Dataset Information

EV-associated miRNAs from pleural lavage as potential diagnostic biomarkers in lung cancer.

ABSTRACT: Lung cancer is the leading cause of cancer-related deaths among men and women in the world, accounting for the 25% of cancer mortality. Early diagnosis is an unmet clinical issue. In this work, we focused to develop a novel approach to identify highly sensitive and specific biomarkers by investigating the use of extracellular vesicles (EVs) isolated from the pleural lavage, a proximal fluid in lung cancer patients, as a source of potential biomarkers. We isolated EVs by ultracentrifuge method from 25 control pleural fluids and 21 pleural lavages from lung cancer patients. Analysis of the expression of EV-associated miRNAs was performed using Taqman OpenArray technology through which we could detect 288 out of the 754 miRNAs that were contained in the OpenArray. The differential expression analysis yielded a list of 14 miRNAs that were significantly dysregulated (adj. p-value?

SUBMITTER: Roman-Canal B

PROVIDER: S-EPMC6803646 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

EV-associated miRNAs from pleural lavage as potential diagnostic biomarkers in lung cancer.

Roman-Canal Berta B Moiola Cristian Pablo CP Gatius Sònia S Bonnin Sarah S Ruiz-Miró Maria M González Esperanza E Ojanguren Amaia A Recuero José Luis JL Gil-Moreno Antonio A Falcón-Pérez Juan M JM Ponomarenko Julia J Porcel José M JM Matias-Guiu Xavier X Colas Eva E

Scientific reports 20191021 1

Lung cancer is the leading cause of cancer-related deaths among men and women in the world, accounting for the 25% of cancer mortality. Early diagnosis is an unmet clinical issue. In this work, we focused to develop a novel approach to identify highly sensitive and specific biomarkers by investigating the use of extracellular vesicles (EVs) isolated from the pleural lavage, a proximal fluid in lung cancer patients, as a source of potential biomarkers. We isolated EVs by ultracentrifuge method fr ...[more]

PMID: 31636323

Similar Datasets

Project description:BackgroundExtracellular vesicles (EVs), ubiquitously released by blood cells, facilitate intercellular communication. In cancer, tumor-derived EVs profoundly affect the microenvironment, promoting tumor progression and raising the risk of recurrence. These EVs contain miRNAs (EV-miRNAs), promising cancer biomarkers. Characterizing plasma EVs and identifying EV-miRNAs associated with breast cancer recurrence are crucial aspects of cancer research since they allow us to discover new biomarkers that are effective for understanding tumor biology and for being used for early detection, disease monitoring, or approaches to personalized medicine. This study aimed to characterize plasma EVs in breast cancer (BC) patients and identify EV-miRNAs associated with BC recurrence.MethodsThis retrospective observational study included 24 BC patients divided into recurrence (n= 11) and non-recurrence (n= 13) groups. Plasma EVs were isolated and characterized. Total RNA from EVs was analyzed for miRNA expression using NanoString's nCounter® miRNA Expression Assays panel. MicroRNA target prediction used mirDIP, and pathway interactions were assessed via Reactome.ResultsA stronger presence of circulating EVs was found to be linked with a less favorable prognosis (p = 0.0062). We discovered a distinct signature of EV-miRNAs, notably including miR-19a-3p and miR-130b-3p, which are significantly associated with breast cancer recurrence. Furthermore, miR-19a-3p and miR-130b-3p were implicated in the regulation of PTEN and MDM4, potentially contributing to breast cancer progression.A notable association emerged, indicating a high concentration of circulating EVs predicts poor prognosis (p = 0.0062). Our study found a distinct EV-miRNA signature involving miR-19a-3p and miR-130b-3p, strongly associated with disease recurrence. We also presented compelling evidence for their regulatory roles in PTEN and MDM4 genes, contributing to BC development.ConclusionThis study revealed that increased plasma EV concentration is associated with BC recurrence. The prognostic significance of EVs is closely tied to the unique expression profiles of miR-19a-3p and miR-130b-3p. These findings underscore the potential of EV-associated miRNAs as valuable indicators for BC recurrence, opening new avenues for diagnosis and treatment exploration.

Project description:Lung cancer is one of the most prevalent and life-threatening neoplasias worldwide due to the deficiency of ideal diagnostic biomarkers. Although aberrant glycosylation has been observed in human serum and tissue, little is known about the alterations in bronchoalveolar lavage fluid (BALF) that are extremely associated with lung cancer. In this study, our aim was to systematically investigate and assess the alterations of protein glycopatterns in BALF and possibility as biomarkers for diagnosis of lung cancer. Here, lectin microarrays and blotting analysis were utilized to detect the differential expression of BALF glycoproteins from patients with 80 adenocarcinomas (ADC), 77 squamous carcinomas (SCC), 51 small cell lung cancer (SCLC), and 73 benign pulmonary diseases (BPD). These 281 specimens were then randomly divided into a training cohort and validation cohort for constructing and verifying the diagnostic models based on the glycopattern abundances. Moreover, an independent test was performed with 120 newly collected BALF samples enrolled in the double-blind cohort to further assess the clinical application potential of the diagnostic models. According to the results, there were 15 (e.g., PHA-E, EEL, and BPL) and 14 lectins (e.g., PTL-II, LCA, and SJA) that individually showed significant variations in different types and stages of lung cancer compared to BPD. Notably, the diagnostic models achieved better discriminate power in the validation cohort and exhibited high accuracies of 0.917, 0.864, 0.712, 0.671, and 0.781 in the double-blind cohort for the diagnosis of lung cancer, early stage lung cancer, ADC, SCC, and SCLC, respectively. Taken together, the present study revealed that the abnormally altered protein glycopatterns in BALF are expected to be novel potential biomarkers for the identification and early diagnosis of lung cancer, which will contribute to explain the mechanism of the development of lung cancer from the perspective of glycobiology.

Dataset Information

EV-associated miRNAs from pleural lavage as potential diagnostic biomarkers in lung cancer.

Publications

EV-associated miRNAs from pleural lavage as potential diagnostic biomarkers in lung cancer.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets