Plasmatic microRNA as Potential Biomarkers of Multiple Sclerosis: Literature Review

Kacperska, Magdalena Justyna; Walenczak, Jakub; Tomasik, Bartłomiej

doi:10.17219/acem/60098

Cited by 20 publications

(13 citation statements)

References 26 publications

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“…The search for biomarkers to improve the diagnosis of MS is an active research topic 7 . Approaches include positron emission tomography addressing neuro-inflammation and astrocyte markers 8 , genetic, immune-inflammatory, and oxidative stress markers 9 , Vitamin D binding protein isoforms and apolipoprotein E in cerebrospinal fluid 10 , and plasma micro RNAs 11 , 12 . Further blood-based biomarkers utilize metabolomic 13 and proteomic markers 14 or serum profiles of cytokines, chemokines and pro-apoptotic molecules 15 .…”

Section: Introductionmentioning

confidence: 99%

Machine-learning based lipid mediator serum concentration patterns allow identification of multiple sclerosis patients with high accuracy

Lötsch

Schiffmann

Schmitz

et al. 2018

Sci Rep

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Based on increasing evidence suggesting that MS pathology involves alterations in bioactive lipid metabolism, the present analysis was aimed at generating a complex serum lipid-biomarker. Using unsupervised machine-learning, implemented as emergent self-organizing maps of neuronal networks, swarm intelligence and Minimum Curvilinear Embedding, a cluster structure was found in the input data space comprising serum concentrations of d = 43 different lipid-markers of various classes. The structure coincided largely with the clinical diagnosis, indicating that the data provide a basis for the creation of a biomarker (classifier). This was subsequently assessed using supervised machine-learning, implemented as random forests and computed ABC analysis-based feature selection. Bayesian statistics-based biomarker creation was used to map the diagnostic classes of either MS patients (n = 102) or healthy subjects (n = 301). Eight lipid-markers passed the feature selection and comprised GluCerC16, LPA20:4, HETE15S, LacCerC24:1, C16Sphinganine, biopterin and the endocannabinoids PEA and OEA. A complex classifier or biomarker was developed that predicted MS at a sensitivity, specificity and accuracy of approximately 95% in training and test data sets, respectively. The present successful application of serum lipid marker concentrations to MS data is encouraging for further efforts to establish an MS biomarker based on serum lipidomics.

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Section: Introductionmentioning

confidence: 99%

Machine-learning based lipid mediator serum concentration patterns allow identification of multiple sclerosis patients with high accuracy

Lötsch

Schiffmann

Schmitz

et al. 2018

Sci Rep

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“…MiRNAs are a class of highly conserved noncoding small RNAs that are 21-24 nucleotides in length. miRNAs regulate translation and degradation of the target gene by complementary binding to the 3’-untranslated region of the target gene mRNA, thereby functioning as an oncogene or tumor suppressor gene during disease development[15]. The miR-34 family is a highly conserved class of miRNAs in evolution.…”

Section: Discussionmentioning

confidence: 99%

MiR-34a overexpression enhances the inhibitory effect of doxorubicin on HepG2 cells

Zheng¹,

Park²,

Wang³

et al. 2019

WJG

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BACKGROUND Hepatocellular carcinoma (HCC) is the third leading cause of death from malignant tumors worldwide. More than 50% of HCC cases occur in China. The prognosis remains poor and overall efficacy is still unsatisfactory. Chemotherapy resistance is the most important reason for the poor outcome. Much progress has been made in the study of chemotherapy resistance of HCC; however, the specific mechanisms of progression of HCC have still only been partially established. Therefore, the mechanism of chemotherapy resistance in HCC requires more research. AIM To investigate the effect of miR-34a expression on the growth inhibition of HepG2 cells by doxorubicin. METHODS A recombinant lentiviral vector containing miR-34a was constructed and transfected into HepG2 cells. The expression of miR-34a was detected by reverse transcription-polymerase chain reaction (commonly known as RT-PCR) before and after transfection. Cells were exposed to 2 μM doxorubicin or phosphate-buffered saline before and after transfection. Cell viability in each group was detected by MTT assay, and cell cycle and apoptosis were detected by flow cytometry. Changes in expression levels of phospho (p)-p53, sirtuin (SIRT) 1, cyclin D1, cyclin-dependent kinase (CDK) 4, CDK6, BCL-2, multidrug resistance protein (MDR) 1/P glycoprotein (P-gp), and AXL were detected by Western blotting. RESULTS Recombinant lentiviral vector LV-hsa-mir-34a was successfully constructed by restriction endonuclease digestion and sequencing. RT-PCR showed that expression of miR-34a in HepG2 cells was significantly upregulated after transfection ( P < 0.01). MTT assay showed that growth of HepG2 cells was inhibited after upregulation of miR-34a, and viability was significantly decreased after combined treatment with doxorubicin ( P < 0.01). Flow cytometry showed that the number of HepG2 cells in G1 phase increased, and G1 phase arrest was more obvious after intervention with doxorubicin ( P < 0.01). The apoptosis rate of HepG2 cells was increased after upregulation of miR-34a, and became more obvious after intervention with doxorubicin ( P < 0.01). Western blotting showed that upregulation of miR-34a combined with treatment with doxorubicin caused significant changes in the expression levels of p-p53, SIRT1, cyclin D1, CDK4, CDK6, BCL-2, MDR1/P-gp and AXL proteins ( P < 0.01). CONCLUSION MiR-34a may enhance the inhibitory effect of doxorubicin by downregulating MDR1/P-gp and AXL, which may be related to p53 expression.

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“…Besides, there are also evidences showing the association between circulating miRNAs and magnetic resonance imaging measurement of multiple sclerosis (MS) severity indicating that serum miRNAs are also significantly changed in MS patients. The alteration of serum miRNA levels could help to the evaluation of MS subtype and progression [54,55].…”

Section: Extracellular Micrornas In the Central Nervous Systemmentioning

confidence: 99%

Roles of extracellular microRNAs in central nervous system

Wang

2019

ExRNA

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MicroRNAs are small non-coding RNAs containing about 18-25 nucleotides which modulate gene expression post-transcriptionally. Recently, microRNAs have been detected in the extracellular space including a wide range of body fluids. These extracellular miRNAs, often encapsulated in secreted extracellular vesicles, can be transferred into recipient cells and thus inhibits the expression of targeted genes. In view of these findings, a new exosome-based therapeutic approach is invented, which can effectively deliver miRNAs/siRNAs into specific cells. In central nervous system, extracellular miRNAs can not only be used as noninvasive biomarkers for diagnosis of several neurological disorders, but also mediate the intercellular communication between neurons and glial cells. In this review, we will discuss the latest research work regarding the roles of secreted miRNAs in central nervous system and evaluate the potential of exosome-mediated miRNAs/siRNAs delivery in neural therapy.

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Plasmatic microRNA as Potential Biomarkers of Multiple Sclerosis: Literature Review

Cited by 20 publications

References 26 publications

Machine-learning based lipid mediator serum concentration patterns allow identification of multiple sclerosis patients with high accuracy

Machine-learning based lipid mediator serum concentration patterns allow identification of multiple sclerosis patients with high accuracy

MiR-34a overexpression enhances the inhibitory effect of doxorubicin on HepG2 cells

Roles of extracellular microRNAs in central nervous system

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