Metabolic heterogeneity underlies reciprocal fates of TH17 cell stemness and plasticity.

A defining feature of adaptive immunity is the development of long-lived memory T cells to curtail infection. Recent studies have identified a unique stem-like T-cell subset amongst exhausted CD8-positive T cells in chronic infection1-3, but it remains unclear whether CD4-positive T-cell subsets with similar features exist in chronic inflammatory conditions. Amongst helper T cells, TH17 cells have prominent roles in autoimmunity and tissue inflammation and are characterized by inherent plasticity4-7, although how such plasticity is regulated is poorly understood. Here we demonstrate that TH17 cells in a mouse model of autoimmune disease are functionally and metabolically heterogeneous; they contain a subset with stemness-associated features but lower anabolic metabolism, and a reciprocal subset with higher metabolic activity that supports transdifferentiation into TH1-like cells. These two TH17-cell subsets are defined by selective expression of the transcription factors TCF-1 and T-bet, and by discrete levels of CD27 expression. We also identify signalling via the kinase complex mTORC1 as a central regulator of TH17-cell fate decisions by coordinating metabolic and transcriptional programmes. TH17 cells with disrupted mTORC1 signalling or anabolic metabolism fail to induce autoimmune neuroinflammation or to develop into TH1-like cells, but instead upregulate TCF-1 expression and acquire stemness-associated features. Single-cell RNA sequencing and experimental validation reveal heterogeneity in fate-mapped TH17 cells, and a developmental arrest in the TH1 transdifferentiation trajectory upon loss of mTORC1 activity or metabolic perturbation. Our results establish that the dichotomy of stemness and effector function underlies the heterogeneous TH17 responses and autoimmune pathogenesis, and point to previously unappreciated metabolic control of plasticity in helper T cells.

Resolving medulloblastoma cellular architecture by single-cell genomics.

Medulloblastoma is a malignant childhood cerebellar tumour type that comprises distinct molecular subgroups. Whereas genomic characteristics of these subgroups are well defined, the extent to which cellular diversity underlies their divergent biology and clinical behaviour remains largely unexplored. Here we used single-cell transcriptomics to investigate intra- and intertumoral heterogeneity in 25 medulloblastomas spanning all molecular subgroups. WNT, SHH and Group 3 tumours comprised subgroup-specific undifferentiated and differentiated neuronal-like malignant populations, whereas Group 4 tumours consisted exclusively of differentiated neuronal-like neoplastic cells. SHH tumours closely resembled granule neurons of varying differentiation states that correlated with patient age. Group 3 and Group 4 tumours exhibited a developmental trajectory from primitive progenitor-like to more mature neuronal-like cells, the relative proportions of which distinguished these subgroups. Cross-species transcriptomics defined distinct glutamatergic populations as putative cells-of-origin for SHH and Group 4 subtypes. Collectively, these data provide insights into the cellular and developmental states underlying subtype-specific medulloblastoma biology.

Single-cell analysis reveals the Comma-1D cell line as a unique model for mammary gland development and breast cancer.

The mammary gland epithelial tree contains two distinct cell populations, luminal and basal. The investigation of how this heterogeneity is developed and how it influences tumorigenesis has been hampered by the need to perform studies on these populations using animal models. Comma-1D is an immortalized mouse mammary epithelial cell line that has unique morphogenetic properties. By performing single-cell RNA-seq studies, we found that Comma-1D cultures consist of two main populations with luminal and basal features, and a smaller population with mixed lineage and bipotent characteristics. We demonstrated that multiple transcription factors associated with the differentiation of the mammary epithelium in vivo also modulate this process in Comma-1D cultures. Additionally, we found that only cells with luminal features were able to acquire transformed characteristics after an oncogenic HER2 (also known as ERBB2) mutant was introduced in their genomes. Overall, our studies characterize, at a single-cell level, the heterogeneity of the Comma-1D cell line and illustrate how Comma-1D cells can be used as an experimental model to study both the differentiation and the transformation processes in vitro.

Impact of T-cell immunity on chemotherapy response in childhood acute lymphoblastic leukemia.

Although acute lymphoblastic leukemia (ALL) is highly responsive to chemotherapy, it is unknown how or which host immune factors influence the long-term remission of this cancer. To this end, we systematically evaluated the effects of T-cell immunity on Ph+ ALL therapy outcomes. Using a murine Arf-/-BCR-ABL1 B-cell ALL model, we showed that loss of T cells in the host drastically increased leukemia relapse after dasatinib or cytotoxic chemotherapy. Although ABL1 mutations emerged early during dasatinib treatment in both immunocompetent and immunocompromised hosts, T-cell immunity was essential for suppressing the outgrowth of drug-resistant leukemia. Bulk and single-cell transcriptome profiling of T cells during therapy pointed to the activation of type 1 immunity-related cytokine signaling being linked to long-term leukemia remission in mice. Consistent with these observations, interferon γ and interleukin 12 directly modulated dasatinib antileukemia efficacy in vivo. Finally, we evaluated peripheral blood immune cell composition in 102 children with ALL during chemotherapy and observed a significant association of T-cell abundance with treatment outcomes. Together, these results suggest that T-cell immunity plays pivotal roles in maintaining long-term remission of ALL, highlighting that the interplay between host immunity and drug resistance can be harnessed to improve ALL chemotherapy outcomes.

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

Analysis of molecular aberrations across multiple cancer types, known as pan-cancer analysis, identifies commonalities and differences in key biological processes that are dysregulated in cancer cells from diverse lineages. Pan-cancer analyses have been performed for adult but not paediatric cancers, which commonly occur in developing mesodermic rather than adult epithelial tissues. Here we present a pan-cancer study of somatic alterations, including single nucleotide variants, small insertions or deletions, structural variations, copy number alterations, gene fusions and internal tandem duplications in 1,699 paediatric leukaemias and solid tumours across six histotypes, with whole-genome, whole-exome and transcriptome sequencing data processed under a uniform analytical framework. We report 142 driver genes in paediatric cancers, of which only 45% match those found in adult pan-cancer studies; copy number alterations and structural variants constituted the majority (62%) of events. Eleven genome-wide mutational signatures were identified, including one attributed to ultraviolet-light exposure in eight aneuploid leukaemias. Transcription of the mutant allele was detectable for 34% of protein-coding mutations, and 20% exhibited allele-specific expression. These data provide a comprehensive genomic architecture for paediatric cancers and emphasize the need for paediatric cancer-specific development of precision therapies.

Cell type identification in spatial transcriptomics data can be improved by leveraging cell-type-informative paired tissue images using a Bayesian probabilistic model.

Spatial transcriptomics technologies have recently emerged as a powerful tool for measuring spatially resolved gene expression directly in tissues sections, revealing cell types and their dysfunction in unprecedented detail. However, spatial transcriptomics technologies are limited in their ability to separate transcriptionally similar cell types and can suffer further difficulties identifying cell types in slide regions where transcript capture is low. Here, we describe a conceptually novel methodology that can computationally integrate spatial transcriptomics data with cell-type-informative paired tissue images, obtained from, for example, the reverse side of the same tissue section, to improve inferences of tissue cell type composition in spatial transcriptomics data. The underlying statistical approach is generalizable to any spatial transcriptomics protocol where informative paired tissue images can be obtained. We demonstrate a use case leveraging cell-type-specific immunofluorescence markers obtained on mouse brain tissue sections and a use case for leveraging the output of AI annotated H&E tissue images, which we used to markedly improve the identification of clinically relevant immune cell infiltration in breast cancer tissue. Thus, combining spatial transcriptomics data with paired tissue images has the potential to improve the identification of cell types and hence to improve the applications of spatial transcriptomics that rely on accurate cell type identification.

Accurate genomic variant detection in single cells with primary template-directed amplification.

Improvements in whole genome amplification (WGA) would enable new types of basic and applied biomedical research, including studies of intratissue genetic diversity that require more accurate single-cell genotyping. Here, we present primary template-directed amplification (PTA), an isothermal WGA method that reproducibly captures >95% of the genomes of single cells in a more uniform and accurate manner than existing approaches, resulting in significantly improved variant calling sensitivity and precision. To illustrate the types of studies that are enabled by PTA, we developed direct measurement of environmental mutagenicity (DMEM), a tool for mapping genome-wide interactions of mutagens with single living human cells at base-pair resolution. In addition, we utilized PTA for genome-wide off-target indel and structural variant detection in cells that had undergone CRISPR-mediated genome editing, establishing the feasibility for performing single-cell evaluations of biopsies from edited tissues. The improved precision and accuracy of variant detection with PTA overcomes the current limitations of accurate WGA, which is the major obstacle to studying genetic diversity and evolution at cellular resolution.

Cancer germline predisposing variants and late mortality from subsequent malignant neoplasms among long-term childhood cancer survivors: a report from the St Jude Lifetime Cohort and the Childhood Cancer Survivor Study.

BACKGROUND: Carriers of cancer predisposing variants are at an increased risk of developing subsequent malignant neoplasms among those who have survived childhood cancer. We aimed to investigate whether cancer predisposing variants contribute to the risk of subsequent malignant neoplasm-related late mortality (5 years or more after diagnosis). METHODS: In this analysis, data were included from two retrospective cohort studies, St Jude Lifetime Cohort (SJLIFE) and the Childhood Cancer Survivor Study (CCSS), with prospective follow-up of patients who were alive for at least 5 years after diagnosis with childhood cancer (ie, long-term childhood cancer survivors) with corresponding germline whole genome or whole exome sequencing data. Cancer predisposing variants affecting 60 genes associated with well-established autosomal-dominant cancer-predisposition syndromes were characterised. Subsequent malignant neoplasms were graded using the National Cancer Institute Common Terminology Criteria for Adverse Events (CTCAE) version 4.03 with modifications. Cause-specific late mortality was based on linkage with the US National Death Index and systematic cohort follow up. Fine-Gray subdistribution hazard models were used to estimate subsequent malignant neoplasm-related late mortality starting from the first biospecimen collection, treating non-subsequent malignant neoplasm-related deaths as a competing risk, adjusting for genetic ancestry, sex, age at diagnosis, and cancer treatment exposures. SJLIFE (NCT00760656) and CCSS (NCT01120353) are registered with ClinicalTrials.gov. FINDINGS: 12 469 (6172 male and 6297 female) participants were included, 4402 from the SJLIFE cohort (median follow-up time since collection of the first biospecimen 7·4 years [IQR 3·1-9·4]) and 8067 from the CCSS cohort (median follow-up time since collection of the first biospecimen 12·6 years [2·2-16·6]). 641 (5·1%) of 12 469 participants carried cancer predisposing variants (294 [6·7%] in the SJLIFE cohort and 347 [4·3%] in the CCSS cohort), which were significantly associated with an increased severity of subsequent malignant neoplasms (CTCAE grade ≥4 vs grade <4: odds ratio 2·15, 95% CI 1·18-4·19, p=0·0085). 263 (2·1%) subsequent malignant neoplasm-related deaths (44 [1·0%] in the SJLIFE cohort; and 219 [2·7%] in the CCSS cohort) and 426 (3·4%) other-cause deaths (103 [2·3%] in SJLIFE; and 323 [4·0%] in CCSS) occurred. Cumulative subsequent malignant neoplasm-related mortality at 10 years after the first biospecimen collection in carriers of cancer predisposing variants was 3·7% (95% CI 1·2-8·5) in SJLIFE and 6·9% (4·1-10·7) in CCSS versus 1·5% (1·0-2·1) in SJLIFE and 2·1% (1·7-2·5) in CCSS in non-carriers. Carrying a cancer predisposing variant was associated with an increased risk of subsequent malignant neoplasm-related mortality (SJLIFE: subdistribution hazard ratio 3·40 [95% CI 1·37-8·43]; p=0·0082; CCSS: 3·58 [2·27-5·63]; p<0·0001). INTERPRETATION: Identifying participants at increased risk of subsequent malignant neoplasms via genetic counselling and clinical genetic testing for cancer predisposing variants and implementing early personalised cancer surveillance and prevention strategies might reduce the substantial subsequent malignant neoplasm-related mortality burden. FUNDING: American Lebanese Syrian Associated Charities and US National Institutes of Health.

A developmentally prometastatic niche to hepatoblastoma in neonatal liver mediated by the Cxcl1/Cxcr2 axis.

BACKGROUND AND AIMS: Hepatoblastoma (HB) is the most common pediatric liver cancer. Its predominant occurrence in very young children led us to investigate whether the neonatal liver provides a protumorigenic niche to HB development. APPROACH AND RESULTS: HB development was compared between orthotopic transplantation models established in postnatal day 5 (P5) and 60 (P60) mice (P5Tx and P60Tx models). Single-cell RNA-sequencing (sc-RNAseq) was performed using tumor and liver tissues from both models and the top candidate cell types and genes identified are investigated for their roles in HB cell growth, migration, and survival. CONCLUSIONS: We found that various HB cell lines including HepG2 cells were consistently and considerably more tumorigenic and metastatic in the P5Tx model than in the P60Tx models. Sc-RNAseq of the P5Tx and P60Tx HepG2 models revealed that the P5Tx tumor was more hypoxic and had a larger number of activated hepatic stellate cells (aHSCs) in the tumor-surrounding liver that express significantly higher levels of Cxcl1 than those from the P60Tx model. We found these differences were developmentally present in normal P5 and P60 liver. We showed that the Cxcl1/Cxcr2 axis mediated HB cell migration and was critical to HB cell survival under hypoxia. Treating HepG2 P60Tx model with recombinant CXCL1 protein induced intrahepatic and pulmonary metastasis and CXCR2 knockout (KO) in HepG2 cells abolished their metastatic potential in the P5Tx model. Lastly, we showed that in tumors from patients with metastatic HB, there was a similar larger population of aHSCs in the tumor-surrounding liver than in localized tumors, and tumor hypoxia was uniquely associated with prognosis of patients with HB among pediatric cancers. We demonstrated that the neonatal liver provides a prometastatic niche to HB development through the Cxcl1/Cxcr2 axis.

Orthotopic patient-derived xenografts of paediatric solid tumours.

Paediatric solid tumours arise from endodermal, ectodermal, or mesodermal lineages. Although the overall survival of children with solid tumours is 75%, that of children with recurrent disease is below 30%. To capture the complexity and diversity of paediatric solid tumours and establish new models of recurrent disease, here we develop a protocol to produce orthotopic patient-derived xenografts at diagnosis, recurrence, and autopsy. Tumour specimens were received from 168 patients, and 67 orthotopic patient-derived xenografts were established for 12 types of cancer. The origins of the patient-derived xenograft tumours were reflected in their gene-expression profiles and epigenomes. Genomic profiling of the tumours, including detailed clonal analysis, was performed to determine whether the clonal population in the xenograft recapitulated the patient's tumour. We identified several drug vulnerabilities and showed that the combination of a WEE1 inhibitor (AZD1775), irinotecan, and vincristine can lead to complete response in multiple rhabdomyosarcoma orthotopic patient-derived xenografts tumours in vivo.

Therapy-induced mutations drive the genomic landscape of relapsed acute lymphoblastic leukemia.

To study the mechanisms of relapse in acute lymphoblastic leukemia (ALL), we performed whole-genome sequencing of 103 diagnosis-relapse-germline trios and ultra-deep sequencing of 208 serial samples in 16 patients. Relapse-specific somatic alterations were enriched in 12 genes (NR3C1, NR3C2, TP53, NT5C2, FPGS, CREBBP, MSH2, MSH6, PMS2, WHSC1, PRPS1, and PRPS2) involved in drug response. Their prevalence was 17% in very early relapse (<9 months from diagnosis), 65% in early relapse (9-36 months), and 32% in late relapse (>36 months) groups. Convergent evolution, in which multiple subclones harbor mutations in the same drug resistance gene, was observed in 6 relapses and confirmed by single-cell sequencing in 1 case. Mathematical modeling and mutational signature analysis indicated that early relapse resistance acquisition was frequently a 2-step process in which a persistent clone survived initial therapy and later acquired bona fide resistance mutations during therapy. In contrast, very early relapses arose from preexisting resistant clone(s). Two novel relapse-specific mutational signatures, one of which was caused by thiopurine treatment based on in vitro drug exposure experiments, were identified in early and late relapses but were absent from 2540 pan-cancer diagnosis samples and 129 non-ALL relapses. The novel signatures were detected in 27% of relapsed ALLs and were responsible for 46% of acquired resistance mutations in NT5C2, PRPS1, NR3C1, and TP53. These results suggest that chemotherapy-induced drug resistance mutations facilitate a subset of pediatric ALL relapses.

RNAIndel: discovering somatic coding indels from tumor RNA-Seq data.

MOTIVATION: Reliable identification of expressed somatic insertions/deletions (indels) is an unmet need due to artifacts generated in PCR-based RNA-Seq library preparation and the lack of normal RNA-Seq data, presenting analytical challenges for discovery of somatic indels in tumor transcriptome. RESULTS: We present RNAIndel, a tool for predicting somatic, germline and artifact indels from tumor RNA-Seq data. RNAIndel leverages features derived from indel sequence context and biological effect in a machine-learning framework. Except for tumor samples with microsatellite instability, RNAIndel robustly predicts 88-100% of somatic indels in five diverse test datasets of pediatric and adult cancers, even recovering subclonal (VAF range 0.01-0.15) driver indels missed by targeted deep-sequencing, outperforming the current best-practice for RNA-Seq variant calling which had 57% sensitivity but with 14 times more false positives. AVAILABILITY AND IMPLEMENTATION: RNAIndel is freely available at https://github.com/stjude/RNAIndel. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

The landscape of coding RNA editing events in pediatric cancer.

BACKGROUND: RNA editing leads to post-transcriptional variation in protein sequences and has important biological implications. We sought to elucidate the landscape of RNA editing events across pediatric cancers. METHODS: Using RNA-Seq data mapped by a pipeline designed to minimize mapping ambiguity, we investigated RNA editing in 711 pediatric cancers from the St. Jude/Washington University Pediatric Cancer Genome Project focusing on coding variants which can potentially increase protein sequence diversity. We combined de novo detection using paired tumor DNA-RNA data with analysis of known RNA editing sites. RESULTS: We identified 722 unique RNA editing sites in coding regions across pediatric cancers, 70% of which were nonsynonymous recoding variants. Nearly all editing sites represented the canonical A-to-I (n = 706) or C-to-U sites (n = 14). RNA editing was enriched in brain tumors compared to other cancers, including editing of glutamate receptors and ion channels involved in neurotransmitter signaling. RNA editing profiles of each pediatric cancer subtype resembled those of the corresponding normal tissue profiled by the Genotype-Tissue Expression (GTEx) project. CONCLUSIONS: In this first comprehensive analysis of RNA editing events in pediatric cancer, we found that the RNA editing profile of each cancer subtype is similar to its normal tissue of origin. Tumor-specific RNA editing events were not identified indicating that successful immunotherapeutic targeting of RNA-edited peptides in pediatric cancer should rely on increased antigen presentation on tumor cells compared to normal but not on tumor-specific RNA editing per se.

Acute depletion of CTCF directly affects MYC regulation through loss of enhancer-promoter looping.

Numerous pieces of evidence support the complex, 3D spatial organization of the genome dictates gene expression. CTCF is essential to define topologically associated domain boundaries and to facilitate the formation of insulated chromatin loop structures. To understand CTCF's direct role in global transcriptional regulation, we integrated the miniAID-mClover3 cassette to the endogenous CTCF locus in a human pediatric B-ALL cell line, SEM, and an immortal erythroid precursor cell line, HUDEP-2, to allow for acute depletion of CTCF protein by the auxin-inducible degron system. In SEM cells, CTCF loss notably disrupted intra-TAD loops and TAD integrity in concurrence with a reduction in CTCF-binding affinity, while showing no perturbation to nuclear compartment integrity. Strikingly, the overall effect of CTCF's loss on transcription was minimal. Whole transcriptome analysis showed hundreds of genes differentially expressed in CTCF-depleted cells, among which MYC and a number of MYC target genes were specifically downregulated. Mechanically, acute depletion of CTCF disrupted the direct interaction between the MYC promoter and its distal enhancer cluster residing ∼1.8 Mb downstream. Notably, MYC expression was not profoundly affected upon CTCF loss in HUDEP-2 cells suggesting that CTCF could play a B-ALL cell line specific role in maintaining MYC expression.

Latent cellular analysis robustly reveals subtle diversity in large-scale single-cell RNA-seq data.

Single-cell RNA sequencing (scRNA-seq) is a powerful tool for characterizing the cell-to-cell variation and cellular dynamics in populations which appear homogeneous otherwise in basic and translational biological research. However, significant challenges arise in the analysis of scRNA-seq data, including the low signal-to-noise ratio with high data sparsity, potential batch effects, scalability problems when hundreds of thousands of cells are to be analyzed among others. The inherent complexities of scRNA-seq data and dynamic nature of cellular processes lead to suboptimal performance of many currently available algorithms, even for basic tasks such as identifying biologically meaningful heterogeneous subpopulations. In this study, we developed the Latent Cellular Analysis (LCA), a machine learning-based analytical pipeline that combines cosine-similarity measurement by latent cellular states with a graph-based clustering algorithm. LCA provides heuristic solutions for population number inference, dimension reduction, feature selection, and control of technical variations without explicit gene filtering. We show that LCA is robust, accurate, and powerful by comparison with multiple state-of-the-art computational methods when applied to large-scale real and simulated scRNA-seq data. Importantly, the ability of LCA to learn from representative subsets of the data provides scalability, thereby addressing a significant challenge posed by growing sample sizes in scRNA-seq data analysis.

High-resolution transcriptional dissection of in vivo Atoh1-mediated hair cell conversion in mature cochleae identifies Isl1 as a co-reprogramming factor.

In vivo direct conversion of differentiated cells holds promise for regenerative medicine; however, improving the conversion efficiency and producing functional target cells remain challenging. Ectopic Atoh1 expression in non-sensory supporting cells (SCs) in mouse cochleae induces their partial conversion to hair cells (HCs) at low efficiency. Here, we performed single-cell RNA sequencing of whole mouse sensory epithelia harvested at multiple time points after conditional overexpression of Atoh1. Pseudotemporal ordering revealed that converted HCs (cHCs) are present along a conversion continuum that correlates with both endogenous and exogenous Atoh1 expression. Bulk sequencing of isolated cell populations and single-cell qPCR confirmed 51 transcription factors, including Isl1, are differentially expressed among cHCs, SCs and HCs. In transgenic mice, co-overexpression of Atoh1 and Isl1 enhanced the HC conversion efficiency. Together, our study shows how high-resolution transcriptional profiling of direct cell conversion can identify co-reprogramming factors required for efficient conversion.

Inhibition of SF3B1 by molecules targeting the spliceosome results in massive aberrant exon skipping.

The recent identification of compounds that interact with the spliceosome (sudemycins, spliceostatin A, and meayamycin) indicates that these molecules modulate aberrant splicing via SF3B1 inhibition. Through whole transcriptome sequencing, we have demonstrated that treatment of Rh18 cells with sudemycin leads to exon skipping as the predominant aberrant splicing event. This was also observed following reanalysis of published RNA-seq data sets derived from HeLa cells after spliceostatin A exposure. These results are in contrast to previous reports that indicate that intron retention was the major consequence of SF3B1 inhibition. Analysis of the exon junctions up-regulated by these small molecules indicated that these sequences were absent in annotated human genes, suggesting that aberrant splicing events yielded novel RNA transcripts. Interestingly, the length of preferred downstream exons was significantly longer than the skipped exons, although there was no difference between the lengths of introns flanking skipped exons. The reading frame of the aberrantly skipped exons maintained a ratio of 2:1:1, close to that of the cassette exons (3:1:1) present in naturally occurring isoforms, suggesting negative selection by the nonsense-mediated decay (NMD) machinery for out-of-frame transcripts. Accordingly, genes involved in NMD and RNAs encoding proteins involved in the splicing process were enriched in both data sets. Our findings, therefore, further elucidate the mechanisms by which SF3B1 inhibition modulates pre-mRNA splicing.

Estimated number of adult survivors of childhood cancer in United States with cancer-predisposing germline variants.

PURPOSE: To estimate the absolute number of adult survivors of childhood cancer in the U.S. population who carry a pathogenic or likely pathogenic variant in a cancer predisposition gene. METHODS: Using the Surveillance, Epidemiology, and End Results (SEER) Program, we estimated the number of childhood cancer survivors on December 31, 2016 for each childhood cancer diagnosis, multiplied this by the proportion of carriers of pathogenic/likely pathogenic variants in the St. Jude Lifetime Cohort (SJLIFE) study, and projected the resulting number onto the U.S. RESULTS: Based on genome sequence data, 11.8% of 2450 SJLIFE participants carry a pathogenic/likely pathogenic variant in one of 156 cancer predisposition genes. Given this information, we estimate that 21 800 adult survivors of childhood cancer in the United States carry a pathogenic/likely pathogenic variant in one of these genes. The highest estimated absolute number of variant carriers are among survivors of central nervous system tumors (n = 4300), particularly astrocytoma (n = 1800) and other gliomas (n = 1700), acute lymphoblastic leukemia (n = 4300), and retinoblastoma (n = 3500). The most frequently mutated genes are RB1 (n = 3000), NF1 (n = 2300), and BRCA2 (n = 800). CONCLUSION: Given the increasing number of childhood cancer survivors in the United States, clinicians should counsel survivors regarding their potential genetic risk, consider referral for genetic counseling and testing, and, as appropriate, implement syndrome-specific cancer surveillance or risk-reducing measures.

C11orf95-RELA fusions drive oncogenic NF-κB signalling in ependymoma.

Members of the nuclear factor-κB (NF-κB) family of transcriptional regulators are central mediators of the cellular inflammatory response. Although constitutive NF-κB signalling is present in most human tumours, mutations in pathway members are rare, complicating efforts to understand and block aberrant NF-κB activity in cancer. Here we show that more than two-thirds of supratentorial ependymomas contain oncogenic fusions between RELA, the principal effector of canonical NF-κB signalling, and an uncharacterized gene, C11orf95. In each case, C11orf95-RELA fusions resulted from chromothripsis involving chromosome 11q13.1. C11orf95-RELA fusion proteins translocated spontaneously to the nucleus to activate NF-κB target genes, and rapidly transformed neural stem cells--the cell of origin of ependymoma--to form these tumours in mice. Our data identify a highly recurrent genetic alteration of RELA in human cancer, and the C11orf95-RELA fusion protein as a potential therapeutic target in supratentorial ependymoma.