Dataset Information

Plasma microRNAs as biomarkers of pancreatic cancer risk in a prospective cohort study.

ABSTRACT: Noninvasive biomarkers for early pancreatic ductal adenocarcinoma (PDAC) diagnosis and disease risk stratification are greatly needed. We conducted a nested case-control study within the Prospective Investigation into Cancer and Nutrition (EPIC) cohort to evaluate prediagnostic microRNAs (miRs) as biomarkers of subsequent PDAC risk. A panel of eight miRs (miR-10a, -10b, -21-3p, -21-5p, -30c, -106b, -155 and -212) based on previous evidence from our group was evaluated in 225 microscopically confirmed PDAC cases and 225 controls matched on center, sex, fasting status and age/date/time of blood collection. MiR levels in prediagnostic plasma samples were determined by quantitative RT-PCR. Logistic regression was used to model levels and PDAC risk, adjusting for covariates and to estimate area under the receiver operating characteristic curves (AUC). Plasma miR-10b, -21-5p, -30c and -106b levels were significantly higher in cases diagnosed within 2 years of blood collection compared to matched controls (all p-values <0.04). Based on adjusted logistic regression models, levels for six miRs (miR-10a, -10b, -21-5p, -30c, -155 and -212) overall, and for four miRs (-10a, -10b, -21-5p and -30c) at shorter follow-up time between blood collection and diagnosis (?5 yr, ?2 yr), were statistically significantly associated with risk. A score based on the panel showed a linear dose-response trend with risk (p-value?=?0.0006). For shorter follow-up (?5 yr), AUC for the score was 0.73, and for individual miRs ranged from 0.73 (miR-212) to 0.79 (miR-21-5p).

SUBMITTER: Duell EJ

PROVIDER: S-EPMC5536971 | biostudies-literature | 2017 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Plasma microRNAs as biomarkers of pancreatic cancer risk in a prospective cohort study.

Duell Eric J EJ Lujan-Barroso Leila L Sala Núria N Deitz McElyea Samantha S Overvad Kim K Tjonneland Anne A Olsen Anja A Weiderpass Elisabete E Busund Lill-Tove LT Moi Line L Muller David D Vineis Paolo P Aune Dagfinn D Matullo Giuseppe G Naccarati Alessio A Panico Salvatore S Tagliabue Giovanna G Tumino Rosario R Palli Domenico D Kaaks Rudolf R Katzke Verena A VA Boeing Heiner H Bueno-de-Mesquita H B As HBA Peeters Petra H PH Trichopoulou Antonia A Lagiou Pagona P Kotanidou Anastasia A Travis Ruth C RC Wareham Nick N Khaw Kay-Tee KT Ramon Quiros Jose J Rodríguez-Barranco Miguel M Dorronsoro Miren M Chirlaque María-Dolores MD Ardanaz Eva E Severi Gianluca G Boutron-Ruault Marie-Christine MC Rebours Vinciane V Brennan Paul P Gunter Marc M Scelo Ghislaine G Cote Greg G Sherman Stuart S Korc Murray M

International journal of cancer 20170612 5

Noninvasive biomarkers for early pancreatic ductal adenocarcinoma (PDAC) diagnosis and disease risk stratification are greatly needed. We conducted a nested case-control study within the Prospective Investigation into Cancer and Nutrition (EPIC) cohort to evaluate prediagnostic microRNAs (miRs) as biomarkers of subsequent PDAC risk. A panel of eight miRs (miR-10a, -10b, -21-3p, -21-5p, -30c, -106b, -155 and -212) based on previous evidence from our group was evaluated in 225 microscopically conf ...[more]

PMID: 28542740

Similar Datasets

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 66Â·1% (95% CI 63Â·2â68Â·9) and a specificity of 80Â·6% (79Â·2â82Â·0) in the 12 months preceding tuberculosis diagnosis. The risk signature was validated in an untouched group of adolescents (p=0Â·018 for RNA sequencing and p=0Â·0095 for qRT-PCR) and in the independent South African and Gambian cohorts (p values <0Â·0001 by qRT-PCR) with a sensitivity of 53Â·7% (42Â·6â64Â·3) and a specificity of 82Â·8% (76Â·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:Introduction: Brain plasticity, synaptic regeneration and neuroinflammation are crucial mechanisms that play important roles in the recovery from acute brain injuries, such as aneurysmal subarachnoid hemorrhage (aSAH), ischemic stroke (IS), and traumatic brain injury (TBI). The p75 neurotrophic receptor (p75NTR) is a significant receptor that modulates brain plasticity, neuroinflammation and apoptosis, making it an interesting target for therapeutic interventions. However, despite the progress made in understanding the molecular mechanisms involved in brain plasticity and neuroinflammation, there are still significant knowledge gaps in identifying protein biomarkers and microRNAs (miRNAs) associated with different types of acute brain injuries. Addressing these gaps will be critical in advancing our understanding of the underlying mechanisms involved in brain injury and developing effective therapies or prognostic strategies for recovery. Hypotheses: We hypothesized that changes in serum levels of p75NTR and its linked neuroinflammatory signaling proteins could predict recovery from acute brain injuries, regardless of injury type. Differentially expressed (DE) circulating miRNAs following acute brain injuries may regulate studied protein targets and overall injury outcome. Methods: A prospective cohort of 74 patients with ischemic stroke (n=30), aneurysmal subarachnoid hemorrhage (n=31), and traumatic brain injury (n=13) was evaluated. Serum samples were collected at two time points after the injury (early at 1.9 ± 1.0 days and late at 5.9 ± 2.2 days) and outcome evaluation was performed after three months. Six proteins were measured using ELISAs: p75NTR, NGF, sortilin, IL1, TNF, and cyclophilin A. A 2-tailed 2-sample t-test, univariate, and multivariate linear discriminant analysis (LDA) was used to compare serum molecules between patients with favorable (modified Rankin Scale (mRS) 0-3) and unfavorable outcome (mRS 4-6). Additionally, circulating miRNAs were extracted from the samples (n=48, early and late) and DE miRNAs were identified using DESeq2. The miRNA putative target genes were predicted and LDA was performed using the normalized expression values of identified DE miRNAs. Results: In this study, p75NTR (p < 0.01) and IL1 (p < 0.05) were found to be independently associated with outcome among the six circulating protein biomarkers studied. Combinatory LDA analysis of all six biomarkers showed significant predictive value for favorable outcome (OR 2.95 (1.46-5.98); area under the curve (AUC)= 71.2%, 95% CI = (0.590-0.833), p = 0.003). Temporal alterations of miRNA expression were observed in the aSAH, TBI, and IS groups (p<0.05, FDR corrected). Twenty-three common miRNAs were identified that differentiated favorable and unfavorable outcome (p<0.05) in all three groups. LDA of four identified miRNAs with predicted targets to studied proteins showed high predictive accuracy (OR (95% CI) 11.7 (2.39-226)); AUC = 94.1%, 95% CI = (0.849 - 1.00), p = 0.016). Conclusions This study indicates that assessing serum levels of p75NTR and its mechanistically linked proteins can predict recovery outcome in patients with different types of acute brain injuries. The combined miRNA and protein biomarker models demonstrated accurate outcome prediction across diverse injury types, implying the presence of a common recovery mechanism. DE miRNAs were found to target the studied molecules, suggesting a potential mechanistical role in recovery. The identified common miRNAs may provide new targets for mechanistic validation in disease models. Further investigation is warranted to validate and explore the potential of these proteins and miRNAs in prognostication and as therapeutic targets for enhancing recovery from acute brain injuries.

Dataset Information

Plasma microRNAs as biomarkers of pancreatic cancer risk in a prospective cohort study.

Publications

Plasma microRNAs as biomarkers of pancreatic cancer risk in a prospective cohort study.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure