scholarly journals Dysregulated MicroRNAs as Biomarkers or Therapeutic Targets in Cisplatin-Induced Nephrotoxicity: A Systematic Review

2021 ◽  
Vol 22 (23) ◽  
pp. 12765
Author(s):  
Nadine de Godoy Torso ◽  
João Kleber Novais Pereira ◽  
Marília Berlofa Visacri ◽  
Pedro Eduardo Nascimento Silva Vasconcelos ◽  
Pía Loren ◽  
...  
Keyword(s):  
Systematic Review ◽  
In Silico ◽  
Literature Search ◽  
Scientific Evidence ◽  
Therapeutic Targets ◽  
In Silico Analysis ◽  
Eligibility Criteria ◽  
Cisplatin Nephrotoxicity ◽  
Silico Analysis

The purpose of this systematic review was to map out and summarize scientific evidence on dysregulated microRNAs (miRNAs) that can be possible biomarkers or therapeutic targets for cisplatin nephrotoxicity and have already been tested in humans, animals, or cells. In addition, an in silico analysis of the two miRNAs found to be dysregulated in the majority of studies was performed. A literature search was performed using eight databases for studies published up to 4 July 2021. Two independent reviewers selected the studies and extracted the data; disagreements were resolved by a third and fourth reviewers. A total of 1002 records were identified, of which 30 met the eligibility criteria. All studies were published in English and reported between 2010 and 2021. The main findings were as follows: (a) miR-34a and miR-21 were the main miRNAs identified by the studies as possible biomarkers and therapeutic targets of cisplatin nephrotoxicity; (b) the in silico analysis revealed 124 and 131 different strongly validated targets for miR-34a and miR-21, respectively; and (c) studies in humans remain scarce.

A systematic review with in silico analysis on transcriptomic profile of gallbladder carcinoma

2020 ◽  
Vol 47 (6) ◽  
pp. 398-408
Author(s):  
Sonam Tulsyan ◽  
Showket Hussain ◽  
Balraj Mittal ◽  
Sundeep Singh Saluja ◽  
Pranay Tanwar ◽  
...  
Keyword(s):  
Systematic Review ◽  
Gallbladder Carcinoma ◽  
In Silico ◽  
In Silico Analysis ◽  
Transcriptomic Profile ◽  
Silico Analysis

scholarly journals Identification of Novel Hypothalamic MicroRNAs as Promising Therapeutics for SARS-CoV-2 by Regulating ACE2 and TMPRSS2 Expression: An In Silico Analysis

2020 ◽  
Vol 10 (10) ◽  
pp. 666
Author(s):  
Debasmita Mukhopadhyay ◽  
Bashair M. Mussa
Keyword(s):  
In Silico ◽  
Binding Capacity ◽  
Therapeutic Targets ◽  
In Silico Analysis ◽  
Neurological Impairment ◽  
Essential Elements ◽  
Cell Entry ◽  
Angiotensin Converting Enzyme 2 ◽  
Transmembrane Serine Protease ◽  
Silico Analysis

Background: Neuroinvasion of severe acute respiratory syndrome coronavirus (SARS-CoV) is well documented and, given the similarities between this virus and SARS-CoV-2, it seems that the neurological impairment that is associated with coronavirus disease 2019 (COVID-19) is due to SARS-CoV-2 neuroinvasion. Hypothalamic circuits are exposed to the entry of the virus via the olfactory bulb and interact centrally with crucial respiratory nuclei. Hypothalamic microRNAs are considered as potential biomarkers and modulators for various diseases and future therapeutic targets. The present study aims to investigate the microRNAs that regulate the expression of hypothalamic angiotensin-converting enzyme 2 (ACE2) and transmembrane serine protease 2 (TMPRSS2), essential elements for SARS-CoV-2 cell entry. Methods: To determine potential hypothalamic miRNAs that can directly bind to ACE2 and TMPRSS2, multiple target bioinformatics prediction algorithms were used, including miRBase, Target scan, and miRWalk2.029. Results: Our in silico analysis has revealed that, although there are over 5000 hypothalamic miRNAs, around 31 miRNAs and 29 miRNAs have shown binding sites and strong binding capacity against ACE2 and TMPRSS2, respectively. Conclusion: These novel potential hypothalamic miRNAs can be used to identify new therapeutic targets to treat neurological symptoms in COVID-19 patients via regulation of ACE2 and TMPRSS2 expression.

scholarly journals DiSCoVERing Innovative Therapies for Rare Tumors: Combining Genetically Accurate Disease Models with In Silico Analysis to Identify Novel Therapeutic Targets

2016 ◽  
Vol 22 (15) ◽  
pp. 3903-3914 ◽  
Author(s):  
Allison R. Hanaford ◽  
Tenley C. Archer ◽  
Antoinette Price ◽  
Ulf D. Kahlert ◽  
Jarek Maciaczyk ◽  
...  
Keyword(s):  
In Silico ◽  
Therapeutic Targets ◽  
In Silico Analysis ◽  
Disease Models ◽  
Rare Tumors ◽  
Innovative Therapies ◽  
Silico Analysis ◽  
Novel Therapeutic

scholarly journals MB-103DiSCoVERing INNOVATIVE THERAPIES: COMBINING GENETICALLY ACCURATE DISEASE MODELS OF MEDULLOBLASTOMA WITH ADVANCED IN SILICO ANALYSIS TO IDENTIFY NOVEL THERAPEUTIC TARGETS

2016 ◽  
Vol 18 (suppl 3) ◽  
pp. iii120.3-iii120
Author(s):  
Allison Hanaford ◽  
Tenley Archer ◽  
Antoinette Price ◽  
Ulf Kahlert ◽  
Jarek Maciaczyk ◽  
...  
Keyword(s):  
In Silico ◽  
Therapeutic Targets ◽  
In Silico Analysis ◽  
Disease Models ◽  
Innovative Therapies ◽  
Silico Analysis ◽  
Novel Therapeutic

scholarly journals The associations between Toll-like receptor 4 gene polymorphisms and hepatitis C virus infection: a systematic review and meta-analysis

2019 ◽  
Vol 39 (2) ◽  
Author(s):  
Narttaya Chaiwiang ◽  
Teera Poyomtip
Keyword(s):  
Hepatocellular Carcinoma ◽  
Systematic Review ◽  
Hepatitis C Virus ◽  
Hepatitis C ◽  
In Silico ◽  
Meta Analysis ◽  
In Silico Analysis ◽  
Hcv Infection ◽  
Toll Like Receptor ◽  
Silico Analysis

Abstract Background and objective: The hepatitis C virus (HCV) is able to cause a life-threatening disease relating to lethal hepatocellular carcinoma. Previous, Toll-like receptor polymorphisms were proposed as promising biomarker for HCV-related hepatocellular carcinoma and disease progression. This study aimed to summarize the association of TLR4 polymorphisms and HCV infection through meta-analysis. Methods: We applied a systematic review and meta-analysis performed by using PubMed, EMBASE and Web of Science searches. The Modified Newcastle-Ottawa scale was used for quality assessment. The odd-ratio (OR) and 95% confidence interval (CI) were calculated to assess the association. In silico analysis was applied for proposing the function as microRNA (miRNA) of non-coding polymorphism. Finally, the miRNA target was predicted and annotated to suggest the possible relationship between polymorphism and HCV infection. Results: Our meta-analysis incorporated seven studies involving rs4986791, rs4986790 and rs2149356. No association exists between rs4986791 and HCV infection. However, the heterozygous model (AG vs GG) of rs4986790 significantly associates with HCV infection (OR = 0.33, 95% CI = 0.21–0.49, P<0.0001). Moreover, the rs2149356 TG genotype also associates with HCV infection in the over-dominant model (TG vs TT+TG: OR = 0.54, 95% CI = 0.40–0.75). In silico analysis of rs2149356G allele showed that this mutation is siRNA, which targets the set of genes, especially in the autophagy pathway. Conclusion: We demonstrated that rs4986790 and rs2149356 are associated with HCV infection.

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