Development of non-invasive method for the detection of mutated circulating nuclear acid
Ontology highlight
ABSTRACT:
DISEASE(S): Pancreatic Cancer Colon Cancer Hepatocellar Carcinoma Gastric Cancer Bile Duct Cancer Inflammatory Bowel Disease (ulcerative Colitis, Crohn) Intraductal Papillary Mucinous Neoplasm Autoimmune Disease Hepatic/ Digestive Tract Disorder
PROVIDER: 2627177 | ecrin-mdr-crc |
REPOSITORIES: ECRIN MDR
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Project description:BackgroundEstablishing a high-accuracy and non-invasive method is essential for evaluating cardiovascular disease. Skin cholesterol is a novel marker for assessing the risk of atherosclerosis and can be used as an independent risk factor of early assessment of atherosclerotic risk.MethodsWe propose a non-invasive skin cholesterol detection method based on absorption spectroscopy. Detection reagents specifically bind to skin cholesterol and react with indicator to produce colored products, the skin cholesterol content can be obtained through absorption spectrum information on colored products detected by non-invasive technology. Gas chromatography is used to measure cholesterol extracted from the skin to verify the accuracy and reliability of the non-invasive test method. A total of 342 subjects were divided into normal group (n = 115), disease group (n = 110) and risk group (n = 117). All subjects underwent non-invasive skin cholesterol test. The diagnostic accuracy of the measured value was analyzed by receiver-operating characteristic (ROC) curve.ResultsThe proposed method is able to identify porcine skin containing gradient concentration of cholesterol. The values measured by non-invasive detection method were significantly correlated with gas chromatography measured results (r = 0.9074, n = 73, p < 0.001). Bland-Altman bias was - 72.78 ± 20.03 with 95% limits of agreement - 112.05 to - 33.51, falling within the prespecified clinically non-significant range. We further evaluated the method of patients with atherosclerosis and risk population as well as normal group, patients and risk atherosclerosis group exhibited higher skin cholesterol content than normal group (all P < 0.001). The area under the ROC curve for distinguishing Normal/Disease group was 0.8642 (95% confidence interval, 0.8138 to 0.9146), meanwhile, the area under the ROC curve for distinguishing Normal/Risk group was 0.8534 (95% confidence interval, 0.8034 to 0.9034).ConclusionsThe method demonstrated its capability of detecting different concentration of skin cholesterol. This non-invasive skin cholesterol detection system may potentially be used as a risk assessment tool for atherosclerosis screening, especially for a large population.
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Project description:Plasma samples from 100 early stage (I to IIIA) non–small-cell lung cancer (NSCLC) patients and 100 non-cancer controls were screened for 754 circulating microRNAs via qRT-PCR, using TaqMan MicroRNA Arrays. Our objective was to identify a panel of circulating microRNAs in plasma that will contribute to early detection of lung cancer.
2015-12-31 | GSE64591 | GEO
Project description:Background: Early detection of prostate cancer (PCa) is limited by the lack of accurate non-invasive biomarkers easily evaluable in men within a screening context. Prostate-specific antigene (PSA) measurement leads to high percentages of both false positives and false negatives. In the era of liquid biopsies, we propose to combine PSA dosage with the evaluation of circulating microRNAs (miRs), to discriminate between men harbouring or not PCa. Methods: miR profiling of plasma samples from 60 men with PCa, 51 with benign prostatic hyperplasia (BPH) and 27 healthy donors (HD) was performed using microarrays. Univariate analysis (linear models with an empirical Bayes approach) and multivariate penalized logistic regression models were applied to highlight miRs and clinical variables associated with the presence of malignant disease, and were combined in a classification score. Finally, the developed score was tested on an independent dataset of 242 plasma samples (68 PCa, 8 premalignant lesions, 93 BPH, 73 HD), where miR expression was evaluated by RT-qPCR. Results: Out of 2006 miRs analyzed, a linear combination of miR-103a-3p and let-7a-5p with PSA defined our score. A classification rule based on this score allowed reclassification of samples with accuracy (0.61), sensitivity (0.87), specificity (0.35) and AUC (0.68) higher than those obtained by PSA alone. On the validation set, the same classification rule still performed better than PSA alone in terms of specificity (0.57 versus 0.55) and AUC (0.76 versus 0.74), allowing correct reclassification of all but one tumors not detected by PSA and 33% of BPH with PSA in the 4-16 ng/ml range. Conclusion: The combination of two circulating miRs with PSA could be an interesting biomarker to detect the presence of PCa (even when PSA levels are below the standard cut-off of 4 ng/ml) and the absence of PCa in an important fraction of men with high PSA, who may avoid unnecessary biopsies.
2019-01-31 | GSE113234 | GEO
Project description:Detection of lung cancer at an early stage by sensitive screening tests could be an important strategy to improving prognosis. Our objective was to identify a panel of circulating microRNAs in plasma that will contribute to early detection of lung cancer.Plasma samples from 100 early stage (I to IIIA) non-small-cell lung cancer (NSCLC) patients and 100 non-cancer controls were screened for 754 circulating microRNAs via qRT-PCR, using TaqMan MicroRNA Arrays. Logistic regression with a lasso penalty was used to select a panel of microRNAs that discriminate between cases and controls. Internal validation of model discrimination was conducted by calculating the bootstrap optimism-corrected AUC for the selected model.We identified a panel of 24 microRNAs with optimum classification performance. The combination of these 24 microRNAs alone could discriminate lung cancer cases from non-cancer controls with an AUC of 0.92 (95% CI: 0.87-0.95). This classification improved to an AUC of 0.94 (95% CI: 0.90-0.97) following addition of sex, age and smoking status to the model. Internal validation of the model suggests that the discriminatory power of the panel will be high when applied to independent samples with a corrected AUC of 0.78 for the 24-miRNA panel alone.Our 24-microRNA predictor improves lung cancer prediction beyond that of known risk factors.
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Project description:Detection of cardiomyocyte death is crucial for the diagnosis and treatment of heart disease. Here we use comparative methylome analysis to identify genomic loci that are unmethylated specifically in cardiomyocytes, and develop these as biomarkers to quantify cardiomyocyte DNA in circulating cell-free DNA (cfDNA) derived from dying cells. Plasma of healthy individuals contains essentially no cardiomyocyte cfDNA, consistent with minimal cardiac turnover. Patients with acute ST-elevation myocardial infarction show a robust cardiac cfDNA signal that correlates with levels of troponin and creatine phosphokinase (CPK), including the expected elevation-decay dynamics following coronary angioplasty. Patients with sepsis have high cardiac cfDNA concentrations that strongly predict mortality, suggesting a major role of cardiomyocyte death in mortality from sepsis. A cfDNA biomarker for cardiomyocyte death may find utility in diagnosis and monitoring of cardiac pathologies and in the study of normal human cardiac physiology and development.
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Project description:The incidence of poliovirus has been significantly reduced by as much as 99.9% globally. Alongside this, however, vaccine-associated paralytic poliomyelitis has emerged. Previously, our team reported in the Lésio-Louna-Léfini Nature Reserve (Republic of Congo) the presence of a new Enterovirus C (Ibou002) in a male gorilla that was put away because of clinical symptoms of facial paralysis. This new virus, isolated was from the stool samples of this gorilla but also from the excrement of an eco-guardian, is very similar to Coxsackievirus (EV-C99) as well as poliovirus 1 and 2. We hypothesised that these symptoms might be due to poliovirus infection. To test our hypothesis, we developed and optimised a non-invasive immunoassay for the detection of Enterovirus-specific antibodies in gorilla faeces that could be useful for routine serosurveillance in such cases. In order to assess the potential role of poliovirus infection, we have developed and optimised a protocol, based on the lyophilisation and solubilisation of small volumes of stool extracts from 16 gorilla and 3 humans, to detect specific antibodies by western blot and ELISA. First, total immunoglobulins were detected in the concentrated stool extracts. Specific antibodies were then detected in 4/16 gorilla samples and 2/3 human samples by western blot using both the polio vaccine antigen and the Ibou002 antigen and by ELISA using the polio vaccine antigen. Humoral responses were greater with the Ibou002 antigen. We therefore suggest that this recombinant virus could lead to a polio-like disease in the endangered western lowland gorilla. The development of a non-invasive approach to detect microorganism-specific immunoglobulins from faecal samples opens numerous prospects for application in zoonotic infectious diseases and could revolutionise the screening of animals for important emerging infections, such as Ebola fever, rabies and coronavirus infections.
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Project description:Hereditary angioedema (HAE) is a rare and potentially life-threatening disease. The pathogenesis of HAE is not well understood. Moreover, non-invasive disease biomarkers are strongly needed for early diagnosis and clinical management of HAE.
2023-09-18 | PXD045435 |
Project description:Chemical signals are produced by aquatic organisms following predatory attacks or perturbations such as parasitic infection. Ectoparasites feeding on host fish are likely to cause release of similar alarm cues into the environment due to the stress, wounding and immune response stimulated upon infection. Alarm cues are often released in the form of proteins and peptides and provide important insights into bodily function and infection status. Here we outline a non-invasive method to identify potential chemical cues associated with infection in fish by extracting, purifying and characterizing proteins from water samples from cultured fish. Gel free proteomic methods were deemed the most suitable for protein detection in saline water samples. It was confirmed that proteins could be characterized from teleost water samples and that variation in protein profiles could be detected between infected and uninfected individuals and fish and parasite only water samples. Our novel assay provides a non-invasive method for assessing the health condition of both wild and farmed aquatic organisms. Similar to environmental DNA monitoring methods, these proteomic techniques could provide an important tool in applied biology and aquaculture biology
2019-01-02 | PXD010987 | Pride
Project description:Untargeted serum metabolomics was combined with machine learning-powered data analytics to develop a test for the concurrent detection of multiple cancers in women. A total of fifteen cancers were tested where the resulting metabolome data was sequentially analysed using two separate algorithms. The first algorithm successfully identified all the cancer-positive samples with an overall accuracy of > 99%. This result was particularly significant given that the samples tested were predominantly from early-stage cancers. Samples identified as cancer-positive were next analysed using a multi-class algorithm, which then enabled accurate discernment of the tissue of origin for the individual samples. Integration of serum metabolomics with appropriate data analytical tools, therefore, provides a powerful screening platform for early-stage cancers.
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Project description:Background: Cervical cancer is the most common malignant tumor in the female reproductive system, while the efficacy of routine screening strategy is unsatisfied. New molecular tests need to be developed. miRNAs participate in many pathologic processes, and circulating miRNAs are promising non-invasive biomarkers in tumors. Objectives: This study aimed to identify the circulating miRNAs associated with both cervical cancer and cervical intraepithelial neoplasia (CIN), and establish a non-invasive classifier for cervical lesions using circulating miRNAs. Methods: This study consisted of 5 steps: miRNAs screening, miRNAs validation, classifier establishment, independent validation and in silico analyses. Three cohorts were included in our study: In screening stage, 24 samples including 14 cases and 10 controls were retrieved; In validation stage, 380 samples including 200 cases and 180 controls were recruited; In independent validation stage, 47 samples comprising 26 cases and 21 controls were included. miRNAs were quantified by RT-qPCR. A classifier was built with random forest algorithm using validation samples and selected miRNAs, which were then validated in an independent cohort. To explore the function of selected miRNAs, in silico analyses were performed. Target genes of selected miRNAs were predicted by the overlap of three online tools. Enrichment analyses were executed with predicted target genes. Differential analysis of target genes was carried out with open access expression assay datasets of cervical tissues. Results: 6 miRNAs (hsa-miR-26b-5p, hsa-miR-146b-5p, hsa-miR-191-5p, hsa-miR-484, hsa-miR-574-3p, hsa-miR-625-3p) were screened out from 754 miRNAs. They were associated with cervical lesions and were selected to establish a classifier. The accuracy of the classifier were 0.7218 (0.7117, 0.7319) in validation samples, which was 0.7021 in the independent cohort. 958 target genes were predicted and enriched in 23 pathways (MAPK, human papillomavirus infection and Wnt signaling pathway, etc.). 55 genes were identified as the most likely target genes by differential analysis. Conclusion: The 6 circulating miRNAs were related to cervical lesions and could serve as non-invasive biomarkers.
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