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A panel of blood-derived miRNAs with a stable expression pattern as a potential pan-cancer detection signature.
Sabbaghian, Amir; Mussack, Veronika; Kirchner, Benedikt; Bui, Maria L U; Kalani, Mohammad Reza; Pfaffl, Michael W; Golalipour, Masoud.
Afiliação
  • Sabbaghian A; Department of Molecular Medicine, Advanced Technologies Faculty, Golestan University of Medical Science, Gorgan, Iran.
  • Mussack V; Department of Animal Physiology and Immunology, TUM School of Life Sciences, Technical University of Munich, Munich, Germany.
  • Kirchner B; Department of Animal Physiology and Immunology, TUM School of Life Sciences, Technical University of Munich, Munich, Germany.
  • Bui MLU; Department of Animal Physiology and Immunology, TUM School of Life Sciences, Technical University of Munich, Munich, Germany.
  • Kalani MR; Department of Molecular Medicine, Advanced Technologies Faculty, Golestan University of Medical Science, Gorgan, Iran.
  • Pfaffl MW; Department of Animal Physiology and Immunology, TUM School of Life Sciences, Technical University of Munich, Munich, Germany.
  • Golalipour M; Department of Molecular Medicine, Advanced Technologies Faculty, Golestan University of Medical Science, Gorgan, Iran.
Front Mol Biosci ; 9: 1030749, 2022.
Article em En | MEDLINE | ID: mdl-36589227
ABSTRACT

Introduction:

MicroRNAs have a significant role in the regulation of the transcriptome. Several miRNAs have been proposed as potential biomarkers in different malignancies. However, contradictory results have been reported on the capability of miRNA biomarkers in cancer detection. The human biological clock involves molecular mechanisms that regulate several genes over time. Therefore, the sampling time becomes one of the significant factors in gene expression studies.

Method:

In the present study, we have tried to find miRNAs with minimum fluctuation in expression levels at different time points that could be more accurate candidates as diagnostic biomarkers. The small RNA-seq raw data of ten healthy individuals across nine-time points were analyzed to identify miRNAs with stable expression.

Results:

We have found five oscillation patterns. The stable miRNAs were investigated in 779 small-RNA-seq datasets of eleven cancer types. All miRNAs with the highest differential expression were selected for further analysis. The selected miRNAs were explored for functional pathways. The predominantly enriched pathways were miRNA in cancer and the P53-signaling pathway. Finally, we have found seven miRNAs, including miR-142-3p, miR-199a-5p, miR-223-5p, let-7d-5p, miR-148b-3p, miR-340-5p, and miR-421. These miRNAs showed minimum fluctuation in healthy blood and were dysregulated in the blood of eleven cancer types.

Conclusion:

We have found a signature of seven stable miRNAs which dysregulate in several cancer types and may serve as potential pan-cancer biomarkers.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2022 Tipo de documento: Article