scholarly journals In Silico Identification and Clinical Validation of a Novel Long Non-Coding RNA/mRNA/miRNA Molecular Network for Potential Biomarkers for Discriminating SARS CoV-2 Infection Severity

Cells ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 3098
Author(s):  
Sara H. A. Agwa ◽  
Hesham Elghazaly ◽  
Mahmoud Shawky El Meteini ◽  
Sherif M. Shawky ◽  
Marwa Ali ◽  
...  
Keyword(s):  
In Silico ◽  
Predictive Biomarkers ◽  
Severe Pneumonia ◽  
Genetic Network ◽  
Molecular Network ◽  
Clinical Validation ◽  
Diagnostic Assays ◽  
Non Coding Rna ◽  
Severity Prediction ◽  
Potential Biomarkers

(1) Background: The coronavirus (COVID-19) pandemic is still a major global health problem, despite the development of several vaccines and diagnostic assays. Moreover, the broad symptoms, from none to severe pneumonia, and the various responses to vaccines and the assays, make infection control challenging. Therefore, there is an urgent need to develop non-invasive biomarkers to quickly determine the infection severity. Circulating RNAs have been proven to be potential biomarkers for a variety of diseases, including infectious ones. This study aimed to develop a genetic network related to cytokines, with clinical validation for early infection severity prediction. (2) Methods: Extensive analyses of in silico data have established a novel IL11RA molecular network (IL11RNA mRNA, LncRNAs RP11-773H22.4 and hsa-miR-4257). We used different databases to confirm its validity. The differential expression within the retrieved network was clinically validated using quantitative RT-PCR, along with routine assessment diagnostic markers (CRP, LDH, D-dimmer, procalcitonin, Ferritin), in100 infected subjects (mild and severe cases) and 100 healthy volunteers. (3) Results: IL11RNA mRNA and LncRNA RP11-773H22.4, and the IL11RA protein, were significantly upregulated, and there was concomitant downregulation of hsa-miR-4257, in infected patients, compared to the healthy controls, in concordance with the infection severity. (4) Conclusion: The in-silico data and clinical validation led to the identification of a potential RNA/protein signature network for novel predictive biomarkers, which is in agreement with ferritin and procalcitonin for determination of COVID-19 severity.

scholarly journals Genomic Analysis of Glioblastoma Multiforme Reveals a Key Transcription Factor Signature Relevant to Prognosis and the Immune Processes

2021 ◽  
Vol 11 ◽  
Author(s):  
Zhen-Hang Li ◽  
Yan-Lei Guan ◽  
Guo-Bin Zhang
Keyword(s):  
Glioblastoma Multiforme ◽  
In Silico ◽  
Prognostic Value ◽  
Genomic Analysis ◽  
Predictive Biomarkers ◽  
Risk Scores ◽  
Functional Aspects ◽  
Number Variation ◽  
Inflammatory Processes ◽  
Functional Analyses

IntroductionGlioblastoma multiforme (GBM) develops through the accumulation of both genetic and expression alterations. Although many gene signatures have been developed as prognostic and predictive biomarkers, their robustness and functional aspects are less well characterized. The expression of most genes is regulated by transcription factors (TFs); therefore, we aimed to investigate a TF signature relevant to GBM prognosis.MethodsWe used bioinformatic methods and data from public databases to establish four clusters of key TF genes, among which cluster 1, comprising 24 TFs, showed significant prognostic value. Further in silico functional analyses were applied to investigate the utility of the TF signature.ResultsDifferent mutation and copy number variation patterns were observed between different risk score groups (based on the TF signature). In silico analyses suggested that the cases with relative high risk scores were involved in immune and inflammatory processes or pathways.ConclusionThe TF signature has significant prognostic value in different cohorts or subgroups of patients with GBM and could lead to the development immunotherapy for GBM.

scholarly journals Aberrant expression of long non-coding RNA in thyroid neoplasms

2019 ◽  
pp. 17-25
Author(s):  
В.Д. Якушина ◽  
А.С. Танас ◽  
А.В. Лавров
Keyword(s):  
Thyroid Cancer ◽  
Signaling Pathway ◽  
In Silico ◽  
Thyroid Nodules ◽  
Differentially Expressed ◽  
Follicular Variant ◽  
Aberrant Expression ◽  
Lncrna Expression ◽  
Non Coding Rna ◽  
Long Non Coding Rna

Актуальность. Длинные некодирующие РНК (днРНК) при раке щитовидной железы плохо изучены; не известны днРНК, общие и специфичные для фолликулярного и классического вариантов папиллярного рака, не установлены днРНК, аберрантно экспрессированные при других основных субтипах злокачественных новообразований щитовидной железы, а также при доброкачественных новообразованиях. Цель исследования - определить днРНК, аберрантно экспрессированные при фолликулярной аденоме (ФА), фолликулярном раке (ФРЩЖ), фолликулярном и классическом вариантах папиллярного рака (ПРЩЖ), анапластическом раке (АРЩЖ) щитовидной железы. Методы. Проанализирована экспрессия днРНК по данным исследований на микрочипах (8 независимых экспериментов, доступных в GEO) и секвенирования РНК (PRJEB11591 и TCGA-THCA). Исследованы 246 образцов нормальной ткани щитовидной железы, 26 - ФА, 30 - ФРЩЖ, 181 - фолликулярного варианта ПРЩЖ, 481 - классического варианта ПРЩЖ и 49 - АРЩЖ. Для классического и фолликулярного вариантов ПРЩЖ выполнена валидация дифференциальной экспрессии in silico. Потенциальные биологические функции были оценены в результате анализа обогащения коэкспрессированных генов. Результаты. Определены днРНК, дифференциально экспрессированные при ФА, ФРЩЖ, фолликулярном и классическом вариантах ПРЩЖ и АРЩЖ. Выявлены 8 днРНК, экспрессия которых изменена во всех субтипах новообразований щитовидной железы, 22 - общих для ПРЩЖ, 32 - специфичных для классического варианта ПРЩЖ, 1 - специфичная для фолликулярного варианта ПРЩЖ, и 177 - специфичных для АРЩЖ. Статистически значимо дифференциально экспрессированных днРНК в ФРЩ по сравнению с ФА не выявлено. Ранее известные онкогенные и супрессорные днРНК NR2F1-AS1, LINC00511, SLC26A4-AS1, CRNDE, RMST впервые обнаружены в новообразованиях щитовидной железы. Выявленные днРНК предположительно вовлечены в клеточную адгезию, организацию экстрацеллюлярного матрикса, образование эндодермы, регуляцию клеточного цикла и митоза, полярности клеток, сигнальные пути VEGF и WNT. Выводы. Установлены общие и специфичные паттерны экспрессии днРНК в доброкачественных и злокачественных новообразованиях щитовидной железы. Background. Long non-coding RNA (lncRNA) in thyroid cancer are poorly investigated; no lncRNAs common and specific for the follicular and classical variants of papillary cancer, as well as no lncRNAs aberrantly expressed in benign nodules or other subtypes of thyroid cancer are established. The objective of the study is to determine long noncoding RNAs aberrantly expressed in follicular adenoma (FA), follicular carcinoma (FTC), follicular and classical variants of papillary carcinoma (PTC), anaplastic carcinoma (ATC). Methods. lncRNA expression was analyzed in dataset of Microarray (8 independent experiments available in GEO) and RNA-seq studies (PRJEB11591 and TCGA-THCA). In total, 246 samples of normal thyroid tissue, 26 FAs, 30 FTCs, 181 follicular variant PTCs, 481 classic variant PTCs and 49 ATCs were examined. In silico validation was performed. Potential biological functions were assessed by enrichment analysis of coexpressed genes. Results. LncRNAs differentially expressed in FA, FTC, follicular, and classical variants of PTC, and ATC are identified. There are 8 lncRNAs common for all investigated thyroid nodules, 22 common for PTC, 32 specific for classical PTC, 1 specific for follicular variant of PTC, and 177 specific for ATC. No lncRNA significantly differentially expressed in FTC compared to FA is identified. The previously described oncogenic and suppressor lncRNAs NR2F1-AS1, LINC00511, SLC26A4-AS1, CRNDE, RMST are detected in thyroid carcinomas for the first time. Identified lncRNA are putatively involved in cell adhesion, extracellular matrix organization, endoderm formation, VEGF signaling pathway, WNT signaling pathway and cell polarity, cell cycle and mitosis. Conclusion. The general and specific patterns of lncRNA expression in benign and malignant thyroid nodules are established.

scholarly journals Potential Novel Biomarkers in Chronic Graft-Versus-Host Disease

2020 ◽  
Vol 11 ◽  
Author(s):  
Rachel E. Crossland ◽  
Francesca Perutelli ◽  
Katarzyna Bogunia-Kubik ◽  
Nuala Mooney ◽  
Nina Milutin Gašperov ◽  
...  
Keyword(s):  
Graft Versus Host Disease ◽  
Predictive Biomarkers ◽  
Bacterial Strains ◽  
Hematopoietic Stem ◽  
Host Disease ◽  
Graft Versus Host ◽  
Novel Biomarkers ◽  
New Treatment ◽  
The Cost ◽  
Potential Biomarkers

Prognostic, diagnostic or predictive biomarkers are urgently needed for assessment of chronic graft-versus-host disease (cGvHD), a major risk for patients undergoing allogeneic hematopoietic stem cell transplantation. The main goal of this review generated within the COST Action EUROGRAFT “Integrated European Network on Chronic Graft Versus Host Disease” was to identify potential novel biomarkers for cGvHD besides the widely accepted molecular and cellular biomarkers. Thus, the focus was on cellular biomarkers, alloantibodies, glycomics, endothelial derived particles, extracellular vesicles, microbiome, epigenetic and neurologic changes in cGvHD patients. Both host-reactive antibodies in general, and particularly alloantibodies have been associated with cGvHD and require further consideration. Glycans attached to IgG modulate its activity and represent a promising predictive and/or stratification biomarker for cGVHD. Furthermore, epigenetic changes such as microRNAs and DNA methylation represent potential biomarkers for monitoring cGvHD patients and novel targets for developing new treatment approaches. Finally, the microbiome likely affects the pathophysiology of cGvHD; bacterial strains as well as microbial metabolites could display potential biomarkers for dysbiosis and risk for the development of cGvHD. In summary, although there are no validated biomarkers currently available for clinical use to better inform on the diagnosis, prognosis or prediction of outcome for cGvHD, many novel sources of potential markers have shown promise and warrant further investigation using well characterized, multi-center patient cohorts.

scholarly journals In silico discovery and modeling of non-coding RNA structure in viruses

Methods ◽  
2015 ◽  
Vol 91 ◽  
pp. 48-56 ◽  
Author(s):  
Walter N. Moss ◽  
Joan A. Steitz
Keyword(s):  
In Silico ◽  
Rna Structure ◽  
Non Coding Rna

scholarly journals Early Onset Ataxia with Comorbid Dystonia: Clinical, Anatomical and Biological Pathway Analysis Expose Shared Pathophysiology

Diagnostics ◽  
2020 ◽  
Vol 10 (12) ◽  
pp. 997
Author(s):  
Deborah A. Sival ◽  
Martinica Garofalo ◽  
Rick Brandsma ◽  
Tom A. Bokkers ◽  
Marloes van den Berg ◽  
...  
Keyword(s):  
Signal Transduction ◽  
In Silico ◽  
Krebs Cycle ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Genetic Network ◽  
Functional Enrichment ◽  
Biological Pathway ◽  
Adult Onset ◽  
Gene Panels

In degenerative adult onset ataxia (AOA), dystonic comorbidity is attributed to one disease continuum. However, in early adult onset ataxia (EOA), the prevalence and pathogenesis of dystonic comorbidity (EOAD+), are still unclear. In 80 EOA-patients, we determined the EOAD+-prevalence in association with MRI-abnormalities. Subsequently, we explored underlying biological pathways by genetic network and functional enrichment analysis. We checked pathway-outcomes in specific EOAD+-genotypes by comparing results with non-specifically (in-silico-determined) shared genes in up-to-date EOA, AOA and dystonia gene panels (that could concurrently cause ataxia and dystonia). In the majority (65%) of EOA-patients, mild EOAD+-features concurred with extra-cerebellar MRI abnormalities (at pons and/or basal-ganglia and/or thalamus (p = 0.001)). Genetic network and functional enrichment analysis in EOAD+-genotypes indicated an association with organelle- and cellular-component organization (important for energy production and signal transduction). In non-specifically, in-silico-determined shared EOA, AOA and dystonia genes, pathways were enriched for Krebs-cycle and fatty acid/lipid-metabolic processes. In frequently occurring EOAD+-phenotypes, clinical, anatomical and biological pathway analyses reveal shared pathophysiology between ataxia and dystonia, associated with cellular energy metabolism and network signal transduction. Insight in the underlying pathophysiology of heterogeneous EOAD+-phenotype-genotype relationships supports the rationale for testing with complete, up-to-date movement disorder gene lists, instead of single EOA gene-panels.

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