Quiescence enables unrestricted cell fate in naive embryonic stem cells.

Quiescence in stem cells is traditionally considered as a state of inactive dormancy or with poised potential. Naive mouse embryonic stem cells (ESCs) can enter quiescence spontaneously or upon inhibition of MYC or fatty acid oxidation, mimicking embryonic diapause in vivo. The molecular underpinning and developmental potential of quiescent ESCs (qESCs) are relatively unexplored. Here we show that qESCs possess an expanded or unrestricted cell fate, capable of generating both embryonic and extraembryonic cell types (e.g., trophoblast stem cells). These cells have a divergent metabolic landscape comparing to the cycling ESCs, with a notable decrease of the one-carbon metabolite S-adenosylmethionine. The metabolic changes are accompanied by a global reduction of H3K27me3, an increase of chromatin accessibility, as well as the de-repression of endogenous retrovirus MERVL and trophoblast master regulators. Depletion of methionine adenosyltransferase Mat2a or deletion of Eed in the polycomb repressive complex 2 results in removal of the developmental constraints towards the extraembryonic lineages. Our findings suggest that quiescent ESCs are not dormant but rather undergo an active transition towards an unrestricted cell fate.

Prognostic iron-metabolism signature robustly stratifies single-cell characteristics of hepatocellular carcinoma.

Cancer immunotherapy has shown to be a promising method in treating hepatocellular carcinoma (HCC), but suboptimal responses in patients are attributed to cellular and molecular heterogeneity. Iron metabolism-related genes (IRGs) are important in maintaining immune system homeostasis and have the potential to help develop new strategies for HCC treatment. Herein, we constructed and validated the iron-metabolism gene prognostic index (IPX) using univariate Cox proportional hazards regression and LASSO Cox regression analysis, successfully categorizing HCC patients into two groups with distinct survival risks. Then, we performed single-sample gene set enrichment analysis, weighted correlation network analysis, gene ontology enrichment analysis, cellular lineage analysis, and SCENIC analysis to reveal the key determinants underlying the ability of this model based on bulk and single-cell transcriptomic data. We identified several driver transcription factors specifically activated in specific malignant cell sub-populations to contribute to the adverse survival outcomes in the IPX-high subgroup. Within the tumor microenvironment (TME), T cells displayed significant diversity in their cellular characteristics and experienced changes in their developmental paths within distinct clusters identified by IPX. Interestingly, the proportion of Treg cells was increased in the high-risk group compared with the low-risk group. These results suggest that iron-metabolism could be involved in reshaping the TME, thereby disrupting the cell cycle of immune cells. This study utilized IRGs to construct a novel and reliable model, which can be used to assess the prognosis of patients with HCC and further clarify the molecular mechanisms of IRGs in HCC at single-cell resolution.

Innovative insights into extrachromosomal circular DNAs in gynecologic tumors and reproduction.

Originating but free from chromosomal DNA, extrachromosomal circular DNAs (eccDNAs) are organized in circular form and have long been found in unicellular and multicellular eukaryotes. Their biogenesis and function are poorly understood as they are characterized by sequence homology with linear DNA, for which few detection methods are available. Recent advances in high-throughput sequencing technologies have revealed that eccDNAs play crucial roles in tumor formation, evolution, and drug resistance as well as aging, genomic diversity, and other biological processes, bringing it back to the research hotspot. Several mechanisms of eccDNA formation have been proposed, including the breakage-fusion-bridge (BFB) and translocation-deletion-amplification models. Gynecologic tumors and disorders of embryonic and fetal development are major threats to human reproductive health. The roles of eccDNAs in these pathological processes have been partially elucidated since the first discovery of eccDNA in pig sperm and the double minutes in ovarian cancer ascites. The present review summarized the research history, biogenesis, and currently available detection and analytical methods for eccDNAs and clarified their functions in gynecologic tumors and reproduction. We also proposed the application of eccDNAs as drug targets and liquid biopsy markers for prenatal diagnosis and the early detection, prognosis, and treatment of gynecologic tumors. This review lays theoretical foundations for future investigations into the complex regulatory networks of eccDNAs in vital physiological and pathological processes.

Integrative analysis of DNA methylomes reveals novel cell-free biomarkers in lung adenocarcinoma.

Lung cancer is a leading cause of cancer-related deaths worldwide, with a low 5-year survival rate due in part to a lack of clinically useful biomarkers. Recent studies have identified DNA methylation changes as potential cancer biomarkers. The present study identified cancer-specific CpG methylation changes by comparing genome-wide methylation data of cfDNA from lung adenocarcinomas (LUAD) patients and healthy donors in the discovery cohort. A total of 725 cell-free CpGs associated with LUAD risk were identified. Then XGBoost algorithm was performed to identify seven CpGs associated with LUAD risk. In the training phase, the 7-CpGs methylation panel was established to classify two different prognostic subgroups and showed a significant association with overall survival (OS) in LUAD patients. We found that the methylation of cg02261780 was negatively correlated with the expression of its representing gene GNA11. The methylation and expression of GNA11 were significantly associated with LAUD prognosis. Based on bisulfite PCR, the methylation levels of five CpGs (cg02261780, cg09595050, cg20193802, cg15309457, and cg05726109) were further validated in tumor tissues and matched non-malignant tissues from 20 LUAD patients. Finally, validation of the seven CpGs with RRBS data of cfDNA methylation was conducted and further proved the reliability of the 7-CpGs methylation panel. In conclusion, our study identified seven novel methylation markers from cfDNA methylation data which may contribute to better prognosis for LUAD patients.

Risk modeling of single-cell transcriptomes reveals the heterogeneity of immune infiltration in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is one of the most common primary hepatic malignancies. E2F transcription factors play an important role in the tumorigenesis and progression of HCC, mainly through the RB/E2F pathway. Prognostic models for HCC based on gene signatures have been developed rapidly in recent years; however, their discriminating ability at the single-cell level remains elusive, which could reflect the underlying mechanisms driving the sample bifurcation. In this study, we constructed and validated a predictive model based on E2F expression, successfully stratifying patients with HCC into two groups with different survival risks. Then we used a single-cell dataset to test the discriminating ability of the predictive model on infiltrating T cells, demonstrating remarkable cellular heterogeneity as well as altered cell fates. We identified distinct cell subpopulations with diverse molecular characteristics. We also found that the distribution of cell subpopulations varied considerably across onset stages among patients, providing a fundamental basis for patient-oriented precision evaluation. Moreover, single-sample gene set enrichment analysis revealed that subsets of CD8+ T cells with significantly different cell adhesion levels could be associated with different patterns of tumor cell dissemination. Therefore, our findings linked the conventional prognostic gene signature to the immune microenvironment and cellular heterogeneity at the single-cell level, thus providing deeper insights into the understanding of HCC tumorigenesis.

An immunomodulatory polypeptide hydrogel for osteochondral defect repair.

Osteochondral injury is a common and frequent orthopedic disease that can lead to more serious degenerative joint disease. Tissue engineering is a promising modality for osteochondral repair, but the implanted scaffolds are often immunogenic and can induce unwanted foreign body reaction (FBR). Here, we prepare a polypept(o)ide-based PAA-RGD hydrogel using a novel thiol/thioester dual-functionalized hyperbranched polypeptide P(EG3Glu-co-Cys) and maleimide-functionalized polysarcosine under biologically benign conditions. The PAA-RGD hydrogel shows suitable biodegradability, excellent biocompatibility, and low immunogenicity, which together lead to optimal performance for osteochondral repair in New Zealand white rabbits even at the early stage of implantation. Further in vitro and in vivo mechanistic studies corroborate the immunomodulatory role of the PAA-RGD hydrogel, which induces minimum FBR responses and a high level of polarization of macrophages into the immunosuppressive M2 subtypes. These findings demonstrate the promising potential of the PAA-RGD hydrogel for osteochondral regeneration and highlight the importance of immunomodulation. The results may inspire the development of PAA-based materials for not only osteochondral defect repair but also various other tissue engineering and bio-implantation applications.

Annotation and evaluation of base editing outcomes in multiple cell types using CRISPRbase.

CRISPR-Cas base editing (BE) system is a powerful tool to expand the scope and efficiency of genome editing with single-nucleotide resolution. The editing efficiency, product purity, and off-target effect differ among various BE systems. Herein, we developed CRISPRbase (http://crisprbase.maolab.org), by integrating 1 252 935 records of base editing outcomes in more than 50 cell types from 17 species. CRISPRbase helps to evaluate the putative editing precision of different BE systems by integrating multiple annotations, functional predictions and a blasting system for single-guide RNA sequences. We systematically assessed the editing window, editing efficiency and product purity of various BE systems. Intensive efforts were focused on increasing the editing efficiency and product purity of base editors since the byproduct could be detrimental in certain applications. Remarkably, more than half of cancer-related off-target mutations were non-synonymous and extremely damaging to protein functions in most common tumor types. Luckily, most of these cancer-related mutations were passenger mutations (4840/5703, 84.87%) rather than cancer driver mutations (863/5703, 15.13%), indicating a weak effect of off-target mutations on carcinogenesis. In summary, CRISPRbase is a powerful and convenient tool to study the outcomes of different base editors and help researchers choose appropriate BE designs for functional studies.

Genetic association and single-cell transcriptome analyses reveal distinct features connecting autoimmunity with cancers.

Autoimmune diseases (ADs) are at a significantly higher risk of cancers with unclear mechanism. By searching GWAS catalog database and Medline, susceptible genes for five common ADs, including systemic lupus erythematosus (SLE), rheumatoid arthritis, Sjögren syndrome, systemic sclerosis, and idiopathic inflammatory myopathies, were collected and then were overlapped with cancer driver genes. Single-cell transcriptome analysis was performed in the comparation between SLE and related cancer. We identified 45 carcinogenic autoimmune disease risk (CAD) genes, which were mainly enriched in T cell signaling pathway and B cell signaling pathway. Integrated single-cell analysis revealed immune cell signaling was significantly downregulated in renal cancer compared with SLE, while stemness signature was significantly enriched in both renal cancer or lymphoma and SLE in specific subpopulations. Drugs targeting CAD genes were shared between ADs and cancer. Our study highlights the common and specific features between ADs and related cancers, and sheds light on a new discovery of treatments.

Comprehensive evaluation of computational methods for predicting cancer driver genes.

Optimal methods could effectively improve the accuracy of predicting and identifying candidate driver genes. Various computational methods based on mutational frequency, network and function approaches have been developed to identify mutation driver genes in cancer genomes. However, a comprehensive evaluation of the performance levels of network-, function- and frequency-based methods is lacking. In the present study, we assessed and compared eight performance criteria for eight network-based, one function-based and three frequency-based algorithms using eight benchmark datasets. Under different conditions, the performance of approaches varied in terms of network, measurement and sample size. The frequency-based driverMAPS and network-based HotNet2 methods showed the best overall performance. Network-based algorithms using protein-protein interaction networks outperformed the function- and the frequency-based approaches. Precision, F1 score and Matthews correlation coefficient were low for most approaches. Thus, most of these algorithms require stringent cutoffs to correctly distinguish driver and non-driver genes. We constructed a website named Cancer Driver Catalog (http://159.226.67.237/sun/cancer_driver/), wherein we integrated the gene scores predicted by the foregoing software programs. This resource provides valuable guidance for cancer researchers and clinical oncologists prioritizing cancer driver gene candidates by using an optimal tool.

CircleBase: an integrated resource and analysis platform for human eccDNAs.

Rapid advances in high-throughput sequencing technologies have led to the discovery of thousands of extrachromosomal circular DNAs (eccDNAs) in the human genome. Loss-of-function experiments are difficult to conduct on circular and linear chromosomes, as they usually overlap. Hence, it is challenging to interpret the molecular functions of eccDNAs. Here, we present CircleBase (http://circlebase.maolab.org), an integrated resource and analysis platform used to curate and interpret eccDNAs in multiple cell types. CircleBase identifies putative functional eccDNAs by incorporating sequencing datasets, computational predictions, and manual annotations. It classifies them into six sections including targeting genes, epigenetic regulations, regulatory elements, chromatin accessibility, chromatin interactions, and genetic variants. The eccDNA targeting and regulatory networks are displayed by informative visualization tools and then prioritized. Functional enrichment analyses revealed that the top-ranked cancer cell eccDNAs were enriched in oncogenic pathways such as the Ras and PI3K-Akt signaling pathways. In contrast, eccDNAs from healthy individuals were not significantly enriched. CircleBase provides a user-friendly interface for searching, browsing, and analyzing eccDNAs in various cell/tissue types. Thus, it is useful to screen for potential functional eccDNAs and interpret their molecular mechanisms in human cancers and other diseases.

p53 inactivation unmasks histone methylation-independent WDR5 functions that drive self-renewal and differentiation of pluripotent stem cells.

p53 alterations occur during culture of pluripotent stem cells (PSCs), but the significance of these events on epigenetic control of PSC fate determination remains poorly understood. Wdr5 deletion in p53-null (DKO) mouse ESCs (mESCs) leads to impaired self-renewal, defective retinal neuroectoderm differentiation, and de-repression of germ cell/meiosis (GCM)-specific genes. Re-introduction of a WDR5 mutant with defective H3K4 methylation activity into DKO ESCs restored self-renewal and suppressed GCM gene expression but failed to induce retinal neuroectoderm differentiation. Mechanistically, mutant WDR5 targets chromatin that is largely devoid of H3K4me3 and regulates gene expression in p53-null mESCs. Furthermore, MAX and WDR5 co-target lineage-specifying chromatin and regulate chromatin accessibility of GCM-related genes. Importantly, MAX and WDR5 are core subunits of a non-canonical polycomb repressor complex 1 responsible for gene silencing. This function, together with canonical, pro-transcriptional WDR5-dependent MLL complex H3K4 methyltransferase activity, highlight how WDR5 mediates crosstalk between transcription and repression during mESC fate choice.

Mechanism for DPY30 and ASH2L intrinsically disordered regions to modulate the MLL/SET1 activity on chromatin.

Recent cryo-EM structures show the highly dynamic nature of the MLL1-NCP (nucleosome core particle) interaction. Functional implication and regulation of such dynamics remain unclear. Here we show that DPY30 and the intrinsically disordered regions (IDRs) of ASH2L work together in restricting the rotational dynamics of the MLL1 complex on the NCP. We show that DPY30 binding to ASH2L leads to stabilization and integration of ASH2L IDRs into the MLL1 complex and establishes new ASH2L-NCP contacts. The significance of ASH2L-DPY30 interactions is demonstrated by requirement of both ASH2L IDRs and DPY30 for dramatic increase of processivity and activity of the MLL1 complex. This DPY30 and ASH2L-IDR dependent regulation is NCP-specific and applies to all members of the MLL/SET1 family of enzymes. We further show that DPY30 is causal for de novo establishment of H3K4me3 in ESCs. Our study provides a paradigm of how H3K4me3 is regulated on chromatin and how H3K4me3 heterogeneity can be modulated by ASH2L IDR interacting proteins.

Discovery of first-in-class inhibitors of ASH1L histone methyltransferase with anti-leukemic activity.

ASH1L histone methyltransferase plays a crucial role in the pathogenesis of different diseases, including acute leukemia. While ASH1L represents an attractive drug target, developing ASH1L inhibitors is challenging, as the catalytic SET domain adapts an inactive conformation with autoinhibitory loop blocking the access to the active site. Here, by applying fragment-based screening followed by medicinal chemistry and a structure-based design, we developed first-in-class small molecule inhibitors of the ASH1L SET domain. The crystal structures of ASH1L-inhibitor complexes reveal compound binding to the autoinhibitory loop region in the SET domain. When tested in MLL leukemia models, our lead compound, AS-99, blocks cell proliferation, induces apoptosis and differentiation, downregulates MLL fusion target genes, and reduces the leukemia burden in vivo. This work validates the ASH1L SET domain as a druggable target and provides a chemical probe to further study the biological functions of ASH1L as well as to develop therapeutic agents.

OncoVar: an integrated database and analysis platform for oncogenic driver variants in cancers.

The prevalence of neutral mutations in cancer cell population impedes the distinguishing of cancer-causing driver mutations from passenger mutations. To systematically prioritize the oncogenic ability of somatic mutations and cancer genes, we constructed a useful platform, OncoVar (https://oncovar.org/), which employed published bioinformatics algorithms and incorporated known driver events to identify driver mutations and driver genes. We identified 20 162 cancer driver mutations, 814 driver genes and 2360 pathogenic pathways with high-confidence by reanalyzing 10 769 exomes from 33 cancer types in The Cancer Genome Atlas (TCGA) and 1942 genomes from 18 cancer types in International Cancer Genome Consortium (ICGC). OncoVar provides four points of view, 'Mutation', 'Gene', 'Pathway' and 'Cancer', to help researchers to visualize the relationships between cancers and driver variants. Importantly, identification of actionable driver alterations provides promising druggable targets and repurposing opportunities of combinational therapies. OncoVar provides a user-friendly interface for browsing, searching and downloading somatic driver mutations, driver genes and pathogenic pathways in various cancer types. This platform will facilitate the identification of cancer drivers across individual cancer cohorts and helps to rank mutations or genes for better decision-making among clinical oncologists, cancer researchers and the broad scientific community interested in cancer precision medicine.

ER-associated degradation preserves hematopoietic stem cell quiescence and self-renewal by restricting mTOR activity.

Hematopoietic stem cells (HSC) self-renew to sustain stem cell pools and differentiate to generate all types of blood cells. HSCs remain in quiescence to sustain their long-term self-renewal potential. It remains unclear whether protein quality control is required for stem cells in quiescence when RNA content, protein synthesis, and metabolic activities are profoundly reduced. Here, we report that protein quality control via endoplasmic reticulum-associated degradation (ERAD) governs the function of quiescent HSCs. The Sel1L/Hrd1 ERAD genes are enriched in the quiescent and inactive HSCs, and conditional knockout of Sel1L in hematopoietic tissues drives HSCs to hyperproliferation, which leads to complete loss of HSC self-renewal and HSC depletion. Mechanistically, ERAD deficiency via Sel1L knockout leads to activation of mammalian target of rapamycin (mTOR) signaling. Furthermore, we identify Ras homolog enriched in brain (Rheb), an activator of mTOR, as a novel protein substrate of Sel1L/Hrd1 ERAD, which accumulates upon Sel1L deletion and HSC activation. Importantly, inhibition of mTOR, or Rheb, rescues HSC defects in Sel1L knockout mice. Protein quality control via ERAD is, therefore, a critical checkpoint that governs HSC quiescence and self-renewal by Rheb-mediated restriction of mTOR activity.

p53 Integrates Temporal WDR5 Inputs during Neuroectoderm and Mesoderm Differentiation of Mouse Embryonic Stem Cells.

How ubiquitous transcription factors (TFs) coordinate temporal inputs from broadly expressed epigenetic factors to control cell fate remains poorly understood. Here, we uncover a molecular relationship between p53, an abundant embryonic TF, and WDR5, an essential member of the MLL chromatin modifying complex, that regulates mouse embryonic stem cell fate. Wild-type Wdr5 or transient Wdr5 knockout promotes a distinct pattern of global chromatin accessibility and spurs neuroectodermal differentiation through an RbBP5-dependent process in which WDR5 binds to, and activates transcription of, neural genes. Wdr5 rescue after its prolonged inhibition targets WDR5 to mesoderm lineage-specifying genes, stimulating differentiation toward mesoderm fates in a p53-dependent fashion. Finally, we identify a direct interaction between WDR5 and p53 that enables their co-recruitment to, and regulation of, genes known to control cell proliferation and fate. Our results unmask p53-dependent mechanisms that temporally integrate epigenetic WDR5 inputs to drive neuroectoderm and mesoderm differentiation from pluripotent cells.

Prevalence and architecture of posttranscriptionally impaired synonymous mutations in 8,320 genomes across 22 cancer types.

Somatic synonymous mutations are one of the most frequent genetic variants occurring in the coding region of cancer genomes, while their contributions to cancer development remain largely unknown. To assess whether synonymous mutations involved in post-transcriptional regulation contribute to the genetic etiology of cancers, we collected whole exome data from 8,320 patients across 22 cancer types. By employing our developed algorithm, PIVar, we identified a total of 22,948 posttranscriptionally impaired synonymous SNVs (pisSNVs) spanning 2,042 genes. In addition, 35 RNA binding proteins impacted by these identified pisSNVs were significantly enriched. Remarkably, we discovered markedly elevated ratio of somatic pisSNVs across all 22 cancer types, and a high pisSNV ratio was associated with worse patient survival in five cancer types. Intriguing, several well-established cancer genes, including PTEN, RB1 and PIK3CA, appeared to contribute to tumorigenesis at both protein function and posttranscriptional regulation levels, whereas some pisSNV-hosted genes, including UBR4, EP400 and INTS1, exerted their function during carcinogenesis mainly via posttranscriptional mechanisms. Moreover, we predicted three drugs associated with two pisSNVs, and numerous compounds associated with expression signature of pisSNV-hosted genes. Our study reveals the prevalence and clinical relevance of pisSNVs in cancers, and emphasizes the importance of considering posttranscriptional impaired synonymous mutations in cancer biology.

AI-Driver: an ensemble method for identifying driver mutations in personal cancer genomes.

The current challenge in cancer research is to increase the resolution of driver prediction from gene-level to mutation-level, which is more closely aligned with the goal of precision cancer medicine. Improved methods to distinguish drivers from passengers are urgently needed to dig out driver mutations from increasing exome sequencing studies. Here, we developed an ensemble method, AI-Driver (AI-based driver classifier, https://github.com/hatchetProject/AI-Driver), to predict the driver status of somatic missense mutations based on 23 pathogenicity features. AI-Driver has the best overall performance compared with any individual tool and two cancer-specific driver predicting methods. We demonstrate the superior and stable performance of our model using four independent benchmarks. We provide pre-computed AI-Driver scores for all possible human missense variants (http://aidriver.maolab.org/) to identify driver mutations in the sea of somatic mutations discovered by personal cancer sequencing. We believe that AI-Driver together with pre-computed database will play vital important roles in the human cancer studies, such as identification of driver mutation in personal cancer genomes, discovery of targeting sites for cancer therapeutic treatments and prediction of tumor biomarkers for early diagnosis by liquid biopsy.

MLL1 Inhibition and Vitamin D Signaling Cooperate to Facilitate the Expanded Pluripotency State.

Dynamic establishment of histone modifications in early development coincides with programed cell fate restriction and loss of totipotency beyond the early blastocyst stage. Causal function of histone-modifying enzymes in this process remains to be defined. Here we show that inhibiting histone methyltransferase MLL1 reprograms naive embryonic stem cells (ESCs) to expanded pluripotent stem cells (EPSCs), with differentiation potential toward both embryonic and extraembryonic lineages in vitro and in vivo. MLL1 inhibition or deletion upregulates gene signatures of early blastomere development. The function of MLL1 in restricting induction of EPSCs is mediated partly by Gc, which regulates cellular response to vitamin D signaling. Combined treatment of MLL1 inhibitor and 1α,25-dihydroxyvitamin D3 (1,25-(OH)2D3) cooperatively enhanced functionality of EPSCs, triggering an extended 2C-like state in vitro and robust totipotent-like property in vivo. Our study sheds light on interplay between epigenetics and vitamin D pathway in cell fate determination.

OncoBase: a platform for decoding regulatory somatic mutations in human cancers.

Whole-exome and whole-genome sequencing have revealed millions of somatic mutations associated with different human cancers, and the vast majority of them are located outside of coding sequences, making it challenging to directly interpret their functional effects. With the rapid advances in high-throughput sequencing technologies, genome-scale long-range chromatin interactions were detected, and distal target genes of regulatory elements were determined using three-dimensional (3D) chromatin looping. Herein, we present OncoBase (http://www.oncobase.biols.ac.cn/), an integrated database for annotating 81 385 242 somatic mutations in 68 cancer types from more than 120 cancer projects by exploring their roles in distal interactions between target genes and regulatory elements. OncoBase integrates local chromatin signatures, 3D chromatin interactions in different cell types and reconstruction of enhancer-target networks using state-of-the-art algorithms. It employs informative visualization tools to display the integrated local and 3D chromatin signatures and effects of somatic mutations on regulatory elements. Enhancer-promoter interactions estimated from chromatin interactions are integrated into a network diffusion system that quantitatively prioritizes somatic mutations and target genes from a large pool. Thus, OncoBase is a useful resource for the functional annotation of regulatory noncoding regions and systematically benchmarking the regulatory effects of embedded noncoding somatic mutations in human carcinogenesis.