Recent Development of Bioinformatics Tools for microRNA Target Prediction

Khatun, Mst. Shamima; Alam, Md. Ashad; Shoombuatong, Watshara; Mollah, Md. Nurul Haque; Kurata, Hiroyuki; Hasan, Md. Mehedi

doi:10.2174/0929867328666210804090224

Cited by 17 publications

(10 citation statements)

References 181 publications

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“…We performed a receiver operating characteristic (ROC) curve analysis, which is a graphical plot that illustrates the diagnostic ability of a binary classifier system. To evaluate the performance of our model, we estimated the area under the ROC curve (AUC) and its 95% confidence interval 43 – 45 . All data processing and analyses were done with MATLAB (R2020a, The MathWorks, Inc.) and R (R Foundation for Statistical Computing, Vienna, Austria).…”

Section: Methodsmentioning

confidence: 99%

Unsupervised machine learning for identifying important visual features through bag-of-words using histopathology data from chronic kidney disease

Lee

Warner

Shaikhouni

et al. 2022

Sci Rep

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Pathologists use visual classification to assess patient kidney biopsy samples when diagnosing the underlying cause of kidney disease. However, the assessment is qualitative, or semi-quantitative at best, and reproducibility is challenging. To discover previously unknown features which predict patient outcomes and overcome substantial interobserver variability, we developed an unsupervised bag-of-words model. Our study applied to the C-PROBE cohort of patients with chronic kidney disease (CKD). 107,471 histopathology images were obtained from 161 biopsy cores and identified important morphological features in biopsy tissue that are highly predictive of the presence of CKD both at the time of biopsy and in one year. To evaluate the performance of our model, we estimated the AUC and its 95% confidence interval. We show that this method is reliable and reproducible and can achieve 0.93 AUC at predicting glomerular filtration rate at the time of biopsy as well as predicting a loss of function at one year. Additionally, with this method, we ranked the identified morphological features according to their importance as diagnostic markers for chronic kidney disease. In this study, we have demonstrated the feasibility of using an unsupervised machine learning method without human input in order to predict the level of kidney function in CKD. The results from our study indicate that the visual dictionary, or visual image pattern, obtained from unsupervised machine learning can predict outcomes using machine-derived values that correspond to both known and unknown clinically relevant features.

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Section: Methodsmentioning

confidence: 99%

Unsupervised machine learning for identifying important visual features through bag-of-words using histopathology data from chronic kidney disease

Lee

Warner

Shaikhouni

et al. 2022

Sci Rep

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“…Competing endogenous RNAs (ceRNAs) are essentially endogenous RNAs that compete for shared microR-NAs (miRNAs) to disrupt each other's functions and thus promote the occurrence and development of multiple cancers, as proven by increasing bioinformatics and cell biology evidence 2,3 . Endogenous RNAs include long noncoding RNAs (lncRNAs), circular RNAs (circRNAs), and pseudogenes, while miRNAs act as "sponges" 4 .…”

Section: Identification Of a Novel Cerna Network Related To Prognosis...mentioning

confidence: 99%

Identification of a novel ceRNA network related to prognosis and immunity in HNSCC based on integrated bioinformatic investigation

Liu

Hei²,

Zhang³

et al. 2022

Sci Rep

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Head and neck squamous cell carcinoma (HNSCC) is characterized by an immunosuppression environment and necessitates the development of new immunotherapy response predictors. The study aimed to build a prognosis-related competing endogenous RNA (ceRNA) network based on immune-related genes (IRGs) and analyze its immunological signatures. Differentially expressed IRGs were identified by bioinformatics analysis with Gene Expression Omnibus (GEO), The Cancer Genome Atlas (TCGA) and ImmPort databases. Finally, via upstream prognosis-related microRNAs (miRNAs) and long noncoding RNAs (lncRNAs) prediction and co-expression analysis, we built an immune-related ceRNA network (LINC00052/hsa-miR-148a-3p/PLAU) related to HNSCC patient prognosis. CIBERSORT analysis demonstrated that there were substantial differences in 11 infiltrating immune cells in HNSCC, and PLAU was closely correlated with 10 type cells, including T cells CD8+ (R = − 0.329), T cells follicular helper (R = − 0.342) and macrophage M0 (R = 0.278). Methylation and Tumor Immune Dysfunction and Exclusion (TIDE) analyses revealed that PLAU upregulation was most likely caused by hypomethylation and that high PLAU expression may be associated with tumor immune evasion in HNSCC, respectively.

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“…( 5 ). MicroRNAs (miRNA) are single-stranded and evolutionarily conserved sequences of short non-coding RNAs (∼21–25 nucleotides), which act as endogenous repressors of gene expression by mRNA degradation and translational repression ( 6 , 7 ), and have been demonstrated to have critical roles in cell differentiation, development, proliferation, signaling, inflammation, and cell death ( 8 , 9 ). Hence, they are considered to be the promising candidates for novel targeted therapeutic approaches to lung diseases.…”

Section: Introductionmentioning

confidence: 99%

Hyperoxia Induced Bronchopulmonary Dysplasia-Like Inflammation via miR34a-TNIP2-IL-1β Pathway

Tao

Zeng

2022

Front. Pediatr.

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Lung injury induced by oxygen is a key contributor to the pathogenesis of preterm infant bronchopulmonary dysplasia (BPD). To date, there are comprehensive therapeutic strategy for this disease, but the underlying mechanism is still in progress. By using lentivirus, we constructed microRNA34a (miR34a)-overexpressing or knockdown A549 cell lines, and exposure to hyperoxia to mimic oxygen induce lung injury. In this study, we investigated 4 proinflammatory cytokines, interleukin-1β (IL-1β), tumor necrosis factor-α (TNF-α), angiopoietin-1 (Ang-1), and Cyclooxygenase-2 (COX-2) in the secreted sputum of infants who received mechanical ventilation, and found that IL-1β was substantially elevated in the first week after oxygen therapy and with no significant decrease until the fourth week, while TNF-α, Ang-1, and COX-2 were increased in the first week but decreased quickly in the following weeks. In addition, in vitro assay revealed that hyperoxia significantly increased the expression of miR-34a, which positively regulated the proinflammatory cytokine IL-1β in a time- and concentration-dependent manner in A549 cells. Overexpressing or knockdown miR34 would exacerbate or inhibit production of IL-1β and its upstream NOD-, LRR-, and pyrin domain-containing protein 3 (NLRP3) inflammasome signaling pathway. Mechanically, it’s found that TNFAIP3 interacting protein 2 (TNIP2), an inhibitor of nuclear factor κB (NF-κB), is a direct target of miR34a, negatively regulated activation of NLRP3 inflammasome and the production of IL-1β. Overexpressing TNIP2 ameliorated hyperoxia-induced production of IL-1β and cell apoptosis. Our findings suggest that TNIP2 may be a potential clinical marker in the diagnosis of BPD.

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Recent Development of Bioinformatics Tools for microRNA Target Prediction

Cited by 17 publications

References 181 publications

Unsupervised machine learning for identifying important visual features through bag-of-words using histopathology data from chronic kidney disease

Unsupervised machine learning for identifying important visual features through bag-of-words using histopathology data from chronic kidney disease

Identification of a novel ceRNA network related to prognosis and immunity in HNSCC based on integrated bioinformatic investigation

Hyperoxia Induced Bronchopulmonary Dysplasia-Like Inflammation via miR34a-TNIP2-IL-1β Pathway

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