Wang, Liguo

Abstract Motivation Illumina DNA methylation arrays have evolved rapidly, expanding genomic coverage while introducing backward incompatibilities by removing many CpG sites present in earlier versions. These changes result in systematic missing values when integrating data across array generations and substantially limiting the reuse of legacy datasets. Results We developed a two-stage framework for imputing missing DNA methylation values. The procedure first imputes randomly missing values using standard imputation techniques and then addresses systematic missingness using multi-output machine learning models, including support vector regression, nearest-neighbor methods, random forest models, and deep neural networks. When evaluated on real datasets with up to fifty percent induced missingness, the proposed framework consistently outperformed conventional imputation approaches. It also accurately imputes the missing CpG sites between methylation arrays and reduced representation bisulfite sequencing data, enabling robust cross-platform data integration. Analyses of large brain tumor methylation datasets demonstrate that the method restores array-specific methylation patterns while preserving biological complexity. Importantly, imputing missing methylation sites significantly improves the performance of epigenetic age prediction models. Availability and implementation This tool is implemented in the Python package “ultra-impute,” freely available at https://github.com/liguowang/ultra-impute. A code snippet demonstrating the usage of the ultra-impute package is provided in a Jupyter Notebook (https://github.com/liguowang/ultra-impute/blob/master/doc/Tutorial.ipynb).

Immunotherapy has been effective in many cancer types but has failed in multiple clinical trials in prostate cancers, with the underlying mechanisms remaining largely unclear. Here, we demonstrate that androgen receptor pathway inhibitor (ARPI) plus irradiation (IR) triggered robust anticancer immunity in prostate cancers in both patients and mice. We show that androgen-activated AR suppressed innate immune signaling by inducing inhibitor of nuclear factor kappa-B kinase subunit epsilon ( IKBKE ) gene repression through HDAC2 interaction with an IKBKE enhancer RNA ( IKBKE eRNA, or IKBKE-e ). ARPI treatment caused IKBKE derepression and enhanced an IR-induced innate immune response via action of RIG-I and MDA5 dsRNA sensors. IKBKE-e ablation largely enhanced innate immunity in prostate cancer cells in culture and anticancer immunity in mice. Our results revealed AR, HDAC2, and IKBKE eRNA as critical intrinsic immune suppressors in prostate cancer cells, suggesting that rejuvenating inhibitor of nuclear factor kappa-B kinase subunit epsilon (IKKε) signaling by targeting IKBKE-e is an actionable strategy to elicit synthetic anticancer immunity in immunologically “cold” cancers such as prostate cancer.

Abstract CDK12 is frequently deleted and/or mutated in human cancers, and CDK12 inactivation is associated with aggressive phenotypes, including the tendency to metastasis. In this study, we showed that CDK12 deficiency induced intronic polyadenylation (IPA) usage in BRD4 to upregulate expression of the bromodomain-containing protein 4 (BRD4) short isoform (BRD4S). BRD4S demonstrated an enhanced capacity to form phase separation despite lacking the intrinsically disordered region located in the C-terminal of full-length BRD4. Oligomerization of BRD4S mediated phase separation through a base-interacting structural domain. CUT&Tag and RNA sequencing analyses revealed that BRD4S preferentially bound to the promoters of TGFβ signaling genes, including TGFB2 and LTBP1, driving their expression. Consistently, BRD4S drove cancer cell dissemination in vitro and metastasis in vivo, which could be blocked by BET or TGFβ signaling pathway inhibitors. Overall, this study identifies IPA usage at the BRD4 gene locus induced by CDK12 deficiency as a mechanism responsible for BRD4S genesis, which represents an important mechanism driving cancer metastasis and a potential target for therapeutic intervention in CDK12-deficient cancers. Significance: The CDK12–BRD4S–TGFβ signaling axis represents a key regulatory module that promotes metastatic progression and can be targeted by BET or TGFβ pathway inhibitors for treating CDK12-deficient cancers.

CDK12 primarily functions as a transcription regulatory cyclin-dependent kinase (CDK) that controls mRNA elongation, splicing, and polyadenylation. The CDK12 gene is implicated in human cancers since it is frequently mutated and/or deleted in prostate and ovarian cancer but paradoxically amplified in breast cancer. Here, we demonstrate that CDK12 promotes serine-933 phosphorylation of DNA2, a nuclease/helicase critical for replication fork stress regulation, and the phosphorylation subsequently facilitates DNA2 polyubiquitination and degradation mediated by the APC/C CDC20 E3 ubiquitin ligase. CDK12 inactivation induces but amplification suppresses genome-wide expression of interferon response and antigen processing and presentation machinery genes in ovarian and breast cancer cells, respectively. Besides causing aberrant DNA2 stabilization, replication stress, genomic instability, and cytosolic double-stranded DNA (dsDNA) accumulation, CDK12 loss also triggers cGAS–STING activation and innate immune response, which can be reversed by forced expression of replication protein A (RPA) subunits or DNA2 depletion. Our findings identify DNA2 as a phosphorylation substrate of CDK12, connecting CDK12 to cell cycle regulation. These data also reveal DNA2 protein destruction as a critical mechanism that dictates genomic instability, cGAS–STING signaling activation, and innate immune response in CDK12-deregulated cancers.

(1) Background: Prostate cancer treatment efficacy is significantly influenced by androgen receptor (AR) signaling pathways. SLC22A3, a membrane transporter, has been linked to SNP rs9364554 risk loci for drug efficacy in prostate cancer. (2) Methods: We examined the location of SNP rs9364554 in the genome and utilized TCGA and other publicly available datasets to analyze the association of this SNP with SLC22A3 transcription levels. We verified onco-mining findings in prostate cancer cell lines using quantitative PCR and Western blots. Additionally, we employed electrophoretic mobility shift assay (EMSA) to detect the binding affinity of transcription factors to this SNP. The ChIP-Seq was used to analyze the enrichment of H3K27ac on the SLC22A3 promoter. (3) Results: In this study, we revealed that SNP rs9364554 resides in the SLC22A3 gene and affects its transcription. The downregulation of SLC22A3 is associated with drug resistance. More importantly, we found that this SNP has different binding affinities with transcription factors, specifically FOXA1 and AR, which significantly affects their regulation of SLC22A3 transcription. (4) Conclusions: Our findings highlight the potential of using this SNP as a biomarker for predicting chemotherapeutic outcomes and uncover possible mechanisms underlying drug resistance in advanced prostate cancers. More importantly, it provides a clinical foundation for targeting FOXA1 to enhance drug efficacy in prostate cancer patients.

Abstract DNMT3A and TET2 are epigenetic regulator genes commonly mutated in age-related clonal hematopoiesis (CH). Despite having opposed epigenetic functions, these mutations are associated with increased all-cause mortality and a low risk for progression to hematologic neoplasms. Although individual impacts on the epigenome have been described using different model systems, the phenotypic complexity in humans remains to be elucidated. Here, we make use of a natural inflammatory response occurring during coronavirus disease 2019 (COVID-19), to understand the association of these mutations with inflammatory morbidity (acute respiratory distress syndrome [ARDS]) and mortality. We demonstrate the age-independent, negative impact of DNMT3A mutant (DNMT3Amt) CH on COVID-19–related ARDS and mortality. Using single-cell proteogenomics we show that DNMT3A mutations involve myeloid and lymphoid lineage cells. Using single-cell multiomics sequencing, we identify cell-specific gene expression changes associated with DNMT3A mutations, along with significant epigenomic deregulation affecting enhancer accessibility, resulting in overexpression of interleukin-32 (IL-32), a proinflammatory cytokine that can result in inflammasome activation in monocytes and macrophages. Finally, we show with single-cell resolution that the loss of function of DNMT3A is directly associated with increased chromatin accessibility in mutant cells. Hence, we demonstrate the negative prognostic impact of DNMT3Amt CH on COVID-19–related ARDS and mortality. DNMT3Amt CH in the context of COVID-19, was associated with inflammatory transcriptional priming, resulting in overexpression of IL32. This overexpression was secondary to increased chromatic accessibility, specific to DNMT3Amt CH cells. DNMT3Amt CH can thus serve as a potential biomarker for adverse outcomes in COVID-19.

Abstract An accurate assessment of p53’s functional statuses is critical for cancer genomic medicine. However, there is a significant challenge in identifying tumors with non-mutational p53 inactivation which is not detectable through DNA sequencing. These undetected cases are often misclassified as p53-normal, leading to inaccurate prognosis and downstream association analyses. To address this issue, we built the support vector machine (SVM) models to systematically reassess p53’s functional statuses in TP53 wild-type (TP53WT) tumors from multiple The Cancer Genome Atlas (TCGA) cohorts. Cross-validation demonstrated the good performance of the SVM models with a mean area under the receiver operating characteristic curve (AUROC) of 0.9822, precision of 0.9747, and recall of 0.9784. Our study revealed that a significant proportion (87%–99%) of TP53WT tumors actually had compromised p53 function. Additional analyses uncovered that these genetically intact but functionally impaired (termed as predictively reduced function of p53 or TP53WT-pRF) tumors exhibited genomic and pathophysiologic features akin to TP53-mutant tumors: heightened genomic instability and elevated levels of hypoxia. Clinically, patients with TP53WT-pRF tumors experienced significantly shortened overall survival or progression-free survival compared to those with predictively normal function of p53 (TP53WT-pN) tumors, and these patients also displayed increased sensitivity to platinum-based chemotherapy and radiation therapy.

Background and Aims: Disruption of the epigenome is a hallmark of human disease, including liver cirrhosis and HCC. While genetic heterogeneity is an established effector of pathologic phenotypes, epigenetic heterogeneity is less well understood. Environmental exposures alter the liver-specific DNA methylation landscape and influence the onset of liver cancer. Given that currently available treatments are unable to target frequently mutated genes in HCC, there is an unmet need for novel therapeutics to prevent or reverse liver damage leading to hepatic tumorigenesis, which the epigenome may provide. Approach and Results: We performed genome-wide profiling of DNA methylation, copy number, and gene expression from multiple liver regions from 31 patients with liver disease to examine their crosstalk and define the individual and combinatorial contributions of these processes to liver disease progression. We identified epigenetic heterogeneity hotspots that are conserved across patients. Elevated epigenetic heterogeneity is associated with increased gene expression heterogeneity. Cirrhotic regions comprise 2 distinct cohorts—one exclusively epigenetic, and the other where epigenetic and copy number variations collaborate. Epigenetic heterogeneity hotspots are enriched for genes central to liver function (eg, HNF1A) and known tumor suppressors (eg, RASSF1A). These hotspots encompass genes including ACSL1, ACSL5, MAT1A, and ELFN1, which have phenotypic effects in functional screens, supporting their relevance to hepatocarcinogenesis. Moreover, epigenetic heterogeneity hotspots are linked to clinical measures of outcome. Conclusions: Substantial epigenetic heterogeneity arises early in liver disease development, targeting key pathways in the progression and initiation of both cirrhosis and HCC. Integration of epigenetic and transcriptional heterogeneity unveils putative epigenetic regulators of hepatocarcinogenesis.

Abstract Motivation Analyzing the overlap between two sets of genomic intervals is a frequent task in the field of bioinformatics. Typically, this is accomplished by counting the number (or proportion) of overlapped regions, which applies an arbitrary threshold to determine if two genomic intervals are overlapped. By making binary calls but disregarding the magnitude of the overlap, such an approach often leads to biased, non-reproducible, and incomparable results. Results We developed the cobind package, which incorporates six statistical measures: the Jaccard coefficient, Sørensen–Dice coefficient, Szymkiewicz–Simpson coefficient, collocation coefficient, pointwise mutual information (PMI), and normalized PMI. These measures allow for a quantitative assessment of the collocation strength between two sets of genomic intervals. To demonstrate the effectiveness of these methods, we applied them to analyze CTCF’s binding sites identified from ChIP-seq, cancer-specific open-chromatin regions (OCRs) identified from ATAC-seq of 17 cancer types, and oligodendrocytes-specific OCRs identified from scATAC-seq. Our results indicated that these new approaches effectively re-discover CTCF’s cofactors, as well as cancer-specific and oligodendrocytes-specific master regulators implicated in disease and cell type development. Availability and implementation The cobind package is implemented in Python and freely available at https://cobind.readthedocs.io/en/latest/.

Abstract Androgen receptor (AR) inhibition by androgen deprivation and/or antiandrogen administration is the mainstay therapy for advanced prostate cancer. However, most prostate cancers ultimately become resistant to these therapies, indicating the importance of identifying mechanisms driving resistance to improve patient outcomes. Here we demonstrated that acute treatment with the antiandrogen enzalutamide (ENZ) decreased glutathione (GSH) production, increased lipid peroxidation, and induced ferroptosis in prostate cancer cells. Consistently, meta-analysis of transcriptomic data linked the androgen-AR axis to metabolism-related biological processes, including lipid metabolism. The cystine transporter gene SLC7A11 was a key AR target, and full-length AR (AR-FL) transactivated SLC7A11 transcription by directly occupying the SLC7A11 promoter and putative enhancer regions. AR variants (AR-V) preferentially bound the SLC7A11 enhancer and upregulated SLC7A11 expression, thereby conferring resistance to ferroptosis induced by ENZ treatment. However, this effect was abolished following downregulation of AR-Vs using the dual CBP/p300 and BET inhibitor NEO2734. These findings reveal ferroptosis induction as an anticancer mechanism of antiandrogens and SLC7A11 as a direct target gene of AR-FL and AR-Vs. AR-V-mediated SLC7A11 expression represents a mechanism coupling ferroptosis resistance to prostate cancer progression. Significance: Upregulation of SLC7A11 can be induced by androgen receptor variants to inhibit antiandrogen-induced prostate cancer cell ferroptosis and to drive castration resistance in prostate cancer.