ATP2B2 de novo variants as a cause of variable neurodevelopmental disorders that feature dystonia, ataxia, intellectual disability, behavioral symptoms, and seizures.

PURPOSE: ATP2B2 encodes the variant-constrained plasma-membrane calcium-transporting ATPase-2, expressed in sensory ear cells and specialized neurons. ATP2B2/Atp2b2 variants were previously linked to isolated hearing loss in patients and neurodevelopmental deficits with ataxia in mice. We aimed to establish the association between ATP2B2 and human neurological disorders. METHODS: Multinational case recruitment, scrutiny of trio-based genomics data, in silico analyses, and functional variant characterization were performed. RESULTS: We assembled 7 individuals harboring rare, predicted deleterious heterozygous ATP2B2 variants. The alleles comprised 5 missense substitutions that affected evolutionarily conserved sites and 2 frameshift variants in the penultimate exon. For 6 variants, a de novo status was confirmed. Unlike described patients with hearing loss, the individuals displayed a spectrum of neurological abnormalities, ranging from ataxia with dystonic features to complex neurodevelopmental manifestations with intellectual disability, autism, and seizures. Two cases with recurrent amino-acid variation showed distinctive overlap with cerebellar atrophy-associated ataxia and epilepsy. In cell-based studies, all variants caused significant alterations in cytosolic calcium handling with both loss- and gain-of-function effects. CONCLUSION: Presentations in our series recapitulate key phenotypic aspects of Atp2b2-mouse models and underline the importance of precise calcium regulation for neurodevelopment and cerebellar function. Our study documents a role for ATP2B2 variants in causing heterogeneous neurodevelopmental and movement-disorder syndromes.

SNooPer: a machine learning-based method for somatic variant identification from low-pass next-generation sequencing.

BACKGROUND: Next-generation sequencing (NGS) allows unbiased, in-depth interrogation of cancer genomes. Many somatic variant callers have been developed yet accurate ascertainment of somatic variants remains a considerable challenge as evidenced by the varying mutation call rates and low concordance among callers. Statistical model-based algorithms that are currently available perform well under ideal scenarios, such as high sequencing depth, homogeneous tumor samples, high somatic variant allele frequency (VAF), but show limited performance with sub-optimal data such as low-pass whole-exome/genome sequencing data. While the goal of any cancer sequencing project is to identify a relevant, and limited, set of somatic variants for further sequence/functional validation, the inherently complex nature of cancer genomes combined with technical issues directly related to sequencing and alignment can affect either the specificity and/or sensitivity of most callers. RESULTS: For these reasons, we developed SNooPer, a versatile machine learning approach that uses Random Forest classification models to accurately call somatic variants in low-depth sequencing data. SNooPer uses a subset of variant positions from the sequencing output for which the class, true variation or sequencing error, is known to train the data-specific model. Here, using a real dataset of 40 childhood acute lymphoblastic leukemia patients, we show how the SNooPer algorithm is not affected by low coverage or low VAFs, and can be used to reduce overall sequencing costs while maintaining high specificity and sensitivity to somatic variant calling. When compared to three benchmarked somatic callers, SNooPer demonstrated the best overall performance. CONCLUSIONS: While the goal of any cancer sequencing project is to identify a relevant, and limited, set of somatic variants for further sequence/functional validation, the inherently complex nature of cancer genomes combined with technical issues directly related to sequencing and alignment can affect either the specificity and/or sensitivity of most callers. The flexibility of SNooPer's random forest protects against technical bias and systematic errors, and is appealing in that it does not rely on user-defined parameters. The code and user guide can be downloaded at https://sourceforge.net/projects/snooper/ .

Genomic characterization of pediatric T-cell acute lymphoblastic leukemia reveals novel recurrent driver mutations.

T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive hematologic malignancy with variable prognosis. It represents 15% of diagnosed pediatric ALL cases and has a threefold higher incidence among males. Many recurrent alterations have been identified and help define molecular subgroups of T-ALL, however the full range of events involved in driving transformation remain to be defined. Using an integrative approach combining genomic and transcriptomic data, we molecularly characterized 30 pediatric T-ALLs and identified common recurrent T-ALL targets such as FBXW7, JAK1, JAK3, PHF6, KDM6A and NOTCH1 as well as novel candidate T-ALL driver mutations including the p.R35L missense mutation in splicesome factor U2AF1 found in 3 patients and loss of function mutations in the X-linked tumor suppressor genes MED12 (frameshit mutation p.V167fs, splice site mutation g.chrX:70339329T>C, missense mutation p.R1989H) and USP9X (nonsense mutation p.Q117*). In vitro functional studies further supported the putative role of these novel T-ALL genes in driving transformation. U2AF1 p.R35L was shown to induce aberrant splicing of downstream target genes, and shRNA knockdown of MED12 and USP9X was shown to confer resistance to apoptosis following T-ALL relevant chemotherapy drug treatment in Jurkat leukemia cells. Interestingly, nearly 60% of novel candidate driver events were identified among immature T-ALL cases, highlighting the underlying genomic complexity of pediatric T-ALL, and the need for larger integrative studies to decipher the mechanisms that contribute to its various subtypes and provide opportunities to refine patient stratification and treatment.

A novel somatic mutation in ACD induces telomere lengthening and apoptosis resistance in leukemia cells.

BACKGROUND: The identification of oncogenic driver mutations has largely relied on the assumption that genes that exhibit more mutations than expected by chance are more likely to play an active role in tumorigenesis. Major cancer sequencing initiatives have therefore focused on recurrent mutations that are more likely to be drivers. However, in specific genetic contexts, low frequency mutations may also be capable of participating in oncogenic processes. Reliable strategies for identifying these rare or even patient-specific (private) mutations are needed in order to elucidate more personalized approaches to cancer diagnosis and treatment. METHODS: Here we performed whole-exome sequencing on three cases of childhood pre-B acute lymphoblastic leukemia (cALL), representing three cytogenetically-defined subgroups (high hyperdiploid, t(12;21) translocation, and cytogenetically normal). We applied a data reduction strategy to identify both common and rare/private somatic events with high functional potential. Top-ranked candidate mutations were subsequently validated at high sequencing depth on an independent platform and in vitro expression assays were performed to evaluate the impact of identified mutations on cell growth and survival. RESULTS: We identified 6 putatively damaging non-synonymous somatic mutations among the three cALL patients. Three of these mutations were well-characterized common cALL mutations involved in constitutive activation of the mitogen-activated protein kinase pathway (FLT3 p.D835Y, NRAS p.G13D, BRAF p.G466A). The remaining three patient-specific mutations (ACD p.G223V, DOT1L p.V114F, HCFC1 p.Y103H) were novel mutations previously undescribed in public cancer databases. Cytotoxicity assays demonstrated a protective effect of the ACD p.G223V mutation against apoptosis in leukemia cells. ACD plays a key role in protecting telomeres and recruiting telomerase. Using a telomere restriction fragment assay, we also showed that this novel mutation in ACD leads to increased telomere length in leukemia cells. CONCLUSION: This study identified ACD as a novel gene involved in cALL and points to a functional role for ACD in enhancing leukemia cell survival. These results highlight the importance of rare/private somatic mutations in understanding cALL etiology, even within well-characterized molecular subgroups.

Whole-exome sequencing of a rare case of familial childhood acute lymphoblastic leukemia reveals putative predisposing mutations in Fanconi anemia genes.

BACKGROUND: Acute lymphoblastic leukemia (ALL) is the most common pediatric cancer. While the multi-step model of pediatric leukemogenesis suggests interplay between constitutional and somatic genomes, the role of inherited genetic variability remains largely undescribed. Nonsyndromic familial ALL, although extremely rare, provides the ideal setting to study inherited contributions to ALL. Toward this goal, we sequenced the exomes of a childhood ALL family consisting of mother, father and two non-twinned siblings diagnosed with concordant pre-B hyperdiploid ALL and previously shown to have inherited a rare form of PRDM9, a histone H3 methyltransferase involved in crossing-over at recombination hotspots and Holliday junctions. We postulated that inheritance of additional rare disadvantaging variants in predisposing cancer genes could affect genomic stability and lead to increased risk of hyperdiploid ALL within this family. METHODS: Whole exomes were captured using Agilent's SureSelect kit and sequenced on the Life Technologies SOLiD System. We applied a data reduction strategy to identify candidate variants shared by both affected siblings. Under a recessive disease model, we focused on rare non-synonymous or frame-shift variants in leukemia predisposing pathways. RESULTS: Though the family was nonsyndromic, we identified a combination of rare variants in Fanconi anemia (FA) genes FANCP/SLX4 (compound heterozygote - rs137976282/rs79842542) and FANCA (rs61753269) and a rare homozygous variant in the Holliday junction resolvase GEN1 (rs16981869). These variants, predicted to affect protein function, were previously identified in familial breast cancer cases. Based on our in-house database of 369 childhood ALL exomes, the sibs were the only patients to carry this particularly rare combination and only a single hyperdiploid patient was heterozygote at both FANCP/SLX4 positions, while no FANCA variant allele carriers were identified. FANCA is the most commonly mutated gene in FA and is essential for resolving DNA interstrand cross-links during replication. FANCP/SLX4 and GEN1 are involved in the cleavage of Holliday junctions and their mutated forms, in combination with the rare allele of PRDM9, could alter Holliday junction resolution leading to nondisjunction of chromosomes and segregation defects. CONCLUSION: Taken together, these results suggest that concomitant inheritance of rare variants in FANCA, FANCP/SLX4 and GEN1 on the specific genetic background of this familial case, could lead to increased genomic instability, hematopoietic dysfunction, and higher risk of childhood leukemia.

Integration of high-resolution methylome and transcriptome analyses to dissect epigenomic changes in childhood acute lymphoblastic leukemia.

B-cell precursor acute lymphoblastic leukemia (pre-B ALL) is the most common pediatric cancer. Although the genetic determinants underlying disease onset remain unclear, epigenetic modifications including DNA methylation are suggested to contribute significantly to leukemogenesis. Using the Illumina 450K array, we assessed DNA methylation in matched tumor-normal samples of 46 childhood patients with pre-B ALL, extending single CpG-site resolution analysis of the pre-B ALL methylome beyond CpG-islands (CGI). Unsupervised hierarchical clustering of CpG-site neighborhood, gene, or microRNA (miRNA) gene-associated methylation levels separated the tumor cohort according to major pre-B ALL subtypes, and methylation in CGIs, CGI shores, and in regions around the transcription start site was found to significantly correlate with transcript expression. Focusing on samples carrying the t(12;21) ETV6-RUNX1 fusion, we identified 119 subtype-specific high-confidence marker CpG-loci. Pathway analyses linked the CpG-loci-associated genes with hematopoiesis and cancer. Further integration with whole-transcriptome data showed the effects of methylation on expression of 17 potential drivers of leukemogenesis. Independent validation of array methylation and sequencing-derived transcript expression with Sequenom Epityper technology and real-time quantitative reverse transcriptase PCR, respectively, indicates more than 80% empirical accuracy of our genome-wide findings. In summary, genome-wide DNA methylation profiling enabled us to separate pre-B ALL according to major subtypes, to map epigenetic biomarkers specific for the t(12;21) subtype, and through a combined methylome and transcriptome approach to identify downstream effects on candidate drivers of leukemogenesis.

Joint genotype inference with germline and somatic mutations.

The joint sequencing of related genomes has become an important means to discover rare variants. Normal-tumor genome pairs are routinely sequenced together to find somatic mutations and their associations with different cancers. Parental and sibling genomes reveal de novo germline mutations and inheritance patterns related to Mendelian diseases.Acute lymphoblastic leukemia (ALL) is the most common paediatric cancer and the leading cause of cancer-related death among children. With the aim of uncovering the full spectrum of germline and somatic genetic alterations in childhood ALL genomes, we conducted whole-exome re-sequencing on a unique cohort of over 120 exomes of childhood ALL quartets, each comprising a patient's tumor and matched-normal material, and DNA from both parents. We developed a general probabilistic model for such quartet sequencing reads mapped to the reference human genome. The model is used to infer joint genotypes at homologous loci across a normal-tumor genome pair and two parental genomes.We describe the algorithms and data structures for genotype inference, model parameter training. We implemented the methods in an open-source software package (QUADGT) that uses the standard file formats of the 1000 Genomes Project. Our method's utility is illustrated on quartets from the ALL cohort.

Rare allelic forms of PRDM9 associated with childhood leukemogenesis.

One of the most rapidly evolving genes in humans, PRDM9, is a key determinant of the distribution of meiotic recombination events. Mutations in this meiotic-specific gene have previously been associated with male infertility in humans and recent studies suggest that PRDM9 may be involved in pathological genomic rearrangements. In studying genomes from families with children affected by B-cell precursor acute lymphoblastic leukemia (B-ALL), we characterized meiotic recombination patterns within a family with two siblings having hyperdiploid childhood B-ALL and observed unusual localization of maternal recombination events. The mother of the family carries a rare PRDM9 allele, potentially explaining the unusual patterns found. From exomes sequenced in 44 additional parents of children affected with B-ALL, we discovered a substantial and significant excess of rare allelic forms of PRDM9. The rare PRDM9 alleles are transmitted to the affected children in half the cases; nonetheless there remains a significant excess of rare alleles among patients relative to controls. We successfully replicated this latter observation in an independent cohort of 50 children with B-ALL, where we found an excess of rare PRDM9 alleles in aneuploid and infant B-ALL patients. PRDM9 variability in humans is thought to influence genomic instability, and these data support a potential role for PRDM9 variation in risk of acquiring aneuploidies or genomic rearrangements associated with childhood leukemogenesis.