepVariant, a new TensorFlow machine learning-based variant caller, and compared this tool to GATK 4.0 and SpeedSeq, using 30×, 15× and 10× WGS data of the well-known NA12878 DNA reference sample. According to our comparison, the performance on SNV calling was almost similar in 30× data, with all three variant callers reaching F-Scores (i.e. harmonic mean of recall and precision) equal to 0.98. In contrast, DeepVariant was more precise in indel calling than GATK and SpeedSeq, as demonstrated by F-Scores of 0.94, 0.90 and 0.84, respectively. We conclude that the DeepVariant tool has great potential and usefulness for analysis of WGS data in medical genetics.

Precision Medicine in Pediatric Cancer: Current Applications and Future Prospects

Precision oncologic medicine is an emerging approach for cancer treatment that has recently taken giant steps in solid clinical practice. Recent advances in molecular diagnostics that can analyze the individual tumor’s variability in genes have provided greater understanding and additional strategies to treat cancers. Although tumors can be tested by several molecular methods, the use of next-generation sequencing (NGS) has greatly facilitated our understanding of pediatric cancer and identified additional therapeutic opportunities. Pediatric tumors have a different genetic make-up, with a fewer number of actionable targets than adult tumors. Nevertheless, precision oncology in the pediatric population has greatly improved the survival of patients with leukemia and solid tumors. This review discusses the current status of pediatric precision oncology and the different clinical scenarios in which it can be effectively applied.

Age-specific biological and molecular profiling distinguishes paediatric from adult acute myeloid leukaemias

Acute myeloid leukaemia (AML) affects children and adults of all ages. AML remains one of the major causes of death in children with cancer and for children with AML relapse is the most common cause of death. Here, by modelling AML in vivo we demonstrate that AML is discriminated by the age of the cell of origin. Young cells give rise to myeloid, lymphoid or mixed phenotype acute leukaemia, whereas adult cells give rise exclusively to AML, with a shorter latency. Unlike adult, young AML cells do not remodel the bone marrow stroma. Transcriptional analysis distinguishes young AML by the upregulation of immune pathways. Analysis of human paediatric AML samples recapitulates a paediatric immune cell interaction gene signature, highlighting two genes, RGS10 and FAM26F as prognostically significant. This work advances our understanding of paediatric AML biology, and provides murine models that offer the potential for developing paediatric specific therapeutic strategies.

Acute myeloid leukaemia (AML) affects people of all ages. Here, the authors model AML in vivo and demonstrate that the age of the cell of origin impacts leukaemia development and the genetic signature where adult cells of origin give rise exclusively to AML and young cells of origin give rise to myeloid, lymphoid or mixed phenotype acute leukaemia.

Somatic TP53 Mutations Are Detectable in Circulating Tumor DNA from Children with Anaplastic Wilms Tumors

BACKGROUND

Diffuse anaplastic Wilms tumor (DAWT) is a rare, high-risk subtype that is often missed on diagnostic needle biopsy. Somatic mutations in TP53 are associated with the development of anaplasia and with poorer survival, particularly in advanced-stage disease. Early identification of DAWT harboring TP53 abnormalities could improve risk stratification of initial therapy and monitoring for recurrence.

METHODS

Droplet digital polymerase chain reaction (ddPCR) was used to evaluate 21 samples from 4 patients with DAWT. For each patient, we assessed TP53 status in frozen tumor, matched germline DNA, and circulating tumor DNA (ctDNA) from plasma, serum, and urine collected throughout treatment.

RESULTS

Mutant TP53 was detectable in ctDNA from plasma and serum in all patients. We did not detect variant TP53 in the same volume (200 μl) of urine. One patient displayed heterogeneity of TP53 in the tumor despite both histological sections displaying anaplasia. Concentration of ctDNA from plasma/serum taken prenephrectomy varied significantly between patients, ranging from 0.44 (0.05-0.90) to 125.25 (109.75-140.25) copies/μl. We observed variation in ctDNA throughout treatment, and in all but one patient, ctDNA levels fell significantly following nephrectomy.

CONCLUSION

We demonstrate for the first time that ddPCR is an effective method for detection of mutant TP53 in ctDNA from children with DAWT even when there is intratumoral somatic heterogeneity. This should be further explored in a larger cohort of patients, as early detection of circulating variant TP53 may have significant clinical impact on future risk stratification and surveillance.

Cancer Subclones Derived from the Patient's Head and Neck Squamous Cell Carcinoma Tumor Stem Cells for the Screening of Personalized Antitumor Immunotherapy and Chemotherapy

Studying on subclonal evolution of cancer stem cells can help illustrate how the immune system recognizes tumor cells, leading to subclonal treatment by immune-based therapies. Here, we discuss that cancer subclones derived from the patient's head and neck squamous cell carcinoma tumor stem cells can be used for the screening of personalized antitumor immunotherapy and chemotherapy, to maximize benefits and to minimize the adversary effects, toward personalized or precision medicine. We propose a "wait-and-watch" scheme for monitoring a lifetime cancer stem cell subclonal development evolved with local environments to cancer.

Transcriptional landscape of B cell precursor acute lymphoblastic leukemia based on an international study of 1,223 cases

Most B cell precursor acute lymphoblastic leukemia (BCP ALL) can be classified into known major genetic subtypes, while a substantial proportion of BCP ALL remains poorly characterized in relation to its underlying genomic abnormalities. We therefore initiated a large-scale international study to reanalyze and delineate the transcriptome landscape of 1,223 BCP ALL cases using RNA sequencing. Fourteen BCP ALL gene expression subgroups (G1 to G14) were identified. Apart from extending eight previously described subgroups (G1 to G8 associated with MEF2D fusions, TCF3-PBX1 fusions, ETV6-RUNX1-positive/ETV6-RUNX1-like, DUX4 fusions, ZNF384 fusions, BCR-ABL1/Ph-like, high hyperdiploidy, and KMT2A fusions), we defined six additional gene expression subgroups: G9 was associated with both PAX5 and CRLF2 fusions; G10 and G11 with mutations in PAX5 (p.P80R) and IKZF1 (p.N159Y), respectively; G12 with IGH-CEBPE fusion and mutations in ZEB2 (p.H1038R); and G13 and G14 with TCF3/4-HLF and NUTM1 fusions, respectively. In pediatric BCP ALL, subgroups G2 to G5 and G7 (51 to 65/67 chromosomes) were associated with low-risk, G7 (with ≤50 chromosomes) and G9 were intermediate-risk, whereas G1, G6, and G8 were defined as high-risk subgroups. In adult BCP ALL, G1, G2, G6, and G8 were associated with high risk, while G4, G5, and G7 had relatively favorable outcomes. This large-scale transcriptome sequence analysis of BCP ALL revealed distinct molecular subgroups that reflect discrete pathways of BCP ALL, informing disease classification and prognostic stratification. The combined results strongly advocate that RNA sequencing be introduced into the clinical diagnostic workup of BCP ALL.

Carbohydrate Targets for CAR T Cells in Solid Childhood Cancers

Application of the CAR targeting strategy in solid tumors is challenged by the need for adequate target antigens. As a consequence of their tissue origin, embryonal cancers can aberrantly express membrane-anchored gangliosides. These are carbohydrate molecules consisting of a glycosphingolipid linked to sialic acids residues. The best-known example is the abundant expression of ganglioside G_D2 on the cell surface of neuroblastomas which derive from G_D2-positive neuroectoderm. Gangliosides are involved in various cellular functions, including signal transduction, cell proliferation, differentiation, adhesion and cell death. In addition, transformation of human cells to cancer cells can be associated with distinct glycosylation profiles which provide advantages for tumor growth and dissemination and can serve as immune targets. Both gangliosides and aberrant glycosylation of proteins escape the direct molecular and proteomic screening strategies currently applied to identify further immune targets in cancers. Due to their highly restricted expression and their functional roles in the malignant behavior, they are attractive targets for immune engineering strategies. G_D2-redirected CAR T cells have shown activity in clinical phase I/II trials in neuroblastoma and next-generation studies are ongoing. Further carbohydrate targets for CAR T cells in preclinical development are O-acetyl-G_D2, NeuGc-GM3 (N-glycolyl GM3), G_D3, SSEA-4, and oncofetal glycosylation variants. This review summarizes knowledge on the role and function of some membrane-expressed non-protein antigens, including gangliosides and abnormal protein glycosylation patterns, and discusses their potential to serve as a CAR targets in pediatric solid cancers.

Genes at the Crossroad of Primary Immunodeficiencies and Cancer

Primary immunodeficiencies (PIDs) are a heterogeneous group of inherited disorders affecting one or multiple components of the innate and/or adaptive immune system. Currently, over 300 underlying genetic defects have been discovered. The most common clinical findings in patients with PIDs are infections, autoimmunity, and malignancies. Despite international efforts, the cancer risk associated with PIDs, given the heterogeneous character of this group of diseases, is difficult to estimate. The diverse underlying mechanisms of cancer in PID add another layer of complexity. Treatment of cancer within a context of PID is complicated by serious toxicities and long-term effects, including second malignancies. This review will focus on the little-known crossroad between PID and cancer genes and the value thereof for directing future research on our understanding of cancer in PID and for the identification of early cancer biomarkers in PID patients.

Adapting crowdsourced clinical cancer curation in CIViC to the ClinGen minimum variant level data community-driven standards

Harmonization of cancer variant representation, efficient communication, and free distribution of clinical variant-associated knowledge are central problems that arise with increased usage of clinical next-generation sequencing. The Clinical Genome Resource (ClinGen) Somatic Working Group (WG) developed a minimal variant level data (MVLD) representation of cancer variants, and has an ongoing collaboration with Clinical Interpretations of Variants in Cancer (CIViC), an open-source platform supporting crowdsourced and expert-moderated cancer variant curation. Harmonization between MVLD and CIViC variant formats was assessed by formal field-by-field analysis. Adjustments to the CIViC format were made to harmonize with MVLD and support ClinGen Somatic WG curation activities, including four new features in CIViC: (1) introduction of an assertions feature for clinical variant assessment following the Association of Molecular Pathologists (AMP) guidelines, (2) group-level curation tracking for organizations, enabling member transparency, and curation effort summaries, (3) introduction of ClinGen Allele Registry IDs to CIViC, and (4) mapping of CIViC assertions into ClinVar submission with automated submissions. A generalizable workflow utilizing MVLD and new CIViC features is outlined for use by ClinGen Somatic WG task teams for curation and submission to ClinVar, and provides a model for promoting harmonization of cancer variant representation and efficient distribution of this information.

Open questions: why are babies rarely born with cancer?

Childhood cancer is fundamentally a disease of dysregulated development. Why does it rarely occur during the fetal period, a time of enormous growth and development?

Multi-omic tumor data reveal diversity of molecular mechanisms that correlate with survival

Outcomes for cancer patients vary greatly even within the same tumor type, and characterization of molecular subtypes of cancer holds important promise for improving prognosis and personalized treatment. This promise has motivated recent efforts to produce large amounts of multidimensional genomic (multi-omic) data, but current algorithms still face challenges in the integrated analysis of such data. Here we present Cancer Integration via Multikernel Learning (CIMLR), a new cancer subtyping method that integrates multi-omic data to reveal molecular subtypes of cancer. We apply CIMLR to multi-omic data from 36 cancer types and show significant improvements in both computational efficiency and ability to extract biologically meaningful cancer subtypes. The discovered subtypes exhibit significant differences in patient survival for 27 of 36 cancer types. Our analysis reveals integrated patterns of gene expression, methylation, point mutations, and copy number changes in multiple cancers and highlights patterns specifically associated with poor patient outcomes.

Deep Learning-Based Multi-Omics Data Integration Reveals Two Prognostic Subtypes in High-Risk Neuroblastoma

High-risk neuroblastoma is a very aggressive disease, with excessive tumor growth and poor outcomes. A proper stratification of the high-risk patients by prognostic outcome is important for treatment. However, there is still a lack of survival stratification for the high-risk neuroblastoma. To fill the gap, we adopt a deep learning algorithm, Autoencoder, to integrate multi-omics data, and combine it with K-means clustering to identify two subtypes with significant survival differences. By comparing the Autoencoder with PCA, iCluster, and DGscore about the classification based on multi-omics data integration, Autoencoder-based classification outperforms the alternative approaches. Furthermore, we also validated the classification in two independent datasets by training machine-learning classification models, and confirmed its robustness. Functional analysis revealed that MYCN amplification was more frequently occurred in the ultra-high-risk subtype, in accordance with the overexpression of MYC/MYCN targets in this subtype. In summary, prognostic subtypes identified by deep learning-based multi-omics integration could not only improve our understanding of molecular mechanism, but also help the clinicians make decisions.

Maximizing the Utility of Cancer Transcriptomic Data

Transcriptomic profiling has been applied to large numbers of cancer samples, by large-scale consortia, including The Cancer Genome Atlas, International Cancer Genome Consortium, and Cancer Cell Line Encyclopedia. Advances in mining cancer transcriptomic data enable us to understand the endless complexity of the cancer transcriptome and thereby to discover new biomarkers and therapeutic targets. In this paper, we review computational resources for deep mining of transcriptomic data to identify, quantify, and determine the functional effects and clinical utility of transcriptomic events, including noncoding RNAs, post-transcriptional regulation, exogenous RNAs, and transcribed genetic variants. These approaches can be applied to other complex diseases, thereby greatly leveraging the impact of this work.

Major changes of cell function and toxicant sensitivity in cultured cells undergoing mild, quasi-natural genetic drift

Genomic drift affects the functional properties of cell lines, and the reproducibility of data from in vitro studies. While chromosomal aberrations and mutations in single pivotal genes are well explored, little is known about effects of minor, possibly pleiotropic, genome changes. We addressed this question for the human dopaminergic neuronal precursor cell line LUHMES by comparing two subpopulations (SP) maintained either at the American-Type-Culture-Collection (ATCC) or by the original provider (UKN). Drastic differences in susceptibility towards the specific dopaminergic toxicant 1-methyl-4-phenylpyridinium (MPP+) were observed. Whole-genome sequencing was performed to identify underlying genetic differences. While both SP had normal chromosome structures, they displayed about 70 differences on the level of amino acid changing events. Some of these differences were confirmed biochemically, but none offered a direct explanation for the altered toxicant sensitivity pattern. As second approach, markers known to be relevant for the intended use of the cells were specifically tested. The “ATCC” cells rapidly down-regulated the dopamine-transporter and tyrosine-hydroxylase after differentiation, while “UKN” cells maintained functional levels. As the respective genes were not altered themselves, we conclude that polygenic complex upstream changes can have drastic effects on biochemical features and toxicological responses of relatively similar SP of cells.