Ontology highlight
ABSTRACT:
PROVIDER: PRJNA984933 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR25022600.fastq.gz | Fastqsanger.gz | |||
| SRR25022601.fastq.gz | Fastqsanger.gz | |||
| SRR25022602.fastq.gz | Fastqsanger.gz | |||
| SRR25022603.fastq.gz | Fastqsanger.gz | |||
| SRR25022604.fastq.gz | Fastqsanger.gz |
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Project description:Concomitant multiple hematological malignancies are rare and challenging to diagnose. They represent a unique model to explore the multistep process of oncogenesis. Here, we report the unique case of 62 years-old man with cardiac tamponade as first manifestation of ALK negative anaplastic large T-cell lymphoma (ALK- ALCL). Following chemotherapy, he showed one year later ALK- ALCL concurrent with diffuse large B-cell lymphoma (DLBCL-NOS) and acute monoblastic leukemia (AML-M5) in a single excisional lymph node. Clinical, pathological and multiomics data (whole exome and targeted deep sequencing, spatial transcriptomics) were analyzed. Two somatic TET2 gene mutations at high allele burden were shared by all three neoplasms, uninvolved bone marrow and CD34+ hematopoietic stem and progenitor cells (HSPCs). Secondary hits characterized each malignancy. ALK- ALCL (pericardial and nodal) showed TP53 and LYN deleterious mutations, DLBCL-NOS disclosed KRAS, STAT6, CREBBP and ATM alterations and AML-M5 had JAK3, PPM1D, NF1 and KMT2D mutations and a complex karyotype. Furthermore we demonstrated that spatial transcriptomics can identify the specific signatures of the three neoplasms. Two TET2 mutations at high allele burden in CD34+HSPCs conferred the favorable soil and the genotoxic stress from chemotherapy likely contributed to multiple hematological malignancies oncogenesis. Our case confirms the pathogenetic link between clonal hematopoiesis and cytotoxic T-cell lymphoma, so far only suspected. Most importantly, this is the first study to document the oncogenic phylogeny of concurrent T-, B-, and myeloid neoplasms from CD34+ HSPCs clone(s) in a single specimen.
2023-03-17 | E-MTAB-12742 | biostudies-arrayexpress
Project description:Purpose: Acute lung injury (ALI) is a severe clinical disorder characterized by diffused capillary-alveolar barrier damage and noncardiogenic lung edema induced by excessive inflammation reactions. Nogo-B, a member of the reticulon 4 protein family, plays a critical role in modulating macrophages and neutrophils’ function in inflammation. Its role in ALI remains unclear. Methods: Pulmonary expression of Nogo-B was investigated in a LPS-induced ALI mice model. The effects and the underline mechanisms of Nogo-B expression on the severity of lung injury was assessed using histological examination, Bronchoalveolar lavage fluid (BALF) protein and inflammatory cells and cytokines measurement, and microarray analysis. Results: Nogo-B was normally highly expressed in the lungs of naïve C57BL/6 mice. Intra-tracheal instillation of LPS significantly repressed the Nogo-B expression in lung tissues and BALF cells of ALI mice. In addition, over-expression of pulmonary Nogo-B using an adenovirus vector which expresses a Nogo-B-RFP-3-flag fusion protein (Ad-Nogo-B) significantly prolonged the survival time of mice challenged with lethal dose of LPS. Histological results and BALF protein measurement convinced that Ad-Nogo-B treated mice had less severity of lung injury and alveolar protein exudation, as compared with control adenovirus treated mice (Ad-RFP). They also had higher MCP-1 secretion and alveolar macrophages infiltration, but lower neutrophils infiltration. Finally, using microarray analysis, we identified a protective gene, PTX3, was highly elevated in Ad-Nogo-B treated mice. Conclusions: Nogo-B played a protective role in LPS-induced ALI, which might exert its role through modulation of inflammatory response and PTX3 secretion. A total of 12 samples from mice treated with or without LPS in the presence of Ad-Nogo-B or Ad-RFP transfection (n=3 for each group)
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Project description:Diffuse parenchymal lung diseases (DPLD) cover heterogeneous types of lung disorders with a plethora of variously combined clinical manifestations. Among many pathological phenotypes, pulmonary fibrosis is the most devastating. Pulmonary fibrosis is a characteristic sign for idiopathic pulmonary fibrosis (IPF); however, it may occur also in later stages of other types of DPLD. Despite a poor prognosis brought by pulmonary fibrosis, there are no specific diagnostic biomarkers for the initial development of this fatal condition. The major hallmark of lung fibrosis is uncontrolled activation of lung fibroblasts to myofibroblasts associated with extracellular matrix deposition and the loss of both lung structure and function. Here, we used this peculiar feature in order to identify specific biomarkers of pulmonary fibrosis in bronchoalveolar lavage fluids. The primary MRC-5 human fibroblasts were activated with BALF collected from patients with clinically diagnosed lung fibrosis; the activated fibroblasts were then washed rigorously, and further incubated to allow secretion; afterwards, the secretomes were analysed by mass spectrometry. In this way, the CD44 protein was identified. Finally, BALF of all DPLD patients were positively tested for the presence of CD44 by ELISA. Biochemical and biophysical characterizations revealed an exosomal origin of CD44. Correlation studies confirmed the exosomal CD44 in BALF as a specific and reliable biomarker of IPF and other types of DPLD accompanied with pulmonary fibrosis.
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Project description:Recent progress in unbiased metagenomic next-generation sequencing (mNGS) allows simultaneous examination of microbial and host genetic material in a single test. Leveraging affordable bronchoalveolar lavage fluid (BALF) mNGS data, we employed machine learning to create a diagnostic approach distinguishing lung cancer from pulmonary infections, conditions prone to misdiagnosis in clinical settings. This prospective study analyzed BALF-mNGS data from lung cancer and pulmonary infection patients, delineating differences in DNA/RNA microbial composition, bacteriophage abundances, and host responses, including gene expression, transposable element levels, immune cell composition, and tumor fraction derived from copy number variation (CNV). Integrating these metrics into a host/microbe metagenomics-driven machine learning model (Model VI) demonstrated robustness, achieving an AUC of 0.87 (95% CI = 0.857-0.883), sensitivity = 73.8%, and specificity = 84.5% in the training cohort, and an AUC of 0.831 (95% CI = 0.819-0.843), sensitivity = 67.1%, and specificity = 94.4% in the validation cohort for distinguishing lung cancer from pulmonary infections. The application of a rule-in and rule-out strategy-based composite predictive model significantly enhances accuracy (ACC) in distinguishing between lung cancer and tuberculosis (ACC=0.913), fungal infection (ACC=0.955), and bacterial infection (ACC=0.836). These findings highlight the potential of cost-effective mNGS-based analysis as a valuable tool for early differentiation between lung cancer and pulmonary infections, offering significant benefits through a single comprehensive testing.
2024-01-08 | GSE252118 | GEO
Project description:The key aim of this experiment is to characterize the iPSC-Mφ population before and after pulmonary transplantation. For this purpose the following cell populations were compared: (i) transplanted iPSC-Mφ, (ii) Mφ obtained by in vitro differentiation of murine lineage-negative bone marrow cells (BM-Mφ), (iii) non-differentiated CD45.1 iPSC, (iv) murine alveolar Mφ (AMφ) isolated from the BALF of healthy control mice, and (v) iPSC-Mφ recovered from the transplanted animals two months after (PMT-Mφ).
2018-07-10 | E-MTAB-6442 | biostudies-arrayexpress
Project description:<p>Despite improved diagnostics, pulmonary pathogens in immunocompromised children frequently evade detection, leading to significant mortality. In this study, we performed RNA and DNA-based metagenomic next generation sequencing (mNGS) on 41 lower respiratory samples collected from 34 children. We identified a rich cross-domain pulmonary microbiome containing bacteria, fungi, RNA viruses, and DNA viruses in each patient. Potentially pathogenic bacteria were ubiquitous among samples but could be distinguished as possible causes of disease by parsing for outlier organisms. Potential pathogens were detected in half of samples previously negative by clinical diagnostics. Ongoing investigation is needed to determine the pathogenic significance of outlier microbes in the lungs of immunocompromised children with pulmonary disease. Metatranscriptomic (RNA) sequencing libraries are reported in the manuscript and are included for this release.</p>
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Project description:Comprehensive proteomic analysis of the protein expression landscape of bronchoalveolar lavage fluid during invasive pulmonary aspergillosis in murine and human samples. 38 murine BALF samples (10 Aspergillus fumigatus infected mice without immunosuppression and without invasive pulmonary aspergillosis (IPA), 19 immunosuppressed and infected mice with IPA and 9 immunosuppressed animals without infection) were analysed for their global protein expression. In addition, 54 human BALF specimen from patients with probable IPA (23 samples), proven IPA (4 cases) and 27 control samples from patients with unrelated pulmonary diseases were analysed for their global protein composition. Host responses and Aspergillus fumigatus-specific proteins detectable in BALF were studied.
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