Browse
Submit Data
Databases
API
Help

Dataset Information

41 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Tissue and exosomal miRNA editing in Non-Small Cell Lung Cancer.

ABSTRACT: RNA editing in microRNAs has been recently proposed as a novel biomarker in cancer. Here, we investigated RNA editing by leveraging small-RNA sequencing data from 87 NSCLC (Non-Small Cell Lung Cancer) samples paired with normal lung tissues from The Cancer Genome Atlas (TCGA) combined with 26 plasma-derived exosome samples from an independent cohort. Using both the editing levels and microRNA editing expression, we detected deregulated microRNA editing events between NSCLC tumor and normal tissues. Interestingly, and for the first time, we also detected editing sites in the microRNA cargo of circulating exosomes, providing the potential to non-invasively discriminate between normal and tumor samples. Of note, miR-411-5p edited in position 5 was significantly dysregulated in tissues as well as in exosomes of NSCLC patients, suggesting a potential targetome shift relevant to lung cancer biology.

SUBMITTER: Nigita G

PROVIDER: S-EPMC6033928 | biostudies-literature | 2018 Jul

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

Tissue and exosomal miRNA editing in Non-Small Cell Lung Cancer.

Nigita Giovanni G Distefano Rosario R Veneziano Dario D Romano Giulia G Rahman Mohammad M Wang Kai K Pass Harvey H Croce Carlo M CM Acunzo Mario M Nana-Sinkam Patrick P

Scientific reports 20180705 1

RNA editing in microRNAs has been recently proposed as a novel biomarker in cancer. Here, we investigated RNA editing by leveraging small-RNA sequencing data from 87 NSCLC (Non-Small Cell Lung Cancer) samples paired with normal lung tissues from The Cancer Genome Atlas (TCGA) combined with 26 plasma-derived exosome samples from an independent cohort. Using both the editing levels and microRNA editing expression, we detected deregulated microRNA editing events between NSCLC tumor and normal tissu ...[more]

PMID: 29976955

Similar Datasets

Tissue and exosomal miRNA editing in Non-Small Cell Lung Cancer

Project description:We analyzed small-RNA sequencing data from plasma-derived exosome (PEV) from a cohort of NSCLC patients at different stages. We identified two ED miRNAs in circulation able to distinguish between normal and tumor sample subtypes.

2018-06-29 | GSE114711 | GEO

Tissue and exosomal miRNA editing in Non-Small Cell Lung Cancer

Project description:Tissue and exosomal miRNA editing in Non-Small Cell Lung Cancer

| PRJNA472351 | ENA

Exosomal microRNA Therapy for Non-Small-Cell Lung Cancer.

Project description:With the progress of molecular diagnosis research on non-small cell lung cancer (NSCLC) cells, four identified categories of microRNAs have been found to be related to disease diagnosis, diagnosis of treatment resistance, prediction of prognosis, and drugs for treatment. To date, nine target mRNA/signal pathways have been confirmed for microRNA drug therapy both in vitro and in vivo. When microRNA drugs enter blood vessels, they target the tumor site and play a similar role to that of targeted drugs. However, whether they will produce serious off-target effects remains unknown, and further clinical research is needed. This review provides the first summary of microRNA therapy for NSCLC.

| S-EPMC10631355 | biostudies-literature

Exosomal proteins as prognostic biomarkers in non-small cell lung cancer.

Project description:BackgroundUse of exosomes as biomarkers in non-small cell lung cancer (NSCLC) is an intriguing approach in the liquid-biopsy era. Exosomes are nano-sized vesicles with membrane-bound proteins that reflect their originating cell. Prognostic biomarkers are needed to improve patient selection for optimal treatment. We here evaluate exosomes by protein phenotyping as a prognostic biomarker in NSCLC.MethodsExosomes from plasma of 276 NSCLC patients were phenotyped using the Extracellular Vesicle Array; 49 antibodies captured the proteins on the exosomes, and a cocktail of biotin-conjugated antibodies binding the general exosome markers CD9, CD81 and CD63 was used to visualise the captured exosomes. For each individual membrane-bound protein, results were analysed based on presence, in a concentration-dependent manner, and correlated to overall survival (OS).ResultsThe 49 proteins attached to the exosomal membrane were evaluated. NY-ESO-1, EGFR, PLAP, EpCam and Alix had a significant concentration-dependent impact on inferior OS. Due to multiple testing, NY-ESO-1 was the only marker that maintained a significant impact on inferior survival (hazard rate (HR) 1.78 95% (1.78-2.44); p = 0.0001) after Bonferroni correction. Results were adjusted for clinico-pathological characteristics, stage, histology, age, sex and performance status.ConclusionWe illustrate the promising aspects associated with the use of exosomal membrane-bound proteins as a biomarker and demonstrate that they are a strong prognostic biomarker in NSCLC.

| S-EPMC5423137 | biostudies-literature

Circulating exosomal microRNAs as prognostic biomarkers for non-small-cell lung cancer.

Project description:Exosomal miRNAs are proposed as excellent candidate biomarkers for clinical applications. However, little is known about their potential roles as prognostic biomarkers in lung cancer. In this study, we explored the prognostic value of plasma exosomal microRNAs (miRNAs) for non-small-cell lung cancer (NSCLC). Using a quantitative polymerase chain reaction (qPCR) array panel, we analyzed 84 plasma exosomal miRNAs in 10 lung adenocarcinoma patients and 10 matched healthy controls. The qPCR array showed 30 aberrantly expressed exosomal miRNAs. Nine candidate miRNAs were selected based on differential expression and previous reports for further evaluating their prognostic roles in 196 NSCLC patients. Elevated levels of exosomal miR-23b-3p, miR-10b-5p and miR-21-5p were independently associated with poor overall survival (with hazard ratio [95% confidence interval]: 2.42 (1.45 - 4.04), P = 0.001; 2.22 (1.18 - 4.16), P = 0.013; 2.12 (1.28 - 3.49), P = 0.003, respectively). When compared to the clinical prognostic variables only model, adding the three exosomal miRNA signatures significantly improved survival predictive accuracy with an increase of time-dependent area under the receiver operating characteristic curve from 0.88 to 0.91 (P=0.015). Our results indicated that plasma exosomal miR-23b-3p, miR-10b-5p and miR-21-5p are promising non-invasive prognostic biomarkers of NSCLC.

| S-EPMC5355076 | biostudies-literature

Exosomal miRNAs species in the blood of small cell and non-small cell lung cancer patients.

Project description:Lung cancer is a devastating disease with overall bleak prognosis. Current methods to diagnose lung cancer are rather invasive and are inadequate to detect the disease at an early stage when treatment is likely to be most effective. In this study, a shotgun sequencing approach was used to study the microRNA (miRNA) cargo of serum-derived exosomes of small cell lung cancer (SCLC) (n=9) and non-small cell lung cancer (NSCLC) (n=11) patients, and healthy controls (n=10). The study has identified 17 miRNA species that are differentially expressed in cancer patients and control subjects. Furthermore, within the patient groups, a set of miRNAs were differentially expressed in exosomal samples obtained before and after chemotherapy treatment. This manuscript demonstrates the potential of exosomal miRNAs for developing noninvasive tests for disease differentiation and treatment monitoring in lung cancer patients.

| S-EPMC5929426 | biostudies-literature

Tumor-Derived Exosomal miRNAs as Diagnostic Biomarkers in Non-Small Cell Lung Cancer.

Project description:BackgroundDelayed diagnosis is the main obstacle to improve prognosis of non-small cell lung cancer (NSCLC). Novel biomarkers for the diagnosis of NSCLC are urgently needed. This study aimed to identify the specific exosomal miRNAs with diagnostic and prognostic potential in NSCLC patients.Materials and methodsTransmission electron microscopy (TEM), qNano and western blots were used to characterize the exosomes isolated from the serum of NSCLC patients (n=330) and healthy donors (n=312) by ultracentrifugation. Exosomal miRNAs were profiled by miRNA microarrays and verified by quantitative PCR (qPCR). The diagnostic accuracy was determined by receiver operating characteristic (ROC) analysis.ResultsA total of differential 22 miRNAs were screened out based on P < 0.05 and fold difference>2.0 by miRNA microarrays, among which, exosomal miR-5684 and miR-125b-5p were significantly down-regulated in NSCLC patients compared to healthy donors, processing favorable diagnostic efficiency for (early) NSCLC. Importantly, the exosomal miR-125b-5p were associated with metastasis (P < 0.0001), chemotherapeutic effect (P=0.007) and survival (P=0.008).ConclusionExosomal miR-5684 and miR-125b-5p levels are significantly down-regulated in NSCLC patients, and serve as the promising diagnostic and prognostic biomarkers for NSCLC.

| S-EPMC7592397 | biostudies-literature

Exosomal lipids for classifying early and late stage non-small cell lung cancer.

Project description:Lung cancer is the leading cause of cancer deaths in the United States. Patients with early stage lung cancer have the best prognosis with surgical removal of the tumor, but the disease is often asymptomatic until advanced disease develops, and there are no effective blood-based screening methods for early detection of lung cancer in at-risk populations. We have explored the lipid profiles of blood plasma exosomes using ultra high-resolution Fourier transform mass spectrometry (UHR-FTMS) for early detection of the prevalent non-small cell lung cancers (NSCLC). Exosomes are nanovehicles released by various cells and tumor tissues to elicit important biofunctions such as immune modulation and tumor development. Plasma exosomal lipid profiles were acquired from 39 normal and 91 NSCLC subjects (44 early stage and 47 late stage). We have applied two multivariate statistical methods, Random Forest (RF) and Least Absolute Shrinkage and Selection Operator (LASSO) to classify the data. For the RF method, the Gini importance of the assigned lipids was calculated to select 16 lipids with top importance. Using the LASSO method, 7 features were selected based on a grouped LASSO penalty. The Area Under the Receiver Operating Characteristic curve for early and late stage cancer versus normal subjects using the selected lipid features was 0.85 and 0.88 for RF and 0.79 and 0.77 for LASSO, respectively. These results show the value of RF and LASSO for metabolomics data-based biomarker development, which provide robust an independent classifiers with sparse data sets. Application of LASSO and Random Forests identifies lipid features that successfully distinguish early stage lung cancer patient from healthy individuals.

| S-EPMC6582997 | biostudies-literature

Genetic variants of miRNA sequences and non-small cell lung cancer survival.

Project description:Recent evidence indicates that small noncoding RNA molecules known as microRNAs (miRNAs) can function as tumor suppressors and oncogenes. Mutation, misexpression, and altered mature miRNA processing are implicated in carcinogenesis and tumor progression. Because SNPs in pre-miRNAs could alter miRNA processing, expression, and/or binding to target mRNA, we conducted a systematic survey of common pre-miRNA SNPs and their surrounding regions and evaluated in detail the association of 4 of these SNPs with the survival of individuals with non-small cell lung cancer (NSCLC). When we assumed that disease susceptibility was inherited as a recessive phenotype, we found that the rs11614913 SNP in hsa-mir-196a2 was associated with survival in individuals with NSCLC. Specifically, survival was significantly decreased in individuals who were homozygous CC at SNP rs11614913. In the genotype-phenotype correlation analysis of 23 human lung cancer tissue samples, rs11614913 CC was associated with a statistically significant increase in mature hsa-mir-196a expression but not with changes in levels of the precursor, suggesting enhanced processing of the pre-miRNA to its mature form. Furthermore, binding assays revealed that the rs11614913 SNP can affect binding of mature hsa-mir-196a2-3p to its target mRNA. Therefore, the rs11614913 SNP in hsa-mir-196a2 may be a prognostic biomarker for NSCLC. Further characterization of miRNA SNPs may open new avenues for the study of cancer and therapeutic interventions.

| S-EPMC2402113 | biostudies-literature

Exosomal circSHKBP1 participates in non-small cell lung cancer progression through PKM2-mediated glycolysis.

Project description:Non-small cell lung cancer (NSCLC) has a high morbidity and mortality, and it is imperative to explore the latent pathogenesis mechanism of NSCLC progression to find potential prognostic biomarkers and therapeutic targets. The present study aimed to explore the biological function of circSHKBP1 in NSCLC. circSHKBP1 was found to be upregulated in NSCLC tissues and cell lines and was enriched in exosomes derived from NSCLC cells. Exosomal circSHKBP1 enhanced the proliferation, migration, invasion, and stemness of NSCLC cells. miRNA-1294 was identified as a target for circSHKBP1, and circSHKBP1 upregulated PKM2 expression by sponging miR-1294. Exosomal circSHKBP1 regulated glycolysis through PKM2 in a HIF-1α-dependent manner in NSCLC cells and promoted M2 polarization and macrophage recruitment. Moreover, exosomal circSHKBP1 promoted NSCLC cell growth, metastasis, and M2 infiltration in vivo. Thus, exosomal circSHKBP1 participated in the progression of NSCLC via the miR-1294/PKM2 axis. circSHKBP1 may be potential biomarker for the diagnosis and treatment of NSCLC.

| S-EPMC8844869 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data