MiR-21 in the Cancers of the Digestive System and Its Potential Role as a Diagnostic, Predictive, and Therapeutic Biomarker

Nguyen, Ha Thi Thu; Kacimi, Salah Eddine Oussama; Nguyen, Truc Ly; Suman, Kamrul Hassan; Lemus-Martin, Roselyn; Humaira, Saleem; Ngoc, Duy

doi:10.3390/biology10050417

Cited by 28 publications

(9 citation statements)

References 164 publications

(197 reference statements)

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“…Examination of miRNAs for specific fractions can significantly increase both the sensitivity and specificity of selected circulating miRNAs as noninvasive biomarkers [ 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 , 63 , 64 , 65 , 66 , 67 , 68 , 69 , 70 , 71 ].…”

Section: Circulating Mirnamentioning

confidence: 99%

miRNAs in Cancer (Review of Literature)

Smolarz

Durczyński

Romanowicz

et al. 2022

IJMS

143

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MicroRNAs (miRNAs) are short, noncoding, single-stranded RNA molecules that regulate gene expression at the post-transcriptional level by binding to mRNAs. miRNAs affect the course of processes of fundamental importance for the proper functioning of the organism. These processes include cell division, proliferation, differentiation, cell apoptosis and the formation of blood vessels. Altered expression of individual miRNAs has been shown in numerous cancers, which may indicate the oncogenic or suppressor potential of the molecules in question. This paper discusses the current knowledge about the possibility of using miRNA as a diagnostic marker and a potential target in modern anticancer therapies.

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Section: Circulating Mirnamentioning

confidence: 99%

miRNAs in Cancer (Review of Literature)

Smolarz

Durczyński

Romanowicz

et al. 2022

IJMS

143

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“…To profile specific characteristics of multi-miRNAs in cancer-derived single EVs, three putative miRNA markers, miR-21, − miR-122, − and miR-375, ,− related to a wide range of cancers, were investigated as examples. Here, nanoflares and CHA amplification were integrated to achieve simultaneous and sensitive detection of EV multi-miRNAs (Scheme A).…”

Section: Resultsmentioning

confidence: 99%

Deep Learning Promotes Profiling of Multiple miRNAs in Single Extracellular Vesicles for Cancer Diagnosis

Zhang,

Qi,

Liu

et al. 2024

ACS Sens.

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Extracellular vesicle microRNAs (EV miRNAs) are critical noninvasive biomarkers for early cancer diagnosis. However, accurate cancer diagnosis based on bulk analysis is hindered by the heterogeneity among EVs. Herein, we report an approach for profiling single-EV multi-miRNA signatures by combining total internal reflection fluorescence (TIRF) imaging with a deep learning (DL) algorithm for the first time. This innovative technique allows for the precise characterization of EV miRNAs at the single-vesicle level, overcoming the challenges posed by EV heterogeneity. TIRF with high resolution and a signal-to-noise ratio can simultaneously detect multi-miRNAs in situ in individual EVs. DL algorithm avoids complicated and inaccurate artificial feature extraction, achieving automated high-resolution image analysis. Using this approach, we reveal that the main variation of EVs from 5 cancer cells and normal plasma is the triple-positive EV subpopulation, and the classification accuracy of single triple-positive EVs from 6 sources can reach above 95%. In the clinical cohort, 20 patients (5 lung cancer, 5 breast cancer, 5 cervical cancer, and 5 colon cancer) and 5 healthy controls are predicted with an overall accuracy of 100%. This single-EV strategy provides new opportunities for exploring more specific EV biomarkers to achieve cancer diagnosis and classification.

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“…Indeed, miR-21 * (32,33,35,49), miR-92a (30,34,46), miR-18a (39,42,49), miR-144 * (37,45,46), and miR-29a (34,42,43), which were the most studied miRNAs in this meta-analysis, were identified as possible non-invasive biomarkers for CRC. MiR-21-5p can regulate a variety of target genes and pathways involved in tumor growth, invasion, and metastasis, as well as play a significant role in 5-FU resistance and CRC cell radiosensitivity (53)(54)(55). Zhang et al demonstrated that miR-425-5p can influence chemoresistance in CRC cells through modulating programmed cell death (56).…”

Section: Discussionmentioning

confidence: 99%

MicroRNA panels as diagnostic biomarkers for colorectal cancer: A systematic review and meta-analysis

2022

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BackgroundCirculating microRNAs (miRNA) have emerged as promising diagnostic biomarkers for several diseases, including cancer. However, the diagnostic accuracy of miRNA panels in colorectal cancer (CRC) remains inconsistent and there is still lack of meta-analyses to determine whether miRNA panels can serve as robust biomarkers for CRC diagnosis.MethodsThis study performed a systematic review and meta-analysis to evaluate the clinical utility of miRNA panels as potential biomarkers for the diagnosis of CRC. The investigation systematically searched PubMed, Medline, Web of Science, Cochrane Library, and Google Scholar (21-year span, between 2000 and 2021) to retrieve articles reporting the diagnostic role of miRNA panels in detecting CRC. Diagnostic meta-analysis of miRNA panels used diverse evaluation indicators, including sensitivity, specificity, Positive Likelihood Ratio (PLR), Negative Likelihood Ratio (NLR), Diagnostic Odds Ratio (DOR), and the area under the curve (AUC) values.ResultsAmong the 313 articles identified, 20 studies met the inclusion criteria. The pooled estimates of miRNA panels for the diagnosis of CRC were 0.85 (95% CI: 0.84–0.86), 0.79 (95% CI: 0.78–0.80), 4.06 (95% CI: 3.89–4.23), 0.20 (95% CI: 0.19–0.20), 22.50 (95% CI: 20.81–24.32) for sensitivity, specificity, PLR, NLR, and DOR, respectively. Moreover, the summary receiver operating characteristics (SROC) curve revealed an AUC value of 0.915 (95% CI: 0.914–0.916), suggesting an outstanding diagnostic accuracy for overall miRNA panels. Subgroup and meta-regression analyses demonstrated that miRNA panels have the highest diagnostic accuracy within serum samples, rather than in other sample-types – with a sensitivity, specificity, PLR, NLR, DOR, and AUC of 0.87, 0.86, 7.33, 0.13, 55.29, and 0.943, respectively. Sensitivity analysis revealed that DOR values did not differ markedly, which indicates that the meta-analysis had strong reliability. Furthermore, this study demonstrated no proof of publication bias for DOR values analyzed using Egger’s regression test (P > 0.05) and funnel plot. Interestingly, miR-15b, miR-21 and miR-31 presented the best diagnostic accuracy values for CRC with sensitivity, specificity, PLR, NLR, DOR, and AUC values of 0.95, 0.94, 17.19, 0.05, 324.81, and 0.948, respectively.ConclusionThis study’s findings indicated that miRNA panels, particularly serum-derived miRNA panels, can serve as powerful and promising biomarkers for early CRC screening.Systematic review registration[www.crd.york.ac.uk/prospero], identifier [CRD42021268172].

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MiR-21 in the Cancers of the Digestive System and Its Potential Role as a Diagnostic, Predictive, and Therapeutic Biomarker

Cited by 28 publications

References 164 publications

miRNAs in Cancer (Review of Literature)

miRNAs in Cancer (Review of Literature)

Deep Learning Promotes Profiling of Multiple miRNAs in Single Extracellular Vesicles for Cancer Diagnosis

MicroRNA panels as diagnostic biomarkers for colorectal cancer: A systematic review and meta-analysis

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