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Identification of the miRNA signature and key genes in colorectal cancer lymph node metastasis

BACKGROUND: Because its metastasis to the lymph nodes are closely related to poor prognosis, miRNAs and mRNAs can serve as biomarkers for the diagnosis, prognosis, and therapy of colorectal cancer (CRC). This study aimed to identify novel gene signatures in the lymph node metastasis of CRC. METHODS:...

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Autores principales: Wang, Xi, Gao, Guangyu, Chen, Zhengrong, Chen, Zhihao, Han, Mingxiao, Xie, Xiaolu, Jin, Qiyuan, Du, Hong, Cao, Zhifei, Zhang, Haifang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8314594/
https://www.ncbi.nlm.nih.gov/pubmed/34315491
http://dx.doi.org/10.1186/s12935-021-02058-9
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author Wang, Xi
Gao, Guangyu
Chen, Zhengrong
Chen, Zhihao
Han, Mingxiao
Xie, Xiaolu
Jin, Qiyuan
Du, Hong
Cao, Zhifei
Zhang, Haifang
author_facet Wang, Xi
Gao, Guangyu
Chen, Zhengrong
Chen, Zhihao
Han, Mingxiao
Xie, Xiaolu
Jin, Qiyuan
Du, Hong
Cao, Zhifei
Zhang, Haifang
author_sort Wang, Xi
collection PubMed
description BACKGROUND: Because its metastasis to the lymph nodes are closely related to poor prognosis, miRNAs and mRNAs can serve as biomarkers for the diagnosis, prognosis, and therapy of colorectal cancer (CRC). This study aimed to identify novel gene signatures in the lymph node metastasis of CRC. METHODS: GSE56350, GSE70574, and GSE95109 datasets were downloaded from the Gene Expression Omnibus (GEO) database, while data from 569 colorectal cancer cases were also downloaded from The Cancer Genome Atlas (TCGA) database. Differentially expressed miRNAs (DE-miRNAs) were calculated using R programming language (Version 3.6.3), while gene ontology and enrichment analysis of target mRNAs were performed using FunRich (http://www.funrich.org). Furthermore, the mRNA–miRNA network was constructed using Cytoscape software (Version 3.8.0). Gene expression levels were verified using the GEO datasets. Similarly, quantitative real-time PCR (qPCR) was used to examine expression profiles from 20 paired non-metastatic and metastatic lymph node tissue samples obtained from patients with CRC. RESULTS: In total, five DE-miRNAs were selected, and 34 mRNAs were identified after filtering the results. Moreover, two key miRNAs (hsa-miR-99a, hsa-miR-100) and one gene (heparan sulfate-glucosamine 3-sulfotransferase 2 [HS3ST2]) were identified. The GEO datasets analysis and qPCR results showed that the expression of key miRNA and genes were consistent with that obtained from the bioinformatic analysis. A novel miRNA–mRNA network capable of predicting the prognosis and confirmed experimentally, hsa-miR-99a-HS3ST2-hsa-miR-100, was found after expression analysis in metastasized lymph node tissue from CRC samples. CONCLUSION: In summary, miRNAs and genes with potential as biomarkers were found and a novel miRNA–mRNA network was established for CRC lymph node metastasis by systematic bioinformatic analysis and experimental validation. This network may be used as a potential biomarker in the development of lymph node metastatic CRC. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12935-021-02058-9.
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spelling pubmed-83145942021-07-28 Identification of the miRNA signature and key genes in colorectal cancer lymph node metastasis Wang, Xi Gao, Guangyu Chen, Zhengrong Chen, Zhihao Han, Mingxiao Xie, Xiaolu Jin, Qiyuan Du, Hong Cao, Zhifei Zhang, Haifang Cancer Cell Int Primary Research BACKGROUND: Because its metastasis to the lymph nodes are closely related to poor prognosis, miRNAs and mRNAs can serve as biomarkers for the diagnosis, prognosis, and therapy of colorectal cancer (CRC). This study aimed to identify novel gene signatures in the lymph node metastasis of CRC. METHODS: GSE56350, GSE70574, and GSE95109 datasets were downloaded from the Gene Expression Omnibus (GEO) database, while data from 569 colorectal cancer cases were also downloaded from The Cancer Genome Atlas (TCGA) database. Differentially expressed miRNAs (DE-miRNAs) were calculated using R programming language (Version 3.6.3), while gene ontology and enrichment analysis of target mRNAs were performed using FunRich (http://www.funrich.org). Furthermore, the mRNA–miRNA network was constructed using Cytoscape software (Version 3.8.0). Gene expression levels were verified using the GEO datasets. Similarly, quantitative real-time PCR (qPCR) was used to examine expression profiles from 20 paired non-metastatic and metastatic lymph node tissue samples obtained from patients with CRC. RESULTS: In total, five DE-miRNAs were selected, and 34 mRNAs were identified after filtering the results. Moreover, two key miRNAs (hsa-miR-99a, hsa-miR-100) and one gene (heparan sulfate-glucosamine 3-sulfotransferase 2 [HS3ST2]) were identified. The GEO datasets analysis and qPCR results showed that the expression of key miRNA and genes were consistent with that obtained from the bioinformatic analysis. A novel miRNA–mRNA network capable of predicting the prognosis and confirmed experimentally, hsa-miR-99a-HS3ST2-hsa-miR-100, was found after expression analysis in metastasized lymph node tissue from CRC samples. CONCLUSION: In summary, miRNAs and genes with potential as biomarkers were found and a novel miRNA–mRNA network was established for CRC lymph node metastasis by systematic bioinformatic analysis and experimental validation. This network may be used as a potential biomarker in the development of lymph node metastatic CRC. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12935-021-02058-9. BioMed Central 2021-07-07 /pmc/articles/PMC8314594/ /pubmed/34315491 http://dx.doi.org/10.1186/s12935-021-02058-9 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Primary Research
Wang, Xi
Gao, Guangyu
Chen, Zhengrong
Chen, Zhihao
Han, Mingxiao
Xie, Xiaolu
Jin, Qiyuan
Du, Hong
Cao, Zhifei
Zhang, Haifang
Identification of the miRNA signature and key genes in colorectal cancer lymph node metastasis
title Identification of the miRNA signature and key genes in colorectal cancer lymph node metastasis
title_full Identification of the miRNA signature and key genes in colorectal cancer lymph node metastasis
title_fullStr Identification of the miRNA signature and key genes in colorectal cancer lymph node metastasis
title_full_unstemmed Identification of the miRNA signature and key genes in colorectal cancer lymph node metastasis
title_short Identification of the miRNA signature and key genes in colorectal cancer lymph node metastasis
title_sort identification of the mirna signature and key genes in colorectal cancer lymph node metastasis
topic Primary Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8314594/
https://www.ncbi.nlm.nih.gov/pubmed/34315491
http://dx.doi.org/10.1186/s12935-021-02058-9
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