Project description:We sequenced 8 colorectal cancer patients' PBMC samples, and 6 healthy donors' PBMC samples. These individuals' plasma RNA have been profiled.
Project description:Aim: To discovery biomarkers in JIA base on gene expression from RNA sequencing on PBMC Method: Paired-end Ilumina sequencing to capture gene expression of PBMC from JIA individuals and healthy controls Results:sample heterogeneity makes RNA sequencing on PBMC unsuitable as a first-step method for screening biomarker candidates in JIA
Project description:Background: Clinical transcriptomics of peripheral blood mononuclear cells (PBMC) are coming into focus as a surrogate approach for prognosis, diagnosis, biomarker discovery and examination disease mechanisms. However, bioassays paired with transcriptomic analytic tools are yet to be developed and made available at point of care. Harnessing personal dynamic genomic responses to tailor patient asthma treatment or prevent disease exacerbations remain unmet medical needs. Method: We developed a rhinovirus-stimulated peripheral blood based-assay (virogram assay) coupled with single-subject analytics (N-of-1-patwhays) to capture dynamic genome-wide expression and dysregulated pathways to retrospectively predict childhood asthma exacerbation. We hypothesized that some genomic factors might predispose any given individual, healthy or asthmatic, to a set of similar transcriptional responses to rhinovirus stimulation. We first generated a classifier from paired sample microarrays, control and stimulated PBMC from healthy subjects and applied this classifier on the transcriptomic analysis of control and HRV-stimulated PBMC samples (virogram assay) from children with asthma. Results: The analysis of the different genomic responses of single-subject paired PBMC samples (HRV-stimulated and control) derived from healthy individuals (external dataset) enabled the discovery of dysregulated pathways related to acquired immunity, epigenetics and morphogenesis. The classifier built on these results and applied on the transcriptional analysis derived from the virogram assay predicted that the risk of asthma exacerbation among asthmatic subjects with an accuracy of 70%. Conclusion: We provide evidence that clinical prognosis can be predicted with a PBMC based-bioassay aligned with adequate single-subject analytics to assess dynamic transcriptomic response to specific disease-associated stimuli.
Project description:Multiple myeloma (MM), also known as plasma cell myeloma, is a cancer of plasma cells, a type of white blood cell normally responsible for producing antibodies. There is no cure for MM. In addition, the mechanism underlying abnormal production of plasma cells is not clear. In this experiment, peripheral blood was obtained from normal healthy donors and multiple myeloma (MM) patients. Peripheral blood mononuclear cells (PBMC) were separated by Ficoll separation solution. Samples of four donors were pooled and Samples of four MM patients were pooled. The aim was to characterize the mRNA profile of MM patients compared to healthy donors and find the new target of diagnosis or treatment for MM.
Project description:This study aimed to explore circRNA expression profiles in the plasma of patients with early-stage lung adenocarcinoma compared to healthy controls. Using Agilent microarray technology, we profiled total RNA extracted from plasma samples of 4 patients with early-stage lung adenocarcinoma (stages IA–IIA) and 4 healthy individuals. All subjects provided peripheral blood samples, and cell-free RNA was isolated from plasma. The objective was to identify potential circRNA biomarkers that could distinguish lung cancer patients from healthy individuals at early stages.
Project description:We report a 29-gene diagnostic signature, which distinguishes individuals with NSCLC from controls with non-malignant lung disease with 91% Sensitivity, 79% Specificity and a ROC AUC of 92%. Accuracy on an independent set of 18 NSCLC samples from the same location was 79%. Samples from an independent location including 12 stage 1 NSCLC and 15 controls, achieved an accuracy of 74%. A study of 18 paired samples taken pre and post surgery shows that the PBMC associated “cancer” signature is significantly reduced after tumor removal, supporting the hypothesis that the signature detected in pre-surgery samples is a response to the presence of the tumor.
