Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

A plasma miRNA-based classifier for small cell lung cancer diagnosis

ABSTRACT: A plasma miRNA-based classifier for small cell lung cancer diagnosis

PROVIDER: PRJNA1005199 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	SRR25628900.fastq.gz	Fastqsanger.gz
	SRR25628901.fastq.gz	Fastqsanger.gz
	SRR25628865.fastq.gz	Fastqsanger.gz
	SRR25628866.fastq.gz	Fastqsanger.gz
	SRR25628867.fastq.gz	Fastqsanger.gz

Items per page:

1 - 5 of 37

Similar Datasets

A plasma miRNA-based classifier for small cell lung cancer diagnosis [miRNA-Seq]

Project description:Objectives: Small cell lung cancer (SCLC) is characterized by poor prognosis and challenging diagnosis. Screening in high-risk smokers results in a reduction in lung cancer mortality, however, screening efforts are primarily focused on non-small cell lung cancer (NSCLC). SCLC diagnosis and surveillance remain significant challenges. The aberrant expression of circulating microRNAs (miRNAs/miRs) is reported in many tumors and can provide insights into the pathogenesis of tumor development and progression. Here, we conducted a comprehensive assessment of circulating miRNAs in SCLC with a goal of developing a miRNA-based biomarker classifier to assist in SCLC diagnoses. Materials and Methods: We profiled deregulated circulating cell-free miRNA in the plasma of SCLC patients. We tested selected miRs on a training cohort and created a classifier by integrating miRNA expression and patient clinical data. Finally, we applied the classifier on a validation dataset. Results: We determined that miR-375-3p can discriminate between SCLC and NSCLC patients, and between SCLC and Squamous Cell Carcinoma patients. Moreover, we found that a model comprising miR-375-3p, miR-320b, and miR-144-3p can be integrated with race and age to distinguish metastatic SCLC from a control group. Conclusion: This study proposes a miRNA-based biomarker classifier for SCLC that considers clinical demographics with specific cut offs to inform SCLC diagnosis.

2023-10-31 | GSE240757 | GEO

A plasma miRNA-based classifier for small cell lung cancer diagnosis [NanoString]

2023-10-31 | GSE240758 | GEO

A plasma miRNA-based classifier for small cell lung cancer diagnosis [miRNA-Seq]

Project description:A plasma miRNA-based classifier for small cell lung cancer diagnosis [miRNA-Seq]

| PRJNA1005200 | ENA

A plasma miRNA-based classifier for small cell lung cancer diagnosis [NanoString]

Project description:A plasma miRNA-based classifier for small cell lung cancer diagnosis [NanoString]

| PRJNA1005201 | ENA

A plasma miRNA-based classifier for small cell lung cancer diagnosis.

Project description:IntroductionSmall cell lung cancer (SCLC) is characterized by poor prognosis and challenging diagnosis. Screening in high-risk smokers results in a reduction in lung cancer mortality, however, screening efforts are primarily focused on non-small cell lung cancer (NSCLC). SCLC diagnosis and surveillance remain significant challenges. The aberrant expression of circulating microRNAs (miRNAs/miRs) is reported in many tumors and can provide insights into the pathogenesis of tumor development and progression. Here, we conducted a comprehensive assessment of circulating miRNAs in SCLC with a goal of developing a miRNA-based classifier to assist in SCLC diagnoses.MethodsWe profiled deregulated circulating cell-free miRNAs in the plasma of SCLC patients. We tested selected miRNAs on a training cohort and created a classifier by integrating miRNA expression and patients' clinical data. Finally, we applied the classifier on a validation dataset.ResultsWe determined that miR-375-3p can discriminate between SCLC and NSCLC patients, and between SCLC and Squamous Cell Carcinoma patients. Moreover, we found that a model comprising miR-375-3p, miR-320b, and miR-144-3p can be integrated with race and age to distinguish metastatic SCLC from a control group.DiscussionThis study proposes a miRNA-based biomarker classifier for SCLC that considers clinical demographics with specific cut offs to inform SCLC diagnosis.

| S-EPMC10585112 | biostudies-literature

A plasma miRNA-based classifier for small cell lung cancer diagnosis

Project description:This SuperSeries is composed of the SubSeries listed below.

2023-10-31 | GSE240759 | GEO

Identification of a robust methylation classifier for cutaneous melanoma diagnosis

Project description:Identification of a robust methylation classifier for cutaneous melanoma diagnosis

| PRJNA494817 | ENA

Diagnosis potential of subarachnoid haemorrhage using miRNA signatures isolated plasma-derived extracellular vesicles

Project description:Diagnosis potential of subarachnoid haemorrhage using miRNA signatures isolated plasma-derived extracellular vesicles

| PRJNA924332 | ENA

Comparison of miRNA expression profile between arterial plasma and venous plasma

Project description:Circulating microRNAs (miRNAs) presented in venous plasma have recently been demonstrated as powerful biomarkers for the diagnosis and prognostic prediction of complex diseases like cancer. Nevertheless, those presented in arterial plasma have been ignored based on the assumption that the miRNA profiles in arterial and venous plasma would be identical. Here, we disputed this intuitive assumption by comparing arterial and venous plasma miRNA expression profiles from male rats using microarray technique. Though the microRNA profiles were largely similar, a considerable number of miRNAs showed significant differential expression, including 10 arterial highly expressed miRNAs and 14 venous highly expressed miRNAs. The differentially expressed miRNAs were validated by qRT-PCR. We performed computational analysis of the function enrichment and disease association of these miRNAs and their targets. Our analysis also suggested significant correlations between plasma miRNA expression and tissue miRNA expression. Four arterial highly expressed miRNAs showed enriched expression in specific tissues and thus could serve as novel biomarker candidates.

2016-11-22 | GSE90098 | GEO

Analysis of plasma small RNAs prior to breast cancer diagnosis

Project description:Analysis of plasma small RNAs prior to breast cancer diagnosis

| PRJNA1001369 | ENA