634 research outputs found

    Multiomic Investigations into Lung Health and Disease

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    Diseases of the lung account for more than 5 million deaths worldwide and are a healthcare burden. Improving clinical outcomes, including mortality and quality of life, involves a holistic understanding of the disease, which can be provided by the integration of lung multi-omics data. An enhanced understanding of comprehensive multiomic datasets provides opportunities to leverage those datasets to inform the treatment and prevention of lung diseases by classifying severity, prognostication, and discovery of biomarkers. The main objective of this review is to summarize the use of multiomics investigations in lung disease, including multiomics integration and the use of machine learning computational methods. This review also discusses lung disease models, including animal models, organoids, and single-cell lines, to study multiomics in lung health and disease. We provide examples of lung diseases where multi-omics investigations have provided deeper insight into etiopathogenesis and have resulted in improved preventative and therapeutic interventions

    The repertoire and features of human platelet microRNAs

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    Playing a central role in the maintenance of hemostasis as well as in thrombotic disorders, platelets contain a relatively diverse messenger RNA (mRNA) transcriptome as well as functional mRNA-regulatory microRNAs, suggesting that platelet mRNAs may be regulated by microRNAs. Here, we elucidated the complete repertoire and features of human platelet microRNAs by high-throughput sequencing. More than 492 different mature microRNAs were detected in human platelets, whereas the list of known human microRNAs was expanded further by the discovery of 40 novel microRNA sequences. As in nucleated cells, platelet microRNAs bear signs of post-transcriptional modifications, mainly terminal adenylation and uridylation. In vitro enzymatic assays demonstrated the ability of human platelets to uridylate microRNAs, which correlated with the presence of the uridyltransferase enzyme TUT4. We also detected numerous microRNA isoforms (isomiRs) resulting from imprecise Drosha and/or Dicer processing, in some cases more frequently than the reference microRNA sequence, including 5′ shifted isomiRs with redirected mRNA targeting abilities. This study unveils the existence of a relatively diverse and complex microRNA repertoire in human platelets, and represents a mandatory step towards elucidating the intraplatelet and extraplatelet role, function and importance of platelet microRNAs

    Pash 3.0: A versatile software package for read mapping and integrative analysis of genomic and epigenomic variation using massively parallel DNA sequencing

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    <p>Abstract</p> <p>Background</p> <p>Massively parallel sequencing readouts of epigenomic assays are enabling integrative genome-wide analyses of genomic and epigenomic variation. Pash 3.0 performs sequence comparison and read mapping and can be employed as a module within diverse configurable analysis pipelines, including ChIP-Seq and methylome mapping by whole-genome bisulfite sequencing.</p> <p>Results</p> <p>Pash 3.0 generally matches the accuracy and speed of niche programs for fast mapping of short reads, and exceeds their performance on longer reads generated by a new generation of massively parallel sequencing technologies. By exploiting longer read lengths, Pash 3.0 maps reads onto the large fraction of genomic DNA that contains repetitive elements and polymorphic sites, including indel polymorphisms.</p> <p>Conclusions</p> <p>We demonstrate the versatility of Pash 3.0 by analyzing the interaction between CpG methylation, CpG SNPs, and imprinting based on publicly available whole-genome shotgun bisulfite sequencing data. Pash 3.0 makes use of gapped k-mer alignment, a non-seed based comparison method, which is implemented using multi-positional hash tables. This allows Pash 3.0 to run on diverse hardware platforms, including individual computers with standard RAM capacity, multi-core hardware architectures and large clusters.</p

    Modeling Ewing Sarcoma Lung Metastasis

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    Ewing Sarcoma (EwS) is the second most common malignant bone tumor in adolescents and young adults. The single-most powerful predictor of outcome in EwS is presence of metastatic burden at the time of diagnosis. Patients with metastatic Ewing Sarcoma have an abysmal 5-year survival rate of 10–25%, which has not changed over the past 30–40 years. Thus, unraveling underlying mechanisms of EwS metastasis are imperative for developing effective therapeutic measures. Investigations towards this goal are limited by the lack of reliable genetically engineered mouse models and specialized metastatic models. Using two established cell lines, A673 and TC71, we generated lung specific metastatic cell lines by serial orthotopic intra-tibial injection followed by isolation of cells from lung metastases. The lung metastatic lines generated exhibit distinct differential molecular signatures from the parental cells when analyzed using a multi-omics approach. These signatures overlapped with EwS patient primary bone and metastatic lung specimens supporting the clinical relevance of these preclinical models of EwS. Basic Protocol 1: (Intratibial Injection in Immunocompromised Mice) Basic Protocol 2: (Development and Characterization of Lung Metastatic Cell Line

    Genome-wide p63-Target Gene Analyses Reveal TAp63/NRF2-Dependent Oxidative Stress Responses

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    The p53 family member TP63 encodes two sets of N-terminal isoforms, TAp63 and ΔNp63 isoforms. They each regulate diverse biological functions in epidermal morphogenesis and in cancer. In the skin, where their activities have been extensively characterized, TAp63 prevents premature aging by regulating the quiescence and genomic stability of stem cells required for wound healing and hair regeneration, while ΔNp63 controls maintenance and terminal differentiation of epidermal basal cells. This functional diversity is surprising given that these isoforms share a high degree of similarity, including an identical sequence for a DNA-binding domain. To understand the mechanisms of the transcriptional programs regulated by each p63 isoform and leading to diverse biological functions, we performed genome-wide analyses using p63 isoform-specific chromatin immunoprecipitation, RNA sequencing, and metabolomics of TAp63-/- and ΔNp63-/- mouse epidermal cells. Our data indicate that TAp63 and ΔNp63 physically and functionally interact with distinct transcription factors for the downstream regulation of their target genes, thus ultimately leading to the regulation of unique transcriptional programs and biological processes. Our findings unveil novel transcriptomes regulated by the p63 isoforms to control diverse biological functions, including the cooperation between TAp63 and NRF2 in the modulation of metabolic pathways and response to oxidative stress providing a mechanistic explanation for the TAp63 knock out phenotypes. SIGNIFICANCE: The p63 isoforms, TAp63 and ΔNp63, control epithelial morphogenesis and tumorigenesis through the interaction with distinct transcription factors and the subsequent regulation of unique transcriptional programs

    Heritable Traits and Lung Cancer Risk: A Two-Sample Mendelian Randomization Study

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    INTRODUCTION: Lung cancer is a complex polygenic disorder. Analysis with Mendelian randomization (MR) allows for genetically predicted risks to be estimated between exposures and outcomes. METHODS: We analyzed 345 heritable traits from the United Kingdom Biobank and estimated their associated effects on lung cancer outcomes using two sample MR. In addition to estimating effects with overall lung cancer, adenocarcinoma, small cell lung cancer, and squamous cell lung cancers, we performed conditional effect modeling with multivariate MR (MVMR) and the traits of alcohol use, smoking initiation, average pre-tax income, and educational attainment. RESULTS: Univariate MR provided evidence for increased age at first sexual intercourse (OR, 0.55; P = 6.15 × 10-13), educational attainment (OR, 0.24; P = 1.07 × 10-19), average household income (OR, 0.58; P = 7.85 × 10-05), and alcohol usually taken with meals (OR, 0.19; P = 1.06 × 10-06) associating with decreased odds of overall lung cancer development. In contrast, a lack of additional educational attainment (OR, 8.00; P = 3.48 × 10-12), body mass index (OR, 1.28; P = 9.00 × 10-08), pack years smoking as a proportion of life span (OR, 9.93; P = 7.96 × 10-12), and weekly beer intake (OR, 3.48; P = 4.08 × 10-07) were associated with an increased risk of overall lung cancer development. CONCLUSIONS: Many heritable traits associated with an increased or inverse risk of lung cancer development. Effects vary based on histologic subtype and conditional third trait exposures. IMPACT: We identified several heritable traits and presented their genetically predictable impact on lung cancer development, providing valuable insights for consideration

    Identification of an Early Survival Prognostic Gene Signature for Localized Osteosarcoma Patients

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    Osteosarcoma is the most prevalent bone tumor in pediatric patients. Neoadjuvant chemotherapy has improved osteosarcoma patient survival, however the 5-year survival rate for localized osteosarcoma is 75% with a 30-50% recurrence rate. We, therefore, sought to identify a prognostic gene signature which could predict poor prognosis in localized osteosarcoma patients. Using the TARGET osteosarcoma transcriptomic dataset, we identified a 13-hub gene signature associated with overall survival and time to death of localized osteosarcoma patients, with the high-risk group showing a 22% and the low-risk group showing 100% overall survival. Furthermore, network analysis identified five modules of co-expressed genes that significantly correlated with survival, and identified 65 pathways enriched across 3 modules, including Hedgehog signaling, which includes 2 of the 13 genes, IHH and GLI1. Subsequently, we demonstrated that GLI antagonists inhibited growth of a recurrent localized PDX-derived cell line with elevated IHH and GLI1 expression, but not a non-relapsed cell line with low pathway activation. Finally, we show that our signature outperforms previously reported signatures in predicting poor prognosis and death within 3 years in patients with localized osteosarcoma

    Identification of a pan-cancer oncogenic microRNA superfamily anchored by a central core seed motif

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    MicroRNAs modulate tumorigenesis through suppression of specific genes. As many tumour types rely on overlapping oncogenic pathways, a core set of microRNAs may exist, which consistently drives or suppresses tumorigenesis in many cancer types. Here we integrate The Cancer Genome Atlas (TCGA) pan-cancer data set with a microRNA target atlas composed of publicly available Argonaute Crosslinking Immunoprecipitation (AGO-CLIP) data to identify pan-tumour microRNA drivers of cancer. Through this analysis, we show a pan-cancer, coregulated oncogenic microRNA ‘superfamily’ consisting of the miR-17, miR-19, miR-130, miR-93, miR-18, miR-455 and miR-210 seed families, which cotargets critical tumour suppressors via a central GUGC core motif. We subsequently define mutations in microRNA target sites using the AGO-CLIP microRNA target atlas and TCGA exome-sequencing data. These combined analyses identify pan-cancer oncogenic cotargeting of the phosphoinositide 3-kinase, TGFβ and p53 pathways by the miR-17-19-130 superfamily members

    Leveraging Integrated RNA Sequencing to Decipher Adrenomedullin\u27s Protective Mechanisms in Experimental Bronchopulmonary Dysplasia

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    Bronchopulmonary dysplasia (BPD) is a chronic lung disease commonly affecting premature infants, with limited therapeutic options and increased long-term consequences. Adrenomedullin (Adm), a proangiogenic peptide hormone, has been found to protect rodents against experimental BPD. This study aims to elucidate the molecular and cellular mechanisms through which Adm influences BPD pathogenesis using a lipopolysaccharide (LPS)-induced model of experimental BPD in mice. Bulk RNA sequencing of Adm-sufficient (wild-type or Adm+/+) and Adm-haplodeficient (Adm+/−) mice lungs, integrated with single-cell RNA sequencing data, revealed distinct gene expression patterns and cell type alterations associated with Adm deficiency and LPS exposure. Notably, computational integration with cell atlas data revealed that Adm-haplodeficient mouse lungs exhibited gene expression signatures characteristic of increased inflammation, natural killer (NK) cell frequency, and decreased endothelial cell and type II pneumocyte frequency. Furthermore, in silico human BPD patient data analysis supported our cell type frequency finding, highlighting elevated NK cells in BPD infants. These results underscore the protective role of Adm in experimental BPD and emphasize that it is a potential therapeutic target for BPD infants with an inflammatory phenotype

    MYC Regulates CSF1 Expression via microRNA 17/20a To Modulate Tumor-Associated Macrophages in Osteosarcoma

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    Osteosarcoma (OS) is the most common primary bone tumor of childhood. Approximately 20%-30% of OSs carry amplification of chromosome 8q24, which harbors the oncogene c-MYC and correlates with a poor prognosis. To understand the mechanisms that underlie the ability of MYC to alter both the tumor and its surrounding tumor microenvironment (TME), we generated and molecularly characterized an osteoblast-specific Cre-Lox-Stop-Lox-c-MycT58A p53fl/+ knockin genetically engineered mouse model (GEMM). Phenotypically, the Myc-knockin GEMM had rapid tumor development with a high incidence of metastasis. MYC-dependent gene signatures in our murine model demonstrated significant homology to the human hyperactivated MYC OS. We established that hyperactivation of MYC led to an immune-depleted TME in OS demonstrated by the reduced number of leukocytes, particularly macrophages. MYC hyperactivation led to the downregulation of macrophage colony-stimulating factor 1, through increased microRNA 17/20a expression, causing a reduction of macrophage population in the TME of OS. Furthermore, we developed cell lines from the GEMM tumors, including a degradation tag-MYC model system, which validated our MYC-dependent findings both in vitro and in vivo. Our studies utilized innovative and clinically relevant models to identify a potentially novel molecular mechanism through which MYC regulates the profile and function of the OS immune landscape
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