Genomic and phenotypic correlates of mosaic loss of chromosome Y in blood.

Mosaic loss of Y (mLOY) is the most common somatic chromosomal alteration detected in human blood. The presence of mLOY is associated with altered blood cell counts and increased risk of Alzheimer's disease, solid tumors, and other age-related diseases. We sought to gain a better understanding of genetic drivers and associated phenotypes of mLOY through analyses of whole genome sequencing of a large set of genetically diverse males from the Trans-Omics for Precision Medicine (TOPMed) program. This approach enabled us to identify differences in mLOY frequencies across populations defined by genetic similarity, revealing a higher frequency of mLOY in the European American (EA) ancestry group compared to those of Hispanic American (HA), African American (AA), and East Asian (EAS) ancestry. Further, we identified two genes ( CFHR1 and LRP6 ) that harbor multiple rare, putatively deleterious variants associated with mLOY susceptibility, show that subsets of human hematopoietic stem cells are enriched for activity of mLOY susceptibility variants, and that certain alleles on chromosome Y are more likely to be lost than others.

A noncoding regulatory variant in IKZF1 increases acute lymphoblastic leukemia risk in Hispanic/Latino children.

Hispanic/Latino children have the highest risk of acute lymphoblastic leukemia (ALL) in the US compared to other racial/ethnic groups, yet the basis of this remains incompletely understood. Through genetic fine-mapping analyses, we identified a new independent childhood ALL risk signal near IKZF1 in self-reported Hispanic/Latino individuals, but not in non-Hispanic White individuals, with an effect size of ∼1.44 (95% confidence interval = 1.33-1.55) and a risk allele frequency of ∼18% in Hispanic/Latino populations and <0.5% in European populations. This risk allele was positively associated with Indigenous American ancestry, showed evidence of selection in human history, and was associated with reduced IKZF1 expression. We identified a putative causal variant in a downstream enhancer that is most active in pro-B cells and interacts with the IKZF1 promoter. This variant disrupts IKZF1 autoregulation at this enhancer and results in reduced enhancer activity in B cell progenitors. Our study reveals a genetic basis for the increased ALL risk in Hispanic/Latino children.

Deciphering cell states and genealogies of human haematopoiesis.

The human blood system is maintained through the differentiation and massive amplification of a limited number of long-lived haematopoietic stem cells (HSCs)1. Perturbations to this process underlie diverse diseases, but the clonal contributions to human haematopoiesis and how this changes with age remain incompletely understood. Although recent insights have emerged from barcoding studies in model systems2-5, simultaneous detection of cell states and phylogenies from natural barcodes in humans remains challenging. Here we introduce an improved, single-cell lineage-tracing system based on deep detection of naturally occurring mitochondrial DNA mutations with simultaneous readout of transcriptional states and chromatin accessibility. We use this system to define the clonal architecture of HSCs and map the physiological state and output of clones. We uncover functional heterogeneity in HSC clones, which is stable over months and manifests as both differences in total HSC output and biases towards the production of different mature cell types. We also find that the diversity of HSC clones decreases markedly with age, leading to an oligoclonal structure with multiple distinct clonal expansions. Our study thus provides a clonally resolved and cell-state-aware atlas of human haematopoiesis at single-cell resolution, showing an unappreciated functional diversity of human HSC clones and, more broadly, paving the way for refined studies of clonal dynamics across a range of tissues in human health and disease.

Lysine demethylase 5C inhibits transcription of prefoldin subunit 5 to activate c-Myc signal transduction and colorectal cancer progression.

BACKGROUND: Lysine demethylase 5C (KDM5C) has been implicated in the development of several human cancers. This study aims to investigate the role of KDM5C in the progression of colorectal cancer (CRC) and explore the associated molecular mechanism. METHODS: Bioinformatics tools were employed to predict the target genes of KDM5C in CRC. The expression levels of KDM5C and prefoldin subunit 5 (PFDN5) in CRC cells were determined by RT-qPCR and western blot assays. The interaction between KDM5C, H3K4me3, and PFDN5 was validated by chromatin immunoprecipitation. Expression and prognostic values of KDM5C and PFDN5 in CRC were analyzed in a cohort of 72 patients. The function of KDM5C/PFDN5 in c-Myc signal transduction was analyzed by luciferase assay. Silencing of KDM5C and PFDN5 was induced in CRC cell lines to analyze the cell malignant phenotype in vitro and tumorigenic activity in nude mice. RESULTS: KDM5C exhibited high expression, while PFDN5 displayed low expression in CRC cells and clinical CRC samples. High KDM5C levels correlated with poor survival and unfavorable clinical presentation, whereas elevated PFDN5 correlated with improved patient outcomes. KDM5C mediated demethylation of H3K4me3 on the PFDN5 promoter, suppressing its transcription and thereby enhancing the transcriptional activity of c-Myc. KDM5C knockdown in CRC cells suppressed cell proliferation, migration and invasion, epithelial-mesenchymal transition, and tumorigenic activity while increasing autophagy and apoptosis rates. However, the malignant behavior of cells was restored by the further silencing of PFDN5. CONCLUSION: This study demonstrates that KDM5C inhibits PFDN5 transcription, thereby activating c-Myc signal transduction and promoting CRC progression.

Systematic investigation of mitochondrial transfer between cancer cells and T cells at single-cell resolution.

Mitochondria (MT) participate in most metabolic activities of mammalian cells. A near-unidirectional mitochondrial transfer from T cells to cancer cells was recently observed to "metabolically empower" cancer cells while "depleting immune cells," providing new insights into tumor-T cell interaction and immune evasion. Here, we leverage single-cell RNA-seq technology and introduce MERCI, a statistical deconvolution method for tracing and quantifying mitochondrial trafficking between cancer and T cells. Through rigorous benchmarking and validation, MERCI accurately predicts the recipient cells and their relative mitochondrial compositions. Application of MERCI to human cancer samples identifies a reproducible MT transfer phenotype, with its signature genes involved in cytoskeleton remodeling, energy production, and TNF-α signaling pathways. Moreover, MT transfer is associated with increased cell cycle activity and poor clinical outcome across different cancer types. In summary, MERCI enables systematic investigation of an understudied aspect of tumor-T cell interactions that may lead to the development of therapeutic opportunities.

Context-aware single-cell multiome approach identified cell-type specific lung cancer susceptibility genes.

Genome-wide association studies (GWAS) identified over fifty loci associated with lung cancer risk. However, the genetic mechanisms and target genes underlying these loci are largely unknown, as most risk-associated-variants might regulate gene expression in a context-specific manner. Here, we generated a barcode-shared transcriptome and chromatin accessibility map of 117,911 human lung cells from age/sex-matched ever- and never-smokers to profile context-specific gene regulation. Accessible chromatin peak detection identified cell-type-specific candidate cis-regulatory elements (cCREs) from each lung cell type. Colocalization of lung cancer candidate causal variants (CCVs) with these cCREs prioritized the variants for 68% of the GWAS loci, a subset of which was also supported by transcription factor abundance and footprinting. cCRE colocalization and single-cell based trait relevance score nominated epithelial and immune cells as the main cell groups contributing to lung cancer susceptibility. Notably, cCREs of rare proliferating epithelial cell types, such as AT2-proliferating (0.13%) and basal cells (1.8%), overlapped with CCVs, including those in TERT. A multi-level cCRE-gene linking system identified candidate susceptibility genes from 57% of lung cancer loci, including those not detected in tissue- or cell-line-based approaches. cCRE-gene linkage uncovered that adjacent genes expressed in different cell types are correlated with distinct subsets of coinherited CCVs, including JAML and MPZL3 at the 11q23.3 locus. Our data revealed the cell types and contexts where the lung cancer susceptibility genes are functional.

Genetic regulation of fetal hemoglobin across global populations.

Human genetic variation has enabled the identification of several key regulators of fetal-to-adult hemoglobin switching, including BCL11A, resulting in therapeutic advances. However, despite the progress made, limited further insights have been obtained to provide a fuller accounting of how genetic variation contributes to the global mechanisms of fetal hemoglobin (HbF) gene regulation. Here, we have conducted a multi-ancestry genome-wide association study of 28,279 individuals from several cohorts spanning 5 continents to define the architecture of human genetic variation impacting HbF. We have identified a total of 178 conditionally independent genome-wide significant or suggestive variants across 14 genomic windows. Importantly, these new data enable us to better define the mechanisms by which HbF switching occurs in vivo. We conduct targeted perturbations to define BACH2 as a new genetically-nominated regulator of hemoglobin switching. We define putative causal variants and underlying mechanisms at the well-studied BCL11A and HBS1L-MYB loci, illuminating the complex variant-driven regulation present at these loci. We additionally show how rare large-effect deletions in the HBB locus can interact with polygenic variation to influence HbF levels. Our study paves the way for the next generation of therapies to more effectively induce HbF in sickle cell disease and ß-thalassemia.

A genetic disorder reveals a hematopoietic stem cell regulatory network co-opted in leukemia.

The molecular regulation of human hematopoietic stem cell (HSC) maintenance is therapeutically important, but limitations in experimental systems and interspecies variation have constrained our knowledge of this process. Here, we have studied a rare genetic disorder due to MECOM haploinsufficiency, characterized by an early-onset absence of HSCs in vivo. By generating a faithful model of this disorder in primary human HSCs and coupling functional studies with integrative single-cell genomic analyses, we uncover a key transcriptional network involving hundreds of genes that is required for HSC maintenance. Through our analyses, we nominate cooperating transcriptional regulators and identify how MECOM prevents the CTCF-dependent genome reorganization that occurs as HSCs differentiate. We show that this transcriptional network is co-opted in high-risk leukemias, thereby enabling these cancers to acquire stem cell properties. Collectively, we illuminate a regulatory network necessary for HSC self-renewal through the study of a rare experiment of nature.

The Number of Intraoperative Intestinal Venous Circulating Tumor Cells Is a Prognostic Factor for Colorectal Cancer Patients.

Purpose: To assess the association between intestinal venous blood (IVB) circulating tumor cells (CTCs) and clinicopathological parameters in stage I-III colorectal cancer (CRC) patients. Methods: Participants were retrospectively retrieved, who were admitted to our hospital or took annual physical exams between December 1, 2015 and December 31, 2018. A negative enrichment-immunofluorescence in situ hybridization (NE-imFISH) technique was used to isolate and identify CTCs. Receiver operating characteristic (ROC) curves and Youden index values were used to determine the critical CTC cutoff value for the diagnosis of CRC. Kaplan-Meier and log-rank methods were used to conduct survival analyses, and multivariate Cox regression analyses were employed for multivariate corrections to comprehensively evaluate the value of CTCs in the diagnosis of CRC. Relationships between IVB CTCs, clinicopathological parameters, and prognosis were then analyzed based upon patient postoperative follow-up data. Results: In total, we retrieved 282 patients including 48 healthy controls, 72 patients with benign colorectal tumors, and 162 CRC patients. CRC patients exhibited significantly higher numbers of CTCs relative to control patients or those with benign disease. CTC numbers in CRC patient peripheral blood (PB) and IVB were closely associated with tumor node metastasis (TNM) staging (P < 0.01), carbohydrate antigen-125 (CA-125) levels (P < 0.001), and KRAS (Kirsten rat sarcoma virus oncogene) mutation status (P < 0.001). The disease-free survival (DFS) of patients in the CTC-negative group was significantly longer than that of patients in the CTC-positive group (24.60 ± 13.31 months vs. 18.70 ± 10.19 months, P < 0.05), with the same being true with respect to their overall survival (OS) (30.60 ± 12.44 months vs. 35.25 ± 11.57 months, P < 0.05). A multivariate analysis revealed that the detection ≥2 CTCs/3.2 ml was independently associated with poorer DFS and OS. CTC counts were independently predictive of CRC patients TNM staging, CA-125, and KRAS mutation status in both univariate and multivariate Cox proportional hazards regression analyses. Conclusion: CTCs are valuable biomarkers that can be monitored to predict CRC patient disease progression.

Variant to function mapping at single-cell resolution through network propagation.

Genome-wide association studies in combination with single-cell genomic atlases can provide insights into the mechanisms of disease-causal genetic variation. However, identification of disease-relevant or trait-relevant cell types, states and trajectories is often hampered by sparsity and noise, particularly in the analysis of single-cell epigenomic data. To overcome these challenges, we present SCAVENGE, a computational algorithm that uses network propagation to map causal variants to their relevant cellular context at single-cell resolution. We demonstrate how SCAVENGE can help identify key biological mechanisms underlying human genetic variation, applying the method to blood traits at distinct stages of human hematopoiesis, to monocyte subsets that increase the risk for severe Coronavirus Disease 2019 (COVID-19) and to intermediate lymphocyte developmental states that predispose to acute leukemia. Our approach not only provides a framework for enabling variant-to-function insights at single-cell resolution but also suggests a more general strategy for maximizing the inferences that can be made using single-cell genomic data.

Variant to function mapping at single-cell resolution through network propagation.

With burgeoning human disease genetic associations and single-cell genomic atlases covering a range of tissues, there are unprecedented opportunities to systematically gain insights into the mechanisms of disease-causal variation. However, sparsity and noise, particularly in the context of single-cell epigenomic data, hamper the identification of disease- or trait-relevant cell types, states, and trajectories. To overcome these challenges, we have developed the SCAVENGE method, which maps causal variants to their relevant cellular context at single-cell resolution by employing the strategy of network propagation. We demonstrate how SCAVENGE can help identify key biological mechanisms underlying human genetic variation including enrichment of blood traits at distinct stages of human hematopoiesis, defining monocyte subsets that increase the risk for severe coronavirus disease 2019 (COVID-19), and identifying intermediate lymphocyte developmental states that are critical for predisposition to acute leukemia. Our approach not only provides a framework for enabling variant-to-function insights at single-cell resolution, but also suggests a more general strategy for maximizing the inferences that can be made using single-cell genomic data.

CUT&RUNTools 2.0: a pipeline for single-cell and bulk-level CUT&RUN and CUT&Tag data analysis.

MOTIVATION: Genome-wide profiling of transcription factor binding and chromatin states is a widely-used approach for mechanistic understanding of gene regulation. Recent technology development has enabled such profiling at single-cell resolution. However, an end-to-end computational pipeline for analyzing such data is still lacking. RESULTS: Here, we have developed a flexible pipeline for analysis and visualization of single-cell CUT&Tag and CUT&RUN data, which provides functions for sequence alignment, quality control, dimensionality reduction, cell clustering, data aggregation and visualization. Furthermore, it is also seamlessly integrated with the functions in original CUT&RUNTools for population-level analyses. As such, this provides a valuable toolbox for the community. AVAILABILITY AND IMPLEMENTATION: https://github.com/fl-yu/CUT-RUNTools-2.0. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Application of low dose pancreas perfusion CT combined with enhancement scanning in diagnosis of pancreatic neuroendocrine tumors.

PURPOSE: To explore the diagnostic value of pancreatic perfusion CT combined with contrast-enhanced CT in one-time scanning (PCECT) in pancreatic neuroendocrine tumors (PNETs) and to evaluate the difference of perfusion parameters between different grades of PNETs. MATERIALS AND METHODS: From October 2016 to December 2018, forty consecutive patients with histopathological-proven PNETs were identified retrospectively that received PCECT for the preoperative PNETs evaluation. Two board certified radiologists who were blinded to the clinical data evaluated the images independently. The image characters of PNETs vs. tumor-free pancreatic parenchymal and different grades of PNETs were analyzed. RESULTS: One-time PCECT scanning had a detection rate of 89.1% for PNETs, which was higher than the detection accuracy of the perfusion CT only (83.6%). The perfusion parameters of PNETs including blood volume (BV), blood flow (BF), mean slope of increase (MSI), and capillary surface permeability (PS) were significantly increased than those of tumor-free pancreatic parenchyma (p < 0.05, respectively). For differential comparison between grade I (G1) and grade II (G2) tumors, the parameters of BF and impulse residue function (IRF) of tumor tissue were significantly higher in the G2 tumors (p < 0.05, for both). In this study, the total radiation dose of the whole PCECT scan was 16.241 ± 2.289 mSv. CONCLUSION: The one-time PCECT scan may improve the detection of PNETs according to morphological features and perfusion parameters with a relative small radiation dose. The perfusion parameters of BF and IRF may be used to help distinguish G1 and G2 tumors in the preoperative evaluation.

Human embryonic stem cell-derived organoid retinoblastoma reveals a cancerous origin.

Retinoblastoma (Rb) is the most prevalent intraocular malignancy in children, with a worldwide survival rate <30%. We have developed a cancerous model of Rb in retinal organoids derived from genetically engineered human embryonic stem cells (hESCs) with a biallelic mutagenesis of the RB1 gene. These organoid Rbs exhibit properties highly consistent with Rb tumorigenesis, transcriptome, and genome-wide methylation. Single-cell sequencing analysis suggests that Rb originated from ARR3-positive maturing cone precursors during development, which was further validated by immunostaining. Notably, we found that the PI3K-Akt pathway was aberrantly deregulated and its activator spleen tyrosine kinase (SYK) was significantly up-regulated. In addition, SYK inhibitors led to remarkable cell apoptosis in cancerous organoids. In conclusion, we have established an organoid Rb model derived from genetically engineered hESCs in a dish that has enabled us to trace the cell of origin and to test novel candidate therapeutic agents for human Rb, shedding light on the development and therapeutics of other malignancies.

scTPA: a web tool for single-cell transcriptome analysis of pathway activation signatures.

MOTIVATION: At present, a fundamental challenge in single-cell RNA-sequencing data analysis is functional interpretation and annotation of cell clusters. Biological pathways in distinct cell types have different activation patterns, which facilitates the understanding of cell functions using single-cell transcriptomics. However, no effective web tool has been implemented for single-cell transcriptome data analysis based on prior biological pathway knowledge. RESULTS: Here, we present scTPA, a web-based platform for pathway-based analysis of single-cell RNA-seq data in human and mouse. scTPA incorporates four widely-used gene set enrichment methods to estimate the pathway activation scores of single cells based on a collection of available biological pathways with different functional and taxonomic classifications. The clustering analysis and cell-type-specific activation pathway identification were provided for the functional interpretation of cell types from a pathway-oriented perspective. An intuitive interface allows users to conveniently visualize and download single-cell pathway signatures. Overall, scTPA is a comprehensive tool for the identification of pathway activation signatures for the analysis of single cell heterogeneity. AVAILABILITY AND IMPLEMENTATION: http://sctpa.bio-data.cn/sctpa. CONTACT: sujz@wmu.edu.cn or yufulong421@gmail.com or zgj@zjut.edu.cn. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Prioritizing Gene Cascading Paths to Model Colorectal Cancer Through Engineered Organoids.

Engineered organoids by sequential introduction of key mutations could help modeling the dynamic cancer progression. However, it remains difficult to determine gene paths which were sufficient to capture cancer behaviors and to broadly explain cancer mechanisms. Here, as a case study of colorectal cancer (CRC), functional and dynamic characterizations of five types of engineered organoids with different mutation combinations of five driver genes (APC, SMAD4, KRAS, TP53, and PIK3CA) showed that sequential introductions of all five driver mutations could induce enhanced activation of more hallmark signatures, tending to cancer. Comparative analysis of engineered organoids and corresponding CRC tissues revealed sequential introduction of key mutations could continually shorten the biological distance from engineered organoids to CRC tissues. Nevertheless, there still existed substantial biological gaps between the engineered organoid even with five key mutations and CRC samples. Thus, we proposed an integrative strategy to prioritize gene cascading paths for shrinking biological gaps between engineered organoids and CRC tissues. Our results not only recapitulated the well-known adenoma-carcinoma sequence model (e.g., AKST-organoid with driver mutations in APC, KRAS, SMAD4, and TP53), but also provided potential paths for delineating alternative pathogenesis underlying CRC populations (e.g., A-organoid with APC mutation). Our strategy also can be applied to both organoids with more mutations and other cancers, which can improve and innovate mechanism across cancer patients for drug design and cancer therapy.

Nc2Eye: A Curated ncRNAomics Knowledgebase for Bridging Basic and Clinical Research in Eye Diseases.

Eye diseases (EDs) represent a group of disorders affecting the visual system, most of which can lead to visual impairment and blindness. Accumulating evidence reveals that non-coding RNAs (ncRNAs) are closely associated with a wide variety of EDs. However, abundant associations between ncRNAs and EDs are scattered across the published literature, obstructing a global view of ncRNA-ED associations. A public resource of high-quality manually curated ncRNAomics knowledge associated with EDs remains unavailable. To address this gap, we thus developed Nc2Eye (http://nc2eye.bio-data.cn/), which is the first knowledgebase dedicated to providing a comprehensive ncRNAomics resource for bridging basic and clinical research in EDs. Through a comprehensive review of more than 2400 published papers, Nc2Eye catalogs 7088 manually curated ncRNA-ED associations involving 4363 ncRNAs across eight species. We also provide detailed descriptions and annotation information for each ncRNA-disease association such as ncRNA categories, experimental methods, expression pattern and related clinical drugs. To further expand the pathogenic ncRNAs, we also collected more than 90 high-throughput EDs-related transcriptome datasets. Furthermore, a user-friendly interface was constructed for convenient and flexible data browsing, querying, and retrieving. We believe that Nc2Eye is a timely and valuable knowledgebase for significantly improving and useful for discovery of new diagnostic and therapeutic biomarkers.

CFEA: a cell-free epigenome atlas in human diseases.

Epigenetic alterations, including 5-methylcytosine (5mC), 5-hydroxymethylcytosine (5hmC) and nucleosome positioning (NP), in cell-free DNA (cfDNA) have been widely observed in human diseases, and many available cfDNA-based epigenome-wide profiles exhibit high sensitivity and specificity in disease detection and classification. However, due to the lack of efficient collection, standardized quality control, and analysis procedures, efficiently integrating and reusing these data remain considerable challenges. Here, we introduce CFEA (http://www.bio-data.cn/CFEA), a cell-free epigenome database dedicated to three types of widely adopted epigenetic modifications (5mC, 5hmC and NP) involved in 27 human diseases. We developed bioinformatic pipelines for quality control and standard data processing and an easy-to-use web interface to facilitate the query, visualization and download of these cell-free epigenome data. We also manually curated related biological and clinical information for each profile, allowing users to better browse and compare cfDNA epigenomes at a specific stage (such as early- or metastasis-stage) of cancer development. CFEA provides a comprehensive and timely resource to the scientific community and supports the development of liquid biopsy-based biomarkers for various human diseases.

Systematic Characterization of Circular RNA-Associated CeRNA Network Identified Novel circRNA Biomarkers in Alzheimer's Disease.

Alzheimer's disease (AD), a degenerative disease of the central nervous system, is the most common form of dementia in old age. The complexity and behavior of circular RNA (circRNA)-associated competing endogenous RNA (ceRNA) network remained poorly characterized in AD. The aim of this study was to elucidate the regulatory networks of dysregulated circRNAs from ceRNA view and identify potential risk circRNAs involved in AD pathogenesis. Consistent differentially expressed genes (CDEGs) were obtained using meta-analysis for multiple microarrays, and differentially expressed miRNAs (DEmiRs) were identified using empirical Bayes method. The circRNA-associated ceRNA network (cirCeNET) was constructed based on "ceRNA hypothesis" using an integrated system biology method. A total of 1,872 CDEGs and 48 DEmiRs were screened across different datasets. By mapping CDEGs and DEmiRs into the cirCeNET, an AD-related circRNA-associated ceRNA network (ADcirCeNET) was constructed, including 3,907 edges and 1,407 nodes (276 circRNAs, 14 miRNAs and 1,117 mRNAs). By prioritizing AD risk circRNA-associated ceRNAs, we found that the circRNA KIAA1586 occurred most frequently in the AD risk circRNA-associated ceRNAs and function as a ceRNA that operates by competitively binding three known AD-risk miRNAs. In silico functional analysis suggested that circRNA KIAA1586-related ceRNA network was significantly enriched in known AD-associated biological processes. Our study provided a global view and systematic dissection of circRNA-associated ceRNA network. The identified circRNA KIAA1586 may be a key risk factor involved in AD pathogenesis.

Sex difference of mutation clonality in diffuse glioma evolution.

BACKGROUND: Sex differences in glioma incidence and outcome have been previously reported but remain poorly understood. Many sex differences that affect the cancer risk were thought to be associated with cancer evolution. METHODS: In this study, we used an integrated framework to infer the timing and clonal status of mutations in ~600 diffuse gliomas from The Cancer Genome Atlas (TCGA) including glioblastomas (GBMs) and low-grade gliomas (LGGs), and investigated the sex difference of mutation clonality. RESULTS: We observed higher overall and subclonal mutation burden in female patients with different grades of gliomas, which could be largely explained by the mutations of the X chromosome. Some well-established drivers were identified showing sex-biased clonality, such as CDH18 and ATRX. Focusing on glioma subtypes, we further found a higher subclonal mutation burden in females than males in the majority of glioma subtypes, and observed opposite clonal tendency of several drivers between male and female patients in a specific subtype. Moreover, analysis of clinically actionable genes revealed that mutations in genes of the mitogen-activated protein kinase (MAPK) signaling pathway were more likely to be clonal in female patients with GBM, whereas mutations in genes involved in the receptor tyrosine kinase signaling pathway were more likely to be clonal in male patients with LGG. CONCLUSIONS: The patients with diffuse glioma showed sex-biased mutation clonality (eg, different subclonal mutation number and different clonal tendency of cancer genes), highlighting the need to consider sex as an important variable for improving glioma therapy and clinical care.