CelFiE-ISH: a probabilistic model for multi-cell type deconvolution from single-molecule DNA methylation haplotypes.

Deconvolution methods infer quantitative cell type estimates from bulk measurement of mixed samples including blood and tissue. DNA methylation sequencing measures multiple CpGs per read, but few existing deconvolution methods leverage this within-read information. We develop CelFiE-ISH, which extends an existing method (CelFiE) to use within-read haplotype information. CelFiE-ISH outperforms CelFiE and other existing methods, achieving 30% better accuracy and more sensitive detection of rare cell types. We also demonstrate the importance of marker selection and of tailoring markers for haplotype-aware methods. While here we use gold-standard short-read sequencing data, haplotype-aware methods will be well-suited for long-read sequencing.

EZH2-driven immune evasion defines high-risk pediatric AML with t(16;21) FUS::ERG gene fusion.

Despite decades of research, acute myeloid leukemia (AML) remains a remarkably lethal malignancy. While pediatric AML (pAML) carries a more favorable prognosis than adult AML, the past 25 years of large clinical trials have produced few improvements in pAML survival. Nowhere is this more evident than in patients carrying a t(16;21)(p11;q22) translocation, which yields the FUS::ERG fusion transcript. Patients with FUS::ERG-positive AML are often primary refractory, and most responders quickly relapse. In COG clinical trials, allogeneic stem cell transplantation was of no benefit to FUS::ERG pAML patients; 100% of transplanted patients succumbed to their disease. Expression of major histocompatibility complex (MHC) class I & II and costimulatory molecules is absent at diagnosis in FUS::ERG AML, mirroring the epigenetic mechanism of post-transplant relapse seen in adult AML and its associated dismal outcomes. Here we show that this class-defining immune-repressive phenotype is driven by overexpression of the EZH2 histone lysine methyltransferase in vitro and in multiple clinical cohorts. We show that treatment with the FDA-approved EZH2 inhibitor tazemetostat along with IFN-γ reverses this phenotype, re-establishes MHC presentation, and severely impairs the viability of FUS::ERG AML cells. EZH2 inhibitors may thus provide the first targeted therapeutic option for patients with this high-risk subtype of pAML, with particular benefit as a bridge to successful allogeneic stem cell transplantation.

EGFR-dependent endocytosis of Wnt9a and Fzd9b promotes ß-catenin signaling during hematopoietic stem cell development in zebrafish.

Cell-to-cell communication through secreted Wnt ligands that bind to members of the Frizzled (Fzd) family of transmembrane receptors is critical for development and homeostasis. Wnt9a signals through Fzd9b, the co-receptor LRP5 or LRP6 (LRP5/6), and the epidermal growth factor receptor (EGFR) to promote early proliferation of zebrafish and human hematopoietic stem cells during development. Here, we developed fluorescently labeled, biologically active Wnt9a and Fzd9b fusion proteins to demonstrate that EGFR-dependent endocytosis of the ligand-receptor complex was required for signaling. In human cells, the Wnt9a-Fzd9b complex was rapidly endocytosed and trafficked through early and late endosomes, lysosomes, and the endoplasmic reticulum. Using small-molecule inhibitors and genetic and knockdown approaches, we found that Wnt9a-Fzd9b endocytosis required EGFR-mediated phosphorylation of the Fzd9b tail, caveolin, and the scaffolding protein EGFR protein substrate 15 (EPS15). LRP5/6 and the downstream signaling component AXIN were required for Wnt9a-Fzd9b signaling but not for endocytosis. Knockdown or loss of EPS15 impaired hematopoietic stem cell development in zebrafish. Other Wnt ligands do not require endocytosis for signaling activity, implying that specific modes of endocytosis and trafficking may represent a method by which Wnt-Fzd specificity is established.

BISCUIT: an efficient, standards-compliant tool suite for simultaneous genetic and epigenetic inference in bulk and single-cell studies.

Data from both bulk and single-cell whole-genome DNA methylation experiments are under-utilized in many ways. This is attributable to inefficient mapping of methylation sequencing reads, routinely discarded genetic information, and neglected read-level epigenetic and genetic linkage information. We introduce the BISulfite-seq Command line User Interface Toolkit (BISCUIT) and its companion R/Bioconductor package, biscuiteer, for simultaneous extraction of genetic and epigenetic information from bulk and single-cell DNA methylation sequencing. BISCUIT's performance, flexibility and standards-compliant output allow large, complex experimental designs to be characterized on clinical timescales. BISCUIT is particularly suited for processing data from single-cell DNA methylation assays, with its excellent scalability, efficiency, and ability to greatly enhance mappability, a key challenge for single-cell studies. We also introduce the epiBED format for single-molecule analysis of coupled epigenetic and genetic information, facilitating the study of cellular and tissue heterogeneity from DNA methylation sequencing.

Developmental priming of cancer susceptibility.

DNA mutations are necessary drivers of cancer, yet only a small subset of mutated cells go on to cause the disease. To date, the mechanisms that determine which rare subset of cells transform and initiate tumorigenesis remain unclear. Here, we take advantage of a unique model of intrinsic developmental heterogeneity (Trim28+/D9) and demonstrate that stochastic early life epigenetic variation can trigger distinct cancer-susceptibility 'states' in adulthood. We show that these developmentally primed states are characterized by differential methylation patterns at typically silenced heterochromatin, and that these epigenetic signatures are detectable as early as 10 days of age. The differentially methylated loci are enriched for genes with known oncogenic potential. These same genes are frequently mutated in human cancers, and their dysregulation correlates with poor prognosis. These results provide proof-of-concept that intrinsic developmental heterogeneity can prime individual, life-long cancer risk.

bamSliceR: cross-cohort variant and allelic bias analysis for rare variants and rare diseases.

Rare diseases and conditions create unique challenges for genetic epidemiologists precisely because cases and samples are scarce. In recent years, whole-genome and whole-transcriptome sequencing (WGS/WTS) have eased the study of rare genetic variants. Paired WGS and WTS data are ideal, but logistical and financial constraints often preclude generating paired WGS and WTS data. Thus, many databases contain a patchwork of specimens with either WGS or WTS data, but only a minority of samples have both. The NCI Genomic Data Commons facilitates controlled access to genomic and transcriptomic data for thousands of subjects, many with unpaired sequencing results. Local reanalysis of expressed variants across whole transcriptomes requires significant data storage, compute, and expertise. We developed the bamSliceR package to facilitate swift transition from aligned sequence reads to expressed variant characterization. bamSliceR leverages the NCI Genomic Data Commons API to query genomic sub-regions of aligned sequence reads from specimens identified through the robust Bioconductor ecosystem. We demonstrate how population-scale targeted genomic analysis can be completed using orders of magnitude fewer resources in this fashion, with minimal compute burden. We demonstrate pilot results from bamSliceR for the TARGET pediatric AML and BEAT-AML projects, where identification of rare but recurrent somatic variants directly yields biologically testable hypotheses. bamSliceR and its documentation are freely available on GitHub at https://github.com/trichelab/bamSliceR.

Long Noncoding RNA Expression Independently Predicts Outcome in Pediatric Acute Myeloid Leukemia.

PURPOSE: Optimized strategies for risk classification are essential to tailor therapy for patients with biologically distinctive disease. Risk classification in pediatric acute myeloid leukemia (pAML) relies on detection of translocations and gene mutations. Long noncoding RNA (lncRNA) transcripts have been shown to associate with and mediate malignant phenotypes in acute myeloid leukemia (AML) but have not been comprehensively evaluated in pAML. METHODS: To identify lncRNA transcripts associated with outcomes, we evaluated the annotated lncRNA landscape by transcript sequencing of 1,298 pediatric and 96 adult AML specimens. Upregulated lncRNAs identified in the pAML training set were used to establish a regularized Cox regression model of event-free survival (EFS), yielding a 37 lncRNA signature (lncScore). Discretized lncScores were correlated with initial and postinduction treatment outcomes using Cox proportional hazards models in validation sets. Predictive model performance was compared with standard stratification methods by concordance analysis. RESULTS: Training set cases with positive lncScores had 5-year EFS and overall survival rates of 26.7% and 42.7%, respectively, compared with 56.9% and 76.3% with negative lncScores (hazard ratio, 2.48 and 3.16; P < .001). Pediatric validation cohorts and an adult AML group yielded comparable results in magnitude and significance. lncScore remained independently prognostic in multivariable models, including key factors used in preinduction and postinduction risk stratification. Subgroup analysis suggested that lncScores provide additional outcome information in heterogeneous subgroups currently classified as indeterminate risk. Concordance analysis showed that lncScore adds to overall classification accuracy with at least comparable predictive performance to current stratification methods that rely on multiple assays. CONCLUSION: Inclusion of the lncScore enhances predictive power of traditional cytogenetic and mutation-defined stratification in pAML with potential, as a single assay, to replace these complex stratification schemes with comparable predictive accuracy.

Comprehensive molecular and clinical characterization of NUP98 fusions in pediatric acute myeloid leukemia.

NUP98 fusions comprise a family of rare recurrent alterations in AML, associated with adverse outcomes. In order to define the underlying biology and clinical implications of this family of fusions, we performed comprehensive transcriptome, epigenome, and immunophenotypic profiling of 2,235 children and young adults with AML and identified 160 NUP98 rearrangements (7.2%), including 108 NUP98-NSD1 (4.8%), 32 NUP98-KDM5A (1.4%) and 20 NUP98-X cases (0.9%) with 13 different fusion partners. Fusion partners defined disease characteristics and biology; patients with NUP98-NSD1 or NUP98-KDM5A had distinct immunophenotypic, transcriptomic, and epigenomic profiles. Unlike the two most prevalent NUP98 fusions, NUP98-X variants are typically not cryptic. Furthermore, NUP98-X cases are associated with WT1 mutations, and have epigenomic profiles that resemble either NUP98-NSD1 or NUP98-KDM5A. Cooperating FLT3-ITD and WT1 mutations define NUP98-NSD1, and chromosome 13 aberrations are highly enriched in NUP98-KDM5A. Importantly, we demonstrate that NUP98 fusions portend dismal overall survival, with the noteworthy exception of patients bearing abnormal chromosome 13 (clinicaltrials gov. Identifiers: NCT00002798, NCT00070174, NCT00372593, NCT01371981).

Evolutionary Landscape of SOX Genes to Inform Genotype-to-Phenotype Relationships.

The SOX transcription factor family is pivotal in controlling aspects of development. To identify genotype-phenotype relationships of SOX proteins, we performed a non-biased study of SOX using 1890 open-reading frame and 6667 amino acid sequences in combination with structural dynamics to interpret 3999 gnomAD, 485 ClinVar, 1174 Geno2MP, and 4313 COSMIC human variants. We identified, within the HMG (High Mobility Group)- box, twenty-seven amino acids with changes in multiple SOX proteins annotated to clinical pathologies. These sites were screened through Geno2MP medical phenotypes, revealing novel SOX15 R104G associated with musculature abnormality and SOX8 R159G with intellectual disability. Within gnomAD, SOX18 E137K (rs201931544), found within the HMG box of ~0.8% of Latinx individuals, is associated with seizures and neurological complications, potentially through blood-brain barrier alterations. A total of 56 highly conserved variants were found at sites outside the HMG-box, including several within the SOX2 HMG-box-flanking region with neurological associations, several in the SOX9 dimerization region associated with Campomelic Dysplasia, SOX14 K88R (rs199932938) flanking the HMG box associated with cardiovascular complications within European populations, and SOX7 A379V (rs143587868) within an SOXF conserved far C-terminal domain heterozygous in 0.716% of African individuals with associated eye phenotypes. This SOX data compilation builds a robust genotype-to-phenotype association for a gene family through more robust ortholog data integration.

Potential methylation-regulated genes and pathways in hepatocellular neoplasm, not otherwise specified.

Background and Aims: The molecular basis of hepatocellular neoplasm, not otherwise specified (HCN-NOS) is unknown. We aimed to identify gene expression patterns, potential methylation-regulated genes and pathways that characterize the tumor, and its possible relationship to hepatoblastoma and hepatocellular carcinoma (HCC). Approach & Results: Parallel genome-wide profiling of gene expression (RNAseq) and DNA methylation (EPIC850) was performed on 4 pairs of pre-treatment HCN-NOS tumors and adjacent non-tumor controls. 2530 significantly differentially expressed genes (DEGs) were identified between tumors and controls. Many of these DEGs were associated with hepatoblastoma and/or HCC. Analysis Match in Ingenuity Pathway Analysis determined that the gene expression profile of HCN-NOS was unique but significantly similar to that of both hepatoblastoma and HCC. A total of 27,195 CpG sites (CpGs) were significantly differentially methylated (DM) between tumors and controls, with a global hypomethylation pattern and predominant CpG island hypermethylation in promotor regions. Aberrant DNA methylation predominated in Developmental Process and Molecular Function Regulator pathways. Embryonic stem cell pathways were significantly enriched. In total, 1055 aberrantly methylated (at CpGs) and differentially expressed genes were identified, including 25 upstream regulators and sixty-one potential CpG island methylation-regulated genes. Eight methylation-regulated genes (TCF3, MYBL2, SRC, HMGA2, PPARGC1A, SLC22A1, COL2A1 and MYCN) had highly consistent gene expression patterns and prognostic value in patients with HCC, based on comparison to publicly available datasets. Conclusions: HCN-NOS has a unique, stem-cell like gene expression and DNA methylation profile related to both hepatoblastoma and HCC but distinct therefrom. Further, 8 methylation-regulated genes associated with prognosis in HCC were identified.

Mitochondrial DNA haplogroup, genetic ancestry, and susceptibility to Ewing sarcoma.

Based on current studies, the incidence of Ewing sarcoma (ES) varies significantly by race and ethnicity, with the disease being most common in patients of European ancestry. However, race/ethnicity has generally been self-reported rather than formally evaluated at a population level using DNA evidence. Additionally, mitochondrial dysfunction is a hallmark of ES, yet there have been no reported studies of mitochondrial genetics in ES. Thus, we evaluated both the mitochondrial and nuclear ancestries of 420 pediatric ES patients in the United States using whole-genome sequencing. We found that the mitochondrial DNA (mtDNA) genomes of only six (1.4 %) patients belonged to African L haplogroups, while those of 90 % of the patients belonged to macrohaplogroup R, which includes haplogroup H, the most common maternal lineage in Europe. Compared to the general US population, European haplogroups were significantly enriched in ES patients (p < 2.2e-16) and the African haplogroups are significantly impoverished (p < 4.6e-16). Using the ancestry informative markers defined in a National Genographic study, the vast majority of patients exhibited significant nuclear ancestry originating from the Mediterranean, Northern Europe, and Southwest Asia, including all six patients with African L mtDNAs. Very few had primarily African nuclear ancestry. This is the first genomic epidemiology study to simultaneously interrogate the mitochondrial and nuclear ancestries of ES patients. While supporting previous findings of enriched European ancestry in ES patients, these results also suggest alternative hypotheses for the significant contribution of mitochondrial ancestry in ES patients, as well as the protective role of African ancestry.

Integrated stem cell signature and cytomolecular risk determination in pediatric acute myeloid leukemia.

Relapsed or refractory pediatric acute myeloid leukemia (AML) is associated with poor outcomes and relapse risk prediction approaches have not changed significantly in decades. To build a robust transcriptional risk prediction model for pediatric AML, we perform RNA-sequencing on 1503 primary diagnostic samples. While a 17 gene leukemia stem cell signature (LSC17) is predictive in our aggregated pediatric study population, LSC17 is no longer predictive within established cytogenetic and molecular (cytomolecular) risk groups. Therefore, we identify distinct LSC signatures on the basis of AML cytomolecular subtypes (LSC47) that were more predictive than LSC17. Based on these findings, we build a robust relapse prediction model within a training cohort and then validate it within independent cohorts. Here, we show that LSC47 increases the predictive power of conventional risk stratification and that applying biomarkers in a manner that is informed by cytomolecular profiling outperforms a uniform biomarker approach.

Integrated DNA Copy Number and Expression Profiling Identifies IGF1R as a Prognostic Biomarker in Pediatric Osteosarcoma.

Osteosarcoma is a primary malignant bone tumor arising from bone-forming mesenchymal cells in children and adolescents. Despite efforts to understand the biology of the disease and identify novel therapeutics, the survival of osteosarcoma patients remains dismal. We have concurrently profiled the copy number and gene expression of 226 osteosarcoma samples as part of the Strategic Partnering to Evaluate Cancer Signatures (SPECS) initiative. Our results demonstrate the heterogeneous landscape of osteosarcoma in younger populations by showing the presence of genome-wide copy number abnormalities occurring both recurrently among samples and in a high frequency. Insulin growth factor receptor 1 (IGF1R) is a receptor tyrosine kinase which binds IGF1 and IGF2 to activate downstream pathways involved in cell apoptosis and proliferation. We identify prevalent amplification of IGF1R corresponding with increased gene expression in patients with poor survival outcomes. Our results substantiate previously tenuously associated copy number abnormalities identified in smaller datasets (13q34+, 20p13+, 4q35-, 20q13.33-), and indicate the significance of high fibroblast growth factor receptor 2 (FGFR2) expression in distinguishing patients with poor prognosis. FGFR2 is involved in cellular proliferation processes such as division, growth and angiogenesis. In summary, our findings demonstrate the prognostic significance of several genes associated with osteosarcoma pathogenesis.

Non-Invasive Profiling of Advanced Prostate Cancer via Multi-Parametric Liquid Biopsy and Radiomic Analysis.

Integrating liquid biopsies of circulating tumor cells (CTCs) and cell-free DNA (cfDNA) with other minimally invasive measures may yield more comprehensive disease profiles. We evaluated the feasibility of concurrent cellular and molecular analysis of CTCs and cfDNA combined with radiomic analysis of CT scans from patients with metastatic castration-resistant PC (mCRPC). CTCs from 22 patients were enumerated, stained for PC-relevant markers, and clustered based on morphometric and immunofluorescent features using machine learning. DNA from single CTCs, matched cfDNA, and buffy coats was sequenced using a targeted amplicon cancer hotspot panel. Radiomic analysis was performed on bone metastases identified on CT scans from the same patients. CTCs were detected in 77% of patients and clustered reproducibly. cfDNA sequencing had high sensitivity (98.8%) for germline variants compared to WBC. Shared and unique somatic variants in PC-related genes were detected in cfDNA in 45% of patients (MAF > 0.1%) and in CTCs in 92% of patients (MAF > 10%). Radiomic analysis identified a signature that strongly correlated with CTC count and plasma cfDNA level. Integration of cellular, molecular, and radiomic data in a multi-parametric approach is feasible, yielding complementary profiles that may enable more comprehensive non-invasive disease modeling and prediction.

Dysregulated heparan sulfate proteoglycan metabolism promotes Ewing sarcoma tumor growth.

The Ewing sarcoma family of tumors is a group of malignant small round blue cell tumors (SRBCTs) that affect children, adolescents, and young adults. The tumors are characterized by reciprocal chromosomal translocations that generate chimeric fusion oncogenes, the most common of which is EWSR1-FLI1. Survival is extremely poor for patients with metastatic or relapsed disease, and no molecularly targeted therapy for this disease currently exists. The absence of a reliable genetic animal model of Ewing sarcoma has impaired investigation of tumor cell/microenvironmental interactions in vivo. We have developed a new genetic model of Ewing sarcoma based on Cre-inducible expression of human EWSR1-FLI1 in wild-type zebrafish, which causes rapid onset of SRBCTs at high penetrance. The tumors express canonical EWSR1-FLI1 target genes and stain for known Ewing sarcoma markers including CD99. Growth of tumors is associated with activation of the MAPK/ERK pathway, which we link to dysregulated extracellular matrix metabolism in general and heparan sulfate proteoglycan catabolism in particular. Targeting heparan sulfate proteoglycans with the specific heparan sulfate antagonist Surfen reduces ERK1/2 signaling and decreases tumorigenicity of Ewing sarcoma cells in vitro and in vivo. These results highlight the important role of the extracellular matrix in Ewing sarcoma tumor growth and the potential of agents targeting proteoglycan metabolism as novel therapies for this disease.

Use of predictive spatial modeling to reveal that primary cancers have distinct central nervous system topography patterns of brain metastasis.

OBJECTIVE: Brain metastasis is the most common intracranial neoplasm. Although anatomical spatial distributions of brain metastasis may vary according to primary cancer subtype, these patterns are not understood and may have major implications for treatment. METHODS: To test the hypothesis that the spatial distribution of brain metastasis varies according to cancer origin in nonrandom patterns, the authors leveraged spatial 3D coordinate data derived from stereotactic Gamma Knife radiosurgery procedures performed to treat 2106 brain metastases arising from 5 common cancer types (melanoma, lung, breast, renal, and colorectal). Two predictive topographic models (regional brain metastasis echelon model [RBMEM] and brain region susceptibility model [BRSM]) were developed and independently validated. RESULTS: RBMEM assessed the hierarchical distribution of brain metastasis to specific brain regions relative to other primary cancers and showed that distinct regions were relatively susceptible to metastasis, as follows: bilateral temporal/parietal and left frontal lobes were susceptible to lung cancer; right frontal and occipital lobes to melanoma; cerebellum to breast cancer; and brainstem to renal cell carcinoma. BRSM provided probability estimates for each cancer subtype, independent of other subtypes, to metastasize to brain regions, as follows: lung cancer had a propensity to metastasize to bilateral temporal lobes; breast cancer to right cerebellar hemisphere; melanoma to left temporal lobe; renal cell carcinoma to brainstem; and colon cancer to right cerebellar hemisphere. Patient topographic data further revealed that brain metastasis demonstrated distinct spatial patterns when stratified by patient age and tumor volume. CONCLUSIONS: These data support the hypothesis that there is a nonuniform spatial distribution of brain metastasis to preferential brain regions that varies according to cancer subtype in patients treated with Gamma Knife radiosurgery. These topographic patterns may be indicative of the abilities of various cancers to adapt to regional neural microenvironments, facilitate colonization, and establish metastasis. Although the brain microenvironment likely modulates selective seeding of metastasis, it remains unknown how the anatomical spatial distribution of brain metastasis varies according to primary cancer subtype and contributes to diagnosis. For the first time, the authors have presented two predictive models to show that brain metastasis, depending on its origin, in fact demonstrates distinct geographic spread within the central nervous system. These findings could be used as a predictive diagnostic tool and could also potentially result in future translational and therapeutic work to disrupt growth of brain metastasis on the basis of anatomical region.

CTCF: an R/bioconductor data package of human and mouse CTCF binding sites.

Summary: CTCF (CCCTC-binding factor) is an 11-zinc-finger DNA binding protein which regulates much of the eukaryotic genome's 3D structure and function. The diversity of CTCF binding motifs has led to a fragmented landscape of CTCF binding data. We collected position weight matrices of CTCF binding motifs and defined strand-oriented CTCF binding sites in the human and mouse genomes, including the recent Telomere to Telomere and mm39 assemblies. We included selected experimentally determined and predicted CTCF binding sites, such as CTCF-bound cis-regulatory elements from SCREEN ENCODE. We recommend filtering strategies for CTCF binding motifs and demonstrate that liftOver is a viable alternative to convert CTCF coordinates between assemblies. Our comprehensive data resource and usage recommendations can serve to harmonize and strengthen the reproducibility of genomic studies utilizing CTCF binding data. Availability and implementation: https://bioconductor.org/packages/CTCF. Companion website: https://dozmorovlab.github.io/CTCF/; Code to reproduce the analyses: https://github.com/dozmorovlab/CTCF.dev. Supplementary information: Supplementary data are available at Bioinformatics Advances online.