AgingBank: a manually curated knowledgebase and high-throughput analysis platform that provides experimentally supported multi-omics data relevant to aging in multiple species.

Discovering the biological basis of aging is one of the greatest remaining challenges for biomedical field. Work on the biology of aging has discovered a range of interventions and pathways that control aging rate. Thus, we developed AgingBank (http://bio-bigdata.hrbmu.edu.cn/AgingBank) which was a manually curated comprehensive database and high-throughput analysis platform that provided experimentally supported multi-omics data relevant to aging in multiple species. AgingBank contained 3771 experimentally verified aging-related multi-omics entries from studies across more than 50 model organisms, including human, mice, worms, flies and yeast. The records included genome (single nucleotide polymorphism, copy number variation and somatic mutation), transcriptome [mRNA, long non-coding RNA (lncRNA), microRNA (miRNA) and circular RNA (circRNA)], epigenome (DNA methylation and histone modification), other modification and regulation elements (transcription factor, enhancer, promoter, gene silence, alternative splicing and RNA editing). In addition, AgingBank was also an online computational analysis platform containing five useful tools (Aging Landscape, Differential Expression Analyzer, Data Heat Mapper, Co-Expression Network and Functional Annotation Analyzer), nearly 112 high-throughput experiments of genes, miRNAs, lncRNAs, circRNAs and methylation sites related with aging. Cancer & Aging module was developed to explore the relationships between aging and cancer. Submit & Analysis module allows users upload and analyze their experiments data. AginBank is a valuable resource for elucidating aging-related biomarkers and relationships with other diseases.

Comprehensive characterization genetic regulation and chromatin landscape of enhancer-associated long non-coding RNAs and their implication in human cancer.

Long non-coding RNAs (lncRNAs) that emanate from enhancer regions (defined as enhancer-associated lncRNAs, or elncRNAs) are emerging as critical regulators in disease progression. However, their biological characteristics and clinical relevance have not been fully portrayed. Here, based on the traditional expression quantitative loci (eQTL) and our optimized residual eQTL method, we comprehensively described the genetic effect on elncRNA expression in more than 300 lymphoblastoid cell lines. Meanwhile, a chromatin atlas of elncRNAs relative to the genetic regulation state was depicted. By applying the maximum likelihood estimate method, we successfully identified causal elncRNAs for protein-coding gene expression reprogramming and showed their associated single nucleotide polymorphisms (SNPs) favor binding of transcription factors. Further epigenome analysis revealed two immune-associated elncRNAs AL662844.4 and LINC01215 possess high levels of H3K27ac and H3K4me1 in human cancer. Besides, pan-cancer analysis of 3D genome, transcriptome, and regulatome data showed they potentially regulate tumor-immune cell interaction through affecting MHC class I genes and CD47, respectively. Moreover, our study showed there exist associations between elncRNA and patient survival. Finally, we made a user-friendly web interface available for exploring the regulatory relationship of SNP-elncRNA-protein-coding gene triplets (http://bio-bigdata.hrbmu.edu.cn/elncVarReg). Our study provides critical mechanistic insights for elncRNA function and illustrates their implications in human cancer.

Metabolic-Related Gene Prognostic Index for Predicting Prognosis, Immunotherapy Response, and Candidate Drugs in Ovarian Cancer.

Ovarian cancer (OC) is a highly heterogeneous disease, with patients at different tumor staging having different survival times. Metabolic reprogramming is one of the key hallmarks of cancer; however, the significance of metabolism-related genes in the prognosis and therapy outcomes of OC is unclear. In this study, we used weighted gene coexpression network analysis and differential expression analysis to screen for metabolism-related genes associated with tumor staging. We constructed the metabolism-related gene prognostic index (MRGPI), which demonstrated a stable prognostic value across multiple clinical trial end points and multiple validation cohorts. The MRGPI population had its distinct molecular features, mutational characteristics, and immune phenotypes. In addition, we investigated the response to immunotherapy in MRGPI subgroups and found that patients with low MRGPI were prone to benefit from anti-PD-1 checkpoint blockade therapy and exhibited a delayed treatment effect. Meanwhile, we identified four candidate therapeutic drugs (ABT-737, crizotinib, panobinostat, and regorafenib) for patients with high MRGPI, and we evaluated the pharmacokinetics and safety of the candidate drugs. In summary, the MRGPI was a robust clinical feature that could predict patient prognosis, immunotherapy response, and candidate drugs, facilitating clinical decision making and therapeutic strategy of OC.

Exploration and bioinformatic prediction for profile of mRNA bound to circular RNA BTBD7_hsa_circ_0000563 in coronary artery disease.

BACKGROUND: As a novel circRNA, BTBD7_hsa_circ_0000563 has not been fully investigated in coronary artery disease (CAD). Our aim is to reveal the possible functional role and regulatory pathway of BTBD7_hsa_circ_0000563 in CAD via exploring genes combined with BTBD7_hsa_circ_0000563. METHODS: A total of 45 peripheral blood mononuclear cell (PBMC) samples of CAD patients were enrolled. The ChIRP-RNAseq assay was performed to directly explore genes bound to BTBD7_hsa_circ_0000563. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were conducted to reveal possible functions of these genes. The interaction network was constructed by the STRING database and the Cytoscape software. The Cytoscape software were used again to identify clusters and hub genes of genes bound to BTBD7_hsa_circ_0000563. The target miRNAs of hub genes were predicted via online databases. RESULTS: In this study, a total of 221 mRNAs directly bound to BTBD7_hsa_circ_0000563 were identified in PBMCs of CAD patients via ChIRP-RNAseq. The functional enrichment analysis revealed that these mRNAs may participate in translation and necroptosis. Moreover, the interaction network showed that there may be a close relationship between these mRNAs. Eight clusters can be further subdivided from the interaction network. RPS3 and RPSA were identified as hub genes and hsa-miR-493-5p was predicted to be the target miRNA of RPS3. CONCLUSIONS: BTBD7_hsa_circ_0000563 and mRNAs directly bound to it may influence the initiation and progression of CAD, among which RPS3 and RPSA may be hub genes. These findings may provide innovative ideas for further research on CAD.

Pan-cancer transcriptomic analysis identified six classes of immunosenescence genes revealed molecular links between aging, immune system and cancer.

Aging is a complex process that significantly impacts the immune system. The aging-related decline of the immune system, termed immunosenescence, can lead to disease development, including cancer. The perturbation of immunosenescence genes may characterize the associations between cancer and aging. However, the systematical characterization of immunosenescence genes in pan-cancer remains largely unexplored. In this study, we comprehensively investigated the expression of immunosenescence genes and their roles in 26 types of cancer. We developed an integrated computational pipeline to identify and characterize immunosenescence genes in cancer based on the expression profiles of immune genes and clinical information of patients. We identified 2218 immunosenescence genes that were significantly dysregulated in a wide variety of cancers. These immunosenescence genes were divided into six categories based on their relationships with aging. Besides, we assessed the importance of immunosenescence genes in clinical prognosis and identified 1327 genes serving as prognostic markers in cancers. BTN3A1, BTN3A2, CTSD, CYTIP, HIF1AN, and RASGRP1 were associated with ICB immunotherapy response and served as prognostic factors after ICB immunotherapy in melanoma. Collectively, our results furthered the understanding of the relationship between immunosenescence and cancer and provided insights into immunotherapy for patients.

Long non-coding RNA in coronary artery disease: the role of PDXDC1-AS1 and SFI1-AS1.

This study investigates the interaction between long non-coding RNAs (lncRNAs) and metabolic risk factors that contribute to coronary artery disease (CAD). A total transcriptome high throughput sequencing study was conducted on peripheral blood mononuclear cells from five patients with CAD and five healthy controls. Validation assay by qRT-PCR was conducted among 270 patients and 47 controls. Finally, to evaluate the lncRNAs' diagnostic value for CAD, the Spearman correlation test and receiver operating characteristic curve (ROC) analysis were utilized. Additionally, univariate and multivariate logistic regression along with crossover analyses were conducted to identify the interaction between lncRNA and environmental risk factors. A total of 2149 of 26,027 lncRNAs identified by RNA sequencing were differentially expressed in CAD patients compared to controls. Validation by qRT-PCR showed significantly different relative expression levels for lncRNAs PDXDC1-AS1, SFI1-AS1, RP13-143G15.3, DAPK1-IT1, PPIE-AS1, and RP11-362A1.1 between the two groups (all P<0.05). The area under the ROC values of PDXDC1-AS1 and SFI1-AS1 is 0.645 (sensitivity=0.443 and specificity=0.920) and 0.629 (sensitivity=0.571 and specificity=0.909), especially. Multivariate logistic regression analyses showed that lncRNAs PDXDC1-AS1 (OR=2.285, 95%CI=1.390-3.754, p=0.001) and SFI1-AS1 (OR=1.163, 95%CI=1.163-2.264, p=0.004) were protective factors against CAD. Under the additive model, cross-over analyses demonstrated significant interactions between lncRNAs PDXDC1-AS1 and smoking in relation to CAD risk (S=3.871, 95%CI=1.140-6.599). PDXDC1-AS1 and SFI1-AS1 were sensitive and specific biomarkers for CAD and exhibited synergistic effects with certain environmental factors. These results highlighted their potential use as CAD diagnostic biomarkers for future research.

Reconstructing the immunosenescence core pathway reveals global characteristics in pan-cancer.

Immunosenescence has been demonstrated to play an important role in tumor progression. However, there is lacking comprehensive analyses of immunosenescence-related pathways. Meanwhile, the sex disparities of immunosenescence in cancer are still poorly understood. In this study, we analyzed the multi-omics data of 12,836 tumor samples, including genomics, transcriptomics, epigenomics, proteomics, and metabolomics. We systematically identified immunosenescence pathways that were disordered across cancer types. The mutations and copy number variations of immunosenescence pathways were found to be more active in pan-cancer. We reconstructed the immunosenescence core pathways (ISC-pathways) to improve the ability of prognostic stratification in 33 cancer types. We also found the head and neck squamous carcinoma (HNSC) contained abundant sex-specific immunosenescence features and showed sex differences in survival. We found that OSI-027 was a potential sex-specific drug in HNSC tumors, which tended to be more effective in male HNSC by targeting the MTOR gene in the PI3K-Akt signaling pathway. In conclusion, our study provided a systematic understanding of immunosenescence pathways and revealed the global characteristics of immunosenescence in pan-cancer. We highlighted MTOR gene could be a powerful immunosenescence biomarker of HNSC that helps to develop sex-specific immunosenescence drugs.

A Freestanding 3D Skeleton with Gradationally Distributed Lithiophilic Sites for Realizing Stable Lithium Anodes.

Lithium (Li) metal anodes are drawing considerable attention owing to their ultrahigh theoretical capacities and low electrochemical reduction potentials. However, their commercialization has been hampered by safety hazards induced by continuous dendrite growth. These issues can be alleviated using the ZnO-modified 3D carbon-based host containing carbon nanotubes (CNTs) and carbon felt (CF) fabricated by electroplating in the present study (denoted as ZnO/CNT@CF). The constructed skeleton has lithiophilic ZnO that is gradationally distributed along its thickness. The utilization of an inverted ZnO/CNT@CF-Li anode obtained by flipping over the carbon skeleton after Li electrodeposition is also reported herein. The synergistic effect of the Li metal and lithiophilic sites reduces the nucleation overpotential, thus inducing Li+ to preferentially deposit inside the porous carbon-based scaffold. The composite electrode compels Li to grow away from the separator, thereby significantly improving battery safety. A symmetric cell with the inverted ZnO/CNT@CF-Li electrode operates steadily for 700 cycles at 1 mA cm-2 and 1 mAh cm-2 . Moreover, the ZnO/CNT@CF-Li|S cell exhibits an initial areal capacity of 10.9 mAh cm-2 at a S loading of 10.4 mg cm-2 and maintains a capacity of 3.0 mAh cm-2 after 320 cycles.

Circular RNA ZBTB46 depletion alleviates the progression of Atherosclerosis by regulating the ubiquitination and degradation of hnRNPA2B1 via the AKT/mTOR pathway.

BACKGROUND: CircZBTB46 has been identified as being associated with the risk of coronary artery disease (CAD) and has the potential to be a diagnostic biomarker for CAD. However, the specific function and detailed mechanism of circZBTB46 in CAD are still unknown. METHODS: The expression levels and properties of circRNAs were examined using qRT‒PCR, RNA FISH, and subcellular localization analysis. ApoE-/- mice fed a high-fat diet were used to establish an atherosclerosis model. HE, Masson, and Oil Red O staining were used to analyze the morphological features of the plaque. CCK-8, Transwell, and wound healing assays, and flow cytometric analysis were used to evaluate cell proliferation, migration, and apoptosis. RNA pull-down, silver staining, mass spectrometry analysis, and RNA-binding protein immunoprecipitation (RIP) were performed to identify the interacting proteins of circZBTB46. RESULTS: CircZBTB46 is highly conserved and is significantly upregulated in atherosclerotic lesions. Functional studies revealed that knockdown of circZBTB46 significantly decreased the atherosclerotic plaque area, attenuating the progression of atherosclerosis. In addition, silencing circZBTB46 inhibited cell proliferation and migration and induced apoptosis. Mechanistically, circZBTB46 physically interacted with hnRNPA2B1 and suppressed its degradation, thereby regulating cell functions and the formation of aortic atherosclerotic plaques. Additionally, circZBTB46 was identified as a functional mediator of PTEN-dependent regulation of the AKT/mTOR signaling pathway and thus affected cell proliferation and migration and induced apoptosis. CONCLUSION: Our study provides the first direct evidence that circZBTB46 functions as an important regulatory molecule for CAD progression by interacting with hnRNPA2B1 and regulating the PTEN/AKT/mTOR pathway.

Lnc2Cancer 3.0: an updated resource for experimentally supported lncRNA/circRNA cancer associations and web tools based on RNA-seq and scRNA-seq data.

An updated Lnc2Cancer 3.0 (http://www.bio-bigdata.net/lnc2cancer or http://bio-bigdata.hrbmu.edu.cn/lnc2cancer) database, which includes comprehensive data on experimentally supported long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs) associated with human cancers. In addition, web tools for analyzing lncRNA expression by high-throughput RNA sequencing (RNA-seq) and single-cell RNA-seq (scRNA-seq) are described. Lnc2Cancer 3.0 was updated with several new features, including (i) Increased cancer-associated lncRNA entries over the previous version. The current release includes 9254 lncRNA-cancer associations, with 2659 lncRNAs and 216 cancer subtypes. (ii) Newly adding 1049 experimentally supported circRNA-cancer associations, with 743 circRNAs and 70 cancer subtypes. (iii) Experimentally supported regulatory mechanisms of cancer-related lncRNAs and circRNAs, involving microRNAs, transcription factors (TF), genetic variants, methylation and enhancers were included. (iv) Appending experimentally supported biological functions of cancer-related lncRNAs and circRNAs including cell growth, apoptosis, autophagy, epithelial mesenchymal transformation (EMT), immunity and coding ability. (v) Experimentally supported clinical relevance of cancer-related lncRNAs and circRNAs in metastasis, recurrence, circulation, drug resistance, and prognosis was included. Additionally, two flexible online tools, including RNA-seq and scRNA-seq web tools, were developed to enable fast and customizable analysis and visualization of lncRNAs in cancers. Lnc2Cancer 3.0 is a valuable resource for elucidating the associations between lncRNA, circRNA and cancer.

Identification of circular RNA BTBD7_hsa_circ_0000563 as a novel biomarker for coronary artery disease and the functional discovery of BTBD7_hsa_circ_0000563 based on peripheral blood mononuclear cells: a case control study.

BACKGROUND: BTBD7_hsa_circ_0000563 is a novel circRNA and contains conserved binding sites with RNA-binding proteins. However, BTBD7_hsa_circ_0000563 has not been fully studied in coronary artery disease (CAD). We aimed to clarify the diagnostic value and the possible functional role of BTBD7_hsa_circ_0000563 in CAD. METHODS: A total of 276 human peripheral blood mononuclear cell (PBMC) samples were employed. The circularization of BTBD7_hsa_circ_0000563 was verified via Sanger sequencing. The expression level of BTBD7_hsa_circ_0000563 in CAD samples and control individuals was analysed via qRT-PCR. The diagnostic potential of BTBD7_hsa_circ_0000563 was evaluated using Spearman's analysis, univariate and multivariable logistic regression analysis, and receiver-operator characteristic (ROC) curve analysis. ChIRP-MS was performed to directly explore the proteins bound to BTBD7_hsa_circ_0000563. Bioinformatic analysis was conducted to investigate the possible functions and interactions of proteins bound to BTBD7_hsa_circ_0000563. RESULTS: In the present study, BTBD7_hsa_circ_0000563 was verified as a circular RNA in the PBMCs of CAD patients. The expression level of BTBD7_hsa_circ_0000563 in the CAD group was significantly lower than that in the control group. The area under the ROC curve was 0.690. ChIRP-MS found seven proteins that were directly bound to BTBD7_hsa_circ_0000563. Bioinformatic analysis of these seven proteins showed that the mitophagy and DNA repair pathways were enriched. These proteins interacted with each other to a certain extent. CONCLUSION: BTBD7_hsa_circ_0000563 may be a novel biomarker for the diagnosis of CAD and may influence the initiation and progression of CAD. These studies may reveal new possibilities for the diagnosis and treatment of CAD.

Characteristics of circular RNAs expression of peripheral blood mononuclear cells in humans with coronary artery disease.

Circular RNAs (circRNAs) function as promising biomarkers and therapeutic targets for coronary artery disease due to their high stability, covalently closed structure, and potential gene regulation. We aimed to identify the expression profile and role of circular RNAs (circRNAs) in coronary artery disease (CAD). We performed RNA sequence analysis of circRNAs in peripheral blood mononuclear cells of five patients with CAD and five controls. Bioinformatics analyses were adopted to explore biological functions of differentially expressed circRNAs. The miRanda and TargetScan tools were used to predict the microRNA (miRNA)-targeting interactions and to construct a triple network of differentially expressed gene-circRNA-miRNA-mRNA. In total, 13,160 downregulated and 12,905 upregulated circRNAs were identified in CAD. A gene ontology annotation analysis showed that genes in the network were involved in organelle organization, cell cycle, mitotic cycle, and cellular metabolic process. Parental genes of the 10 dysregulated circRNAs were involved in metabolism and protein modification, and these circRNAs might regulate gene expression associated with CAD via miRNA sponges. As potential competing endogenous RNAs (ceRNAs), dysregulated circRNAs may be involved in the pathogenesis of CAD, which provides new insights into the diagnosis and prognosis of coronary artery disease.

Identifying and characterizing lincRNA genomic clusters reveals its cooperative functions in human cancer.

BACKGROUND: Emerging evidence has revealed that some long intergenic non-coding RNAs (lincRNAs) are likely to form clusters on the same chromosome, and lincRNA genomic clusters might play critical roles in the pathophysiological mechanism. However, the comprehensive investigation of lincRNA clustering is rarely studied, particularly the characterization of their functional significance across different cancer types. METHODS: In this study, we firstly constructed a computational method basing a sliding window approach for systematically identifying lincRNA genomic clusters. We then dissected these lincRNA genomic clusters to identify common characteristics in cooperative expression, conservation among divergent species, targeted miRNAs, and CNV frequency. Next, we performed comprehensive analyses in differentially-expressed patterns and overall survival outcomes for patients from The Cancer Genome Atlas (TCGA) and The Genotype-Tissue Expression (GTEx) across multiple cancer types. Finally, we explored the underlying mechanisms of lincRNA genomic clusters by functional enrichment analysis, pathway analysis, and drug-target interaction. RESULTS: We identified lincRNA genomic clusters according to the algorithm. Clustering lincRNAs tended to be co-expressed, highly conserved, targeted by more miRNAs, and with similar deletion and duplication frequency, suggesting that lincRNA genomic clusters may exert their effects by acting in combination. We further systematically explored conserved and cancer-specific lincRNA genomic clusters, indicating they were involved in some important mechanisms of disease occurrence through diverse approaches. Furthermore, lincRNA genomic clusters can serve as biomarkers with potential clinical significance and involve in specific pathological processes in the development of cancer. Moreover, a lincRNA genomic cluster named Cluster127 in DLK1-DIO3 imprinted locus was discovered, which contained MEG3, MEG8, MEG9, MIR381HG, LINC02285, AL132709.5, and AL132709.1. Further analysis indicated that Cluster127 may have the potential for predicting prognosis in cancer and could play their roles by participating in the regulation of PI3K-AKT signaling pathway. CONCLUSIONS: Clarification of the lincRNA genomic clusters specific roles in human cancers could be beneficial for understanding the molecular pathogenesis of different cancer types.

Comprehensive quantitative radiogenomic evaluation reveals novel radiomic subtypes with distinct immune pattern in glioma.

BACKGROUND: Accurate classification of gliomas is critical to the selection of immunotherapy, and MRI contains a large number of radiomic features that may suggest some prognostic relevant signals. We aim to predict new subtypes of gliomas using radiomic features and characterize their survival, immune, genomic profiles and drug response. METHODS: We initially obtained 341 images of 36 patients from the CPTAC dataset for the development of deep learning models. Further 1812 images of 111 patients from TCGA_GBM and 152 images of 53 patients from TCGA_LGG were collected for testing and validation. A deep learning method based on Mask R-CNN was developed to identify new subtypes of glioma patients and compared the survival status, immune infiltration patterns, genomic signatures, specific drugs, and predictive models of different subtypes. RESULTS: 200 glioma patients (mean age, 33 years ± 19 [standard deviation]) were enrolled. The accuracy of the deep learning model for identifying tumor regions achieved 88.3 % (98/111) in the test set and 83 % (44/53) in the validation set. The sample was divided into two subtypes based on radiomic features showed different prognostic outcomes (hazard ratio, 2.70). According to the results of the immune infiltration analysis, the subtype with a poorer prognosis was defined as the immunosilencing radiomic (ISR) subtype (n = 43), and the other subtype was the immunoactivated radiomic (IAR) subtype (n = 53). Subtype-specific genomic signatures distinguished celllines into ISR celllines (n = 9) and control celllines (n = 13), and identified eight ISR-specific drugs, four of which were validated by the OCTAD database. Three machine learning-based classifiers showed that radiomic and genomic co-features better predicted the radiomic subtypes of gliomas. CONCLUSIONS: These findings provide insights into how radiogenomic could identify specific subtypes that predict prognosis, immune and drug sensitivity in a non-invasive manner.

A Bifunctional Fluorine-Free Electrolyte Additive for Realizing Dendrite-Free Lithium Anodes.

Owing to the strong energy advantage of lithium anodes, the development of lithium-metal batteries has become an inevitable trend. However, plagued by the instability of solid-electrolyte interphase (SEI) films, lithium metal anodes face challenges such as lithium dendrite formation and volume expansion. Studies have proven that modulating the composition and structure of SEI films by using electrolyte additives is a convenient and valid method. Currently, it is widely accepted that fluoride is an effective additive but, based on the high cost of fluoride production and environmental concerns, the development of fluoride-free additives is of great significance. In this work, the bifunctional additive N,O-bis(trimethylsilyl)acetamide (BSA) is proposed, which can build up a SEI layer that is rich in SiOx and Li3 N on the surface of the lithium anode to control the deposition behavior of lithium and clean the electrolyte of HF to protect the electrode. The experimental results indicate that BSA suppresses the generation of lithium dendrites and controls the volume expansion of lithium anodes. Moreover, compared with the commonly used carbonate electrolytes, the battery containing BSA has the best overall performance. Methodologically, the results can be extended to other additives containing Si-O functional groups to replace the same type of fluorine-containing additives.

Detailed profiling of m6A modified circRNAs and synergistic effects of circRNA and environmental risk factors for coronary artery disease.

The modification of N6-methyladenosine (m6A) modification is implicated in human diseases. However, considerable uncertainty is associated with the regulatory mechanisms of m6A circRNAs in coronary artery disease (CAD), which require further clarification. In this study, m6A-modified RNA immunoprecipitation sequencing (MeRIP-seq) was conducted to investigate m6A-modified circRNAs in human coronary artery smooth muscle cells (HCASMCs) and to identify potential biomarkers for CAD. A total of 830 and 331 up- and down-regulated m6A peaks, (corresponding to 463 and 243 up- and down-regulated circRNAs, respectively), were identified in HCASMCs in a pathological condition. Functional analysis suggested that these circRNAs appeared to participate in intracellular protein, histone deacetylase complex, ATP-dependent activity, autophagy, and AMPK signaling pathway. Four candidate circRNAs were selected for further evaluation in HCASMCs and human samples. The results suggested that hsa_circHECTD1 and hsa_circZBTB46 were significantly increased in patients with CAD (p-value = 0.039 and p-value = 0.014) and may act as potential diagnostic biomarkers of CAD. Furthermore, statistical results showed that hsa_circHECTD1 and hsa_circSEC62 were positively correlated with triglyceride (TG) (r = 0.213, p-value = 0.014) and Gensini Score (used to quantify the severity of CAD) (r = 0.349, p-value <0.001), respectively. Logistic regression revealed that hsa_circZBTB46 was strongly correlated with the incidence of CAD, and the synergistic effects of circRNAs and hypertension enhanced the risk of CAD. These results show that hsa_circHECTD1 and hsa_circZBTB46 may be new targets for further studies, and this study enhances our understanding of the effects of m6A-circRNAs on the pathogenesis of CAD.

Interaction between the expression of hsa_circRPRD1A and hsa_circHERPUD2 and classical coronary risk factors promotes the development of coronary artery disease.

BACKGROUND: Recent studies suggest that classical coronary risk factors play a significant role in the pathogenesis of coronary artery disease. Our study aims to explore the interaction of circRNA with classical coronary risk factors in coronary atherosclerotic disease. METHOD: Combined analysis of RNA sequencing results from coronary segments and peripheral blood mononuclear cells of patients with coronary atherosclerotic disease was employed to identify critical circRNAs. Competing endogenous RNA networks were constructed by miRanda-3.3a and TargetScan7.0. The relative expression quantity of circRNA in peripheral blood mononuclear cells was determined by qRT-PCR in a large cohort including 256 patients and 49 controls. Spearman's correlation test, receiver operating characteristic curve analysis, multivariable logistic regression analysis, one-way analysis of variance, and crossover analysis were performed. RESULTS: A total of 34 circRNAs were entered into our study, hsa_circRPRD1A, hsa_circHERPUD2, hsa_circLMBR1, and hsa_circDHTKD1 were selected for further investigation. A circRNA-miRNA-mRNA network is composed of 20 microRNAs and 66 mRNAs. The expression of hsa_circRPRD1A (P = 0.004) and hsa_circHERPUD2 (P = 0.003) were significantly down-regulated in patients with coronary artery disease compared to controls. The area under the curve of hsa_circRPRD1A and hsa_circHERPUD2 is 0.689 and 0.662, respectively. Univariate and multivariable logistic regression analyses identified hsa_circRPRD1A (OR = 0.613, 95%CI:0.380-0.987, P = 0.044) as a protective factor for coronary artery disease. Based on the additive model, crossover analysis demonstrated that there was an antagonistic interaction between the expression of hsa_circHERPUD2 and alcohol consumption in subjects with coronary artery disease. CONCLUSION: Our findings imply that hsa_circRPRD1A and hsa_circHERPUD2 could be used as biomarkers for the diagnosis of coronary artery disease and provide epidemiological support for the interactions between circRNAs and classical coronary risk factors.

Immune Pathways with Aging Characteristics Improve Immunotherapy Benefits and Drug Prediction in Human Cancer.

(1) Background: Perturbation of immune-related pathways can make substantial contributions to cancer. However, whether and how the aging process affects immune-related pathways during tumorigenesis remains largely unexplored. (2) Methods: Here, we comprehensively investigated the immune-related genes and pathways among 25 cancer types using genomic and transcriptomic data. (3) Results: We identified several pathways that showed aging-related characteristics in various cancers, further validated by conventional aging-related gene sets. Genomic analysis revealed high mutation burdens in cytokines and cytokines receptors pathways, which were strongly correlated with aging in diverse cancers. Moreover, immune-related pathways were found to be favorable prognostic factors in melanoma. Furthermore, the expression level of these pathways had close associations with patient response to immune checkpoint blockade therapy in melanoma and non-small cell lung cancer. Applying a net-work-based method, we predicted immune- and aging-related genes in pan-cancer and utilized these genes for potential immunotherapy drug discovery. Mapping drug target data to our top-ranked genes identified potential drug targets, FYN, JUN, and SRC. (4) Conclusions: Taken together, our systematic study helped interpret the associations among immune-related pathways, aging, and cancer and could serve as a resource for promoting clinical treatment.

Tumor biology, immune infiltration and liver function define seven hepatocellular carcinoma subtypes linked to distinct drivers, survival and drug response.

BACKGROUND & AIMS: Tumor heterogeneity is jointly determined by the components of the tumor ecosystem (TES) including tumor cells, immune cells, stromal cells, and non-cellular components. We aimed to identify subtypes using TES-related genes and determine subtype specific drivers and treatments for hepatocellular carcinoma (HCC). METHODS: We collected 68 genesets depicting tumor biology, immune infiltration, and liver function, totaling 2831 genes, and collected mRNA profiles and clinical data for over 6000 tumors from 65 datasets in the GEO, TCGA, ICGC, and several other databases. We designed a three-step clustering pipeline to identify subtypes. The microenvironment, genomic alteration, and drug response differences were systematically compared among subtypes. RESULTS: Seven subtypes (TES-1/2/3/4/5/6/7) were revealed in 159 tumors from the CHCC-HBV cohort. We constructed a single sample classifier using paired genes (sscpgsTES). TES subtypes were significantly associated with multiple clinical variables including etiology, and survival in 14 of 17 cohorts and the meta-cohort. TES-1 had the poorest prognosis and highest proliferation level. Both TES-2 and TES-7 were immune-enriched, however, TES-2 had a significantly worse prognosis, and hypoxic and immunosuppressive microenvironment. TES-4 had activated Wnt pathway, driven by CTNNB1 mutation. Good prognosis TES-6 exhibited the best differentiation. TES-5 and TES-3 were considered as novel subclasses by comparing with ten previous subtyping systems. TES-5 tumors had high AFP but good overall survival, and ∼45% of them harbored AXIN1 mutation. TES-3 was immune and stromal desert, may be driven by high copy number alteration burden, and had the poorest response to immune checkpoint inhibitor. TES-1 and TES-2 had significantly lower response to transarterial chemoembolization, but they showed significantly higher sensitivity to compound YM-155. CONCLUSIONS: Tumor ecosystem subtypes expand existing HCC subtyping systems, have distinct drivers, prognosis, and treatment vulnerabilities.

Proteomic characterization of epithelial ovarian cancer delineates molecular signatures and therapeutic targets in distinct histological subtypes.

Clear cell carcinoma (CCC), endometrioid carcinoma (EC), and serous carcinoma (SC) are the major histological subtypes of epithelial ovarian cancer (EOC), whose differences in carcinogenesis are still unclear. Here, we undertake comprehensive proteomic profiling of 80 CCC, 79 EC, 80 SC, and 30 control samples. Our analysis reveals the prognostic or diagnostic value of dysregulated proteins and phosphorylation sites in important pathways. Moreover, protein co-expression network not only provides comprehensive view of biological features of each histological subtype, but also indicates potential prognostic biomarkers and progression landmarks. Notably, EOC have strong inter-tumor heterogeneity, with significantly different clinical characteristics, proteomic patterns and signaling pathway disorders in CCC, EC, and SC. Finally, we infer MPP7 protein as potential therapeutic target for SC, whose biological functions are confirmed in SC cells. Our proteomic cohort provides valuable resources for understanding molecular mechanisms and developing treatment strategies of distinct histological subtypes.