Literature DB >> 29589310

RT-qPCR for Fecal Mature MicroRNA Quantification and Validation.

Farid E Ahmed1, Nancy C Ahmed2, Mostafa M Gouda3, Paul W Vos4, Chris Bonnerup5.   

Abstract

By routinely and systematically being able to perform quantitative stem-loop reverse transcriptase (RT) followed by TaqMan® minor-groove binding (MGB) probe, real-time quantitative PCR analysis on exfoliated enriched colonocytes in stool, using human (Homo sapiens, hsa) micro(mi)RNAs to monitor changes of their expression at various stages of colorectal (CRC) progression, this method allows for the reliable and quantitative diagnostic screening of colon cancer (CC). Although the expression of some miRNA genes tested in tissue shows less variability in normal or cancerous patients than in stool, the noninvasive stool by itself is well suited for CC screening. An miRNA approach using stool promises to offer more sensitivity and specificity than currently used genomic, methylomic, or proteomic methods for CC screening.To present an application of employing miRNAs as diagnostic markers for CC screening, we carried out global microarray expression studies on stool colonocytes isolated by paramagnetic beads, using Affymetrix GeneChip miRNA 3.0 Array, to select a panel of miRNAs for subsequent focused semiquantitative PCR analysis studies. We then conducted a stem-loop RT-TaqMan® MGB probes, followed by a modified real-time qPCR expression study on 20 selected miRNAs for subsequent validation of the extracted immunocaptured total small RNA isolated from stool colonocytes. Results showed 12 miRNAs (miR-7, miR-17, miR-20a, miR-21, miR-92a, miR-96, miR-106a, miR-134, miR-183, miR-196a, miR-199a-3p, and miR214) to have an increased expression in stool of CC patients, and that later TNM stages exhibited more increased expressions than adenomas, while 8 miRNAs (miR-9, miR-29b, miR-127-5p, miR-138, miR-143, miR-146a, miR-222, and miR-938) showed decreased expressions in stool of CC patients, which becomes more pronounced as the cancer progresses from early to late TNM stages (0-IV).

Entities:  

Keywords:  Adenocarcinoma; Colon cancer; Colonocyte; Colorectal cancer; TaqMan

Mesh:

Substances:

Year:  2018        PMID: 29589310     DOI: 10.1007/978-1-4939-7765-9_13

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  5 in total

1.  EV-associated miRNAs from peritoneal lavage as potential diagnostic biomarkers in colorectal cancer.

Authors:  Berta Roman-Canal; Jordi Tarragona; Cristian Pablo Moiola; Sònia Gatius; Sarah Bonnin; Maria Ruiz-Miró; José Enrique Sierra; Maria Rufas; Esperanza González; José M Porcel; Antonio Gil-Moreno; Juan M Falcón-Pérez; Julia Ponomarenko; Xavier Matias-Guiu; Eva Colas
Journal:  J Transl Med       Date:  2019-06-20       Impact factor: 5.531

2.  microRNA-96 promotes occurrence and progression of colorectal cancer via regulation of the AMPKα2-FTO-m6A/MYC axis.

Authors:  Caifeng Yue; Jierong Chen; Ziyue Li; Laisheng Li; Jugao Chen; Yunmiao Guo
Journal:  J Exp Clin Cancer Res       Date:  2020-11-12

3.  Multitarget Stool mRNA Test for Detecting Colorectal Cancer Lesions Including Advanced Adenomas.

Authors:  Elizabeth Herring; Éric Tremblay; Nathalie McFadden; Shigeru Kanaoka; Jean-François Beaulieu
Journal:  Cancers (Basel)       Date:  2021-03-11       Impact factor: 6.639

Review 4.  Use of Omics Technologies for the Detection of Colorectal Cancer Biomarkers.

Authors:  Marina Alorda-Clara; Margalida Torrens-Mas; Pere Miquel Morla-Barcelo; Toni Martinez-Bernabe; Jorge Sastre-Serra; Pilar Roca; Daniel Gabriel Pons; Jordi Oliver; Jose Reyes
Journal:  Cancers (Basel)       Date:  2022-02-06       Impact factor: 6.639

5.  Bioinformatics Analysis: The Regulatory Network of hsa_circ_0007843 and hsa_circ_0007331 in Colon Cancer.

Authors:  Zeping Han; Huafang Chen; Zhonghui Guo; Jianxia Zhu; Xingyi Xie; Yuguang Li; Jinhua He
Journal:  Biomed Res Int       Date:  2021-07-23       Impact factor: 3.411

  5 in total

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