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Ependymomas are common childhood brain tumours that occur throughout the nervous system, but are most common in the paediatric hindbrain. Current standard therapy comprises surgery and radiation, but not cytotoxic chemotherapy as it does not further increase survival. Whole-genome and whole-exome sequencing of 47 hindbrain ependymomas reveals an extremely low mutation rate, and zero significant recurrent somatic single nucleotide variants. Although devoid of recurrent single nucleotide variants and focal copy number aberrations, poor-prognosis hindbrain ependymomas exhibit a CpG island methylator phenotype. Transcriptional silencing driven by CpG methylation converges exclusively on targets of the Polycomb repressive complex 2 which represses expression of differentiation genes through trimethylation of H3K27. CpG island methylator phenotype-positive hindbrain ependymomas are responsive to clinical drugs that target either DNA or H3K27 methylation both in vitro and in vivo. We conclude that epigenetic modifiers are the first rational therapeutic candidates for this deadly malignancy, which is epigenetically deregulated but genetically bland.

Summary: A main task in computational cancer analysis is the identification of patient subgroups (i.e. cohorts) based on metadata attributes (patient stratification) or genomic markers of response (biomarkers). Coral is a web-based cohort analysis tool that is designed to support this task: Users can interactively create and refine cohorts, which can then be compared, characterized and inspected down to the level of single items. Coral visualizes the evolution of cohorts and also provides intuitive access to prevalence information. Furthermore, findings can be stored, shared and reproduced via the integrated session management. Coral is pre-loaded with data from over 128 000 samples from the AACR Project GENIE, the Cancer Genome Atlas and the Cell Line Encyclopedia., Availability and Implementation: Coral is publicly available at https://coral.caleydoapp.org. The source code is released at https://github.com/Caleydo/coral., Supplementary Information: Supplementary data are available at Bioinformatics online., (© The Author(s) 2021. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Drugs targeting the programmed cell death protein 1 (PD-1) pathway are approved as therapies for an increasing number of cancer entities, including renal cell carcinoma. Despite a significant increase in overall survival, most treated patients do not show durable clinical responses. A combination of checkpoint inhibitors could provide a promising improvement. The aim of the study was to determine the most promising checkpoint blockade combination for renal cell carcinoma patients. Tumor-infiltrating lymphocytes (TIL) and autologous peripheral blood mononuclear cells (PBMC) were isolated from patients undergoing surgery for primary tumors. Cells were stained for multicolor flow cytometry to determine the (co)expression of five inhibitory receptors (iR), PD-1, LAG-3, Tim-3, BTLA, and CTLA-4, on T-cell populations. The function of these TILs was assessed by intracellular cytokine staining after in vitro stimulation in the presence or absence of PD-1 ± LAG-3 or Tim-3-specific antibodies. Although the percentage of iR + T cells was low in PBMCs, both CD4 + and CD8 + T cells showed increased frequencies of PD-1 + , LAG-3 + , and Tim-3 + cells on TILs. The most frequent iR combination was PD-1 and LAG-3 on both CD4 + and CD8 + TILs. Blockade of PD-1 resulted in significant LAG-3, but not Tim-3, upregulation. The dual blockade of PD-1 and LAG-3, but not PD-1 and Tim-3, led to increased IFNγ release upon in vitro stimulation. Together, these data suggest that dual blockade of PD-1 and LAG-3 is a promising checkpoint blockade combination for renal cell carcinoma., (©2019 American Association for Cancer Research.)

Summary: Ordino is a web-based analysis tool for cancer genomics that allows users to flexibly rank, filter and explore genes, cell lines and tissue samples based on pre-loaded data, including The Cancer Genome Atlas, the Cancer Cell Line Encyclopedia and manually uploaded information. Interactive tabular data visualization that facilitates the user-driven prioritization process forms a core component of Ordino. Detail views of selected items complement the exploration. Findings can be stored, shared and reproduced via the integrated session management., Availability and Implementation: Ordino is publicly available at https://ordino.caleydoapp.org. The source code is released at https://github.com/Caleydo/ordino under the Mozilla Public License 2.0., Supplementary Information: Supplementary data are available at Bioinformatics online., (© The Author(s) 2019. Published by Oxford University Press.)

SMARCA4/BRG1 and SMARCA2/BRM, the two mutually exclusive catalytic subunits of the BAF complex, display a well-established synthetic lethal relationship in SMARCA4-deficient cancers. Using CRISPR-Cas9 screening, we identify SMARCA4 as a novel dependency in SMARCA2-deficient esophageal squamous cell carcinoma (ESCC) models, reciprocal to the known synthetic lethal interaction. Restoration of SMARCA2 expression alleviates the dependency on SMARCA4, while engineered loss of SMARCA2 renders ESCC models vulnerable to concomitant depletion of SMARCA4. Dependency on SMARCA4 is linked to its ATPase activity, but not to bromodomain function. We highlight the relevance of SMARCA4 as a drug target in esophageal cancer using an engineered ESCC cell model harboring a SMARCA4 allele amenable to targeted proteolysis and identify SMARCA4-dependent cell models with low or absent SMARCA2 expression from additional tumor types. These findings expand the concept of SMARCA2/SMARCA4 paralog dependency and suggest that pharmacological inhibition of SMARCA4 represents a novel therapeutic opportunity for SMARCA2-deficient cancers.

Storing analytical provenance generates a knowledge base with a large potential for recalling previous results and guiding users in future analyses. However, without extensive manual creation of meta information and annotations by the users, search and retrieval of analysis states can become tedious. We present KnowledgePearls, a solution for efficient retrieval of analysis states that are structured as provenance graphs containing automatically recorded user interactions and visualizations. As a core component, we describe a visual interface for querying and exploring analysis states based on their similarity to a partial definition of a requested analysis state. Depending on the use case, this definition may be provided explicitly by the user by formulating a search query or inferred from given reference states. We explain our approach using the example of efficient retrieval of demographic analyses by Hans Rosling and discuss our implementation for a fast look-up of previous states. Our approach is independent of the underlying visualization framework. We discuss the applicability for visualizations which are based on the declarative grammar Vega and we use a Vega-based implementation of Gapminder as guiding example. We additionally present a biomedical case study to illustrate how KnowledgePearls facilitates the exploration process by recalling states from earlier analyses.

Background: Medulloblastoma is associated with rare hereditary cancer predisposition syndromes; however, consensus medulloblastoma predisposition genes have not been defined and screening guidelines for genetic counselling and testing for paediatric patients are not available. We aimed to assess and define these genes to provide evidence for future screening guidelines., Methods: In this international, multicentre study, we analysed patients with medulloblastoma from retrospective cohorts (International Cancer Genome Consortium [ICGC] PedBrain, Medulloblastoma Advanced Genomics International Consortium [MAGIC], and the CEFALO series) and from prospective cohorts from four clinical studies (SJMB03, SJMB12, SJYC07, and I-HIT-MED). Whole-genome sequences and exome sequences from blood and tumour samples were analysed for rare damaging germline mutations in cancer predisposition genes. DNA methylation profiling was done to determine consensus molecular subgroups: WNT (MB WNT ), SHH (MB SHH ), group 3 (MB Group3 ), and group 4 (MB Group4 ). Medulloblastoma predisposition genes were predicted on the basis of rare variant burden tests against controls without a cancer diagnosis from the Exome Aggregation Consortium (ExAC). Previously defined somatic mutational signatures were used to further classify medulloblastoma genomes into two groups, a clock-like group (signatures 1 and 5) and a homologous recombination repair deficiency-like group (signatures 3 and 8), and chromothripsis was investigated using previously established criteria. Progression-free survival and overall survival were modelled for patients with a genetic predisposition to medulloblastoma., Findings: We included a total of 1022 patients with medulloblastoma from the retrospective cohorts (n=673) and the four prospective studies (n=349), from whom blood samples (n=1022) and tumour samples (n=800) were analysed for germline mutations in 110 cancer predisposition genes. In our rare variant burden analysis, we compared these against 53 105 sequenced controls from ExAC and identified APC, BRCA2, PALB2, PTCH1, SUFU, and TP53 as consensus medulloblastoma predisposition genes according to our rare variant burden analysis and estimated that germline mutations accounted for 6% of medulloblastoma diagnoses in the retrospective cohort. The prevalence of genetic predispositions differed between molecular subgroups in the retrospective cohort and was highest for patients in the MB SHH subgroup (20% in the retrospective cohort). These estimates were replicated in the prospective clinical cohort (germline mutations accounted for 5% of medulloblastoma diagnoses, with the highest prevalence [14%] in the MB SHH subgroup). Patients with germline APC mutations developed MB WNT and accounted for most (five [71%] of seven) cases of MB WNT that had no somatic CTNNB1 exon 3 mutations. Patients with germline mutations in SUFU and PTCH1 mostly developed infant MB SHH . Germline TP53 mutations presented only in childhood patients in the MB SHH subgroup and explained more than half (eight [57%] of 14) of all chromothripsis events in this subgroup. Germline mutations in PALB2 and BRCA2 were observed across the MB SHH , MB Group3 , and MB Group4 molecular subgroups and were associated with mutational signatures typical of homologous recombination repair deficiency. In patients with a genetic predisposition to medulloblastoma, 5-year progression-free survival was 52% (95% CI 40-69) and 5-year overall survival was 65% (95% CI 52-81); these survival estimates differed significantly across patients with germline mutations in different medulloblastoma predisposition genes., Interpretation: Genetic counselling and testing should be used as a standard-of-care procedure in patients with MB WNT and MB SHH because these patients have the highest prevalence of damaging germline mutations in known cancer predisposition genes. We propose criteria for routine genetic screening for patients with medulloblastoma based on clinical and molecular tumour characteristics., Funding: German Cancer Aid; German Federal Ministry of Education and Research; German Childhood Cancer Foundation (Deutsche Kinderkrebsstiftung); European Research Council; National Institutes of Health; Canadian Institutes for Health Research; German Cancer Research Center; St Jude Comprehensive Cancer Center; American Lebanese Syrian Associated Charities; Swiss National Science Foundation; European Molecular Biology Organization; Cancer Research UK; Hertie Foundation; Alexander and Margaret Stewart Trust; V Foundation for Cancer Research; Sontag Foundation; Musicians Against Childhood Cancer; BC Cancer Foundation; Swedish Council for Health, Working Life and Welfare; Swedish Research Council; Swedish Cancer Society; the Swedish Radiation Protection Authority; Danish Strategic Research Council; Swiss Federal Office of Public Health; Swiss Research Foundation on Mobile Communication; Masaryk University; Ministry of Health of the Czech Republic; Research Council of Norway; Genome Canada; Genome BC; Terry Fox Research Institute; Ontario Institute for Cancer Research; Pediatric Oncology Group of Ontario; The Family of Kathleen Lorette and the Clark H Smith Brain Tumour Centre; Montreal Children's Hospital Foundation; The Hospital for Sick Children: Sonia and Arthur Labatt Brain Tumour Research Centre, Chief of Research Fund, Cancer Genetics Program, Garron Family Cancer Centre, MDT's Garron Family Endowment; BC Childhood Cancer Parents Association; Cure Search Foundation; Pediatric Brain Tumor Foundation; Brainchild; and the Government of Ontario., (Copyright © 2018 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

Medulloblastoma is one of the most common malignant pediatric brain tumors derived from posterior fossa. The current treatment includes maximal safe surgical resection, radiotherapy, whole cranio-spinal radiation and adjuvant with chemotherapy. However, it can only limitedly prolong the survival time with severe side effects and relapse. Defining the intratumoral heterogeneity, cellular origin and identifying the interaction network within tumor microenvironment are helpful for understanding the mechanisms of medulloblastoma tumorigenesis and relapse. Due to technological limitations, the mechanisms of cellular heterogeneity and tumor origin have not been fully understood. Recently, the emergence of single-cell technology has provided a powerful tool for achieving the goal of understanding the mechanisms of tumorigenesis. Several studies have demonstrated the intratumoral heterogeneity and tumor origin for each subtype of medulloblastoma utilizing the single-cell RNA-seq, which has not been uncovered before using conventional technologies. In this review, we present an overview of the current progress in understanding of cellular heterogeneity and tumor origin of medulloblastoma and discuss novel findings in the age of single-cell technologies., (© 2024. The Author(s).)

Current therapies for medulloblastoma, a highly malignant childhood brain tumour, impose debilitating effects on the developing child, and highlight the need for molecularly targeted treatments with reduced toxicity. Previous studies have been unable to identify the full spectrum of driver genes and molecular processes that operate in medulloblastoma subgroups. Here we analyse the somatic landscape across 491 sequenced medulloblastoma samples and the molecular heterogeneity among 1,256 epigenetically analysed cases, and identify subgroup-specific driver alterations that include previously undiscovered actionable targets. Driver mutations were confidently assigned to most patients belonging to Group 3 and Group 4 medulloblastoma subgroups, greatly enhancing previous knowledge. New molecular subtypes were differentially enriched for specific driver events, including hotspot in-frame insertions that target KBTBD4 and 'enhancer hijacking' events that activate PRDM6. Thus, the application of integrative genomics to an extensive cohort of clinical samples derived from a single childhood cancer entity revealed a series of cancer genes and biologically relevant subtype diversity that represent attractive therapeutic targets for the treatment of patients with medulloblastoma.

Extensive prior research focused on somatic copy-number alterations (SCNAs) affecting cancer genes, yet the extent to which recurrent SCNAs exert their influence through rearrangement of cis-regulatory elements (CREs) remains unclear. Here we present a framework for inferring cancer-related gene overexpression resulting from CRE reorganization (e.g., enhancer hijacking) by integrating SCNAs, gene expression data and information on topologically associating domains (TADs). Analysis of 7,416 cancer genomes uncovered several pan-cancer candidate genes, including IRS4, SMARCA1 and TERT. We demonstrate that IRS4 overexpression in lung cancer is associated with recurrent deletions in cis, and we present evidence supporting a tumor-promoting role. We additionally pursued cancer-type-specific analyses and uncovered IGF2 as a target for enhancer hijacking in colorectal cancer. Recurrent tandem duplications intersecting with a TAD boundary mediate de novo formation of a 3D contact domain comprising IGF2 and a lineage-specific super-enhancer, resulting in high-level gene activation. Our framework enables systematic inference of CRE rearrangements mediating dysregulation in cancer.

Embryogenesis is remarkably robust to segregating mutations and environmental variation; under a range of conditions, embryos of a given species develop into stereotypically patterned organisms. Such robustness is thought to be conferred, in part, through elements within regulatory networks that perform similar, redundant tasks. Redundant enhancers (or "shadow" enhancers), for example, can confer precision and robustness to gene expression, at least at individual, well-studied loci. However, the extent to which enhancer redundancy exists and can thereby have a major impact on developmental robustness remains unknown. Here, we systematically assessed this, identifying over 1,000 predicted shadow enhancers during Drosophila mesoderm development. The activity of 23 elements, associated with five genes, was examined in transgenic embryos, while natural structural variation among individuals was used to assess their ability to buffer against genetic variation. Our results reveal three clear properties of enhancer redundancy within developmental systems. First, it is much more pervasive than previously anticipated, with 64% of loci examined having shadow enhancers. Their spatial redundancy is often partial in nature, while the non-overlapping function may explain why these enhancers are maintained within a population. Second, over 70% of loci do not follow the simple situation of having only two shadow enhancers-often there are three (rols), four (CadN and ade5), or five (Traf1), at least one of which can be deleted with no obvious phenotypic effects. Third, although shadow enhancers can buffer variation, patterns of segregating variation suggest that they play a more complex role in development than generally considered., (Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Structural variants are implicated in numerous diseases and make up the majority of varying nucleotides among human genomes. Here we describe an integrated set of eight structural variant classes comprising both balanced and unbalanced variants, which we constructed using short-read DNA sequencing data and statistically phased onto haplotype blocks in 26 human populations. Analysing this set, we identify numerous gene-intersecting structural variants exhibiting population stratification and describe naturally occurring homozygous gene knockouts that suggest the dispensability of a variety of human genes. We demonstrate that structural variants are enriched on haplotypes identified by genome-wide association studies and exhibit enrichment for expression quantitative trait loci. Additionally, we uncover appreciable levels of structural variant complexity at different scales, including genic loci subject to clusters of repeated rearrangement and complex structural variants with multiple breakpoints likely to have formed through individual mutational events. Our catalogue will enhance future studies into structural variant demography, functional impact and disease association.

TCF3-HLF-positive acute lymphoblastic leukemia (ALL) is currently incurable. Using an integrated approach, we uncovered distinct mutation, gene expression and drug response profiles in TCF3-HLF-positive and treatment-responsive TCF3-PBX1-positive ALL. We identified recurrent intragenic deletions of PAX5 or VPREB1 in constellation with the fusion of TCF3 and HLF. Moreover somatic mutations in the non-translocated allele of TCF3 and a reduction of PAX5 gene dosage in TCF3-HLF ALL suggest cooperation within a restricted genetic context. The enrichment for stem cell and myeloid features in the TCF3-HLF signature may reflect reprogramming by TCF3-HLF of a lymphoid-committed cell of origin toward a hybrid, drug-resistant hematopoietic state. Drug response profiling of matched patient-derived xenografts revealed a distinct profile for TCF3-HLF ALL with resistance to conventional chemotherapeutics but sensitivity to glucocorticoids, anthracyclines and agents in clinical development. Striking on-target sensitivity was achieved with the BCL2-specific inhibitor venetoclax (ABT-199). This integrated approach thus provides alternative treatment options for this deadly disease.

Cancers are heterogeneous diseases with unifying features of abnormal and consuming cell growth, where the deregulation of normal cellular functions is initiated by the accumulation of genomic mutations in cells of - potentially - any organ. At diagnosis malignancies typically present with patterns of somatic genome variants on diverse levels of heterogeneity. Among the different types of genomic alterations, copy number variants (CNV) represent a distinct, near-ubiquitous class of structural variants. Cancer classifications are foundational for patient care and oncology research. Terminologies such as the National Cancer Institute Thesaurus provide large sets of hierarchical cancer classification vocabularies and promote data interoperability and ontology-driven computational analysis. To find out how categorical classifications correspond to genomic observations, we conducted a meta-analysis of inter-sample genomic heterogeneity for classification hierarchies on CNV profiles from 97,142 individual samples across 512 cancer entities, and evaluated recurring CNV signatures across diagnostic subsets. Our results highlight specific biological mechanisms across cancer entities with the potential for improvement of patient stratification and future enhancement of cancer classification systems and provide some indications for cooperative genomic events across distinct clinical entities. [ABSTRACT FROM AUTHOR]

This comprehensive review provides insights and suggested strategies for the analysis of germline variants using second- and third-generation sequencing technologies (SGS and TGS). It addresses the critical stages of data processing, starting from alignment and preprocessing to quality control, variant calling, and the removal of artifacts. The document emphasized the importance of meticulous data handling, highlighting advanced methodologies for annotating variants and identifying structural variations and methylated DNA sites. Special attention is given to the inspection of problematic variants, a step that is crucial for ensuring the accuracy of the analysis, particularly in clinical settings where genetic diagnostics can inform patient care. Additionally, the document covers the use of various bioinformatics tools and software that enhance the precision and reliability of these analyses. It outlines best practices for the annotation of variants, including considerations for problematic genetic alterations such as those in the human leukocyte antigen region, runs of homozygosity, and mitochondrial DNA alterations. The document also explores the complexities associated with identifying structural variants and copy number variations, underscoring the challenges posed by these large-scale genomic alterations. The objective is to offer a comprehensive framework for researchers and clinicians, ensuring that genetic analyses conducted with SGS and TGS are both accurate and reproducible. By following these best practices, the document aims to increase the diagnostic accuracy for hereditary diseases, facilitating early diagnosis, prevention, and personalized treatment strategies. This review serves as a valuable resource for both novices and experts in the field, providing insights into the latest advancements and methodologies in genetic analysis. It also aims to encourage the adoption of these practices in diverse research and clinical contexts, promoting consistency and reliability across studies. [ABSTRACT FROM AUTHOR]

Background: 4-methylimidazole is a ubiquitous and potentially carcinogenic environmental toxicant. Genetic factors that contribute to variation in susceptibility to its toxic effects are challenging to assess in human populations. We used the Drosophila melanogaster Genetic Reference Panel (DGRP), a living library of natural genetic variation, to identify genes with human orthologs associated with variation in susceptibility to 4-methylimidazole. Results: We screened 204 DGRP lines for survival following 24-hour exposure to 4-methylimidazole. We found extensive genetic variation for survival, with a broad sense heritability of 0.82; as well as genetic variation in sexual dimorphism, with a cross-sex genetic correlation of 0.59. Genome-wide association analyses identified a total of 241 candidate molecular polymorphisms in or near 273 unique genes associated with survival. These polymorphisms had either sex-specific or sex-antagonistic effects, and most had putative regulatory effects. We generated interaction networks using these candidate genes as inputs and computationally recruited genes with known physical or genetic interactions. The network genes were significantly over-represented for gene ontology terms involving all aspects of development (including nervous system development) and cellular and organismal functions as well as canonical signaling pathways, and most had human orthologs. Conclusions: The genetic basis of variation in sensitivity to acute exposure to 4-methylimidazole in Drosophila is attributable to variation in genes and networks of genes known for their effects on multiple developmental and cellular processes, including possible neurotoxicity. Given evolutionary conservation of the underlying genes and pathways, these insights may be applicable to humans. [ABSTRACT FROM AUTHOR]

Nr2f transcription factors (TFs) are conserved regulators of vertebrate atrial cardiomyocyte (AC) differentiation. However, little is known about the mechanisms directing Nr2f expression in ACs. Here, we identified a conserved enhancer 3' to the nr2f1a locus, which we call 3'reg1-nr2f1a (3'reg1), that can promote Nr2f1a expression in ACs. Sequence analysis of the enhancer identified putative Lef/Tcf and Foxf TF binding sites. Mutation of the Lef/Tcf sites within the 3'reg1 reporter, knockdown of Tcf7l1a, and manipulation of canonical Wnt signaling support that Tcf7l1a is derepressed via Wnt signaling to activate the transgenic enhancer and promote AC differentiation. Similarly, mutation of the Foxf binding sites in the 3'reg1 reporter, coupled with gain- and loss-of-function analysis supported that Foxf1 promotes expression of the enhancer and AC differentiation. Functionally, we find that Wnt signaling acts downstream of Foxf1 to promote expression of the 3'reg1 reporter within ACs and, importantly, both Foxf1 and Wnt signaling require Nr2f1a to promote a surplus of differentiated ACs. CRISPR-mediated deletion of the endogenous 3'reg1 abrogates the ability of Foxf1 and Wnt signaling to produce surplus ACs in zebrafish embryos. Together, our data support that downstream members of a conserved regulatory network involving Wnt signaling and Foxf1 function on a nr2f1a enhancer to promote AC differentiation in the zebrafish heart. Author summary: Vertebrate hearts are comprised of atrial chambers, which receive blood, and ventricular chambers which expel blood, whose functions need to be coordinated for proper blood circulation. During development, different genetic programs direct the development of these chambers within the vertebrate heart. Members of a family of genes called Nr2fs are conserved regulators of atrial chamber development in vertebrates, with mutations in Nr2f2 of humans being associated with congenital heart defects affecting the atrium. Here, we examine how the gene nr2f1a, which is required for normal atrial chamber development in the model zebrafish, is regulated. Using tools, including transgenic reporter lines and genetic mutants, we identify that factors previously shown to regulate atrial chamber development in mammals have conserved roles regulating a genetic element that promotes nr2f1a expression within developing atrial cells. Since there is a lack of understanding regarding regulation of Nr2f genes during vertebrate atrial cell development, our work provides insights into the conservation of genetic networks that promote heart development in vertebrates and if perturbed could underlie congenital heart defects. [ABSTRACT FROM AUTHOR]

The 3D genome prediction in cancer is crucial for uncovering the impact of structural variations (SVs) on tumorigenesis, especially when they are present in noncoding regions. We present InfoHiC, a systemic framework for predicting the 3D cancer genome directly from whole-genome sequencing (WGS). InfoHiC utilizes contig-specific copy number encoding on the SV contig assembly, and performs a contig-to-total Hi-C conversion for the cancer Hi-C prediction from multiple SV contigs. We showed that InfoHiC can predict 3D genome folding from all types of SVs using breast cancer cell line data. We applied it to WGS data of patients with breast cancer and pediatric patients with medulloblastoma, and identified neo topologically associating domains. For breast cancer, we discovered super-enhancer hijacking events associated with oncogenic overexpression and poor survival outcomes. For medulloblastoma, we found SVs in noncoding regions that caused super-enhancer hijacking events of medulloblastoma driver genes (GFI1, GFI1B, and PRDM6). In addition, we provide trained models for cancer Hi-C prediction from WGS at https://github.com/dmcb-gist/InfoHiC, uncovering the impacts of SVs in cancer patients and revealing novel therapeutic targets. Synopsis: InfoHiC is developed for cancer 3D genome prediction enabling to find neo-TADs and neo-loops starting from whole genome sequencing reads. InfoHiC is trained from available cancer Hi-C data and predicts Hi-C matrices for patients with cancer, which eliminates the burden of high Hi-C sequencing costs. InfoHiC takes whole genome sequencing reads in contrast to other Hi-C prediction tools requiring pre-defined sequences, enabling Hi-C prediction from cancer genomes where users cannot define sequence inputs easily. It analyzes all structural variation types including those found in non-coding regions, and predicts the impact on cancer development in the 3D genome context. It can lead to personalized medication by discovering neo-TADs and neo-loops in patients where common coding driver mutations or copy number changes are not found. InfoHiC is developed for cancer 3D genome prediction enabling to find neo-TADs and neo-loops starting from whole genome sequencing reads. [ABSTRACT FROM AUTHOR]

Simple Summary: Adult medulloblastoma is an uncommon brain tumor, distinct from its pediatric counterpart in clinical presentation and molecular characteristics. Its management often relies on treatment strategies derived from pediatric cases due to limited research on adults. Our study evaluates the clinical and molecular characteristics of 53 adult patients treated at a single center and explores factors influencing survival outcomes. We found that the extent of surgery and disease stage significantly impacted survival, while molecular subtypes did not correlate with prognosis. High-risk patients exhibited poor outcomes, suggesting a need for more aggressive treatment approaches. Understanding these factors is crucial for improving survival rates in adult patients. Background/Objectives: Adult medulloblastoma is a rare entity, with management data extrapolated from pediatric medulloblastoma cases. We aim to report the clinical characteristics, prognostic factors, and treatment outcome of a cohort of adult patients with medulloblastoma. Methods: Fifty-three patients aged ≥ 18 years with medulloblastoma treated at King Hussein Cancer Center between 2007 and 2019 were retrospectively reviewed. Patients' diseases were staged according to modified Chang's staging system. All patients received adjuvant craniospinal irradiation followed by a posterior fossa boost. Baseline disease characteristics, including molecular subgrouping, were tested as prognostic factors of progression-free survival (PFS) and overall survival (OS) by using univariate analysis. Results: Median follow-up was 70 months (range 37.5–104.5 months). Twenty-two tumors were of the SHH-activated subtype. Conversely, WNT-activated and group 4 tumors had three cases each. Only 37.7% of patients died. The mean 3-year, 5-year, and 10-year OS were 85% (75–95%), 74% (62–87%), and 50% (33–75%), respectively. Significant differences in OS were associated with the extent of surgery (p = 0.017), M stage (p = 0.009), and risk status (p < 0.001). Relapses were detected in 28.3% of cases. The 3-year, 5-year, and 10-year PFS were 81% (71–92%), 75% (63–88%), and 66% (52–83%), respectively. Significant differences in PFS were associated with the extent of surgery (p = 0.008) and risk status (p = 0.012). Molecular subgrouping did not correlate with OS or PFS. Conclusions: Our results revealed poor survival of patients with high-risk disease, which may necessitate the intensification of chemotherapy. Molecular subgrouping did not correlate with the outcome in this cohort. [ABSTRACT FROM AUTHOR]

Relapse remains a determinant of treatment failure and contributes significantly to mortality in acute myeloid leukemia (AML) patients. Despite efforts to understand AML progression and relapse mechanisms, findings on acquired gene mutations in relapse vary, suggesting inherent genetic heterogeneity and emphasizing the role of epigenetic modifications. We conducted a multi-omic analysis using Omni-C, ATAC-seq, and RNA-seq on longitudinal samples from two adult AML patients at diagnosis and relapse. Herein, we characterized genetic and epigenetic changes in AML progression to elucidate the underlying mechanisms of relapse. Differential interaction analysis showed significant 3D chromatin landscape reorganization between relapse and diagnosis samples. Comparing global open chromatin profiles revealed that relapse samples had significantly fewer accessible chromatin regions than diagnosis samples. In addition, we discovered that relapse-related upregulation was achieved either by forming new active enhancer contacts or by losing interactions with poised enhancers/potential silencers. Altogether, our study highlights the impact of genetic and epigenetic changes on AML progression, underlining the importance of multi-omic approaches in understanding disease relapse mechanisms and guiding potential therapeutic interventions. [ABSTRACT FROM AUTHOR]

Background: Mutton quality is closely related to genetic variants and gene expression alterations during growth and development, resulting in differences in nutritional values, flavor, and odor. Results: We first evaluated and compared the composition of crude protein, crude fat, cholesterol, amino acid (AA), and fatty acid (FA) in the longissimus dorsi muscle of Guizhou black goats (GZB, n = 5) and Yunshang black goats (YBG, n = 6). The contents of cholesterol and FA related to odor in GZB were significantly lower than that in YBG, while the concentrations of umami amino acids and intramuscular fat were significantly higher in GZB. Furthermore, structural variants (SVs) in the genomes of GZB (n = 30) and YBG (n = 11) were explored. It was found that some regions in Chr 10/12/18 were densely involved with a large number of SVs in the genomes of GZB and YBG. By setting FST ≥ 0.25, we got 837 stratified SVs, of which 25 SVs (involved in 12 genes, e.g., CORO1A, CLIC6, PCSK2, and TMEM9) were limited in GZB. Functional enrichment analysis of 14 protein-coding genes (e.g., ENPEP, LIPC, ABCA5, and SLC6A15) revealed multiple terms and pathways related with metabolisms of AA, FA, and cholesterol. The SVs (n = 10) obtained by the whole genome resequencing were confirmed in percentages of 36.67 to 86.67% (n = 96) by PCR method. The SVa and SVd polymorphisms indicated a moderate negative correlation with HMGCS1 activity (n = 17). Conclusion: This study is the first to comprehensively reveal potential SVs related to mutton nutritional values, flavor, and odor based on genomic compare between two black goat breeds with closely genetic relationship. The SVs generated in this study provide a data resource for deeper studies to understand the genomic characteristics and possible evolutionary outcomes with better nutritional values, flavor and extremely light odor. [ABSTRACT FROM AUTHOR]

Treatment based on immune checkpoint blockade has revolutionized cancer therapy. Despite the remarkable success achieved and the preclinical development of multiple checkpoint inhibitors targeting other checkpoints, only antibodies targeting the PD-1/PD-L1 axis and CTLA-4 have been approved for patient treatment, especially in solid tumors. Currently, with the approval of relatlimab, a LAG-3 blocking antibody, a third player, has been used in the fight against cancer. The endorsement of relatlimab marks a significant milestone in cancer immunotherapy, opening new avenues for combination therapies and enhancing treatment outcomes. However, the complex biology of LAG-3 may hinder its full development as a therapeutic alternative. In this review, we provide in-depth insight into the biology of LAG-3 and its current and future development in cancer treatment. [ABSTRACT FROM AUTHOR]

Humans are curious to understand the causes of traits that distinguish us from other animals and that distinguish vastly different species from one another. We also have a proclivity for simple stories and sometimes tend toward seeking and accepting simple genetic explanations for large evolutionary shifts, even to a single gene. Here, I reveal how a biased expectation of mechanistic simplicity threads through the long history of evolutionary and developmental genetics. I argue, however, that expecting a simple mechanism threatens a deeper understanding of evolution, and I define the limitations for interpreting experimental evidence in evolutionary developmental genetics. [ABSTRACT FROM AUTHOR]

Simple Summary: We discuss the role of risk-stratification and personalized treatment for various pediatric cancer patients, with the goal being to improve tumor control and decrease late effects of radiation in long-term survivors. We discuss settings in which radiation can be safely omitted or de-escalated, such as Hodgkin lymphoma, Wilms tumor with lung metastases and WNT pathway Medulloblastoma, and settings that warrant treatment escalation such as larger tumors with rhabdomyosarcoma or Ewing sarcoma, poor responders to chemotherapy and oligometastatic disease settings. We also summarize currently enrolling COG and other cooperative group trials. While the cure rate of cancer in children has markedly improved in the last few decades, late effects continue to be a problem in survivors. Radiotherapy, which is a major component of treatment in many cancers, is one of the major agents responsible for late toxicity. In the past decade, radiotherapy has been omitted in patients achieving excellent response to chemotherapy, such as in Hodgkin lymphoma and some Wilms tumors with lung metastases. Likewise, response to chemotherapy has been used to determine whether lower doses of radiation can be delivered in intracranial germinoma and pediatric nasopharyngeal carcinoma. Molecular subtyping in medulloblastoma is currently being employed, and in WNT-pathway M0 tumors, the reduction in radiotherapy dose to the craniospinal axis and tumor bed is currently being investigated. Finally, dose escalation was recently evaluated in patients with rhabdomyosarcoma > 5 cm who do not achieve a complete response to initial 9 weeks of chemotherapy as well as for unresectable Ewing sarcoma patients to improve local control. [ABSTRACT FROM AUTHOR]

Background: Structural variations (SVs) are widespread across genome and have a great impact on evolution, disease, and phenotypic diversity. Despite the development of numerous bioinformatic tools, commonly referred to as SV callers, tailored for detecting SVs using whole genome sequence (WGS) data and employing diverse algorithms, their performance necessitates rigorous evaluation with real data and validated SVs. Moreover, a considerable proportion of these tools have been primarily designed and optimized using human genome data. Consequently, their applicability and performance in Avian species, characterized by smaller genomes and distinct genomic architectures, remain inadequately assessed. Results: We performed a comprehensive assessment of the performance of ten widely used SV callers using population-level real genomic data with the validated five common types of SVs. The performance of SV callers varies with the types and sizes of SVs. As compared with other tools, GRIDSS, Lumpy, Wham, and Manta present better detection accuracy. Pindel can detect more small SVs than others. CNVnator and CNVkit can detect more medium and large copy number variations. Given the poor consistency among different SV callers, the combination calling strategy is not recommended. All tools show poor ability in the detection of insertions (especially with size > 150 bp). At least 50× read depth is required to detect more than 80% of the SVs for most tools. Conclusions: This study highlights the importance and necessity of using real sequencing data, rather than simulated data only, with validated SVs for SV caller evaluation. Some practical guidance and suggestions are provided for SV detection in future researches. [ABSTRACT FROM AUTHOR]

Background: Congenital heart disease (CHD) is the most common congenital anomaly. Almost 90% of isolated cases have an unexplained genetic etiology after clinical testing. Non-canonical splice variants that disrupt mRNA splicing through the loss or creation of exon boundaries are not routinely captured and/or evaluated by standard clinical genetic tests. Recent computational algorithms such as SpliceAI have shown an ability to predict such variants, but are not specific to cardiac-expressed genes and transcriptional isoforms. Methods: We used genome sequencing (GS) (n = 1101 CHD probands) and myocardial RNA-Sequencing (RNA-Seq) (n = 154 CHD and n = 43 cardiomyopathy probands) to identify and validate splice disrupting variants, and to develop a heart-specific model for canonical and non-canonical splice variants that can be applied to patients with CHD and cardiomyopathy. Two thousand five hundred seventy GS samples from the Medical Genome Reference Bank were analyzed as healthy controls. Results: Of 8583 rare DNA splice-disrupting variants initially identified using SpliceAI, 100 were associated with altered splice junctions in the corresponding patient myocardium affecting 95 genes. Using strength of myocardial gene expression and genome-wide DNA variant features that were confirmed to affect splicing in myocardial RNA, we trained a machine learning model for predicting cardiac-specific splice-disrupting variants (AUC 0.86 on internal validation). In a validation set of 48 CHD probands, the cardiac-specific model outperformed a SpliceAI model alone (AUC 0.94 vs 0.67 respectively). Application of this model to an additional 947 CHD probands with only GS data identified 1% patients with canonical and 11% patients with non-canonical splice-disrupting variants in CHD genes. Forty-nine percent of predicted splice-disrupting variants were intronic and > 10 bp from existing splice junctions. The burden of high-confidence splice-disrupting variants in CHD genes was 1.28-fold higher in CHD cases compared with healthy controls. Conclusions: A new cardiac-specific in silico model was developed using complementary GS and RNA-Seq data that improved genetic yield by identifying a significant burden of non-canonical splice variants associated with CHD that would not be detectable through panel or exome sequencing. [ABSTRACT FROM AUTHOR]

Background: The genetic basis underlying spawning abilities in the Pacific white shrimp, Penaeus vannamei, remains largely unexplored. To investigate genetic variations potentially related to reproductive performance, a systematic bioinformatic analysis was conducted to identify structural variations (SVs) with different polymorphic spectra in P. vannamei with high fertility (HF) and low fertility (LF). Results: A total of 2,323 and 1,859 SV events were identified exclusively in the HF and LF groups, respectively. These SVs were mapped to 277 genes in the HF group and 231 genes in the LF group. Gene Ontology (GO) enrichment analysis based on SNPs (single nucleotide polymorphism) and SVs revealed several neural-related processes, suggesting the importance of neural regulation in reproduction. Notably, we identified a set of promising genes, including Cttn, Spast, Ppp4c, Spire1, Lhcgr, and Ftz-f1, which may enhance fertility in shrimp. Conclusion: In conclusion, this study is the first to establish a link between SVs and reproductive traits in P. vannamei. The promising genes discovered have the potential to serve as crucial markers for enhancing reproductive traits through targeted genotyping. [ABSTRACT FROM AUTHOR]

Understanding how cell identity is encoded by the genome and acquired during differentiation is a central challenge in cell biology. I have developed a theoretical framework called EnhancerNet, which models the regulation of cell identity through the lens of transcription factor-enhancer interactions. I demonstrate that autoregulation in these interactions imposes a constraint on the model, resulting in simplified dynamics that can be parameterized from observed cell identities. Despite its simplicity, EnhancerNet recapitulates a broad range of experimental observations on cell identity dynamics, including enhancer selection, cell fate induction, hierarchical differentiation through multipotent progenitor states and direct reprogramming by transcription factor overexpression. The model makes specific quantitative predictions, reproducing known reprogramming recipes and the complex haematopoietic differentiation hierarchy without fitting unobserved parameters. EnhancerNet provides insights into how new cell types could evolve and highlights the functional importance of distal regulatory elements with dynamic chromatin in multicellular evolution. [ABSTRACT FROM AUTHOR]

Understanding the genetic basis of species differences in flowering time and inflorescence architecture can shed light on speciation and molecular breeding. Melastoma shows rapid speciation, with about 100 species formed in the past few million years, and, meanwhile, possesses high ornamental values. Two largely sympatric and closely related species of this genus, M. candidum and M. normale, differ markedly in flowering time and flower number per inflorescence. Here, we constructed an F2 population between M. candidum and M. normale, and used extreme bulks for flowering time and flower number per inflorescence in this population to identify genomic regions underlying the two traits. We found high differentiation on nearly the whole chromosome 7 plus a few regions on other chromosomes between the two extreme bulks for flowering time. Large chromosomal inversions on chromosome 7 between the two species, which contain flowering-related genes, can explain recombinational suppression on the chromosome. We identified 1872 genes with one or more highly differentiated SNPs between the two bulks for flowering time, including CSTF77, FY, SPA3, CDF3, AGL8, AGL15, FHY1, COL9, CIB1, FKF1 and FAR1, known to be related to flowering. We also identified 680 genes with one or more highly differentiated SNPs between the two bulks for flower number per inflorescence, including PNF, FIL and LAS, knows to play important roles in inflorescence development. These large inversions on chromosome 7 prevent us from narrowing down the genomic region(s) associated with flowering time differences between the two species. Flower number per inflorescence in Melastoma appears to be controlled by multiple genes, without any gene of major effect. Our study indicates that large chromosomal inversions can hamper the identification of the genetic basis of important traits, and the inflorescence architecture of Melastoma species may have a complex genetic basis. [ABSTRACT FROM AUTHOR]

Background: Substantial discoveries during the past century have revealed that transposable elements (TEs) can play a crucial role in genome evolution by affecting gene expression and inducing genetic rearrangements, among other molecular and structural effects. Yet, our knowledge on the role of TEs in adaptation to extreme climates is still at its infancy. The availability of long-read sequencing has opened up the possibility to identify and study potential functional effects of TEs with higher precision. In this work, we used Drosophila montana as a model for cold-adapted organisms to study the association between TEs and adaptation to harsh climates. Results: Using the PacBio long-read sequencing technique, we de novo identified and manually curated TE sequences in five Drosophila montana genomes from eco-geographically distinct populations. We identified 489 new TE consensus sequences which represented 92% of the total TE consensus in D. montana. Overall, 11–13% of the D. montana genome is occupied by TEs, which as expected are non-randomly distributed across the genome. We identified five potentially active TE families, most of them from the retrotransposon class of TEs. Additionally, we found TEs present in the five analyzed genomes that were located nearby previously identified cold tolerant genes. Some of these TEs contain promoter elements and transcription binding sites. Finally, we detected TEs nearby fixed and polymorphic inversion breakpoints. Conclusions: Our research revealed a significant number of newly identified TE consensus sequences in the genome of D. montana, suggesting that non-model species should be studied to get a comprehensive view of the TE repertoire in Drosophila species and beyond. Genome annotations with the new D. montana library allowed us to identify TEs located nearby cold tolerant genes, and present at high population frequencies, that contain regulatory regions and are thus good candidates to play a role in D. montana cold stress response. Finally, our annotations also allow us to identify for the first time TEs present in the breakpoints of three D. montana inversions. [ABSTRACT FROM AUTHOR]

Background: Fusobacterium nucleatum (F. nucleatum) is one of the key tumorigenic bacteria in colorectal cancer (CRC), yet how F. nucleatum is involved in colorectal cancer carcinogenesis remains unknown. Results: In the present study, we carried out PathSeq analysis on RNA sequencing data from the 430 primary colon adenocarcinomas in TCGA database to assess the relationship between patients' survival and F. nucleatum abundance. Among patients with cecum and ascending colon tumors, we found that F. nucleatum transcriptome abundance is positively correlated with mutation load. We further demonstrated that patients with both high tumoral abundance of F. nucleatum and high mutation load exhibited poorer survival and DNA damage. We furthermore determined that F. nucleatum-conditioned medium (Fn. CM) induces DNA damage in both in vitro and in vivo studies. In addition, two F. nucleatum-secreted mutagens, namely DL-homocystine and allantoic acid, were identified to lead to DNA damage. Conclusions: Our finding delineates the genotoxicity of F.nucleatum-secreted mutagens, which provides a basis for further work to investigate the role of F. nucleatum in the pathogenicity of CRC. [ABSTRACT FROM AUTHOR]

Background: Structural variations play a significant role in genetic diseases and evolutionary mechanisms. Extensive research has been conducted over the past decade to detect simple structural variations, leading to the development of well-established detection methods. However, recent studies have highlighted the potentially greater impact of complex structural variations on individuals compared to simple structural variations. Despite this, the field still lacks precise detection methods specifically designed for complex structural variations. Therefore, the development of a highly efficient and accurate detection method is of utmost importance. Result: In response to this need, we propose a novel method called FindCSV, which leverages deep learning techniques and consensus sequences to enhance the detection of SVs using long-read sequencing data. Compared to current methods, FindCSV performs better in detecting complex and simple structural variations. Conclusions: FindCSV is a new method to detect complex and simple structural variations with reasonable accuracy in real and simulated data. The source code for the program is available at https://github.com/nwpuzhengyan/FindCSV. [ABSTRACT FROM AUTHOR]

Background: Structural variations (SVs) are key genetic contributors to neurodevelopmental disorders (NDDs). Exome sequencing (ES), the current first-line tool for genetic testing of NDDs, falls short in SVs detection. This diagnostic gap is being actively addressed by new methods such as optical genome mapping (OGM). Methods: This study evaluated the utility of combining OGM and RNA-seq in the detection and interpretation of SVs in ES-negative NDDs. OGM was performed in 43 patients with NDDs with inconclusive ES results. Candidate SVs were selected based on disease association and pathogenicity evaluation, and further validated or reconstructed by alternative methods, including long-read sequencing for a complex rearrangement event. RNA-Seq was performed on blood samples from patients with candidate SVs to facilitate interpretation of pathogenicity. Results: OGM detected four candidate SVs, and RNA-seq confirmed the pathogenicity of three SVs in the patient cohort. This combined approach solved three cases—two cases with de novo SVs in genes associated with autosomal dominant NDDs, including a deletion encompassing the promoter and 5′UTR of MBD5 and an intragenic duplication of PAFAH1B1, and a third case possessing an intragenic duplication in trans with a pathogenic single-nucleotide variant of PLA2G6, associated with autosomal recessive NDDs. The expression alteration of the affected genes and the tandem positioning of two intragenic duplications were confirmed by RNA-seq. In the fourth case, OGM detected a complex rearrangement involving chromosomes 2 and 6, much more complex than the de novo t(2:6)(q13;q15) indicated by conventional cytogenetic analysis. Reconstruction showed that 17 segments of 6q15 spanning 9.3 Mb were disarranged and joined 2q11.2, with four breakpoints detected in the 5′ and 3′ non-coding region of the NDD-associated gene SYNCRIP. RNA-seq revealed largely preserved SYNCRIP expression, leaving the pathogenicity of this complex rearrangement event uncertain. Conclusions: SVs in ES-negative NDDs can be identified by OGM, which is particularly useful for SVs in non-coding regions not covered by ES. OGM helps to construct complex SVs and provides information on the location and orientation of duplications, which is crucial for pathogenicity interpretation. The integration of RNA-seq facilitates the interpretation of the functional consequences of SVs at the transcriptional level. These findings demonstrate the utility and feasibility of combining OGM and RNA-seq in ES-negative cases with NDDs. [ABSTRACT FROM AUTHOR]