Project description:MicroRNAs from serum samples could detect pancreatic and biliary tract cancer patients more accurately than other traditional markers. Prospective miRNA markers for pancreatic/biliary tract cancer were selected in the training cohort. Using these miRNAs, discriminant analysis was performed, and the diagnostic accuracy, sensitivity and specificity were calculated in the test cohort.
Project description:Identification of blood biomarkers that prospectively predict progression of Mycobacterium tuberculosis infection to tuberculosis disease might lead to interventions that combat the tuberculosis epidemic. We aimed to assess whether global gene expression measured in whole blood of healthy people allowed identification of prospective signatures of risk of active tuberculosis disease. RESULTS:Between July 6, 2005, and April 23, 2007, we enrolled 6363 from the ACS study and 4466 from independent South African and Gambian cohorts. 46 progressors and 107 matched controls were identified in the ACS cohort. A 16 gene signature of risk was identified. The signature predicted tuberculosis progression with a sensitivity of 66·1% (95% CI 63·2â68·9) and a specificity of 80·6% (79·2â82·0) in the 12 months preceding tuberculosis diagnosis. The risk signature was validated in an untouched group of adolescents (p=0·018 for RNA sequencing and p=0·0095 for qRT-PCR) and in the independent South African and Gambian cohorts (p values <0·0001 by qRT-PCR) with a sensitivity of 53·7% (42·6â64·3) and a specificity of 82·8% (76·7â86) in 12 months preceding tuberculosis. Interpretation: The whole blood tuberculosis risk signature prospectively identified people at risk of developing active tuberculosis, opening the possibility for targeted intervention to prevent the disease. In this prospective cohort study, we followed up healthy, South African adolescents aged 12â18 years from the adolescent cohort study (ACS) who were infected with M tuberculosis for 2 years. We collected blood samples from study participants every 6 months and monitored the adolescents for progression to tuberculosis disease. A prospective signature of risk was derived from whole blood RNA sequencing data by comparing participants who developed active tuberculosis disease (progressors) with those who remained healthy (matched controls). After adaptation to multiplex qRT-PCR, the signature was used to predict tuberculosis disease in untouched adolescent samples and in samples from independent cohorts of South African and Gambian adult progressors and controls. Participants of the independent cohorts were household contacts of adults with active pulmonary tuberculosis disease.
Project description:Alzheimer’s disease (AD) is the most common subtype of dementia, followed by Vascular Dementia (VaD), and Dementia with Lewy Bodies (DLB). Recently, microRNAs (miRNAs) have received a lot of attention as the novel biomarkers for dementia. Here, using serum miRNA expression of 1,601 Japanese individuals, we investigated potential miRNA bio- markers and constructed risk prediction models, based on a supervised principal component analysis (PCA) logistic regression method, according to the subtype of dementia. The final risk prediction model achieved a high accuracy of 0.873 on a validation cohort in AD, when using 78 miRNAs: Accuracy = 0.836 with 86 miRNAs in VaD; Accuracy = 0.825 with 110 miRNAs in DLB. To our knowledge, this is the first report applying miRNA-based risk pre- diction models to a dementia prospective cohort. Our study demonstrates our models to be effective in prospective disease risk prediction; and with further improvement may contribute to practical clinical use in dementia.
Project description:Pancreatic cancer stem cells (CSCs) have been described as CD24+/CD44+/EpCAM+ or CD133+ cells. However, no study has determined the co-expression of all of these markers in pancreatic ductal adenocarcinoma. Similarly to other combinations of CSC markers, CD24+/ CD44+/EpCAM+/CD133+ phenotype might more accurately identify true pancreatic CSCs. Therefore, we performed a detailed co-expression analysis of CD24, CD44, EpCAM, and CD133 in 3 cell lines derived from primary pancreatic ductal adenocarcinomas (PDACs). Gene expression profiling was applied in order to further investigate the observed differences in proportion of cells that co-expressed CSC markers among the cell lines.
Project description:MicroRNAs from serum samples could detect pancreatic and biliary tract cancer patients more accurately than other traditional markers.