Dataset Information

Extracellular vesicles miR-574-5p and miR-181a-5p as prognostic markers in NSCLC patients treated with nivolumab

ABSTRACT: Plasma from 245 patients with advanced NSCLC who received nivolumab as second-line therapy was collected and analyzed. EV-miRnome was profiled on 174/245 patients by microarray platform and selected EV-miRs were validated by qPCR. A prognostic model combining EV-miR and clinical variables was built using stepwise Cox regression analysis and tested on an independent patient cohort (71/245). EV-PD-L1 gene copy number was assessed by digital PCR. For 54 patients with disease control, EV-miR changes at best response versus baseline were investigated by microarray and validated by qPCR. EV-miRNome profiling at baseline identified two EV-miR (miR-181a-5p, miR-574-5p) that, combined with performance status, are capable of discriminating patients unlikely from those that are likely to benefit from immunotherapy (median overall survival of 4 months or higher than 9 months, respectively). EV-PD-L1 digital evaluation reported higher baseline copy number in patients at increased mortality risk, without improving the prognostic score. Best response EV-miRNome profiling selected six deregulated EV-miRs (miR19a-3p, miR-20a-5p, miR-142-3p, miR-1260a, miR-1260b, miR-5100) in responding patients. Their longitudinal monitoring highlighted a significant downmodulation already in the first treatment cycles, which lasted more than six months. Grantee: Simona Coco Grantor: Italian Ministry of Health Grant ID: CO-2016-02361470 Grant Title: Exosomal miRNA signature as prognostic marker in advanced non-small cell lung cancer (NSCLC) patients treated with Nivolumab

ORGANISM(S): Homo sapiens

PROVIDER: GSE207715 | GEO | 2024/07/28

REPOSITORIES: GEO

ACCESS DATA

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Project description:Objectives: Secretion of extracellular vesicles (EV) and associated micro-RNAs (miR) is altered during cellular stress and may serve as biomarkers of organ injury. We hypothesized that measuring changes in urinary levels of EV and miR will predict the onset of acute kidney injury in cardiac surgery patients. Design: Predictive accuracy biomarker study performed in the cohort of the REVAKI-2 trial Setting: Single center ICU between September 2015 and September 2018 Interventions: Intravenous sildenafil citrate 12.5 mg kg-1 over 150 min or dextrose 5% at the commencement of surgery. Measurements and main results: Urine samples were collected before and 24 hours after the procedure from 93 cardiac surgery patients. Urine EV concentrations and size distribution were assessed using NanoSight. EV derivation and levels were measured using flow cytometry. Samples from 10 selected patients were sequenced to detect differentially expressed miR. Verification was performed with advanced TaqMan assays in samples from all patients. Urine EV concentrations significantly increased in patients with AKI after surgery, with the percentage of EV positive for aquaporin-2 and β1-integrin also increasing. Pre surgery podocalyxin-positive EV were significantly lower, and β1-integrin EV werehigher in patients with AKI. The levels of the former correlated with the severity of theinjury. miR-125a-5p was expressed at higher levels in urine from patients with AKI stage 2/3. Levels of miR-10a-5p decreased after surgery in AKI patients; its levels correlated with the severity of the injury. Preoperative levels of podocalyxin EVs and miR-125a-5p had moderate AKI predictive value and, in a logistic model together with ICU lactate levels, offered good (AUC = 80.9%) AKI prediction. Conclusions: Lower levels of podocalyxin-positive EV at baseline predict the severity of post-surgery AKI. Urine EV concentrations and miR expression offer excellent predictive accuracy when combined with commonly measured biomarkers.

Dataset Information

Extracellular vesicles miR-574-5p and miR-181a-5p as prognostic markers in NSCLC patients treated with nivolumab

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets