Dataset Information

FIMICS: A panel of long noncoding RNAs for cardiovascular conditions.

ABSTRACT: Cardiovascular disorders such as heart failure are leading causes of mortality. Patient stratification via identification of novel biomarkers could improve management of cardiovascular diseases of complex etiologies. Long-noncoding RNAs (lncRNAs) are highly tissue-specific in nature and have emerged as important biomarkers in human diseases. In this study, we aimed to identify cardiac-enriched lncRNAs as potential biomarkers for cardiovascular conditions. Deep RNA sequencing and quantitative PCR identified differentially expressed lncRNAs between failing and non-failing hearts. An independent dataset was used to evaluate the enrichment of lncRNAs in normal hearts. We identified a panel of 2906 lncRNAs, named FIMICS, that were either cardiac-enriched or differentially expressed between failing and non-failing hearts. Expression of lncRNAs in blood samples differentiated patients with myocarditis and acute myocardial infarction. We hereby present the FIMICS panel, a readily available tool to provide insights into cardiovascular pathologies and which could be helpful for diagnosis, monitoring and prognosis purposes.

SUBMITTER: Firat H

PROVIDER: S-EPMC9898641 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature

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FIMICS: A panel of long noncoding RNAs for cardiovascular conditions.

Firat Huseyin H Zhang Lu L Baksi Shounak S Leszek Przemyslaw P Schordan Eric E Ounzain Samir S Kottwitz Jan J Patriki Dimitri D Heidecker Bettina B Lüscher Thomas F TF Pedrazzini Thierry T Devaux Yvan Y

Heliyon 20230120 1

Cardiovascular disorders such as heart failure are leading causes of mortality. Patient stratification via identification of novel biomarkers could improve management of cardiovascular diseases of complex etiologies. Long-noncoding RNAs (lncRNAs) are highly tissue-specific in nature and have emerged as important biomarkers in human diseases. In this study, we aimed to identify cardiac-enriched lncRNAs as potential biomarkers for cardiovascular conditions. Deep RNA sequencing and quantitative PCR ...[more]

PMID: 36747920

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Project description:Rationale: Long extracellular RNAs (exRNAs) in plasma can be profiled by new sequencing technologies, even with low abundance. However, cancer-related exRNAs and their variations remain understudied. Methods: We investigated different variations (i.e. differential expression, alternative splicing, alternative polyadenylation, and differential editing) in diverse long exRNA species (e.g. long noncoding RNAs and circular RNAs) using 79 plasma exosomal RNA-seq (exoRNA-seq) datasets of multiple cancer types. We then integrated 53 exoRNA-seq datasets and 65 self-profiled cell-free RNA-seq (cfRNA-seq) datasets to identify recurrent variations in liver cancer patients. We further combined TCGA tissue RNA-seq datasets and validated biomarker candidates by RT-qPCR in an individual cohort of more than 100 plasma samples. Finally, we used machine learning models to identify a signature of 3 noncoding RNAs for the detection of liver cancer. Results: We found that different types of RNA variations identified from exoRNA-seq data were enriched in pathways related to tumorigenesis and metastasis, immune, and metabolism, suggesting that cancer signals can be detected from long exRNAs. Subsequently, we identified more than 100 recurrent variations in plasma from liver cancer patients by integrating exoRNA-seq and cfRNA-seq datasets. From these datasets, 5 significantly up-regulated long exRNAs were confirmed by TCGA data and validated by RT-qPCR in an independent cohort. When using machine learning models to combine two of these validated circular and structured RNAs (SNORD3B-1, circ-0080695) with a miRNA (miR-122) as a panel to classify liver cancer patients from healthy donors, the average AUROC of the cross-validation was 89.4%. The selected 3-RNA panel successfully detected 79.2% AFP-negative samples and 77.1% early-stage liver cancer samples in the testing and validation sets. Conclusions: Our study revealed that different types of RNA variations related to cancer can be detected in plasma and identified a 3-RNA detection panel for liver cancer, especially for AFP-negative and early-stage patients.

Dataset Information

FIMICS: A panel of long noncoding RNAs for cardiovascular conditions.

Publications

FIMICS: A panel of long noncoding RNAs for cardiovascular conditions.

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