Dataset Information

Blood platelet RNA enables the detection of multiple sclerosis.

ABSTRACT: Background:In multiple sclerosis (MS), clinical assessment, MRI and cerebrospinal fluid are important in the diagnostic process. However, no blood biomarker has been confirmed as a useful tool in the diagnostic work-up. Objectives:Blood platelets contain a rich spliced mRNA repertoire that can alter during megakaryocyte development but also during platelet formation and platelet circulation. In this proof of concept study, we evaluate the diagnostic potential of spliced blood platelet RNA for the detection of MS. Methods:We isolated and sequenced platelet RNA of blood samples obtained from 57 MS patients and 66 age- and gender-matched healthy controls (HCs). 60% was used to develop a particle swarm-optimized (PSO) support vector machine classification algorithm. The remaining 40% served as an independent validation series. Results:In total, 1249 RNAs with differential spliced junction expression levels were identified between platelets of MS patients as compared to HCs, including EPSTI1, IFI6, and RPS6KA3, in line with reported inflammatory signatures in the blood of MS patients. The RNAs were subsequently used as input for a MS classifier, capable of detecting MS with 80% accuracy in the independent validation series. Conclusions:Spliced platelet RNA may enable the blood-based diagnosis of MS, warranting large-scale validation.

SUBMITTER: Sol N

PROVIDER: S-EPMC7418262 | biostudies-literature | 2020 Jul-Sep

REPOSITORIES: biostudies-literature

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Blood platelet RNA enables the detection of multiple sclerosis.

Sol Nik N Leurs Cyra E CE Veld Sjors Gjg In 't SGI' Strijbis Eva M EM Vancura Adrienne A Schweiger Markus W MW Teunissen Charlotte E CE Mateen Farrah J FJ Tannous Bakhos A BA Best Myron G MG Würdinger Thomas T Killestein Joep J

Multiple sclerosis journal - experimental, translational and clinical 20200730 3

<h4>Background</h4>In multiple sclerosis (MS), clinical assessment, MRI and cerebrospinal fluid are important in the diagnostic process. However, no blood biomarker has been confirmed as a useful tool in the diagnostic work-up.<h4>Objectives</h4>Blood platelets contain a rich spliced mRNA repertoire that can alter during megakaryocyte development but also during platelet formation and platelet circulation. In this proof of concept study, we evaluate the diagnostic potential of spliced blood plat ...[more]

PMID: 32843989

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Project description:BackgroundEarly diagnosis is crucial for effective medical management of cancer patients. Tissue biopsy has been widely used for cancer diagnosis, but its invasive nature limits its application, especially when repeated biopsies are needed. Over the past few years, genomic explorations have led to the discovery of various blood-based biomarkers. Tumor Educated Platelets (TEPs) have, of late, generated considerable interest due to their ability to infer tumor existence and subtype accurately. So far, a majority of the studies involving TEPs have offered marker-panels consisting of several hundreds of genes. Profiling large numbers of genes incur a significant cost, impeding its diagnostic adoption. As such, it is important to construct minimalistic molecular signatures comprising a small number of genes.ResultsTo address the aforesaid challenges, we analyzed publicly available TEP expression profiles and identified a panel of 11 platelet-genes that reliably discriminates between cancer and healthy samples. To validate its efficacy, we chose non-small cell lung cancer (NSCLC), the most prevalent type of lung malignancy. When applied to platelet-gene expression data from a published study, our machine learning model could accurately discriminate between non-metastatic NSCLC cases and healthy samples. We further experimentally validated the panel on an in-house cohort of metastatic NSCLC patients and healthy controls via real-time quantitative Polymerase Chain Reaction (RT-qPCR) (AUC = 0.97). Model performance was boosted significantly after artificial data-augmentation using the EigenSample method (AUC = 0.99). Lastly, we demonstrated the cancer-specificity of the proposed gene-panel by benchmarking it on platelet transcriptomes from patients with Myocardial Infarction (MI).ConclusionWe demonstrated an end-to-end bioinformatic plus experimental workflow for identifying a minimal set of TEP associated marker-genes that are predictive of the existence of cancers. We also discussed a strategy for boosting the predictive model performance by artificial augmentation of gene expression data.

Dataset Information

Blood platelet RNA enables the detection of multiple sclerosis.

Publications

Blood platelet RNA enables the detection of multiple sclerosis.

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