Cistrome Data Browser: expanded datasets and new tools for gene regulatory analysis

Chromatin-bound RB targets promoters, enhancers, and CTCF-bound loci and is redistributed by cell-cycle progression

The interaction of RB with chromatin is key to understanding its molecular functions. Here, for first time, we identify the full spectrum of chromatin-bound RB. Rather than exclusively binding promoters, as is often described, RB targets three fundamentally different types of loci (promoters, enhancers, and insulators), which are largely distinguishable by the mutually exclusive presence of E2F1, c-Jun, and CTCF. While E2F/DP facilitates RB association with promoters, AP-1 recruits RB to enhancers. Although phosphorylation in CDK sites is often portrayed as releasing RB from chromatin, we show that the cell cycle redistributes RB so that it enriches at promoters in G1 and at non-promoter sites in cycling cells. RB-bound promoters include the classic E2F-targets and are similar between lineages, but RB-bound enhancers associate with different categories of genes and vary between cell types. Thus, RB has a well-preserved role controlling E2F in G1, and it targets cell-type-specific enhancers and CTCF sites when cells enter S-phase.

Functional genomics uncovers the transcription factor BNC2 as required for myofibroblastic activation in fibrosis

Tissue injury triggers activation of mesenchymal lineage cells into wound-repairing myofibroblasts, whose unrestrained activity leads to fibrosis. Although this process is largely controlled at the transcriptional level, whether the main transcription factors involved have all been identified has remained elusive. Here, we report multi-omics analyses unraveling Basonuclin 2 (BNC2) as a myofibroblast identity transcription factor. Using liver fibrosis as a model for in-depth investigations, we first show that BNC2 expression is induced in both mouse and human fibrotic livers from different etiologies and decreases upon human liver fibrosis regression. Importantly, we found that BNC2 transcriptional induction is a specific feature of myofibroblastic activation in fibrotic tissues. Mechanistically, BNC2 expression and activities allow to integrate pro-fibrotic stimuli, including TGFβ and Hippo/YAP1 signaling, towards induction of matrisome genes such as those encoding type I collagen. As a consequence, Bnc2 deficiency blunts collagen deposition in livers of mice fed a fibrogenic diet. Additionally, our work establishes BNC2 as potentially druggable since we identified the thalidomide derivative CC-885 as a BNC2 inhibitor. Altogether, we propose that BNC2 is a transcription factor involved in canonical pathways driving myofibroblastic activation in fibrosis.

Myofibroblasts contribute to the development of liver fibrosis. Here, the authors report that the transcription factor Basonuclin 2 (BNC2) integrates fibrogenic signals and drives myofibroblastic transcriptional activation in liver fibrosis.

Targeted protein degradation reveals RNA Pol II heterogeneity and functional diversity

RNA polymerase II (RNA Pol II) subunits are thought to be involved in various transcription-associated processes, but it is unclear whether they play different regulatory roles in modulating gene expression. Here, we performed nascent and mature transcript sequencing after the acute degradation of 12 mammalian RNA Pol II subunits and profiled their genomic binding sites and protein interactomes to dissect their molecular functions. We found that RNA Pol II subunits contribute differently to RNA Pol II cellular localization and transcription processes and preferentially regulate RNA processing (such as RNA splicing and 3' end maturation). Genes sensitive to the depletion of different RNA Pol II subunits tend to be involved in diverse biological functions and show different RNA half-lives. Sequences, associated protein factors, and RNA structures are correlated with RNA Pol II subunit-mediated differential gene expression. These findings collectively suggest that the heterogeneity of RNA Pol II and different genes appear to depend on some of the subunits.

FOXR2 Is an Epigenetically Regulated Pan-Cancer Oncogene That Activates ETS Transcriptional Circuits

Forkhead box R2 (FOXR2) is a forkhead transcription factor located on the X chromosome whose expression is normally restricted to the testis. In this study, we performed a pan-cancer analysis of FOXR2 activation across more than 10,000 adult and pediatric cancer samples and found FOXR2 to be aberrantly upregulated in 70% of all cancer types and 8% of all individual tumors. The majority of tumors (78%) aberrantly expressed FOXR2 through a previously undescribed epigenetic mechanism that involves hypomethylation of a novel promoter, which was functionally validated as necessary for FOXR2 expression and proliferation in FOXR2-expressing cancer cells. FOXR2 promoted tumor growth across multiple cancer lineages and co-opted ETS family transcription circuits across cancers. Taken together, this study identifies FOXR2 as a potent and ubiquitous oncogene that is epigenetically activated across the majority of human cancers. The identification of hijacking of ETS transcription circuits by FOXR2 extends the mechanisms known to active ETS transcription factors and highlights how transcription factor families cooperate to enhance tumorigenesis.

SIGNIFICANCE

This work identifies a novel promoter that drives aberrant FOXR2 expression and delineates FOXR2 as a pan-cancer oncogene that specifically activates ETS transcriptional circuits across human cancers. See related commentary by Liu and Northcott, p. 2977.

H3K9 tri-methylation at Nanog times differentiation commitment and enables the acquisition of primitive endoderm fate

Mouse embryonic stem cells have an inherent propensity to explore gene regulatory states associated with either self-renewal or differentiation. This property depends on ERK, which downregulates pluripotency genes such as Nanog. Here, we aimed at identifying repressive histone modifications that would mark Nanog for inactivation in response to ERK activity. We found that the transcription factor ZFP57, which binds methylated DNA to nucleate heterochromatin, is recruited upstream of Nanog, within a region enriched for histone H3 lysine 9 tri-methylation (H3K9me3). Whereas before differentiation H3K9me3 at Nanog depends on ERK, in somatic cells it becomes independent of ERK. Moreover, the loss of H3K9me3 at Nanog, induced by deleting the region or by knocking out DNA methyltransferases or Zfp57, is associated with reduced heterogeneity of NANOG, delayed commitment into differentiation and impaired ability to acquire a primitive endoderm fate. Hence, a network axis centred on DNA methylation, ZFP57 and H3K9me3 links Nanog regulation to ERK activity for the timely establishment of new cell identities. We suggest that establishment of irreversible H3K9me3 at specific master regulators allows the acquisition of particular cell fates during differentiation.

Summary: A regulatory axis integrating ERK, ZFP57, DNA and H3K9 methylation underlies the transition of Nanog expression from heterogeneous and dynamic to irreversibly silenced, enabling differentiation commitment and primitive endoderm specification.

Blocking CHOP-dependent TXNIP shuttling to mitochondria attenuates albuminuria and mitigates kidney injury in nephrotic syndrome

Albuminuria is a hallmark of glomerular disease of various etiologies. It is not only a symptom of glomerular disease but also a cause leading to glomerulosclerosis, interstitial fibrosis, and eventually, a decline in kidney function. The molecular mechanism underlying albuminuria-induced kidney injury remains poorly defined. In our genetic model of nephrotic syndrome (NS), we have identified CHOP (C/EBP homologous protein)-TXNIP (thioredoxin-interacting protein) as critical molecular linkers between albuminuria-induced ER dysfunction and mitochondria dyshomeostasis. TXNIP is a ubiquitously expressed redox protein that binds to and inhibits antioxidant enzyme, cytosolic thioredoxin 1 (Trx1), and mitochondrial Trx2. However, very little is known about the regulation and function of TXNIP in NS. By utilizing Chop-/- and Txnip-/- mice as well as 68Ga-Galuminox, our molecular imaging probe for detection of mitochondrial reactive oxygen species (ROS) in vivo, we demonstrate that CHOP up-regulation induced by albuminuria drives TXNIP shuttling from nucleus to mitochondria, where it is required for the induction of mitochondrial ROS. The increased ROS accumulation in mitochondria oxidizes Trx2, thus liberating TXNIP to associate with mitochondrial nod-like receptor protein 3 (NLRP3) to activate inflammasome, as well as releasing mitochondrial apoptosis signal-regulating kinase 1 (ASK1) to induce mitochondria-dependent apoptosis. Importantly, inhibition of TXNIP translocation and mitochondrial ROS overproduction by CHOP deletion suppresses NLRP3 inflammasome activation and p-ASK1-dependent mitochondria apoptosis in NS. Thus, targeting TXNIP represents a promising therapeutic strategy for the treatment of NS.

Regulation of neuroendocrine plasticity by the RNA-binding protein ZFP36L1

Some small cell lung cancers (SCLCs) are highly sensitive to inhibitors of the histone demethylase LSD1. LSD1 inhibitors are thought to induce their anti-proliferative effects by blocking neuroendocrine differentiation, but the mechanisms by which LSD1 controls the SCLC neuroendocrine phenotype are not well understood. To identify genes required for LSD1 inhibitor sensitivity in SCLC, we performed a positive selection genome-wide CRISPR/Cas9 loss of function screen and found that ZFP36L1, an mRNA-binding protein that destabilizes mRNAs, is required for LSD1 inhibitor sensitivity. LSD1 binds and represses ZFP36L1 and upon LSD1 inhibition, ZFP36L1 expression is restored, which is sufficient to block the SCLC neuroendocrine differentiation phenotype and induce a non-neuroendocrine "inflammatory" phenotype. Mechanistically, ZFP36L1 binds and destabilizes SOX2 and INSM1 mRNAs, two transcription factors that are required for SCLC neuroendocrine differentiation. This work identifies ZFP36L1 as an LSD1 target gene that controls the SCLC neuroendocrine phenotype and demonstrates that modulating mRNA stability of lineage transcription factors controls neuroendocrine to non-neuroendocrine plasticity.

Repression of enhancer RNA PHLDA1 promotes tumorigenesis and progression of Ewing sarcoma via decreasing infiltrating T‐lymphocytes: A bioinformatic analysis

Background: The molecular mechanisms of EWS-FLI-mediating target genes and downstream pathways may provide a new way in the targeted therapy of Ewing sarcoma. Meanwhile, enhancers transcript non-coding RNAs, known as enhancer RNAs (eRNAs), which may serve as potential diagnosis markers and therapeutic targets in Ewing sarcoma.

Materials and methods: Differentially expressed genes (DEGs) were identified between 85 Ewing sarcoma samples downloaded from the Treehouse database and 3 normal bone samples downloaded from the Sequence Read Archive database. Included in DEGs, differentially expressed eRNAs (DEeRNAs) and target genes corresponding to DEeRNAs (DETGs), as well as the differentially expressed TFs, were annotated. Then, cell type identification by estimating relative subsets of known RNA transcripts (CIBERSORT) was used to infer portions of infiltrating immune cells in Ewing sarcoma and normal bone samples. To evaluate the prognostic value of DEeRNAs and immune function, cross validation, independent prognosis analysis, and Kaplan–Meier survival analysis were implemented using sarcoma samples from the Cancer Genome Atlas database. Next, hallmarks of cancer by gene set variation analysis (GSVA) and immune gene sets by single-sample gene set enrichment analysis (ssGSEA) were identified to be significantly associated with Ewing sarcoma. After screening by co-expression analysis, most significant DEeRNAs, DETGs and DETFs, immune cells, immune gene sets, and hallmarks of cancer were merged to construct a co-expression regulatory network to eventually identify the key DEeRNAs in tumorigenesis of Ewing sarcoma. Moreover, Connectivity Map Analysis was utilized to identify small molecules targeting Ewing sarcoma. External validation based on multidimensional online databases and scRNA-seq analysis were used to verify our key findings.

Results: A six-different-dimension regulatory network was constructed based on 17 DEeRNAs, 29 DETFs, 9 DETGs, 5 immune cells, 24 immune gene sets, and 8 hallmarks of cancer. Four key DEeRNAs (CCR1, CD3D, PHLDA1, and RASD1) showed significant co-expression relationships in the network. Connectivity Map Analysis screened two candidate compounds, MS-275 and pyrvinium, that might target Ewing sarcoma. PHLDA1 (key DEeRNA) was extensively expressed in cancer stem cells of Ewing sarcoma, which might play a critical role in the tumorigenesis of Ewing sarcoma.

Conclusion: PHLDA1 is a key regulator in the tumorigenesis and progression of Ewing sarcoma. PHLDA1 is directly repressed by EWS/FLI1 protein and low expression of FOSL2, resulting in the deregulation of FOX proteins and CC chemokine receptors. The decrease of infiltrating T‐lymphocytes and TNFA signaling may promote tumorigenesis and progression of Ewing sarcoma.

Screening of primary open-angle glaucoma diagnostic markers based on immune-related genes and immune infiltration

Purpose

Primary open-angle glaucoma (POAG) continues to be a poorly understood disease. Although there were multiple researches on the identification of POAG biomarkers, few studies systematically revealed the immune-related cells and immune infiltration of POAG. Bioinformatics analyses of optic nerve (ON) and trabecular meshwork (TM) gene expression data were performed to further elucidate the immune-related genes of POAG and identify candidate target genes for treatment.

Methods

We performed a gene analysis of publicly available microarray data, namely, the GSE27276-GPL2507, GSE2378-GPL8300, GSE9944-GPL8300, and GSE9944-GPL571 datasets from the Gene Expression Omnibus database. The obtained datasets were used as input for parallel pathway analyses. Based on random forest and support vector machine (SVM) analysis to screen the key genes, significantly changed pathways were clustered into functional categories, and the results were further investigated. CIBERSORT was used to evaluate the infiltration of immune cells in POAG tissues. A network visualizing the differences between the data in the POAG and normal groups was created. GO and KEGG enrichment analyses were performed using the Metascape database. We divided the differentially expressed mRNAs into upregulated and downregulated groups and predicted the drug targets of the differentially expressed genes through the Connectivity Map (CMap) database.

Results

A total of 49 differentially expressed genes, including 19 downregulated genes and 30 upregulated genes, were detected. Five genes ((Keratin 14) KRT14, (Hemoglobin subunit beta) HBB, (Acyl-CoA Oxidase 2) ACOX2, (Hephaestin) HEPH and Keratin 13 (KRT13)) were significantly changed. The results showed that the expression profiles of drug disturbances, including those for avrainvillamide-analysis-3, cytochalasin-D, NPI-2358, oxymethylone and vinorelbine, were negatively correlated with the expression profiles of disease disturbances. This finding indicated that these drugs may reduce or even reverse the POAG disease state.

Conclusion

This study provides an overview of the processes involved in the molecular pathogenesis of POAG in the ON and TM. The findings provide a new understanding of the molecular mechanism of POAG from the perspective of immunology.

Construction of the prognostic enhancer RNA regulatory network in osteosarcoma

•

Our enhancer RNAs-based prognostic model showed good predictive ability in osteosarcoma.

•

CCAAT enhancer binding protein alpha (CEBPA) may regulate CD8A molecule (CD8A).

•

CD8A activation may promote CD3E molecule (CD3E) expression and activate allograft rejection in CD8+ T cells.

•

Above signal axis provided new insights in the mechanism of osteosarcoma tumorigenesis.

Background

Osteosarcoma (OS) is a common malignant tumor in osteoarticular system, the 5-year overall survival of which is poor. Enhancer RNAs (eRNAs) have been implicated in the tumorigenesis of various cancer types, whereas their roles in OS tumorigenesis remains largely unclear.

Methods

Differentially expressed eRNAs (DEEs), transcription factors (DETFs), target genes (DETGs) were identified using limma (Linear Models for Microarray Analysis) package. Prognosis-related DEEs were accessed by univariate Cox regression analysis. A multivariate model was constructed to evaluate the prognosis of OS samples. Prognosis-related DEEs, DETFs, DETGs, immune cells, and hallmark gene sets were co-analyzed to construct an regulatory network. Specific inhibitors were also filtered by connectivity Map analysis. External validation and scRNA-seq analysis were performed to verify our key findings.

Results

3,981 DETGs, 468 DEEs, 51 DETFs, and 27 differentially expressed hallmark gene sets were identified. A total of Multivariate risk predicting model based on 18 prognosis-related DEEs showed a high accuracy (area under curve (AUC) = 0.896). GW-8510 was the candidate inhibitor targeting prognosis-related DEEs (mean = 0.670, p < 0.001). Based on the OS tumorigenesis-related regulation network, we identified that CCAAT enhancer binding protein alpha (CEBPA, DETF) may regulate CD8A molecule (CD8A, DEE), thereby promoting the transcription of CD3E molecule (CD3E, DETG), which may affect allograft rejection based on CD8+ T cells.

Conclusion

We constructed an eRNA-based prognostic model for predicting the OS patients’ prognosis and explored the potential regulation network for OS tumorigenesis by an integrated bioinformatics analysis, providing promising therapeutic targets for OS patients.

MX2: Identification and systematic mechanistic analysis of a novel immune-related biomarker for systemic lupus erythematosus

Background

Systemic lupus erythematosus (SLE) is an autoimmune disease that involves multiple organs. However, the current SLE-related biomarkers still lack sufficient sensitivity, specificity and predictive power for clinical application. Thus, it is significant to explore new immune-related biomarkers for SLE diagnosis and development.

Methods

We obtained seven SLE gene expression profile microarrays (GSE121239/11907/81622/65391/100163/45291/49454) from the GEO database. First, differentially expressed genes (DEGs) were screened using GEO2R, and SLE biomarkers were screened by performing WGCNA, Random Forest, SVM-REF, correlation with SLEDAI and differential gene analysis. Receiver operating characteristic curves (ROCs) and AUC values were used to determine the clinical value. The expression level of the biomarker was verified by RT‒qPCR. Subsequently, functional enrichment analysis was utilized to identify biomarker-associated pathways. ssGSEA, CIBERSORT, xCell and ImmuCellAI algorithms were applied to calculate the sample immune cell infiltration abundance. Single-cell data were analyzed for gene expression specificity in immune cells. Finally, the transcriptional regulatory network of the biomarker was constructed, and the corresponding therapeutic drugs were predicted.

Results

Multiple algorithms were screened together for a unique marker gene, MX2, and expression analysis of multiple datasets revealed that MX2 was highly expressed in SLE compared to the normal group (all P < 0.05), with the same trend validated by RT‒qPCR (P = 0.026). Functional enrichment analysis identified the main pathway of MX2 promotion in SLE as the NOD-like receptor signaling pathway (NES=2.492, P < 0.001, etc.). Immuno-infiltration analysis showed that MX2 was closely associated with neutrophils, and single-cell and transcriptomic data revealed that MX2 was specifically expressed in neutrophils. The NOD-like receptor signaling pathway was also remarkably correlated with neutrophils (r >0.3, P < 0.001, etc.). Most of the MX2-related interacting proteins were associated with SLE, and potential transcription factors of MX2 and its related genes were also significantly associated with the immune response.

Conclusion

Our study found that MX2 can serve as an immune-related biomarker for predicting the diagnosis and disease activity of SLE. It activates the NOD-like receptor signaling pathway and promotes neutrophil infiltration to aggravate SLE.

CisCross: A gene list enrichment analysis to predict upstream regulators in Arabidopsis thaliana

Having DNA-binding profiles for a sufficient number of genome-encoded transcription factors (TFs) opens up the perspectives for systematic evaluation of the upstream regulators for the gene lists. Plant Cistrome database, a large collection of TF binding profiles detected using the DAP-seq method, made it possible for Arabidopsis. Here we re-processed raw DAP-seq data with MACS2, the most popular peak caller that leads among other ones according to quality metrics. In the benchmarking study, we confirmed that the improved collection of TF binding profiles supported a more precise gene list enrichment procedure, and resulted in a more relevant ranking of potential upstream regulators. Moreover, we consistently recovered the TF binding profiles that were missing in the previous collection of DAP-seq peak sets. We developed the CisCross web service (https://plamorph.sysbio.ru/ciscross/) that gives more flexibility in the analysis of potential upstream TF regulators for Arabidopsis thaliana genes.

Identification of differentially expressed autophagy genes associated with osteogenic differentiation in human bone marrow mesenchymal stem cells

BACKGROUND

Mesenchymal stem cells derived from human tissues have been widely used for tissue regeneration because of their strong self-renewal capacity and multi-potential properties. Autophagy plays a vital role in maintaining bone homeostasis. However, the mechanism underlying this role for autophagy in the osteogenic differentiation of mesenchymal stem cells remains to be elucidated.

METHODS

Two microarray datasets were downloaded from the GEO database. Fourteen bone marrow mesenchymal stem cell samples comprising control and induction groups were selected to identify differentially expressed autophagy-related genes via multiple bioinformatics approaches, followed by functional analysis. Interactions among differentially expressed autophagy genes, miRNAs, and transcription factors were analyzed and visualized using Cytoscape software. The association between hub differentially expressed genes and autophagy was validated by qRT-PCR.

RESULTS

Ten autophagy-related genes (including VPS8, NDRG4, and CYBB) were identified as osteogenic hub genes. Correlation analysis revealed that CYBB was highly correlated with the sensitivity to multiple drugs, such as imexon, megestrol acetate, and isotretinoin. The regulatory network displayed a complex connection among miRNAs, transcription factors, and differentially expressed autophagy genes. Friends' analysis showed that NDRG4 was highly closely related to other hub genes (P < 0.05). Furthermore, NDRG4 expression was downregulated in the induction group (P < 0.01). NDRG4 was significantly correlated with infiltrating immune cells, including monocytes, eosinophils, type 17 T helper cells, neutrophils, activated CD8 T cells, and immature B cells. Levels of the 10 autophagy-related genes (including VPS8, NDRG4, and CYBB) were successfully validated based on in vitro experiments.

CONCLUSION

We identified candidate molecules to further investigate their functions in osteogenesis, providing novel insights into the role of autophagy in mesenchymal stem cell differentiation.

Web-MCOT Server for Motif Co-Occurrence Search in ChIP-Seq Data

(1) Background: The widespread application of ChIP-seq technology requires annotation of cis-regulatory modules through the search of co-occurred motifs. (2) Methods: We present the web server Motifs Co-Occurrence Tool (Web-MCOT) that for a single ChIP-seq dataset detects the composite elements (CEs) or overrepresented homo- and heterotypic pairs of motifs with spacers and overlaps, with any mutual orientations, uncovering various similarities to recognition models within pairs of motifs. The first (Anchor) motif in CEs respects the target transcription factor of the ChIP-seq experiment, while the second one (Partner) can be defined either by a user or a public library of Partner motifs being processed. (3) Results: Web-MCOT computes the significances of CEs without reference to motif conservation and those with more conserved Partner and Anchor motifs. Graphic results show histograms of CE abundance depending on orientations of motifs, overlap and spacer lengths; logos of the most common CE structural types with an overlap of motifs, and heatmaps depicting the abundance of CEs with one motif possessing higher conservation than another. (4) Conclusions: Novel capacities of Web-MCOT allow retrieving from a single ChIP-seq dataset with maximal information on the co-occurrence of motifs and potentiates planning of next ChIP-seq experiments.

Polymeric immunoglobulin receptor suppresses colorectal cancer through the AKT-FOXO3/4 axis by downregulating LAMB3 expression

Colorectal cancer (CRC) remains one of the most common malignancies worldwide and its mechanism is unclear. Polymeric immunoglobulin receptor (PIGR) which plays an important role in mucosal immunity is widely expressed in the mucosal epithelium and is dysregulated in different tumors. However, the role and underlying mechanisms of PIGR in CRC remain unclear. Here, we demonstrated that PIGR was hypermethylated and downregulated in our cohort (N = 272), and these features were associated with reduced overall survival in patients (HRmethylation 1.61, 95% CI [1.11-2.33]). These findings were validated by external TCGA and GEO data. Moreover, PIGR overexpression inhibits CRC cell malignant phenotypes in vitro and impedes CRC cells growth in male BALB/c nude mice. Mechanistically, PIGR physically associates with RE1 silencing transcription factor (REST) and blocks the transcription of laminin subunit beta 3 (LAMB3). Subsequently, the AKT-FOXO3/4 axis was suppressed by downregulated LAMB3. In the drug sensitive assay, PIGR-overexpressing cells were more sensitive to cisplatin and gemcitabine. Together, PIGR may serve as a powerful prognostic biomarker and putative tumor suppressor by suppressing the AKT-FOXO3/4 axis by downregulating LAMB3 in CRC. Our study may offer a novel therapeutic strategy for treating CRC patients who highly express PIGR with cisplatin and gemcitabine.

TTN mutations predict a poor prognosis in patients with thyroid cancer

OBJECTIVE

We aimed to investigate the relationship between titin (TTN) gene mutations and thyroid cancer (THCA) and to explore the feasibility of the TTN gene as a potential prognostic indicator of THCA.

METHODS

From TCGA-THCA cohort, we performed a series of analyses to evaluate the prognostic value and potential mechanism of TTN in THCA. These patients were divided into the mutant-type (MUT) group and the wild-type (WT) group. Differentially expressed genes (DEGs) in the two groups were screened using the 'DESeq2' R package. Functional enrichment analysis was performed, and the protein-protein interaction (PPI) network, transcription factor (TF)-target interaction networks, and competitive endogenous RNA (ceRNA) regulatory networks were established for the DEGs. The TIMER database was applied for immune cell infiltration. Survival analysis and Cox regression analysis were used to analyze the potential prognostic value of the TTN gene.

RESULTS

Differential expression analysis showed that 409 genes were significantly up-regulated and 36 genes were down-regulated. Functional enrichment analysis revealed that TTN gene mutations played a potential role in the development of THCA. Analysis of the immune microenvironment indicated that TTN gene mutations were significantly associated with enrichment of M0 macrophages. Survival analysis showed that the MUT group predicted poorer prognosis than the WT group. Cox regression analysis demonstrated that TTN gene mutations were an independent risk factor for THCA. Nomograms also confirmed the prognostic values of the TTN gene in THCA. Conclusions In summary, our results demonstrated that TTN gene mutations predict poor prognosis in patients with THCA. This is the first study to research TTN gene mutations in THCA and to investigate their prognostic value in THCA.

Comprehensive Analysis of CRIP1 Expression in Acute Myeloid Leukemia

Acute myeloid leukemia (AML) is a highly heterogeneous hematological malignancy that imposes great challenges in terms of drug resistance and relapse. Previous studies revealed heterogeneous leukemia cells and their relevant gene markers, such as CRIP1 as clinically prognostic in t (8;21) AML patients. However, the expression and role of CRIP1 in AML are poorly understood. We used the single-cell RNA sequencing and gene expression data from t (8;21) AML patients to analyze the immune and regulation networks of CRIP1. Two independent cohorts from GSE37642 and The Cancer Genome Atlas (TCGA) datasets were employed as validation cohorts. In addition, the methylation data from TCGA were used to analyze the methylation effect of the CRIP1 expression. Gene expression profile from t (8;21) AML patients showed that the CRIP1-high group exhibited an enrichment of immune-related pathways, including tumor necrosis factor (TNF)α signaling via nuclear factor kappa B (NFκB) pathways. Further studies using CIBERSORT showed that the CRIP1-high group had a significantly higher infiltration of exhausted CD8 T cells and activated mast cells. The CRIP1 expression was validated in the GSE37642-GPL96, GSE37642-GPL570, and TCGA datasets. In addition, with the methylation data, four CpG probes of CRIP1 (cg07065217, cg04411625, cg25682097, and 11763800) were identified as negatively associated with the CRIP1 gene expression in AML patients. Our data provide a comprehensive overview of the regulation of CRIP1 expression in AML patients. The evaluation of the TNFα-NFκB signaling pathway as well as the immune heterogeneity might provide new insights for exploring improvements in AML treatment.

Stemness Analysis Uncovers That The Peroxisome Proliferator-Activated Receptor Signaling Pathway Can Mediate Fatty Acid Homeostasis In Sorafenib-Resistant Hepatocellular Carcinoma Cells

Hepatocellular carcinoma (HCC) stem cells are regarded as an important part of individualized HCC treatment and sorafenib resistance. However, there is lacking systematic assessment of stem-like indices and associations with a response of sorafenib in HCC. Our study thus aimed to evaluate the status of tumor dedifferentiation for HCC and further identify the regulatory mechanisms under the condition of resistance to sorafenib. Datasets of HCC, including messenger RNAs (mRNAs) expression, somatic mutation, and clinical information were collected. The mRNA expression-based stemness index (mRNAsi), which can represent degrees of dedifferentiation of HCC samples, was calculated to predict drug response of sorafenib therapy and prognosis. Next, unsupervised cluster analysis was conducted to distinguish mRNAsi-based subgroups, and gene/geneset functional enrichment analysis was employed to identify key sorafenib resistance-related pathways. In addition, we analyzed and confirmed the regulation of key genes discovered in this study by combining other omics data. Finally, Luciferase reporter assays were performed to validate their regulation. Our study demonstrated that the stemness index obtained from transcriptomic is a promising biomarker to predict the response of sorafenib therapy and the prognosis in HCC. We revealed the peroxisome proliferator-activated receptor signaling pathway (the PPAR signaling pathway), related to fatty acid biosynthesis, that was a potential sorafenib resistance pathway that had not been reported before. By analyzing the core regulatory genes of the PPAR signaling pathway, we identified four candidate target genes, retinoid X receptor beta (RXRB), nuclear receptor subfamily 1 group H member 3 (NR1H3), cytochrome P450 family 8 subfamily B member 1 (CYP8B1) and stearoyl-CoA desaturase (SCD), as a signature to distinguish the response of sorafenib. We proposed and validated that the RXRB and NR1H3 could directly regulate NR1H3 and SCD, respectively. Our results suggest that the combined use of SCD inhibitors and sorafenib may be a promising therapeutic approach.

[VIPR1 promoter methylation promotes transcription factor AP-2α binding to inhibit VIPR1 expression and promote hepatocellular carcinoma cell growth in vitro]

OBJECTIVE

To explore the transcriptional regulation mechanism and biological function of low expression of vasoactive intestinal peptide receptor 1 (VIPR1) in hepatocellular carcinoma (HCC).

METHODS

We constructed plasmids carrying wild-type VIPR1 promoter or two mutant VIPR1 promoter sequences for transfection of the HCC cell lines Hep3B and Huh7, and examined the effect of AP-2α expression on VIPR1 promoter activity using dual-luciferase reporter assay. Pyrosequencing was performed to detect the changes in VIPR1 promoter methylation level in HCC cells treated with a DNA methyltransferase inhibitor (DAC). Chromatin immunoprecipitation was used to evaluate the binding ability of AP-2α to VIPR1 promoter. Western blotting was used to assess the effect of AP-2α knockdown on VIPR1 expression and examine the differential expression of VIPR1 in the two cell lines. The effects of VIPR1 overexpression and knockdown on the proliferation, cell cycle and apoptosis of HCC cells were analyzed using CCK8 assay and flow cytometry. We also observed the growth of HCC xenograft with lentivirus-mediated over-expression of VIPR1 in nude mice.

RESULTS

Compared with the wild-type VIPR1 promoter group, co-transfection with the vector carrying two promoter mutations and the AP-2α-over-expressing plasmid obviously restored the luciferase activity in HCC cells (P < 0.05). DAC treatment of the cells significantly decreased the methylation level of VIPR1 promoter and inhibited the binding of AP-2α to VIPR1 promoter (P < 0.01). The HCC cells with AP-2α knockdown showed increased VIPR1 expression, which was lower in Huh7 cells than in Hep3B cells. VIPR1 overexpression in HCC cells caused significant cell cycle arrest in G2/M phase (P < 0.01), promoted cell apoptosis (P < 0.001), and inhibited cell proliferation (P < 0.001), while VIPR1 knockdown produced the opposite effects. In the tumor-bearing nude mice, VIPR1 overexpression in the HCC cells significantly suppressed the increase of tumor volume (P < 0.001) and weight (P < 0.05).

CONCLUSION

VIPR1 promoter methylation in HCC promotes the binding of AP-2α and inhibits VIPR1 expression, while VIPR1 overexpression causes cell cycle arrest, promotes cell apoptosis, and inhibits cell proliferation and tumor growth.

Targeting HIC1/TGF-β axis-shaped prostate cancer microenvironment restrains its progression

Prostate cancer (PCa) is a malignant tumor that seriously threatens men's health worldwide. Recently, stromal cells in the tumor microenvironment (TME) have been reported to contribute to the progression of PCa. However, the role and mechanism of how PCa cells interact with stromal cells to reshape the TME remain largely unknown. Here, using a spontaneous prostate adenocarcinoma (PRAD) model driven by the loss of Pten and Hic1, we found that M2 macrophages markedly infiltrated the stroma of Pten and Hic1 double conditional knockout (dCKO) mice compared with those in control (Ctrl) mice due to higher TGF-β levels secreted by HIC1-deleted PCa cells. Mechanistically, TGF-β in TME promoted the polarization of macrophages into "M2" status by activating the STAT3 pathway and modulating c-Myc to upregulate CXCR4 expression. Meanwhile, TGF-β activated the fibroblasts to form cancer-associated fibroblasts (CAFs) that secrete higher CXCL12 levels, which bound to its cognate receptor CXCR4 on M2 macrophages. Upon interaction with CAFs, M2 macrophages secreted more CXCL5, which promoted the epithelial-mesenchymal transition (EMT) of PCa via CXCR2. Moreover, using the TGF-β receptor I antagonist, galunisertib, significantly inhibited the tumor growth and progression of the TRAMP-C1 cell line-derived subcutaneous tumor model. Finally, we confirmed that the stromal microenvironment was shaped by TGF-β in HIC1-deficient PCa and was associated with the progression of PCa.

DNA methylation dynamics and dysregulation delineated by high-throughput profiling in the mouse

We have developed a mouse DNA methylation array that contains 296,070 probes representing the diversity of mouse DNA methylation biology. We present a mouse methylation atlas as a rich reference resource of 1,239 DNA samples encompassing distinct tissues, strains, ages, sexes, and pathologies. We describe applications for comparative epigenomics, genomic imprinting, epigenetic inhibitors, patient-derived xenograft assessment, backcross tracing, and epigenetic clocks. We dissect DNA methylation processes associated with differentiation, aging, and tumorigenesis. Notably, we find that tissue-specific methylation signatures localize to binding sites for transcription factors controlling the corresponding tissue development. Age-associated hypermethylation is enriched at regions of Polycomb repression, while hypomethylation is enhanced at regions bound by cohesin complex members. Apc ^Min/+ polyp-associated hypermethylation affects enhancers regulating intestinal differentiation, while hypomethylation targets AP-1 binding sites. This Infinium Mouse Methylation BeadChip (version MM285) is widely accessible to the research community and will accelerate high-sample-throughput studies in this important model organism.

Identification of Survival Risk and Immune-Related Characteristics of Kidney Renal Clear Cell Carcinoma

Background

Immunity exerts momentous functions in the progression and treatment of kidney renal clear cell carcinoma (KIRC). A better understanding of the relationship between KIRC and immunity may make a great contribution to evaluating the prognosis and immune-related therapeutic response of KIRC.

Methods

A series of information such as RNA sequence, clinical data, and tumor mutation burden (TMB) of KIRC patients were downloaded through The Cancer Genome Atlas (TCGA). Next, combining the survival information and gene expression data of TCGA and Gene Expression Omnibus (GEO), we established an immune gene-related prognosis model (IGRPM) and analyzed it. Then we constructed a nomogram which was convenient for clinicians to judge the prognosis of KIRC. Last but not the least, the expressions of some genes used to construct IGRPM in early KIRC, and adjacent normal tissues were verified through real-time fluorescence quantitative polymerase chain reaction (RT-qPCR). Perl (strawberry-perl-5.30.0.1-64bit), R software (4.0.3), and GraphPad Prism 7 were used to process the relevant data.

Results

The single-sample gene set enrichment analysis (ssGSEA) showed that there were significant differences in StromalScore, ImmuneScore, ESTIMATEScore, TumorPurity, 22 kinds of human immune cells infiltration, and HLA genes expression between high immunity group (Immunity_H) and low immunity group (Immunity_L). The Immunity_H expressed more immune-related genes and enriched more immune-related functions than the Immunity_L. In addition, compared with the low-risk group, the high-risk group had worse survival outcome and higher TMB. Combining IGRPM-based risk characteristic and TMB, we found that low-TMB + low-risk was the most beneficial to the survival outcome of KIRC patients. The risk characteristic based on IGRPM could be used as an independent prognostic factor for KIRC, and the nomogram constructed for evaluating the prognosis of KIRC showed excellent predictive potential. The RT-qPCR results suggested that not all the genes used to construct IGRPM showed differential expression in early KIRC compared with adjacent normal tissues, but all these genes had significant influence on the prognosis of KIRC.

Conclusion

These comprehensive immune assessments and survival predictions, integrating multiple aspects of data and clinical information, can provide additional value to the current Tumor Node Metastasis staging system for risk stratification of KIRC and may facilitate the development of KIRC immunotherapy.

Circadian clock function does not require the histone methyltransferase MLL3

The circadian clock controls the physiological function of tissues through the regulation of thousands of genes in a cell-type-specific manner. The core cellular circadian clock is a transcription-translation negative feedback loop, which can recruit epigenetic regulators to facilitate temporal control of gene expression. Histone methyltransferase, mixed lineage leukemia gene 3 (MLL3) was reported to be required for the maintenance of circadian oscillations in cultured cells. Here, we test the role of MLL3 in circadian organization in whole animals. Using mice expressing catalytically inactive MLL3, we show that MLL3 methyltransferase activity is in fact not required for circadian oscillations in vitro in a range of tissues, nor for the maintenance of circadian behavioral rhythms in vivo. In contrast to a previous report, loss of MLL3-dependent methylation did not affect the global levels of H3K4 methylation in liver, indicating substantial compensation from other methyltransferases. Furthermore, we found little evidence of genomic repositioning of H3K4me3 marks. We did, however, observe repositioning of H3K4me1 from intronic regions to intergenic regions and gene promoters; however, there were no changes in H3K4me1 mark abundance around core circadian clock genes. Output functions of the circadian clock, such as control of inflammation, were largely intact in MLL3-methyltransferase-deficient mice, although some gene-specific changes were observed, with sexually dimorphic loss of circadian regulation of specific cytokines. Taken together, these observations indicate that MLL3-directed histone methylation is not essential for core circadian clock function; however, it may influence the inflammatory response.

A T cell resilience model associated with response to immunotherapy in multiple tumor types

Despite breakthroughs in cancer immunotherapy, most tumor-reactive T cells cannot persist in solid tumors due to an immunosuppressive environment. We developed Tres (tumor-resilient T cell), a computational model utilizing single-cell transcriptomic data to identify signatures of T cells that are resilient to immunosuppressive signals, such as transforming growth factor-β1, tumor necrosis factor-related apoptosis-inducing ligand and prostaglandin E2. Tres reliably predicts clinical responses to immunotherapy in melanoma, lung cancer, triple-negative breast cancer and B cell malignancies using bulk T cell transcriptomic data from pre-treatment tumors from patients who received immune-checkpoint inhibitors (n = 38), infusion products for chimeric antigen receptor T cell therapies (n = 34) and pre-manufacture samples for chimeric antigen receptor T cell or tumor-infiltrating lymphocyte therapies (n = 84). Further, Tres identified FIBP, whose functions are largely unknown, as the top negative marker of tumor-resilient T cells across many solid tumor types. FIBP knockouts in murine and human donor CD8+ T cells significantly enhanced T cell-mediated cancer killing in in vitro co-cultures. Further, Fibp knockout in murine T cells potentiated the in vivo efficacy of adoptive cell transfer in the B16 tumor model. Fibp knockout T cells exhibit reduced cholesterol metabolism, which inhibits effector T cell function. These results demonstrate the utility of Tres in identifying biomarkers of T cell effectiveness and potential therapeutic targets for immunotherapies in solid tumors.

Contribution of prognostic ferroptosis-related subtypes classification and hub genes of sepsis

BACKGROUND

Sepsis in patients is a great threat to human health due to its high incidence rate, its rapid and unpredictable progression, as well as it is difficult to treat, and it has poor prognosis. Ferroptosis is a newly discovered type of cell death characterized by the iron-dependent peroxide aggregation. Furthermore, ferroptosis is different from other forms of cell death, namely apoptosis, necrosis, pyroptosis and autophagy. Our study investigated the role of ferroptosis-related genes in sepsis.

METHODS

The GSE65682 dataset from the Gene Expression Omnibus (GEO) database was used to screen ferroptosis-related genes associated with sepsis, and the GSE134347 dataset for the external validation of selected hub genes. The univariate Cox regression analysis, Kaplan-Meier (K-M) survival analysis and weighted gene co-expression network analysis (WGCNA) were used to identify hub genes. Evaluation of the immune cell infiltration in sepsis was used to explain the immune heterogeneity among the cell subtypes. Gene set variation analysis (GSVA) and transcriptional regulatory analysis of selected hub genes further elucidated the probable mechanism of ferroptosis-related genes associated with prognosis in sepsis. Finally, we constructed a competing endogenous RNA (ceRNA) network model.

RESULTS

A total of 479 RNA-seq data points were used for analysis, including 365 samples from patients who survived sepsis and 114 samples from patients who succumbed to sepsis from the available GSE65682 dataset. Consequently, the univariate Cox regression analysis and consensus clustering analysis divide all 479 sepsis samples into two clusters of "survivals" vs. "non-survivals". Following complex analysis were identified as the most important ferroptosis-related genes. Indeed, the WGCNA and K-M analyses associated the expression patterns of NEDD4L and SIAH2 hub genes as the best prognosis for the survival of sepsis (p < 0.05). The expression trend was also consistent with the survival trend of the NEDD4L and SIAH2 hub genes by the external validation of GSE134347 (p < 0.05). Immune cell infiltration analysis indicated that the types and numbers of different immune cells vary among different subtypes and NEDD4L and SIAH2 hub genes. For example, NEDD4L and SIAH2 gene expression had a positive correlation with M0 macrophages and a negative correlation with neutrophils (p > 0.05). Finally, analysis of two hub genes and transcription factors (TFs) showed that 71 TFs were predicted to be related to NEDD4L while 64 TFs to SIAH2 by the Cistrome DB online database.

CONCLUSION

We suggest that NEDD4L and SIAH2 hub genes are involved in the ferroptosis-associated sepsis. The pattern of NEDD4L and SIAH2 expression in patients undergoing sepsis may have prognostic potential for the severity of sepsis and eventually for patients' survival.

A sequence-based global map of regulatory activity for deciphering human genetics

Epigenomic profiling has enabled large-scale identification of regulatory elements, yet we still lack a systematic mapping from any sequence or variant to regulatory activities. We address this challenge with Sei, a framework for integrating human genetics data with sequence information to discover the regulatory basis of traits and diseases. Sei learns a vocabulary of regulatory activities, called sequence classes, using a deep learning model that predicts 21,907 chromatin profiles across >1,300 cell lines and tissues. Sequence classes provide a global classification and quantification of sequence and variant effects based on diverse regulatory activities, such as cell type-specific enhancer functions. These predictions are supported by tissue-specific expression, expression quantitative trait loci and evolutionary constraint data. Furthermore, sequence classes enable characterization of the tissue-specific, regulatory architecture of complex traits and generate mechanistic hypotheses for individual regulatory pathogenic mutations. We provide Sei as a resource to elucidate the regulatory basis of human health and disease.

Sei is a new framework for integrating human genetics data with a sequence-based mapping of predicted regulatory activities to elucidate mechanisms contributing to complex traits and diseases.

Clinical significance and potential regulatory mechanism of overexpression of pituitary tumor-transforming gene transcription factor in bladder cancer

Background

Pituitary tumor transforming gene-1 (PTTG1) transcription factor is identified as carcinogenic and associated with tumor invasiveness, but its role in bladder cancer (BLCA) remains obscure. This research is intended to analyze the aberrant expression and clinical significance of PTTG1 in BLCA, explore the relationship between PTTG1 and tumor microenvironment characteristics and predict its potential transcriptional activity in BLCA tissue.

Methods

We compared the expression discrepancy of PTTG1 mRNA in BLCA and normal bladder tissue, using the BLCA transcriptomic datasets from GEO, ArrayExpress, TCGA, and GTEx. In-house immunohistochemical staining was implemented to determine the PTTG1 protein intensity. The prognostic value of PTTG1 was evaluated using the Kaplan-Meier Plotter. CRISPR screen data was utilized to estimate the effect PTTG1 interference has on BLCA cell lines. We predicted the abundance of the immune cells in the BLCA tumor microenvironment using the microenvironment cell populations-counter and ESTIMATE algorithms. Single-cell RNA sequencing data was applied to identify the major cell types in BLCA, and the dynamics of BLCA progression were revealed using pseudotime analysis. PTTG1 target genes were predicted by CistromeDB.

Results

The elevated expression level of PTTG1 was confirmed in 1037 BLCA samples compared with 127 non-BLCA samples, with a standardized mean difference value of 1.04. Higher PTTG1 expression status exhibited a poorer BLCA prognosis. Moreover, the PTTG1 Chronos genetic effect scores were negative, indicating that PTTG1 silence may inhibit the proliferation and survival of BLCA cells. With PTTG1 mRNA expression level increasing, higher natural killer, cytotoxic lymphocyte, and monocyte lineage cell infiltration levels were observed. A total of four candidate targets containing CHEK2, OCIAD2, UBE2L3, and ZNF367 were determined ultimately.

Conclusions

PTTG1 mRNA over-expression may become a potential biomarker for BLCA prognosis. Additionally, PTTG1 may correlate with the BLCA tumor microenvironment and exert transcriptional activity by targeting CHEK2, OCIAD2, UBE2L3, and ZNF367 in BLCA tissue.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-09810-y.

Drug-induced epigenomic plasticity reprograms circadian rhythm regulation to drive prostate cancer towards androgen-independence

In prostate cancer, androgen receptor (AR)-targeting agents are very effective in various disease stages. However, therapy resistance inevitably occurs and little is known about how tumor cells adapt to bypass AR suppression. Here, we performed integrative multi-omics analyses on tissues isolated before and after 3 months of AR-targeting enzalutamide monotherapy from high-risk prostate cancer patients enrolled in a neoadjuvant clinical trial. Transcriptomic analyses demonstrated that AR inhibition drove tumors towards a neuroendocrine-like disease state. Additionally, epigenomic profiling revealed massive enzalutamide-induced reprogramming of pioneer factor FOXA1 - from inactive chromatin sites towards active cis-regulatory elements that dictate pro-survival signals. Notably, treatment-induced FOXA1 sites were enriched for circadian clock component ARNTL. Post-treatment ARNTL levels associated with poor outcome, and ARNTL knockout strongly decreased prostate cancer cell growth. Our data highlight a remarkable cistromic plasticity of FOXA1 following AR-targeted therapy, and revealed an acquired dependency on circadian regulator ARNTL, a novel candidate therapeutic target.

Clinical significance of cyclin-dependent kinase inhibitor 2C expression in cancers: from small cell lung carcinoma to pan-cancers

Background

Cyclin-dependent kinase inhibitor 2C (CDKN2C) was identified to participate in the occurrence and development of multiple cancers; however, its roles in small cell lung carcinoma (SCLC) remain unclear.

Methods

Differential expression analysis of CDKN2C between SCLC and non-SCLC were performed based on 937 samples from multiple centers. The prognosis effects of CDKN2C in patients with SCLC were detected using both Kaplan–Meier curves and log-rank tests. Using receiver-operating characteristic curves, whether CDKN2C expression made it feasible to distinguish SCLC was determined. The potential mechanisms of CDKN2C in SCLC were investigated by gene ontology terms and signaling pathways (Kyoto Encyclopedia of Genes and Genomes). Based on 10,080 samples, a pan-cancer analysis was also performed to determine the roles of CDKN2C in multiple cancers.

Results

For the first time, upregulated CDKN2C expression was detected in SCLC samples at both the mRNA and protein levels (p of Wilcoxon rank-sum test < 0.05; standardized mean difference = 2.86 [95% CI 2.20–3.52]). Transcription factor FOXA1 expression may positively regulate CDKN2C expression levels in SCLC. High CDKN2C expression levels were related to the poor prognosis of patients with SCLC (hazard ratio > 1, p < 0.05) and showed pronounced effects for distinguishing SCLC from non-SCLC (sensitivity, specificity, and area under the curve ≥ 0.95). CDKN2C expression may play a role in the development of SCLC by affecting the cell cycle. Furthermore, the first pan-cancer analysis revealed the differential expression of CDKN2C in 16 cancers (breast invasive carcinoma, etc.) and its independent prognostic significance in nine cancers (e.g., adrenocortical carcinoma). CDKN2C expression was related to the immune microenvironment, suggesting its potential usefulness as a prognostic marker in immunotherapy.

Conclusions

This study identified upregulated CDKN2C expression and its clinical significance in SCLC and other multiple cancers, suggesting its potential usefulness as a biomarker in treating and differentiating cancers.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12890-022-02036-5.

Comprehensive Analysis of VCAN Expression Profiles and Prognostic Values in HCC

Background: Hepatocellular carcinoma (HCC) is the world’s most common cause of cancer death. Therefore, more molecular mechanisms need to be clarified to meet the urgent need to develop new detection and treatment strategies.

Methods: We used TCGAportal, Kaplan–Meier Plotter, the Cistrome DB Toolkit Database, MExpress, GEPIA2, and other databases to discuss the expression profiles, possible biological function, and potential prognostic value of versican (VCAN) in HCC. We conducted cell experiments such as Transwell migration and invasion assays, wound healing assay, and CCK8 experiment to explore the function of VCAN in HCC.

Result: We selected three HCC transcriptome databases GSE124535, GSE136247, and GSE144269 and analyzed the overexpressed genes contained in them. The overlapping genes were found by the Venn map, and two interacting network modules were found by Mcode. Module 1 was mainly related to mitosis and cell cycle, and module 2 was mainly related to EMT, angiogenesis, glycolysis, and so on. We found that the seed gene in module 2 is VCAN. Data from TCGAportal showed that compared with normal tissues, the expression of VCAN was up-regulated in HCC tissues. The patients with high expression of VCAN had shorter distant recurrence-free survival and overall survival. Multiple possible VCAN interactions had also been identified. These results revealed that the level of VCAN was higher in the subtypes of HCC with higher malignant degree and was connected to the poor prognosis. In addition, the treatment of VCAN with DNA methyltransferase inhibitors and transcription factor inhibitors may improve the prognosis of patients with HCC.

Conclusion: Our findings systematically elucidated the expression profile and different prognostic values of VCAN in HCC, which may provide new therapeutic targets and potential prognostic biomarkers for HCC patients.

Nucleosome-Omics: A Perspective on the Epigenetic Code and 3D Genome Landscape

Genetic information is loaded on chromatin, which involves DNA sequence arrangement and the epigenetic landscape. The epigenetic information including DNA methylation, nucleosome positioning, histone modification, 3D chromatin conformation, and so on, has a crucial impact on gene transcriptional regulation. Out of them, nucleosomes, as basal chromatin structural units, play an important central role in epigenetic code. With the discovery of nucleosomes, various nucleosome-level technologies have been developed and applied, pushing epigenetics to a new climax. As the underlying methodology, next-generation sequencing technology has emerged and allowed scientists to understand the epigenetic landscape at a genome-wide level. Combining with NGS, nucleosome-omics (or nucleosomics) provides a fresh perspective on the epigenetic code and 3D genome landscape. Here, we summarized and discussed research progress in technology development and application of nucleosome-omics. We foresee the future directions of epigenetic development at the nucleosome level.

Systematic analysis on expression quantitative trait loci identifies a novel regulatory variant in ring finger and WD repeat domain 3 associated with prognosis of pancreatic cancer

BACKGROUND

Pancreatic adenocarcinoma (PAAD) is an extremely lethal malignancy. Identification of the functional genes and genetic variants related to PAAD prognosis is important and challenging. Previously identified prognostic genes from several expression profile analyses were inconsistent. The regulatory genetic variants that affect PAAD prognosis were largely unknown.

METHODS

Firstly, a meta-analysis was performed with seven published datasets to systematically explore the candidate prognostic genes for PAAD. Next, to identify the regulatory variants for those candidate genes, expression quantitative trait loci analysis was implemented with PAAD data resources from The Cancer Genome Atlas. Then, a two-stage association study in a total of 893 PAAD patients was conducted to interrogate the regulatory variants and find the prognostic locus. Finally, a series of biochemical experiments and phenotype assays were carried out to demonstrate the biological function of variation and genes in PAAD progression process.

RESULTS

A total of 128 genes were identified associated with the PAAD prognosis in the meta-analysis. Fourteen regulatory loci in 12 of the 128 genes were discovered, among which, only rs4887783, the functional variant in the promoter of Ring Finger and WD Repeat Domain 3 ( RFWD3 ), presented significant association with PAAD prognosis in both stages of the population study. Dual-luciferase reporter and electrophoretic mobility shift assays demonstrated that rs4887783-G allele, which predicts the worse prognosis, enhanced the binding of transcript factor REST, thus elevating RFWD3 expression. Further phenotypic assays revealed that excess expression of RFWD3 promoted tumor cell migration without affecting their proliferation rate. RFWD3 was highly expressed in PAAD and might orchestrate the genes in the DNA repair process.

CONCLUSIONS

RFWD3 and its regulatory variant are novel genetic factors for PAAD prognosis.

GeMI: interactive interface for transformer-based Genomic Metadata Integration

The Gene Expression Omnibus (GEO) is a public archive containing >4 million digital samples from functional genomics experiments collected over almost two decades. The accompanying metadata describing the experiments suffer from redundancy, inconsistency and incompleteness due to the prevalence of free text and the lack of well-defined data formats and their validation. To remedy this situation, we created Genomic Metadata Integration (GeMI; http://gmql.eu/gemi/), a web application that learns to automatically extract structured metadata (in the form of key-value pairs) from the plain text descriptions of GEO experiments. The extracted information can then be indexed for structured search and used for various downstream data mining activities. GeMI works in continuous interaction with its users. The natural language processing transformer-based model at the core of our system is a fine-tuned version of the Generative Pre-trained Transformer 2 (GPT2) model that is able to learn continuously from the feedback of the users thanks to an active learning framework designed for the purpose. As a part of such a framework, a machine learning interpretation mechanism (that exploits saliency maps) allows the users to understand easily and quickly whether the predictions of the model are correct and improves the overall usability. GeMI’s ability to extract attributes not explicitly mentioned (such as sex, tissue type, cell type, ethnicity and disease) allows researchers to perform specific queries and classification of experiments, which was previously possible only after spending time and resources with tedious manual annotation. The usefulness of GeMI is demonstrated on practical research use cases.

Database URL

http://gmql.eu/gemi/

A cancer-associated RNA polymerase III identity drives robust transcription and expression of snaR-A noncoding RNA

RNA polymerase III (Pol III) includes two alternate isoforms, defined by mutually exclusive incorporation of subunit POLR3G (RPC7α) or POLR3GL (RPC7β), in mammals. The contributions of POLR3G and POLR3GL to transcription potential has remained poorly defined. Here, we discover that loss of subunit POLR3G is accompanied by a restricted repertoire of genes transcribed by Pol III. Particularly sensitive is snaR-A, a small noncoding RNA implicated in cancer proliferation and metastasis. Analysis of Pol III isoform biases and downstream chromatin features identifies loss of POLR3G and snaR-A during differentiation, and conversely, re-establishment of POLR3G gene expression and SNAR-A gene features in cancer contexts. Our results support a model in which Pol III identity functions as an important transcriptional regulatory mechanism. Upregulation of POLR3G, which is driven by MYC, identifies a subgroup of patients with unfavorable survival outcomes in specific cancers, further implicating the POLR3G-enhanced transcription repertoire as a potential disease factor.

RNA polymerase III changes its subunit composition during mammalian development. Here the authors report that loss of subunit POLR3G, which re-emerges in cancer, promotes expression of small NF90-associated RNA (snaR-A), a noncoding RNA implicated in cell proliferation and metastasis.

Mutual exclusivity of ESR1 and TP53 mutations in endocrine resistant metastatic breast cancer

Both TP53 and ESR1 mutations occur frequently in estrogen receptor positive (ER+) metastatic breast cancers (MBC) and their distinct roles in breast cancer tumorigenesis and progression are well appreciated. Recent clinical studies discovered mutual exclusivity between TP53 and ESR1 mutations in metastatic breast cancers; however, mechanisms underlying this intriguing clinical observation remain largely understudied and unknown. Here, we explored the interplay between TP53 and ESR1 mutations using publicly available clinical and experimental data sets. We first confirmed the robust mutational exclusivity using six independent cohorts with 1,056 ER+ MBC samples and found that the exclusivity broadly applies to all ER+ breast tumors regardless of their clinical and distinct mutational features. ESR1 mutant tumors do not exhibit differential p53 pathway activity, whereas we identified attenuated ER activity and expression in TP53 mutant tumors, driven by a p53-associated E2 response gene signature. Further, 81% of these p53-associated E2 response genes are either direct targets of wild-type (WT) p53-regulated transactivation or are mutant p53-associated microRNAs, representing bimodal mechanisms of ER suppression. Lastly, we analyzed the very rare cases with co-occurrences of TP53 and ESR1 mutations and found that their simultaneous presence was also associated with reduced ER activity. In addition, tumors with dual mutations showed higher levels of total and PD-L1 positive macrophages. In summary, our study utilized multiple publicly available sources to explore the mechanism underlying the mutual exclusivity between ESR1 and TP53 mutations, providing further insights and testable hypotheses of the molecular interplay between these two pivotal genes in ER+ MBC.

Identification of an immune gene-associated prognostic signature in patients with bladder cancer

A deeper understanding of the interaction between tumor cell and the immune microenvironment in bladder cancer may help select predictive and prognostic biomarkers. The current study aims to construct a prognostic signature for bladder cancer by analysis of molecular characteristics, as well as tumor-immune interactions. RNA-sequencing and clinical information from bladder cancer patients were downloaded from the TCGA database. The single sample Gene Sets Enrichment Analysis (ssGSEA) and Cell type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT) were employed to separate the samples into two clusters. Lasso Cox regression was performed to construct an immune gene signature for bladder cancer. The correlation between key target genes of immune checkpoint blockade and the prognostic signature was also analyzed. Dataset from Gene Expression Omnibus (GEO) was retrieved for validation. Two immunophenotypes and immunological characteristics were identified, and a 17-immune gene signature was constructed to provide an independent prognostic signature for bladder cancer. The signature was verified through external validation and correlated with genomic characteristics and clinicopathologic features. Finally, a nomogram was generated from the clinical characteristics and immune signature. Our study reveals a tumor-immune microenvironment signature useful for prognosis in bladder cancer. The results provide information on the potential development of treatment strategies for bladder cancer patients. Prospective studies are warranted to validate the prognostic capability of this model, but these data highlight the role of the microenvironment in the clinical outcome of patients.

Allele-specific H3K9me3 and DNA methylation co-marked CpG-rich regions serve as potential imprinting control regions in pre-implantation embryo

Parental DNA methylation and histone modifications undergo distinct global reprogramming in mammalian pre-implantation embryos, but the landscape of epigenetic crosstalk and its effects on embryogenesis are largely unknown. Here we comprehensively analyse the association between DNA methylation and H3K9me3 reprogramming in mouse pre-implantation embryos and reveal that CpG-rich genomic loci with high H3K9me3 signal and DNA methylation level (CHM) are hotspots of DNA methylation maintenance during pre-implantation embryogenesis. We further profile the allele-specific epigenetic map with unprecedented resolution in gynogenetic and androgenetic embryos, respectively, and identify 1,279 allele-specific CHMs, including 19 known imprinting control regions (ICRs). Our study suggests that 22 ICR-like regions (ICRLRs) may regulate allele-specific transcription similarly to known ICRs, and five of them are confirmed to be important for mouse embryo development. Taken together, our study reveals the widespread existence of allele-specific CHMs and largely extends the scope of allele-specific regulation in mammalian pre-implantation embryos.

A MYC inhibitor selectively alters the MYC and MAX cistromes and modulates the epigenomic landscape to regulate target gene expression

MYC regulates multiple gene programs, raising questions about the potential selectivity and downstream transcriptional consequences of MYC inhibitors as cancer therapeutics. Here, we examined the effect of a small-molecule MYC inhibitor, MYCi975, on the MYC/MAX cistromes, epigenome, transcriptome, and tumorigenesis. Integrating these data revealed three major classes of MYCi975-modulated gene targets: type 1 (down-regulated), type 2 (up-regulated), and type 3 (unaltered). While cell cycle and signal transduction pathways were heavily targeted by MYCi, RNA biogenesis and core transcriptional pathway genes were spared. MYCi975 altered chromatin binding of MYC and the MYC network family proteins, and chromatin accessibility and H3K27 acetylation alterations revealed MYCi975 suppression of MYC-regulated lineage factors AR/ARv7, FOXA1, and FOXM1. Consequently, MYCi975 synergistically sensitized resistant prostate cancer cells to enzalutamide and estrogen receptor-positive breast cancer cells to 4-hydroxytamoxifen. Our results demonstrate that MYCi975 selectively inhibits MYC target gene expression and provide a mechanistic rationale for potential combination therapies.

Transcriptional regulation and small compound targeting of ACE2 in lung epithelial cells

Angiotensin-converting enzyme 2 (ACE2) is the receptor of COVID-19 pathogen SARS-CoV-2, but the transcription factors (TFs) that regulate the expression of the gene encoding ACE2 (ACE2) have not been systematically dissected. In this study we evaluated TFs that control ACE2 expression, and screened for small molecule compounds that could modulate ACE2 expression to block SARS-CoV-2 from entry into lung epithelial cells. By searching the online datasets we found that 24 TFs might be ACE2 regulators with signal transducer and activator of transcription 3 (Stat3) as the most significant one. In human normal lung tissues, the expression of ACE2 was positively correlated with phosphorylated Stat3 (p-Stat3). We demonstrated that Stat3 bound ACE2 promoter, and controlled its expression in 16HBE cells stimulated with interleukin 6 (IL-6). To screen for medicinal compounds that could modulate ACE2 expression, we conducted luciferase assay using HLF cells transfected with ACE2 promoter-luciferase constructs. Among the 64 compounds tested, 6-O-angeloylplenolin (6-OAP), a sesquiterpene lactone in Chinese medicinal herb Centipeda minima (CM), represented the most potent ACE2 repressor. 6-OAP (2.5 µM) inhibited the interaction between Stat3 protein and ACE2 promoter, thus suppressed ACE2 transcription. 6-OAP (1.25-5 µM) and its parental medicinal herb CM (0.125%-0.5%) dose-dependently downregulated ACE2 in 16HBE and Beas-2B cells; similar results were observed in the lung tissues of mice following administration of 6-OAP or CM for one month. In addition, 6-OAP/CM dose-dependently reduced IL-6 production and downregulated chemokines including CXCL13 and CX3CL1 in 16HBE cells. Moreover, we found that 6-OAP/CM inhibited the entry of SARS-CoV-2 S protein pseudovirus into target cells. These results suggest that 6-OAP/CM are ACE2 inhibitors that may potentially protect lung epithelial cells from SARS-CoV-2 infection.

Interferon‑stimulated gene 15 promotes progression of endometrial carcinoma and weakens antitumor immune response

Endometrial carcinoma (EC) is one of the most common gynecological cancers with a poor prognosis. Therefore, clarifying the details of the molecular mechanisms is of great importance for EC diagnosis and clinical management. Interferon-stimulated gene 15 (ISG15) plays an important role in the development of various cancers. However, its role in EC remains unclear. High ISG15 expression was observed in EC, which was associated with poor clinical outcomes and pathological stage of patients with EC, thus representing a promising marker for EC progression. Further exploratory analysis revealed that the elevated ISG15 levels in EC were driven by aberrant DNA methylation, independent of copy number variation and specific transcription factor aberrations. Accordingly, knockdown of ISG15 by small interfering RNA attenuated the malignant cellular phenotype of EC cell lines, including proliferation and colony formation in vitro. Finally, investigation of the molecular mechanisms indicated that ISG15 promoted the cell cycle G1/S transition in EC. Furthermore, ISG15 promoted EC progression by activating the MYC proto-oncogene protein signaling pathway. Moreover, ECs with high levels of ISG15 harbored a more vital immune escape ability, evidenced not only by significantly less invasive CD8⁺ T cells, but also higher expression of T cell inhibitory factors, such as programmed death-ligand 1. These results suggest a tumor-promoting role of ISG15 in EC, which may be a promising marker for diagnosis, prognosis and therapeutic immunity.

Metabolic Reprogramming of Alloreactive T Cells Through TCR/MYC/mTORC1/E2F6 Signaling in aGvHD Patients

Acute graft-versus-host disease (aGvHD) is the most common complication after allogeneic hematopoietic stem cell transplantation (allo-HSCT) and significantly linked with morbidity and mortality. Although much work has been engaged to investigate aGvHD pathogenesis, the understanding of alloreactive T-cell activation remains incomplete. To address this, we studied transcriptional activation of carbohydrate, nucleotide, tricarboxylic acid (TCA) cycle, and amino acid metabolism of T cells before aGvHD onset by mining the Gene Expression Omnibus (GEO) datasets. Glycolysis had the most extensive correlation with other activated metabolic sub-pathways. Through Pearson correlation analyses, we found that glycolytic activation was positively correlated with activated CD4 memory T-cell subset and T-cell proliferation and migration. T-cell receptor (TCR), mechanistic target of rapamycin complex 1 (mTORC1), myelocytomatosis oncogene (MYC) signaling pathways and E2F6 might be “master regulators” of glycolytic activity. aGvHD predictive model constructed by glycolytic genes (PFKP, ENO3, and GAPDH) through logistic regression showed high predictive and discriminative value. Furthermore, higher expressions of PFKP, ENO3, and GAPDH in alloreactive T cells were confirmed in our pre-aGvHD patient cohort. And the predictive value of the aGvHD risk model was also validated. In summary, our study demonstrated that glycolytic activation might play a pivotal function in alloreactive T-cell activation before aGvHD onset and would be the potential target for aGvHD therapy.

The nuclear receptor ERR cooperates with the cardiogenic factor GATA4 to orchestrate cardiomyocyte maturation

Estrogen-related receptors (ERR) α and γ were shown recently to serve as regulators of cardiac maturation, yet the underlying mechanisms have not been delineated. Herein, we find that ERR signaling is necessary for induction of genes involved in mitochondrial and cardiac-specific contractile processes during human induced pluripotent stem cell-derived cardiomyocyte (hiPSC-CM) differentiation. Genomic interrogation studies demonstrate that ERRγ occupies many cardiomyocyte enhancers/super-enhancers, often co-localizing with the cardiogenic factor GATA4. ERRγ interacts with GATA4 to cooperatively activate transcription of targets involved in cardiomyocyte-specific processes such as contractile function, whereas ERRγ-mediated control of metabolic genes occurs independent of GATA4. Both mechanisms require the transcriptional coregulator PGC-1α. A disease-causing GATA4 mutation is shown to diminish PGC-1α/ERR/GATA4 cooperativity and expression of ERR target genes are downregulated in human heart failure samples suggesting that dysregulation of this circuitry may contribute to congenital and acquired forms of heart failure.

Mature cardiac muscle requires high mitochondrial ATP production and specialized contractile proteins. Here the authors demonstrate that cardiomyocyte-specific contractile maturation involves cooperation between the nuclear receptor ERRγ and cardiogenic transcription factor GATA4, but ERRγ controls metabolic genes independently.

GenomicDistributions: fast analysis of genomic intervals with Bioconductor

Background

Epigenome analysis relies on defined sets of genomic regions output by widely used assays such as ChIP-seq and ATAC-seq. Statistical analysis and visualization of genomic region sets is essential to answer biological questions in gene regulation. As the epigenomics community continues generating data, there will be an increasing need for software tools that can efficiently deal with more abundant and larger genomic region sets. Here, we introduce GenomicDistributions, an R package for fast and easy summarization and visualization of genomic region data.

Results

GenomicDistributions offers a broad selection of functions to calculate properties of genomic region sets, such as feature distances, genomic partition overlaps, and more. GenomicDistributions functions are meticulously optimized for best-in-class speed and generally outperform comparable functions in existing R packages. GenomicDistributions also offers plotting functions that produce editable ggplot objects. All GenomicDistributions functions follow a uniform naming scheme and can handle either single or multiple region set inputs.

Conclusions

GenomicDistributions offers a fast and scalable tool for exploratory genomic region set analysis and visualization. GenomicDistributions excels in user-friendliness, flexibility of outputs, breadth of functions, and computational performance. GenomicDistributions is available from Bioconductor (https://bioconductor.org/packages/release/bioc/html/GenomicDistributions.html).

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08467-y.

MUC1-C Dictates JUN and BAF-Mediated Chromatin Remodeling at Enhancer Signatures in Cancer Stem Cells

The oncogenic MUC1-C protein promotes dedifferentiation of castrate-resistant prostate cancer (CRPC) and triple-negative breast cancer (TNBC) cells. Chromatin remodeling is critical for the cancer stem cell (CSC) state; however, there is no definitive evidence that MUC1-C regulates chromatin accessibility and thereby expression of stemness-associated genes. We demonstrate that MUC1-C drives global changes in chromatin architecture in the dedifferentiation of CRPC and TNBC cells. Our results show that MUC1-C induces differentially accessible regions (DAR) across their genomes, which are significantly associated with differentially expressed genes (DEG). Motif and cistrome analysis further demonstrated MUC1-C-induced DARs align with genes regulated by the JUN/AP-1 family of transcription factors. MUC1-C activates the BAF chromatin remodeling complex, which is recruited by JUN in enhancer selection. In studies of the NOTCH1 gene, which is required for CRPC and TNBC cell self-renewal, we demonstrate that MUC1-C is necessary for (i) occupancy of JUN and ARID1A/BAF, (ii) increases in H3K27ac and H3K4me3 signals, and (iii) opening of chromatin accessibility on a proximal enhancer-like signature. Studies of the EGR1 and LY6E stemness-associated genes further demonstrate that MUC1-C-induced JUN/ARID1A complexes regulate chromatin accessibility on proximal and distal enhancer-like signatures. These findings uncover a role for MUC1-C in chromatin remodeling that is mediated at least in part by JUN/AP-1 and ARID1A/BAF in association with driving the CSC state.

IMPLICATIONS

These findings show that MUC1-C, which is necessary for the CRPC and TNBC CSC state, activates a novel pathway involving JUN/AP-1 and ARID1A/BAF that regulates chromatin accessibility of stemness-associated gene enhancers.

Ogt Demonstrated Conspicuous Clinical Significance in Cancers, from Pan-Cancer to Small-Cell Lung Cancer

The clinical progression of small-cell lung cancer (SCLC) remains pessimistic. The aim of the present study was to promote the understanding of the clinical significance and mechanism of O-linked N-acetylglucosamine (GlcNAc) transferase (OGT) in SCLC. Wilcoxon tests, standardized mean difference (SMD), and Kruskal–Wallis tests were utilized to compare OGT level differences among the experimental and control groups. The univariate Cox regression analysis, Kaplan–Meier curves, and receiver operating characteristic curves were applied to determine OGT's clinical relevance in cancers. The Spearman correlation analysis and enrichment analysis were utilized to explore the underlying mechanisms of OGT in cancers. For the first time in the field, we provide an overview of OGT in 32 cancers using a large number of samples (n = 21,196), determining distinct OGT expression in 25 cancers and its prognosis effects in 12 cancers. Furthermore, using 950 samples from multiple sources, upregulated OGT was found in both mRNA and protein levels in SCLC (SMD = 0.93, 95% CI [0.24, 1.63]). Higher OGT levels represented a more unfavorable disease-free interval for SCLC patients (p < 0.001). The research also identified OGT expression as a potential marker for SCLC prediction (sensitivity = 0.79, specificity = 0.86, and AUC = 0.88). The high expression of OGT in SCLC may result from the positive regulation of two transcription factors—DEK and XRN2. We primarily investigated the underlying mechanisms of OGT in SCLC. Herein, based on the analyses from pan-cancer to SCLC, OGT demonstrated conspicuous clinical significance. OGT may be an underlying biomarker for the treatment and identification of some cancers, including SCLC.

TargetGeneReg 2.0: a comprehensive web-atlas for p53, p63, and cell cycle-dependent gene regulation

In recent years, our web-atlas at www.TargetGeneReg.org has enabled many researchers to uncover new biological insights and to identify novel regulatory mechanisms that affect p53 and the cell cycle – signaling pathways that are frequently dysregulated in diseases like cancer. Here, we provide a substantial upgrade of the database that comprises an extension to include non-coding genes and the transcription factors ΔNp63 and RFX7. TargetGeneReg 2.0 combines gene expression profiling and transcription factor DNA binding data to determine, for each gene, the response to p53, ΔNp63, and cell cycle signaling. It can be used to dissect common, cell type and treatment-specific effects, identify the most promising candidates, and validate findings. We demonstrate the increased power and more intuitive layout of the resource using realistic examples.