Etiology of oncogenic fusions in 5,190 childhood cancers and its clinical and therapeutic implication.

Oncogenic fusions formed through chromosomal rearrangements are hallmarks of childhood cancer that define cancer subtype, predict outcome, persist through treatment, and can be ideal therapeutic targets. However, mechanistic understanding of the etiology of oncogenic fusions remains elusive. Here we report a comprehensive detection of 272 oncogenic fusion gene pairs by using tumor transcriptome sequencing data from 5190 childhood cancer patients. We identify diverse factors, including translation frame, protein domain, splicing, and gene length, that shape the formation of oncogenic fusions. Our mathematical modeling reveals a strong link between differential selection pressure and clinical outcome in CBFB-MYH11. We discover 4 oncogenic fusions, including RUNX1-RUNX1T1, TCF3-PBX1, CBFA2T3-GLIS2, and KMT2A-AFDN, with promoter-hijacking-like features that may offer alternative strategies for therapeutic targeting. We uncover extensive alternative splicing in oncogenic fusions including KMT2A-MLLT3, KMT2A-MLLT10, C11orf95-RELA, NUP98-NSD1, KMT2A-AFDN and ETV6-RUNX1. We discover neo splice sites in 18 oncogenic fusion gene pairs and demonstrate that such splice sites confer therapeutic vulnerability for etiology-based genome editing. Our study reveals general principles on the etiology of oncogenic fusions in childhood cancer and suggests profound clinical implications including etiology-based risk stratification and genome-editing-based therapeutics.

Malignant Progression of an Ancestral Bone Marrow Clone Harboring a CIC-NUTM2A Fusion in Isolated Myeloid Sarcoma.

Myeloid sarcoma is a rare condition consisting of extramedullary myeloid blasts found in association with acute myeloid leukemia or, in the absence of bone marrow involvement. We identified an infant with isolated myeloid sarcoma whose bone marrow was negative for involvement by flow cytometry. Sequencing revealed the fusion oncogene CIC-NUTM2A and identified the sarcoma to be clonally evolved from the bone marrow, which carried the fusion despite the absence of pathology. Murine modeling confirmed the ability of the fusion to transform hematopoietic cells and identified receptor tyrosine kinase (RTK) signaling activation consistent with disruption of the CIC transcriptional repressor. These findings extend the definition of CIC-rearranged malignancies to include hematologic disease, provide insight into the mechanism of oncogenesis, and demonstrate the importance of molecular analysis and tracking of bone marrow involvement over the course of treatment in myeloid sarcoma, including patients that lack flow cytometric evidence of leukemia at diagnosis. IMPLICATIONS: This study illustrates molecular involvement of phenotypically normal bone marrow in myeloid sarcoma, which has significant implications in clinical care. Further, it extends the definition of CIC-rearrangements to include hematologic malignancies and shows evidence of RTK activation that may be exploited therapeutically in cancer(s) driven by these fusions.

Therapeutic and prognostic insights from the analysis of cancer mutational signatures.

The somatic mutations in each cancer genome are caused by multiple mutational processes, each of which leaves a characteristic imprint (or 'signature'), potentially caused by specific etiologies or exposures. Deconvolution of these signatures offers a glimpse into the evolutionary history of individual tumors. Recent work has shown that mutational signatures may also yield therapeutic and prognostic insights, including the identification of cell-intrinsic signatures as biomarkers of drug response and prognosis. For example, mutational signatures indicating homologous recombination deficiency are associated with poly(ADP)-ribose polymerase (PARP) inhibitor sensitivity, whereas APOBEC-associated signatures are associated with ataxia telangiectasia and Rad3-related kinase (ATR) inhibitor sensitivity. Furthermore, therapy-induced mutational signatures implicated in cancer progression have also been uncovered, including the identification of thiopurine-induced TP53 mutations in leukemia. In this review, we explore the various ways mutational signatures can reveal new therapeutic and prognostic insights, thus extending their traditional role in identifying disease etiology.

Polygenic Risk Score Improves Risk Stratification and Prediction of Subsequent Thyroid Cancer after Childhood Cancer.

BACKGROUND: Subsequent thyroid cancer (STC) is one of the most common malignancies in childhood cancer survivors. We aimed to evaluate the polygenic contributions to STC risk and potential utility in improving risk prediction. METHODS: A polygenic risk score (PRS) was calculated from 12 independent SNPs associated with thyroid cancer risk in the general population. Associations between PRS and STC risk were evaluated among survivors from St. Jude Lifetime Cohort (SJLIFE) and were replicated in survivors from Childhood Cancer Survivor Study (CCSS). A risk prediction model integrating the PRS and clinical factors, initially developed in SJLIFE, and its performance were validated in CCSS. RESULTS: Among 2,370 SJLIFE survivors with a median follow-up of 28.8 [interquartile range (IQR) = 21.9-36.1] years, 65 (2.7%) developed STC. Among them, the standardized PRS was associated with an increased rate of STC [relative rate (RR) = 1.57; 95% confidence interval (CI) = 1.24-1.98; P < 0.001]. Similar associations were replicated in 6,416 CCSS survivors, among whom 121 (1.9%) developed STC during median follow-up of 28.9 (IQR = 22.6-34.6) years (RR = 1.52; 95% CI = 1.25-1.83; P < 0.001). A risk prediction model integrating the PRS with clinical factors showed better performance than the model considering only clinical factors in SJLIFE (P = 0.004, AUC = 83.2% vs. 82.1%, at age 40), which was further validated in CCSS (P = 0.010, AUC = 72.9% vs. 70.6%). CONCLUSIONS: Integration of the PRS with clinical factors provided a statistically significant improvement in risk prediction of STC, although the magnitude of improvement was modest. IMPACT: PRS improves risk stratification and prediction of STC, suggesting its potential utility for optimizing screening strategies in survivorship care.

Genomes for Kids: The Scope of Pathogenic Mutations in Pediatric Cancer Revealed by Comprehensive DNA and RNA Sequencing.

Genomic studies of pediatric cancer have primarily focused on specific tumor types or high-risk disease. Here, we used a three-platform sequencing approach, including whole-genome sequencing (WGS), whole-exome sequencing (WES), and RNA sequencing (RNA-seq), to examine tumor and germline genomes from 309 prospectively identified children with newly diagnosed (85%) or relapsed/refractory (15%) cancers, unselected for tumor type. Eighty-six percent of patients harbored diagnostic (53%), prognostic (57%), therapeutically relevant (25%), and/or cancer-predisposing (18%) variants. Inclusion of WGS enabled detection of activating gene fusions and enhancer hijacks (36% and 8% of tumors, respectively), small intragenic deletions (15% of tumors), and mutational signatures revealing of pathogenic variant effects. Evaluation of paired tumor-normal data revealed relevance to tumor development for 55% of pathogenic germline variants. This study demonstrates the power of a three-platform approach that incorporates WGS to interrogate and interpret the full range of genomic variants across newly diagnosed as well as relapsed/refractory pediatric cancers. SIGNIFICANCE: Pediatric cancers are driven by diverse genomic lesions, and sequencing has proven useful in evaluating high-risk and relapsed/refractory cases. We show that combined WGS, WES, and RNA-seq of tumor and paired normal tissues enables identification and characterization of genetic drivers across the full spectrum of pediatric cancers. This article is highlighted in the In This Issue feature, p. 2945.

Data-driven approaches to advance research and clinical care for pediatric cancer.

Pediatric cancer is a rare disease with a distinct etiology and mutational landscape compared with adult cancer. Multi-omics profiling of retrospective and prospective cohorts coupled with innovative computational analysis have been instrumental in uncovering mechanisms of tumorigenesis and drug resistance that are now informing pediatric cancer clinical therapy. In this review we present the major data resources of pediatric cancer and actionable insights into pediatric cancer etiology stemming from the identification of oncogenic gene fusions, mutational signature analysis, systems biology, cancer predisposition and survivorship studies - that have led to improved clinical diagnosis, discovery of new drug-targets, pharmacological therapy, and screening for genetic predisposition. Ultimately, integration of large-scale omics datasets generated through international collaboration is required to maximize the power of data-driven approaches to advance pediatric cancer research informing clinical therapy.

St. Jude Cloud: A Pediatric Cancer Genomic Data-Sharing Ecosystem.

Effective data sharing is key to accelerating research to improve diagnostic precision, treatment efficacy, and long-term survival in pediatric cancer and other childhood catastrophic diseases. We present St. Jude Cloud (https://www.stjude.cloud), a cloud-based data-sharing ecosystem for accessing, analyzing, and visualizing genomic data from >10,000 pediatric patients with cancer and long-term survivors, and >800 pediatric sickle cell patients. Harmonized genomic data totaling 1.25 petabytes are freely available, including 12,104 whole genomes, 7,697 whole exomes, and 2,202 transcriptomes. The resource is expanding rapidly, with regular data uploads from St. Jude's prospective clinical genomics programs. Three interconnected apps within the ecosystem-Genomics Platform, Pediatric Cancer Knowledgebase, and Visualization Community-enable simultaneously performing advanced data analysis in the cloud and enhancing the Pediatric Cancer knowledgebase. We demonstrate the value of the ecosystem through use cases that classify 135 pediatric cancer subtypes by gene expression profiling and map mutational signatures across 35 pediatric cancer subtypes. SIGNIFICANCE: To advance research and treatment of pediatric cancer, we developed St. Jude Cloud, a data-sharing ecosystem for accessing >1.2 petabytes of raw genomic data from >10,000 pediatric patients and survivors, innovative analysis workflows, integrative multiomics visualizations, and a knowledgebase of published data contributed by the global pediatric cancer community.This article is highlighted in the In This Issue feature, p. 995.

Pan-neuroblastoma analysis reveals age- and signature-associated driver alterations.

Neuroblastoma is a pediatric malignancy with heterogeneous clinical outcomes. To better understand neuroblastoma pathogenesis, here we analyze whole-genome, whole-exome and/or transcriptome data from 702 neuroblastoma samples. Forty percent of samples harbor at least one recurrent driver gene alteration and most aberrations, including MYCN, ATRX, and TERT alterations, differ in frequency by age. MYCN alterations occur at median 2.3 years of age, TERT at 3.8 years, and ATRX at 5.6 years. COSMIC mutational signature 18, previously associated with reactive oxygen species, is the most common cause of driver point mutations in neuroblastoma, including most ALK and Ras-activating variants. Signature 18 appears early and is continuous throughout disease evolution. Signature 18 is enriched in neuroblastomas with MYCN amplification, 17q gain, and increased expression of mitochondrial ribosome and electron transport-associated genes. Recurrent FGFR1 variants in six patients, and ALK N-terminal structural alterations in five samples, identify additional patients potentially amenable to precision therapy.

Persistent activation of interlinked type 2 airway epithelial gene networks in sputum-derived cells from aeroallergen-sensitized symptomatic asthmatics.

Atopic asthma is a persistent disease characterized by intermittent wheeze and progressive loss of lung function. The disease is thought to be driven primarily by chronic aeroallergen-induced type 2-associated inflammation. However, the vast majority of atopics do not develop asthma despite ongoing aeroallergen exposure, suggesting additional mechanisms operate in conjunction with type 2 immunity to drive asthma pathogenesis. We employed RNA-Seq profiling of sputum-derived cells to identify gene networks operative at baseline in house dust mite-sensitized (HDMS) subjects with/without wheezing history that are characteristic of the ongoing asthmatic state. The expression of type 2 effectors (IL-5, IL-13) was equivalent in both cohorts of subjects. However, in HDMS-wheezers they were associated with upregulation of two coexpression modules comprising multiple type 2- and epithelial-associated genes. The first module was interlinked by the hubs EGFR, ERBB2, CDH1 and IL-13. The second module was associated with CDHR3 and mucociliary clearance genes. Our findings provide new insight into the molecular mechanisms operative at baseline in the airway mucosa in atopic asthmatics undergoing natural aeroallergen exposure, and suggest that susceptibility to asthma amongst these subjects involves complex interactions between type 2- and epithelial-associated gene networks, which are not operative in equivalently sensitized/exposed atopic non-asthmatics.