Endoluminal Biopsy for Vein of Galen Malformation.

BACKGROUND AND OBJECTIVES: Vein of Galen malformation (VOGM), the result of arteriovenous shunting between choroidal and/or subependymal arteries and the embryologic prosencephalic vein, is among the most severe cerebrovascular disorders of childhood. We hypothesized that in situ analysis of the VOGM lesion using endoluminal tissue sampling (ETS) is feasible and may advance our understanding of VOGM genetics, pathogenesis, and maintenance. METHODS: We collected germline DNA (cheek swab) from patients and their families for genetic analysis. In situ VOGM "endothelial" cells (ECs), defined as CD31+ and CD45-, were obtained from coils through ETS during routine endovascular treatment. Autologous peripheral femoral ECs were also collected from the access sheath. Single-cell RNA sequencing of both VOGM and peripheral ECs was performed to demonstrate feasibility to define the transcriptional architecture. Comparison was also made with a published normative cerebrovascular transcriptome atlas. A subset of VOGM ECs was reserved for future DNA sequencing to assess for somatic and second-hit mutations. RESULTS: Our cohort contains 6 patients who underwent 10 ETS procedures from arterial and/or venous access during routine VOGM treatment (aged 12 days to ∼6 years). No periprocedural complications attributable to ETS occurred. Six unique coil types were used. ETS captured 98 ± 88 (mean ± SD; range 17-256) experimental ECs (CD31+ and CD45-). There was no discernible correlation between cell yield and coil type or route of access. Single-cell RNA sequencing demonstrated hierarchical clustering and unique cell populations within the VOGM EC compartment compared with peripheral EC controls when annotated using a publicly available cerebrovascular cell atlas. CONCLUSION: ETS may supplement investigations aimed at development of a molecular-genetic taxonomic classification scheme for VOGM. Moreover, results may eventually inform the selection of personalized pharmacologic or genetic therapies for VOGM and cerebrovascular disorders more broadly.

The genetic basis of hydrocephalus: genes, pathways, mechanisms, and global impact.

Hydrocephalus (HC) is a heterogenous disease characterized by alterations in cerebrospinal fluid (CSF) dynamics that may cause increased intracranial pressure. HC is a component of a wide array of genetic syndromes as well as a secondary consequence of brain injury (intraventricular hemorrhage (IVH), infection, etc.) that can present across the age spectrum, highlighting the phenotypic heterogeneity of the disease. Surgical treatments include ventricular shunting and endoscopic third ventriculostomy with or without choroid plexus cauterization, both of which are prone to failure, and no effective pharmacologic treatments for HC have been developed. Thus, there is an urgent need to understand the genetic architecture and molecular pathogenesis of HC. Without this knowledge, the development of preventive, diagnostic, and therapeutic measures is impeded. However, the genetics of HC is extraordinarily complex, based on studies of varying size, scope, and rigor. This review serves to provide a comprehensive overview of genes, pathways, mechanisms, and global impact of genetics contributing to all etiologies of HC in humans.

Body Weight Correlates with Molecular Variances in Patients with Cancer.

Overweight and obesity are identified by a high body mass index (BMI) and carry significant health risks due to associated comorbidities. Although epidemiologic data connect overweight/obesity with 13 cancer types, a better understanding of the molecular mechanisms underlying this correlation is needed to improve prevention and treatment strategies. In this study, we conducted a comprehensive analysis of molecular differences between overweight or obese patients and normal weight patients across 14 different cancer types from The Cancer Genome Atlas. Using the propensity score weighting algorithm to control for confounding factors, obesity-specific mutational features were identified, such as higher mutation burden in rectal cancer and biased mutational signatures in other cancers. Differentially expressed genes (DEG) in tumors from patients with overweight/obesity were predominantly upregulated and enriched in inflammatory and hormone-related pathways. These DEGs were significantly associated with survival rates in various cancer types, highlighting the impact of elevated body fat on gene expression profiles and clinical outcomes in patients with cancer. Interestingly, while high BMI seemed to have a negative impact on most cancer types, the normal weight-biased mutational and gene expression patterns indicated overweight/obesity may be beneficial in endometrial cancer, suggesting the presence of an "obesity paradox" in this context. Body fat also significantly impacted the tumor microenvironment by modulating immune cell infiltration, underscoring the importance of understanding the interplay between weight and immune response in cancer progression. Together, this study systematically elucidates the molecular differences corresponding to body weight in multiple cancer types, offering potentially critical insights for developing precision therapy for patients with cancer. SIGNIFICANCE: Elucidation of the complex interplay between body weight and the molecular landscape of cancer could potentially guide tailored therapies and improve patient management amid the global obesity crisis.

Deciphering the exact breakpoints of structural variations using long sequencing reads with DeBreak.

Long-read sequencing has demonstrated great potential for characterizing all types of structural variations (SVs). However, existing algorithms have insufficient sensitivity and precision. To address these limitations, we present DeBreak, a computational method for comprehensive and accurate SV discovery. Based on alignment results, DeBreak employs a density-based approach for clustering SV candidates together with a local de novo assembly approach for reconstructing long insertions. A partial order alignment algorithm ensures precise SV breakpoints with single base-pair resolution, and a k-means clustering method can report multi-allele SV events. DeBreak outperforms existing tools on both simulated and real long-read sequencing data from both PacBio and Nanopore platforms. An important application of DeBreak is analyzing cancer genomes for potentially tumor-driving SVs. DeBreak can also be used for supplementing whole-genome assembly-based SV discovery.

Gene Fusion Detection and Characterization in Long-Read Cancer Transcriptome Sequencing Data with FusionSeeker.

Gene fusions are prevalent in a wide array of cancer types with different frequencies. Long-read transcriptome sequencing technologies, such as PacBio, Iso-Seq, and Nanopore direct RNA sequencing, provide full-length transcript sequencing reads, which could facilitate detection of gene fusions. In this work, we developed a method, FusionSeeker, to comprehensively characterize gene fusions in long-read cancer transcriptome data and reconstruct accurate fused transcripts from raw reads. FusionSeeker identified gene fusions in both exonic and intronic regions, allowing comprehensive characterization of gene fusions in cancer transcriptomes. Fused transcript sequences were reconstructed with FusionSeeker by correcting sequencing errors in the raw reads through partial order alignment algorithm. Using these accurate transcript sequences, FusionSeeker refined gene fusion breakpoint positions and predicted breakpoints at single bp resolution. Overall, FusionSeeker will enable users to discover gene fusions accurately using long-read data, which can facilitate downstream functional analysis as well as improved cancer diagnosis and treatment. SIGNIFICANCE: FusionSeeker is a new method to discover gene fusions and reconstruct fused transcript sequences in long-read cancer transcriptome sequencing data to help identify novel gene fusions important for tumorigenesis and progression.

Protein arginine methyltransferase 1 in the generation of immune megakaryocytes: A perspective review.

Megakaryocytes (Mks) in bone marrow are heterogeneous in terms of polyploidy. They not only produce platelets but also support the self-renewal of hematopoietic stem cells and regulate immune responses. Yet, how the diverse functions are generated from the heterogeneous Mks is not clear at the molecular level. Advances in single-cell RNA seq analysis from several studies have revealed that bone marrow Mks are heterogeneous and can be clustered into 3 to 4 subpopulations: a subgroup that is adjacent to the hematopoietic stem cells, a subgroup expressing genes for platelet biogenesis, and a subgroup expressing immune-responsive genes, the so-called immune Mks that exist in both humans and mice. Immune Mks are predominantly in the low-polyploid (≤8 N nuclei) fraction and also exist in the lung. Protein arginine methyltransferase 1 (PRMT1) expression is positively correlated with the expression of genes involved in immune response pathways and is highly expressed in immune Mks. In addition, we reported that PRMT1 promotes the generation of low-polyploid Mks. From this perspective, we highlighted the data suggesting that PRMT1 is essential for the generation of immune Mks via its substrates RUNX1, RBM15, and DUSP4 that we reported previously. Thus, we suggest that protein arginine methylation may play a critical role in the generation of proinflammatory platelet progeny from immune Mks, which may affect many immune, thrombotic, and inflammatory disorders.

Selective suppression of melanoma lacking IFN-γ pathway by JAK inhibition depends on T cells and host TNF signaling.

Therapeutic resistance to immune checkpoint blockers (ICBs) in melanoma patients is a pressing issue, of which tumor loss of IFN-γ signaling genes is a major underlying mechanism. However, strategies of overcoming this resistance mechanism have been largely elusive. Moreover, given the indispensable role of tumor-infiltrating T cells (TILs) in ICBs, little is known about how tumor-intrinsic loss of IFN-γ signaling (IFNγR1KO) impacts TILs. Here, we report that IFNγR1KO melanomas have reduced infiltration and function of TILs. IFNγR1KO melanomas harbor a network of constitutively active protein tyrosine kinases centered on activated JAK1/2. Mechanistically, JAK1/2 activation is mediated by augmented mTOR. Importantly, JAK1/2 inhibition with Ruxolitinib selectively suppresses the growth of IFNγR1KO but not scrambled control melanomas, depending on T cells and host TNF. Together, our results reveal an important role of tumor-intrinsic IFN-γ signaling in shaping TILs and manifest a targeted therapy to bypass ICB resistance of melanomas defective of IFN-γ signaling.

Reduced sister chromatid cohesion acts as a tumor penetrance modifier.

Sister chromatid cohesion (SCC) is an important process in chromosome segregation. ESCO2 is essential for establishment of SCC and is often deleted/altered in human cancers. We demonstrate that esco2 haploinsufficiency results in reduced SCC and accelerates the timing of tumor onset in both zebrafish and mouse p53 heterozygous null models, but not in p53 homozygous mutant or wild-type animals. These data indicate that esco2 haploinsufficiency accelerates tumor onset in a loss of heterozygosity (LOH) sensitive background. Analysis of The Cancer Genome Atlas (TCGA) confirmed ESCO2 deficient tumors have elevated number of LOH events throughout the genome. Further, we demonstrated heterozygous loss of sgo1, important in maintaining SCC, also results in reduced SCC and accelerated tumor formation in a p53 heterozygous background. Surprisingly, while we did observe elevated levels of chromosome missegregation and micronuclei formation in esco2 heterozygous mutant animals, this chromosomal instability did not contribute to the accelerated tumor onset in a p53 heterozygous background. Interestingly, SCC also plays a role in homologous recombination, and we did observe elevated levels of mitotic recombination derived p53 LOH in tumors from esco2 haploinsufficient animals; as well as elevated levels of mitotic recombination throughout the genome of human ESCO2 deficient tumors. Together these data suggest that reduced SCC contributes to accelerated tumor penetrance through elevated mitotic recombination.

B-assembler: a circular bacterial genome assembler.

BACKGROUND: Accurate bacteria genome de novo assembly is fundamental to understand the evolution and pathogenesis of new bacteria species. The advent and popularity of Third-Generation Sequencing (TGS) enables assembly of bacteria genomes at an unprecedented speed. However, most current TGS assemblers were specifically designed for human or other species that do not have a circular genome. Besides, the repetitive DNA fragments in many bacterial genomes plus the high error rate of long sequencing data make it still very challenging to accurately assemble their genomes even with a relatively small genome size. Therefore, there is an urgent need for the development of an optimized method to address these issues. RESULTS: We developed B-assembler, which is capable of assembling bacterial genomes when there are only long reads or a combination of short and long reads. B-assembler takes advantage of the structural resolving power of long reads and the accuracy of short reads if applicable. It first selects and corrects the ultra-long reads to get an initial contig. Then, it collects the reads overlapping with the ends of the initial contig. This two-round assembling procedure along with optimized error correction enables a high-confidence and circularized genome assembly. Benchmarked on both synthetic and real sequencing data of several species of bacterium, the results show that both long-read-only and hybrid-read modes can accurately assemble circular bacterial genomes free of structural errors and have fewer small errors compared to other assemblers. CONCLUSIONS: B-assembler provides a better solution to bacterial genome assembly, which will facilitate downstream bacterial genome analysis.

Accurate long-read de novo assembly evaluation with Inspector.

Long-read de novo genome assembly continues to advance rapidly. However, there is a lack of effective tools to accurately evaluate the assembly results, especially for structural errors. We present Inspector, a reference-free long-read de novo assembly evaluator which faithfully reports types of errors and their precise locations. Notably, Inspector can correct the assembly errors based on consensus sequences derived from raw reads covering erroneous regions. Based on in silico and long-read assembly results from multiple long-read data and assemblers, we demonstrate that in addition to providing generic metrics, Inspector can accurately identify both large-scale and small-scale assembly errors.

ClipSV: improving structural variation detection by read extension, spliced alignment and tree-based decision rules.

Structural variation (SV), which consists of genomic variation from 50 to millions of base pairs, confers considerable impacts on human diseases, complex traits and evolution. Accurately detecting SV is a fundamental step to characterize the features of individual genomes. Currently, several methods have been proposed to detect SVs using the next-generation sequencing (NGS) platform. However, due to the short length of sequencing reads and the complexity of SV content, the SV-detecting tools are still limited by low sensitivity, especially for insertion detection. In this study, we developed a novel tool, ClipSV, to improve SV discovery. ClipSV utilizes a read extension and spliced alignment approach to overcoming the limitation of read length. By reconstructing long sequences from SV-associated short reads, ClipSV discovers deletions and short insertions from the long sequence alignments. To comprehensively characterize insertions, ClipSV implements tree-based decision rules that can efficiently utilize SV-containing reads. Based on the evaluations of both simulated and real sequencing data, ClipSV exhibited an overall better performance compared to currently popular tools, especially for insertion detection. As NGS platform represents the mainstream sequencing capacity for routine genomic applications, we anticipate ClipSV will serve as an important tool for SV characterization in future genomic studies.

RNF2 ablation reprograms the tumor-immune microenvironment and stimulates durable NK and CD4+ T-cell-dependent antitumor immunity.

Expanding the utility of immune-based cancer treatments is a clinical challenge due to tumor-intrinsic factors that suppress the immune response. Here we report the identification of tumoral ring finger protein 2 (RNF2), the core subunit of polycomb repressor complex 1, as a negative regulator of antitumor immunity in various human cancers, including breast cancer. In syngeneic murine models of triple-negative breast cancer, we found that deleting genes encoding the polycomb repressor complex 1 subunits Rnf2, BMI1 proto-oncogene, polycomb ring finger (Bmi1), or the downstream effector of Rnf2, remodeling and spacing factor 1 (Rsf1), was sufficient by itself to induce durable tumor rejection and establish immune memory by enhancing infiltration and activation of natural killer and CD4+ T cells, but not CD8+ T cells, into the tumor and enabled their cooperativity. These findings uncover an epigenetic reprogramming of the tumor-immune microenvironment, which fosters durable antitumor immunity and memory.

Scalable De Novo Genome Assembly Using a Pregel-Like Graph-Parallel System.

De novo genome assembly is the process of stitching short DNA sequences to generate longer DNA sequences, without using any reference sequence for alignment. It enables high-throughput genome sequencing and thus accelerates the discovery of new genomes. In this paper, we present a toolkit, called PPA-assembler, for de novo genome assembly in a distributed setting. The operations in our toolkit provide strong performance guarantees, and can be assembled to implement various sequencing strategies. PPA-assembler adopts the popular de Bruijn graph based approach for sequencing, and each operation is implemented as a program in Google's Pregel framework which can be easily deployed in a generic cluster. Experiments on large real and simulated datasets demonstrate that PPA-assembler is much more efficient than the state-of-the-arts while providing comparable sequencing quality. PPA-assembler has been open-sourced at https://github.com/yaobaiwei/PPA-Assembler.

Ozone and Particulate Matter Exposure and Alzheimer's Disease: A Review of Human and Animal Studies.

Alzheimer's disease (AD), an aging-related neurodegenerative disease, is a major cause of dementia in the elderly. Although the early-onset (familial) AD is attributed to mutations in the genes coding for amyloid-ß protein precursor (AßPP) and presenilin1/presenilin 2 (PS1/PS2), the cause for the late-onset AD (LOAD), which accounts for more than 95% of AD cases, remains unclear. Aging is the greatest risk factor for LOAD, whereas the apolipo protein E4 allele (APOEɛ4) is believed to be a major genetic risk factor in acquiring LOAD, with female APOEɛ4 carriers at highest risk. Nonetheless, not all the elderly, even older female APOEɛ4 carriers, develop LOAD, suggesting that other factors, including environmental exposure, must play a role. This review summarizes recent studies that show a potential role of environmental exposure, especially ozone and particulate matter exposure, in the development of AD. Interactions between environmental exposure, genetic risk factor (APOEɛ4), and sex in AD pathophysiology are also discussed briefly. Identification of environmental risk factor(s) and elucidation of the complex interactions between genetic and environmental risk factors plus aging and female sex in the onset of AD will be a key to our understanding of the etiology and pathogenesis of AD and the development of the strategies for its prevention and treatment.

Pan-cancer analysis of whole genomes identifies driver rearrangements promoted by LINE-1 retrotransposition.

About half of all cancers have somatic integrations of retrotransposons. Here, to characterize their role in oncogenesis, we analyzed the patterns and mechanisms of somatic retrotransposition in 2,954 cancer genomes from 38 histological cancer subtypes within the framework of the Pan-Cancer Analysis of Whole Genomes (PCAWG) project. We identified 19,166 somatically acquired retrotransposition events, which affected 35% of samples and spanned a range of event types. Long interspersed nuclear element (LINE-1; L1 hereafter) insertions emerged as the first most frequent type of somatic structural variation in esophageal adenocarcinoma, and the second most frequent in head-and-neck and colorectal cancers. Aberrant L1 integrations can delete megabase-scale regions of a chromosome, which sometimes leads to the removal of tumor-suppressor genes, and can induce complex translocations and large-scale duplications. Somatic retrotranspositions can also initiate breakage-fusion-bridge cycles, leading to high-level amplification of oncogenes. These observations illuminate a relevant role of L1 retrotransposition in remodeling the cancer genome, with potential implications for the development of human tumors.

MRLR: unraveling high-resolution meiotic recombination by linked reads.

MOTIVATION: Meiotic recombination facilitates the transmission of exchanged genetic material between homologous chromosomes and plays a crucial role in increasing the genetic variations in eukaryotic organisms. In humans, thousands of crossover events have been identified by genotyping related family members. However, most of these crossover regions span tens to hundreds of kb, which is not sufficient resolution to accurately identify the crossover breakpoints in a typical trio family. RESULTS: We have developed MRLR, a software using 10X linked reads to identify crossover events at a high resolution. By reconstructing the gamete genome, MRLR only requires a trio family dataset and can efficiently discover the crossover events. Using MRLR, we revealed a fine-scale pattern of crossover regions in six human families. From the two closest heterozygous alleles around the crossovers, we determined that MRLR achieved a median resolution 4.5 kb. This method can delineate a genome-wide landscape of crossover events at a precise scale, which is important for both functional and genomic features analysis of meiotic recombination. AVAILABILITY AND IMPLEMENTATION: MRLR is freely available at https://github.com/ChongLab/MRLR, implemented in Perl. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Multi-platform discovery of haplotype-resolved structural variation in human genomes.

The incomplete identification of structural variants (SVs) from whole-genome sequencing data limits studies of human genetic diversity and disease association. Here, we apply a suite of long-read, short-read, strand-specific sequencing technologies, optical mapping, and variant discovery algorithms to comprehensively analyze three trios to define the full spectrum of human genetic variation in a haplotype-resolved manner. We identify 818,054 indel variants (<50 bp) and 27,622 SVs (≥50 bp) per genome. We also discover 156 inversions per genome and 58 of the inversions intersect with the critical regions of recurrent microdeletion and microduplication syndromes. Taken together, our SV callsets represent a three to sevenfold increase in SV detection compared to most standard high-throughput sequencing studies, including those from the 1000 Genomes Project. The methods and the dataset presented serve as a gold standard for the scientific community allowing us to make recommendations for maximizing structural variation sensitivity for future genome sequencing studies.

Megabase Length Hypermutation Accompanies Human Structural Variation at 17p11.2.

DNA rearrangements resulting in human genome structural variants (SVs) are caused by diverse mutational mechanisms. We used long- and short-read sequencing technologies to investigate end products of de novo chromosome 17p11.2 rearrangements and query the molecular mechanisms underlying both recurrent and non-recurrent events. Evidence for an increased rate of clustered single-nucleotide variant (SNV) mutation in cis with non-recurrent rearrangements was found. Indel and SNV formation are associated with both copy-number gains and losses of 17p11.2, occur up to ∼1 Mb away from the breakpoint junctions, and favor C > G transversion substitutions; results suggest that single-stranded DNA is formed during the genesis of the SV and provide compelling support for a microhomology-mediated break-induced replication (MMBIR) mechanism for SV formation. Our data show an additional mutational burden of MMBIR consisting of hypermutation confined to the locus and manifesting as SNVs and indels predominantly within genes.

Combining accurate tumor genome simulation with crowdsourcing to benchmark somatic structural variant detection.

BACKGROUND: The phenotypes of cancer cells are driven in part by somatic structural variants. Structural variants can initiate tumors, enhance their aggressiveness, and provide unique therapeutic opportunities. Whole-genome sequencing of tumors can allow exhaustive identification of the specific structural variants present in an individual cancer, facilitating both clinical diagnostics and the discovery of novel mutagenic mechanisms. A plethora of somatic structural variant detection algorithms have been created to enable these discoveries; however, there are no systematic benchmarks of them. Rigorous performance evaluation of somatic structural variant detection methods has been challenged by the lack of gold standards, extensive resource requirements, and difficulties arising from the need to share personal genomic information. RESULTS: To facilitate structural variant detection algorithm evaluations, we create a robust simulation framework for somatic structural variants by extending the BAMSurgeon algorithm. We then organize and enable a crowdsourced benchmarking within the ICGC-TCGA DREAM Somatic Mutation Calling Challenge (SMC-DNA). We report here the results of structural variant benchmarking on three different tumors, comprising 204 submissions from 15 teams. In addition to ranking methods, we identify characteristic error profiles of individual algorithms and general trends across them. Surprisingly, we find that ensembles of analysis pipelines do not always outperform the best individual method, indicating a need for new ways to aggregate somatic structural variant detection approaches. CONCLUSIONS: The synthetic tumors and somatic structural variant detection leaderboards remain available as a community benchmarking resource, and BAMSurgeon is available at https://github.com/adamewing/bamsurgeon .