Alternative splicing of a chromatin modifier alters the transcriptional regulatory programs of stem cell maintenance and neuronal differentiation.

Development of embryonic stem cells (ESCs) into neurons requires intricate regulation of transcription, splicing, and translation, but how these processes interconnect is not understood. We found that polypyrimidine tract binding protein 1 (PTBP1) controls splicing of DPF2, a subunit of BRG1/BRM-associated factor (BAF) chromatin remodeling complexes. Dpf2 exon 7 splicing is inhibited by PTBP1 to produce the DPF2-S isoform early in development. During neuronal differentiation, loss of PTBP1 allows exon 7 inclusion and DPF2-L expression. Different cellular phenotypes and gene expression programs were induced by these alternative DPF2 isoforms. We identified chromatin binding sites enriched for each DPF2 isoform, as well as sites bound by both. In ESC, DPF2-S preferential sites were bound by pluripotency factors. In neuronal progenitors, DPF2-S sites were bound by nuclear factor I (NFI), while DPF2-L sites were bound by CCCTC-binding factor (CTCF). DPF2-S sites exhibited enhancer modifications, while DPF2-L sites showed promoter modifications. Thus, alternative splicing redirects BAF complex targeting to impact chromatin organization during neuronal development.

Evaluation of the efficacy and safety of immunotherapy in sarcoma: a two-center study.

Background: Sarcoma is a highly heterogeneous malignancy with a poor prognosis. Although chemotherapy and targeted therapy have improved the prognosis to some extent, the efficacy remains unsatisfactory in some patients. The efficacy and safety of immunotherapy in sarcoma need further evaluation. Methods: We conducted a two-center study of sarcoma patients receiving PD-1 immunotherapy at Tianjin Medical University Cancer Institute and Hospital and Henan Provincial Cancer Hospital. The treatment regimens included PD-1 inhibitor monotherapy and combination therapy based on PD-1 inhibitors. The observed primary endpoints were median progression-free survival (mPFS) and median overall survival (mOS). Survival curves were compared using the Kaplan-Meier method. Results: A total of 43 patients were included from the two centers. The median follow-up time for all patients was 13 months (range, 1-48 months). In the group of 37 patients with advanced or unresectable sarcoma, the mPFS was 6 months (95%CI: 5-12 months), and the mOS was 16 months (95%CI: 10-28 months). The ORR was 10.8% (4/37), and the DCR was 18.9% (7/37). Subgroup analysis showed no significant differences in mPFS (p=0.11) and mOS (p=0.88) between patients with PD-L1 negative/positive expression. There were also no significant differences in mPFS (p=0.13) or mOS (p=0.72) between PD-1 inhibitor monotherapy and combination therapy. Additionally, there were no significant differences in mPFS (p=0.52) or mOS (p=0.49) between osteogenic sarcoma and soft tissue sarcoma. Furthermore, the results showed no significant differences in mPFS (p=0.66) or mOS (p=0.96) between PD-1 inhibitors combined with targeted therapy and PD-1 inhibitors combined with AI chemotherapy. Among the 6 patients receiving adjuvant therapy after surgery, the mPFS was 15 months (95%CI: 6-NA months), and the mOS was not reached. In terms of safety, most adverse events were mild (grade 1-2) and manageable. The most severe grade 4 adverse events were bone marrow suppression, which occurred in 4 patients but resolved after treatment. There was also one case of a grade 4 adverse event related to hypertension. Conclusion: Immunotherapy is an effective treatment modality for sarcoma with manageable safety. Further inclusion of more patients or prospective clinical trials is needed to validate these findings.

An interpretable model predicts visual outcomes of no light perception eyes after open globe injury.

BACKGROUND: The visual outcome of open globe injury (OGI)-no light perception (NLP) eyes is unpredictable traditionally. This study aimed to develop a model to predict the visual outcomes of vitrectomy surgery in OGI-NLP eyes using a machine learning algorithm and to provide an interpretable system for the prediction results. METHODS: Clinical data of 459 OGI-NLP eyes were retrospectively collected from 19 medical centres across China to establish a training data set for developing a model, called 'VisionGo', which can predict the visual outcome of the patients involved and compare with the Ocular Trauma Score (OTS). Another 72 cases were retrospectively collected and used for human-machine comparison, and an additional 27 cases were prospectively collected for real-world validation of the model. The SHapley Additive exPlanations method was applied to analyse feature contribution to the model. An online platform was built for real-world application. RESULTS: The area under the receiver operating characteristic curve (AUC) of VisionGo was 0.75 and 0.90 in previtrectomy and intravitrectomy application scenarios, which was much higher than the OTS (AUC=0.49). VisionGo showed better performance than ophthalmologists in both previtrectomy and intravitrectomy application scenarios (AUC=0.73 vs 0.57 and 0.87 vs 0.64). In real-world validation, VisionGo achieved an AUC of 0.60 and 0.91 in previtrectomy and intravitrectomy application scenarios. Feature contribution analysis indicated that wound length-related indicators, vitreous status and retina-related indicators contributed highly to visual outcomes. CONCLUSIONS: VisionGo has achieved an accurate and reliable prediction in visual outcome after vitrectomy for OGI-NLP eyes.

Landscape of enhancer disruption and functional screen in melanoma cells.

BACKGROUND: The high mutation rate throughout the entire melanoma genome presents a major challenge in stratifying true driver events from the background mutations. Numerous recurrent non-coding alterations, such as those in enhancers, can shape tumor evolution, thereby emphasizing the importance in systematically deciphering enhancer disruptions in melanoma. RESULTS: Here, we leveraged 297 melanoma whole-genome sequencing samples to prioritize highly recurrent regions. By performing a genome-scale CRISPR interference (CRISPRi) screen on highly recurrent region-associated enhancers in melanoma cells, we identified 66 significant hits which could have tumor-suppressive roles. These functional enhancers show unique mutational patterns independent of classical significantly mutated genes in melanoma. Target gene analysis for the essential enhancers reveal many known and hidden mechanisms underlying melanoma growth. Utilizing extensive functional validation experiments, we demonstrate that a super enhancer element could modulate melanoma cell proliferation by targeting MEF2A, and another distal enhancer is able to sustain PTEN tumor-suppressive potential via long-range interactions. CONCLUSIONS: Our study establishes a catalogue of crucial enhancers and their target genes in melanoma growth and progression, and illuminates the identification of novel mechanisms of dysregulation for melanoma driver genes and new therapeutic targeting strategies.

Noncoding SNP at rs1663689 represses ADGRG6 via interchromosomal interaction and reduces lung cancer progression.

A previous genome-wide association study (GWAS) revealed an association of the noncoding SNP rs1663689 with susceptibility to lung cancer in the Chinese population. However, the underlying mechanism is unknown. In this study, using allele-specific 4C-seq in heterozygous lung cancer cells combined with epigenetic information from CRISPR/Cas9-edited cell lines, we show that the rs1663689 C/C variant represses the expression of ADGRG6, a gene located on a separate chromosome, through an interchromosomal interaction of the rs1663689 bearing region with the ADGRG6 promoter. This reduces downstream cAMP-PKA signaling and subsequently tumor growth both in vitro and in xenograft models. Using patient-derived organoids, we show that rs1663689 T/T-but not C/C-bearing lung tumors are sensitive to the PKA inhibitor H89, potentially informing therapeutic strategies. Our study identifies a genetic variant-mediated interchromosomal interaction underlying ADGRG6 regulation and suggests that targeting the cAMP-PKA signaling pathway may be beneficial in lung cancer patients bearing the homozygous risk genotype at rs1663689.

Systematic fine-mapping and functional studies of prostate cancer risk variants.

To date, genome-wide association studies (GWAS) have revealed over 200 genetic risk loci associated with prostate cancer; yet, true disease-causing variants remain elusive. Identification of causal variants and their targets from association signals is complicated by high linkage disequilibrium and limited availability of functional genomics data for specific tissue/cell types. Here, we integrated statistical fine-mapping and functional annotation from prostate-specific epigenomic profiles, 3D genome features, and quantitative trait loci data to distinguish causal variants from associations and identify target genes. Our fine-mapping analysis yielded 3,395 likely causal variants, and multiscale functional annotation linked them to 487 target genes. We prioritized rs10486567 as a genome-wide top-ranked SNP and predicted HOTTIP as its target. Deletion of the rs10486567-associated enhancer in prostate cancer cells decreased their capacity for invasive migration. HOTTIP overexpression in enhancer-KO cell lines rescued defective invasive migration. Furthermore, we found that rs10486567 regulates HOTTIP through allele-specific long-range chromatin interaction.

eaQTLdb: An atlas of enhancer activity quantitative trait loci across cancer types.

Enhancers are key regulatory elements that exert crucial roles in diverse biological processes, including tumorigenesis and cancer development. Active enhancers could produce transcripts termed enhancer RNAs (eRNAs), which could be used as an index of enhancer activity. Here, we present a versatile data portal, enhancer activity quantitative trait loci database (eaQTLdb; http://www.bioailab.com:3838/eaQTLdb), for exploring the effects of genetic variants on enhancer activity and prioritizing candidate variants across different cancer types. By leveraging the accumulated multiomics data, we systematically identified genetic variants which influence enhancer activity in different cancer types, termed as eaQTLs. We have linked the eaQTLs to hallmarks of cancer and patients' overall survival to illustrate their potential biological roles in cancer development and progression. Notably, eaQTLs associated with the infiltration abundance of 24 different immune cell types were identified and incorporated into eaQTLdb. In addition, we applied colocalization analyses to examine 59 complex diseases and traits to identify eaQTLs colocalized with diseases/traits GWAS signals. Overall, eaQTLdb, incorporating a rich resource for exploration of eaQTLs in different cancer types, will not only benefit users in prioritizing candidate genetic variants and enhancers, but also help researchers decipher the roles of eaQTLs in the dysregulated pathways of cancer and tumor immune microenvironment, opening new diagnostic and therapeutic avenues in precise medicine.

Retrograde regulation of mitochondrial fission and epithelial to mesenchymal transition in hepatocellular carcinoma by GCN5L1.

Metabolic reprogram is crucial to support cancer cell growth and movement as well as determine cell fate. Mitochondrial protein acetylation regulates mitochondrial metabolism, which is relevant to cancer cell migration and invasion. The functional role of mitochondrial protein acetylation on cancer cell migration remains unclear. General control of amino acid synthesis 5 like-1(GCN5L1), as the regulator of mitochondrial protein acetylation, functions on metabolic reprogramming in mouse livers. In this study, we find that GCN5L1 expression is significantly decreased in metastatic HCC tissues. Loss of GCN5L1 promotes reactive oxygen species (ROS) generation through enhanced fatty acid oxidation (FAO), followed by activation of cellular ERK and DRP1 to promote mitochondrial fission and epithelia to mesenchymal transition (EMT) to boost cell migration. Moreover, palmitate and carnitine-stimulated FAO promotes mitochondrial fission and EMT gene expression to activate HCC cell migration. On the other hand, increased cellular acetyl-CoA level, the product of FAO, enhances HCC cell migration. Taken together, our finding uncovers the metastasis suppressor role as well as the underlying mechanism of GCN5L1 in HCC and also provides evidence of FAO retrograde control of HCC metastasis.

CD73, a Promising Therapeutic Target of Diclofenac, Promotes Metastasis of Pancreatic Cancer through a Nucleotidase Independent Mechanism.

CD73, a cell surface-bound nucleotidase, facilitates extracellular adenosine formation by hydrolyzing 5'-AMP to adenosine. Several studies have shown that CD73 plays an essential role in immune escape, cell proliferation and tumor angiogenesis, making it an attractive target for cancer therapies. However, there are limited clinical benefits associated with the mainstream enzymatic inhibitors of CD73, suggesting that the mechanism underlying the role of CD73 in tumor progression is more complex than anticipated, and further investigation is necessary. In this study, CD73 is found to overexpress in the cytoplasm of pancreatic ductal adenocarcinoma (PDAC) cells and promotes metastasis in a nucleotidase-independent manner, which cannot be restrained by the CD73 monoclonal antibodies or small-molecule enzymatic inhibitors. Furthermore, CD73 promotes the metastasis of PDAC by binding to the E3 ligase TRIM21, competing with the Snail for its binding site. Additionally, a CD73 transcriptional inhibitor, diclofenac, a non-steroidal anti-inflammatory drug, is more effective than the CD73 blocking antibody for the treatment of PDAC metastasis. Diclofenac also enhances the therapeutic efficacy of gemcitabine in the spontaneous KPC (LSL-KrasG12D/+ , LSL-Trp53R172H/+ , and Pdx-1-Cre) pancreatic cancer model. Therefore, diclofenac may be an effective anti-CD73 therapy, when used alone or in combination with gemcitabine-based chemotherapy regimen, for metastatic PDAC.

ABO blood groups and expression of blood group antigens of epithelial ovarian cancer in Chinese women.

BACKGROUND: ABO blood groups has been associated with risk of several cancers; however, the results for an association with ovarian cancer are inconsistent and little is known about the expression of histo-blood group (ABH) antigens and ABO gene in ovarian tumor tissues. METHODS: To assess the impact of genotype-derived ABO blood types on the risk of EOC, we conducted a case-control study in 1,870 EOC and 4,829 controls. Expression of A and B antigen in 70 pairs of ovarian tumor tissues and adjacent normal tissues were detected by immunohistochemistry. Gene expression and DNA methylation profiling was conducted in ovarian tumor tissues. RESULTS: We identified that blood group A was associated with increased risk for EOC compared to blood group O (OR = 1.18, 95% CI = 1.03-1.36, p = 0.019). Increased frequency of aberrant expression of histo-blood group antigens was observed in patients with blood group A (76.5%) compared to patients with blood group O (21.1%) and B (5.0%) by immunohistochemistry (p < 0.001). ABO gene expression was down-regulated in ovarian tumor tissues compared with paired adjacent normal tissues (p = 0.027). In addition, ABO gene expression was positively correlated with NFYB (r = 0.38, p < 0.001) and inversely correlated with DNA methylation level of four CpG sites on ABO gene (cg11879188, r = - 0.3, p = 0.002; cg22535403, r = - 0.30, p = 0.002; cg13506600, r = - 0.22, p = 0.025; cg07241568, r = - 0.21, p = 0.049) in ovarian tumor tissues. CONCLUSION: We identified blood group A was associated with increased EOC risk in Chinese women and provided the clues of the possible molecular mechanisms of blood group A related to ovarian cancer risk.

Minimally Invasive Preclinical Monitoring of the Peritoneal Cavity Tumor Microenvironment.

Intraperitoneal (i.p.) experimental models in mice can recapitulate the process of i.p. dissemination in abdominal cancers and may help uncover critical information about future successful clinical treatments. i.p. cellular composition is studied in preclinical models addressing a wide spectrum of other pathophysiological states such as liver cirrhosis, infectious disease, autoimmunity, and aging. The peritoneal cavity is a multifaceted microenvironment that contains various immune cell populations, including T, B, NK, and various myeloid cells, such as macrophages. Analysis of the peritoneal cavity is often obtained by euthanizing mice and performing terminal peritoneal lavage. This procedure inhibits continuous monitoring of the peritoneal cavity in a single mouse and necessitates the usage of more mice to assess the cavity at multiple timepoints, increasing the cost, time, and variability of i.p. studies. Here, we present a simple, novel method termed in vivo intraperitoneal lavage (IVIPL) for the minimally invasive monitoring of cells in the peritoneal cavity of mice. In this proof-of-concept, IVIPL provided real-time insights into the i.p. tumor microenvironment for the development and study of ovarian cancer therapies. Specifically, we studied CAR-T cell therapy in a human high-grade serous ovarian cancer (HGSOC) xenograft mouse model, and we studied the immune composition of the i.p. tumor microenvironment (TME) in a mouse HGSOC syngeneic model.

Genome-wide association and functional interrogation identified a variant at 3p26.1 modulating ovarian cancer survival among Chinese women.

Ovarian cancer survival varies considerably among patients, to which germline variation may also contribute in addition to mutational signatures. To identify genetic markers modulating ovarian cancer outcome, we performed a genome-wide association study in 2130 Chinese ovarian cancer patients and found a hitherto unrecognized locus at 3p26.1 to be associated with the overall survival (Pcombined = 8.90 × 10-10). Subsequent statistical fine-mapping, functional annotation, and eQTL mapping prioritized a likely casual SNP rs9311399 in the non-coding regulatory region. Mechanistically, rs9311399 altered its enhancer activity through an allele-specific transcription factor binding and a long-range interaction with the promoter of a lncRNA BHLHE40-AS1. Deletion of the rs9311399-associated enhancer resulted in expression changes in several oncogenic signaling pathway genes and a decrease in tumor growth. Thus, we have identified a novel genetic locus that is associated with ovarian cancer survival possibly through a long-range gene regulation of oncogenic pathways.

Serine metabolism antagonizes antiviral innate immunity by preventing ATP6V0d2-mediated YAP lysosomal degradation.

Serine metabolism promotes tumor oncogenesis and regulates immune cell functions, but whether it also contributes to antiviral innate immunity is unknown. Here, we demonstrate that virus-infected macrophages display decreased expression of serine synthesis pathway (SSP) enzymes. Suppressing the SSP key enzyme phosphoglycerate dehydrogenase (PHGDH) by genetic approaches or by treatment with the pharmaceutical inhibitor CBR-5884 and by exogenous serine restriction enhanced IFN-ß-mediated antiviral innate immunity in vitro and in vivo. Mechanistic experiments showed that virus infection or serine metabolism deficiency increased the expression of the V-ATPase subunit ATP6V0d2 by inhibiting S-adenosyl methionine-dependent H3K27me3 occupancy at the promoter. ATP6V0d2 promoted YAP lysosomal degradation to relieve YAP-mediated blockade of the TBK1-IRF3 axis and, thus, enhance IFN-ß production. These findings implicate critical functions of PHGDH and the key immunometabolite serine in blunting antiviral innate immunity and also suggest manipulation of serine metabolism as a therapeutic strategy against virus infection.

Ultrafast and scalable variant annotation and prioritization with big functional genomics data.

The advances of large-scale genomics studies have enabled compilation of cell type-specific, genome-wide DNA functional elements at high resolution. With the growing volume of functional annotation data and sequencing variants, existing variant annotation algorithms lack the efficiency and scalability to process big genomic data, particularly when annotating whole-genome sequencing variants against a huge database with billions of genomic features. Here, we develop VarNote to rapidly annotate genome-scale variants in large and complex functional annotation resources. Equipped with a novel index system and a parallel random-sweep searching algorithm, VarNote shows substantial performance improvements (two to three orders of magnitude) over existing algorithms at different scales. It supports both region-based and allele-specific annotations and introduces advanced functions for the flexible extraction of annotations. By integrating massive base-wise and context-dependent annotations in the VarNote framework, we introduce three efficient and accurate pipelines to prioritize the causal regulatory variants for common diseases, Mendelian disorders, and cancers.

The support of genetic evidence for cardiovascular risk induced by antineoplastic drugs.

Cardiovascular dysfunction is one of the most common complications of long-term cancer treatment. Growing evidence has shown that antineoplastic drugs can increase cardiovascular risk during cancer therapy, seriously affecting patient survival. However, little is known about the genetic factors associated with the cardiovascular risk of antineoplastic drugs. We established a compendium of genetic evidence that supports cardiovascular risk induced by antineoplastic drugs. Most of this genetic evidence is attributed to causal alleles altering the expression of cardiovascular disease genes. We found that antineoplastic drugs predicted to induce cardiovascular risk are significantly enriched in drugs associated with cardiovascular adverse reactions, including many first-line cancer treatments. Functional experiments validated that retinoid X receptor agonists can reduce triglyceride lipolysis, thus modulating cardiovascular risk. Our results establish a link between the causal allele of cardiovascular disease genes and the direction of pharmacological modulation, which could facilitate cancer drug discovery and clinical trial design.

HRP2-DPF3a-BAF complex coordinates histone modification and chromatin remodeling to regulate myogenic gene transcription.

Functional crosstalk between histone modifications and chromatin remodeling has emerged as a key regulatory mode of transcriptional control during cell fate decisions, but the underlying mechanisms are not fully understood. Here we discover an HRP2-DPF3a-BAF epigenetic pathway that coordinates methylated histone H3 lysine 36 (H3K36me) and ATP-dependent chromatin remodeling to regulate chromatin dynamics and gene transcription during myogenic differentiation. Using siRNA screening targeting epigenetic modifiers, we identify hepatoma-derived growth factor-related protein 2 (HRP2) as a key regulator of myogenesis. Knockout of HRP2 in mice leads to impaired muscle regeneration. Mechanistically, through its HIV integrase binding domain (IBD), HRP2 associates with the BRG1/BRM-associated factor (BAF) chromatin remodeling complex by interacting directly with the BAF45c (DPF3a) subunit. Through its Pro-Trp-Trp-Pro (PWWP) domain, HRP2 preferentially binds to H3K36me2. Consistent with the biochemical studies, ChIP-seq analyses show that HRP2 colocalizes with DPF3a across the genome and that the recruitment of HRP2/DPF3a to chromatin is dependent on H3K36me2. Integrative transcriptomic and cistromic analyses, coupled with ATAC-seq, reveal that HRP2 and DPF3a activate myogenic genes by increasing chromatin accessibility through recruitment of BRG1, the ATPase subunit of the BAF complex. Taken together, these results illuminate a key role for the HRP2-DPF3a-BAF complex in the epigenetic coordination of gene transcription during myogenic differentiation.

Diversity spectrum analysis identifies mutation-specific effects of cancer driver genes.

Mutation-specific effects of cancer driver genes influence drug responses and the success of clinical trials. We reasoned that these effects could unbalance the distribution of each mutation across different cancer types, as a result, the cancer preference can be used to distinguish the effects of the causal mutation. Here, we developed a network-based framework to systematically measure cancer diversity for each driver mutation. We found that half of the driver genes harbor cancer type-specific and pancancer mutations simultaneously, suggesting that the pervasive functional heterogeneity of the mutations from even the same driver gene. We further demonstrated that the specificity of the mutations could influence patient drug responses. Moreover, we observed that diversity was generally increased in advanced tumors. Finally, we scanned potentially novel cancer driver genes based on the diversity spectrum. Diversity spectrum analysis provides a new approach to define driver mutations and optimize off-label clinical trials.

JMJD6 modulates DNA damage response through downregulating H4K16ac independently of its enzymatic activity.

The initiation and transduction of DNA damage response (DDR) occur in the context of chromatin, and modifications as well as the structure of chromatin are crucial for DDR signaling. How the profound chromatin alterations are confined to DNA lesions by epigenetic factors remains largely unclear. Here, we discover that JMJD6, a Jumonji C domain-containing protein, is recruited to DNA double-strand breaks (DSBs) after microirradiation. JMJD6 controls the spreading of histone ubiquitination, as well as the subsequent accumulation of repair proteins and transcriptional silencing around DSBs, but does not regulate the initial DNA damage sensing. Furthermore, JMJD6 deficiency results in promotion of the efficiency of nonhomologous end joining (NHEJ) and homologous recombination (HR), rapid cell-cycle checkpoint recovery, and enhanced survival after irradiation. Regarding the mechanism involved, we demonstrate that JMJD6, independently of its catalytic activity, interacts with SIRT1 and recruits it to chromatin to downregulate H4K16ac around DSBs. Our study reveals JMJD6 as a modulator of the epigenome around DNA lesions, and adds to the understanding of the role of epigenetic factors in DNA damage response.

Methods and resources to access mutation-dependent effects on cancer drug treatment.

In clinical cancer treatment, genomic alterations would often affect the response of patients to anticancer drugs. Studies have shown that molecular features of tumors could be biomarkers predictive of sensitivity or resistance to anticancer agents, but the identification of actionable mutations are often constrained by the incomplete understanding of cancer genomes. Recent progresses of next-generation sequencing technology greatly facilitate the extensive molecular characterization of tumors and promote precision medicine in cancers. More and more clinical studies, cancer cell lines studies, CRISPR screening studies as well as patient-derived model studies were performed to identify potential actionable mutations predictive of drug response, which provide rich resources of molecularly and pharmacologically profiled cancer samples at different levels. Such abundance of data also enables the development of various computational models and algorithms to solve the problem of drug sensitivity prediction, biomarker identification and in silico drug prioritization by the integration of multiomics data. Here, we review the recent development of methods and resources that identifies mutation-dependent effects for cancer treatment in clinical studies, functional genomics studies and computational studies and discuss the remaining gaps and future directions in this area.

regBase: whole genome base-wise aggregation and functional prediction for human non-coding regulatory variants.

Predicting the functional or pathogenic regulatory variants in the human non-coding genome facilitates the interpretation of disease causation. While numerous prediction methods are available, their performance is inconsistent or restricted to specific tasks, which raises the demand of developing comprehensive integration for those methods. Here, we compile whole genome base-wise aggregations, regBase, that incorporate largest prediction scores. Building on different assumptions of causality, we train three composite models to score functional, pathogenic and cancer driver non-coding regulatory variants respectively. We demonstrate the superior and stable performance of our models using independent benchmarks and show great success to fine-map causal regulatory variants on specific locus or at base-wise resolution. We believe that regBase database together with three composite models will be useful in different areas of human genetic studies, such as annotation-based casual variant fine-mapping, pathogenic variant discovery as well as cancer driver mutation identification. regBase is freely available at https://github.com/mulinlab/regBase.