Analysis of exosomal cargo provides accurate clinical, histologic and mutational information in non-small cell lung cancer.
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ABSTRACT:
PROVIDER: PRJNA814254 | ENA |
REPOSITORIES: ENA
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Project description:Despite advances in the understanding of lung cancer biology and the development of new drugs, most cases of lung cancer are diagnosed at an advanced stages. The present study is a proof of concept with the main aim of implementing the use of exosomes as a minimal invasive platform to search new biomarkers and determine tumor features in NSCLC.
2022-06-29 | GSE198238 | GEO
Project description:Lung cancer is a malignant disease with high mortality and poor prognosis, frequently diagnosed at advanced stages. Nowadays, immense progress in treatment has been achieved. However, the present scenario continues to be critical, and a full comprehension of tumor progression mechanisms is required, with exosomes being potentially relevant players. Exosomes are membranous vesicles that contain biological information, which can be transported cell-to-cell and modulate relevant processes in the hallmarks of cancer. The present research aims to characterize the exosomes' cargo and study their role in NSCLC to identify biomarkers. We analyzed exosomes secreted by primary cultures and cell lines, grown in monolayer and tumorsphere formations. Exosomal DNA content showed molecular alterations, whereas RNA high-throughput analysis resulted in a pattern of differentially expressed genes depending on histology. The most significant differences were found in XAGE1B, CABYR, NKX2-1, SEPP1, CAPRIN1, and RIOK3 genes when samples from two independent cohorts of resected NSCLC patients were analyzed. We identified and validated biomarkers for adenocarcinoma and squamous cell carcinoma. Our results could represent a relevant contribution concerning exosomes in clinical practice, allowing for the identification of biomarkers that provide information regarding tumor features, prognosis and clinical behavior of the disease.
| S-EPMC9264915 | biostudies-literature
Project description:The mRNA cargo of B-16V and B-16V-delta-BAG6 cells was sequenced with RNA seq.
2019-11-29 | E-MTAB-7123 | biostudies-arrayexpress
Project description:Predictors built from gene expression data accurately predict ER, PR, and HER2 status, and divide tumor grade into high-grade and low-grade clusters; intermediate-grade tumors are not a unique group. In contrast, gene expression data cannot be used to predict tumor size or lymphatic-vascular invasion. Experiment Overall Design: Microarray data from the tumors of 129 patients were analyzed for the ability to predict biomarkers (ER, PR, HER2), histologic features (grade and lymphatic-vascular invasion), and stage-related information (tumor size and lymph node metastasis). Multiple statistical predictors were used and the prediction accuracy determined by error rates of prediction and by dimensional scaling and visualization of the states under study. Models to predict lymph node metastasis were built by combinations of molecular, histologic and anatomic features.
2008-06-14 | E-GEOD-5460 | biostudies-arrayexpress
Project description:Preterm premature rupture of membranes (PPROM), which precedes approximately 30–40% of preterm births, is the main cause of neonatal morbidity, mortality, and long-term sequelae. In particular, almost half of all PPRPM cases are frequently complicated by subclinical acute inflammation in the placenta and fetal tissue, commonly named as acute histologic chorioamnionitis [HCA]. Increasing evidences suggest that HCA carries additional risks to both the pregnant women and their fetuses, including greater risk of imminent preterm birth, as well as sepsis, neurologic morbidity, and mortality in neonates. More accurate and early prenatal predictive markers (especially noninvasive ones) are urgently needed for identifying subclinical HCA in the context of PPROM.To identify potential biomarkers in the plasma that could predict histologic chorioamnionitis (HCA) in women with preterm premature rupture of membranes (PPROM), using shotgun and targeted proteomic analyses.
2022-08-12 | PXD027573 | Pride
Project description:Background: Histologic grade in breast cancer provides clinically important prognostic information. However, 30%-60% of tumors are classified as histologic grade 2. This grade is associated with an intermediate risk of recurrence and is thus not informative for clinical decision making. We examined whether histologic grade was associated with gene expression profi les of breast cancers and whether such profi les could be used to improve histologic grading. Methods: We analyzed microarray data from 189 invasive breast carcinomas and from three published gene expression datasets from breast carcinomas. We identified differentially expressed genes in a training set of 64 estrogen receptor (ER)-positive tumor samples by comparing expression profiles between histologic grade 3 tumors and histologic grade 1 tumors and used the expression of these genes to define the gene expression grade index. Data from 597 independent tumors were used to evaluate the association between relapse-free survival and the gene expression grade index in a Kaplan-Meier analysis. All statistical tests were two-sided. Results: We identified 97 genes in our training set that were associated with histologic grade; most of these genes were involved in cell cycle regulation and proliferation. In validation datasets, the gene expression grade index was strongly associated with histologic grade 1 and 3 status; however, among histologic grade 2 tumors, the index spanned the values for histologic grade 1-3 tumors. Among patients with histologic grade 2 tumors, a high gene expression grade index was associated with a higher risk of recurrence than a low gene expression grade index (hazard ratio = 3.61, 95% confidence interval = 2.25 to 5.78; P<.001, log-rank test). Conclusions: Gene expression grade index appeared to reclassify patients with histologic grade 2 tumors into two groups with high versus low risks of recurrence. This approach may improve the accuracy of tumor grading and thus its prognostic value. NB: The patients coming from Uppsala Hospital have been also used in other studies as in GSE3494. You can find the common set of patients in removing the abbreviation "UPP_" from the sample names and compare the results with the "INDEX (ID)" from the GSE3494 series. Keywords: disease state analysis
2006-02-16 | GSE2990 | GEO
Project description:<p>The composition and physical properties of the extracellular matrix (ECM) critically influence tumor progression, but the molecular mechanisms underlying ECM layering are poorly understood. Tumor-stroma interaction is critically dependent on cell-cell communication mediated by exosomes, small vesicles generated within multivesicular bodies (MVBs). Here, we show that caveolin-1 (Cav1) is a central modulator of both exosome biogenesis and exosomal protein cargo sorting through the regulation of cholesterol content at the endosomal compartment/MVBs. Quantitative proteomics profiling revealed that Cav1 is required for exosomal sorting of ECM protein cargo subsets including tenascin-C (TnC), and for fibroblast-derived exosomes to efficiently depose ECM and promote tumor cell invasiveness. Cav1-driven exosomal ECM deposition not only promotes local stromal remodeling, but also the generation of distant ECM-enriched stromal niches. These results support a model by which Cav1 is a central regulatory hub for tumor-stroma interactions through a novel exosome-dependent ECM deposition mechanism.</p><p><br></p><p>Linked studies: <a href='https://www.ebi.ac.uk/metabolights/MTBLS1977' rel='noopener noreferrer' target='_blank'>MTBLS1977</a></p>
2020-10-07 | MTBLS1969 | MetaboLights
Project description:<p>The composition and physical properties of the extracellular matrix (ECM) critically influence tumor progression, but the molecular mechanisms underlying ECM layering are poorly understood. Tumor-stroma interaction is critically dependent on cell-cell communication mediated by exosomes, small vesicles generated within multivesicular bodies (MVBs). Here, we show that caveolin-1 (Cav1) is a central modulator of both exosome biogenesis and exosomal protein cargo sorting through the regulation of cholesterol content at the endosomal compartment/MVBs. Quantitative proteomics profiling revealed that Cav1 is required for exosomal sorting of ECM protein cargo subsets including tenascin-C (TnC), and for fibroblast-derived exosomes to efficiently depose ECM and promote tumor cell invasiveness. Cav1-driven exosomal ECM deposition not only promotes local stromal remodeling, but also the generation of distant ECM-enriched stromal niches. These results support a model by which Cav1 is a central regulatory hub for tumor-stroma interactions through a novel exosome-dependent ECM deposition mechanism.</p><p><br></p><p>Linked studies: <a href='https://www.ebi.ac.uk/metabolights/MTBLS1969' rel='noopener noreferrer' target='_blank'>MTBLS1969</a></p>
2020-10-07 | MTBLS1977 | MetaboLights
Project description:Composting biotechnology information Genome sequencing
| PRJNA1060420 | ENA
Project description:Previously we have described the role of liver stellate cell exosomes in triggering macrophage migration and immune activation, we wanted to study what cargo in this exosomes were responsible for such activation. We found a few interesting mRNAs and siRNAs involved in the immune response pathway and cytokine production. We have found that Ectodysplasin A, a hepatokine, has an important role in stimulating the macrophage response and to be highly expressed in liver cirrhosis.
2022-01-31 | E-MTAB-11373 | biostudies-arrayexpress