Skip to main content
Top
Published in: Cancer Cell International 1/2019

Open Access 01-12-2019 | Metastasis | Primary research

Integrated analyses of microRNA-29 family and the related combination biomarkers demonstrate their widespread influence on risk, recurrence, metastasis and survival outcome in colorectal cancer

Authors: Qiliang Peng, Zhengyang Feng, Yi Shen, Jiahao Zhu, Li Zou, Yuntian Shen, Yaqun Zhu

Published in: Cancer Cell International | Issue 1/2019

Login to get access

Abstract

Background

Emerging evidence has revealed miR-29 family as promising biomarkers for colorectal cancer (CRC), but their biomarker potential and molecular mechanisms remain poorly understood.

Methods

We performed a comprehensive meta-analysis to evaluate the biomarker performance of individual miR-29 and the related miRNA combination biomarkers. Meanwhile, we conducted an integrative bioinformatics analysis to unfold the underlying biological function of miR-29 and their relationship with CRC.

Results

Using miR-29 expression to diagnose CRC produced 0.82 area under the curve, 70% sensitivity and 81% specificity while the combination biomarkers based on miR-29 enhanced the diagnostic power with an AUC of 0.86, a sensitivity of 78% and a specificity of 91%. For the prognosis evaluation, patients with higher expression of miR-29 had better survival outcome (pooled HR 0.78; 95% CI 0.56–1.07). In addition, miR-29 has also been identified as potential biomarker for predicting recurrence and metastasis in CRC. Then the genes regulated by the miR-29 family were retrieved and found closely associated with the molecular pathogenesis of CRC according to the gene ontology and pathway analysis. Furthermore, hub nodes and significant modules were identified from the protein–protein interaction network constructed with miR-29 family targets, which were also confirmed highly involved in the establishment and development of CRC.

Conclusions

Current evidences suggest miR-29 family may become promising biomarkers for risk, recurrence, metastasis and survival outcome of CRC. Meanwhile our data highlight the potential clinical use of miRNA combination biomarkers. Nevertheless, further prospective studies are warranted before the application of the useful biomarkers in the clinical.
Literature
1.
go back to reference Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2018;68(6):394–424.PubMedCrossRef Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2018;68(6):394–424.PubMedCrossRef
2.
go back to reference Siegel RL, Miller KD, Fedewa SA, et al. Colorectal cancer statistics, 2017. CA Cancer J Clin. 2017;67(3):177–93.CrossRefPubMed Siegel RL, Miller KD, Fedewa SA, et al. Colorectal cancer statistics, 2017. CA Cancer J Clin. 2017;67(3):177–93.CrossRefPubMed
3.
go back to reference Schreuders EH, Ruco A, Rabeneck L, et al. Colorectal cancer screening: a global overview of existing programmes. Gut. 2015;64(10):1637–49.PubMedCrossRef Schreuders EH, Ruco A, Rabeneck L, et al. Colorectal cancer screening: a global overview of existing programmes. Gut. 2015;64(10):1637–49.PubMedCrossRef
4.
go back to reference Vermeer NC, Snijders HS, Holman FA, et al. Colorectal cancer screening: systematic review of screen-related morbidity and mortality. Cancer Treat Rev. 2017;54:87–98.PubMedCrossRef Vermeer NC, Snijders HS, Holman FA, et al. Colorectal cancer screening: systematic review of screen-related morbidity and mortality. Cancer Treat Rev. 2017;54:87–98.PubMedCrossRef
5.
7.
go back to reference Dong H, Lei J, Ding L, Wen Y, Ju H, Zhang X. MicroRNA: function, detection, and bioanalysis. Chem Rev. 2013;113(8):6207–33.PubMedCrossRef Dong H, Lei J, Ding L, Wen Y, Ju H, Zhang X. MicroRNA: function, detection, and bioanalysis. Chem Rev. 2013;113(8):6207–33.PubMedCrossRef
8.
go back to reference Zhu L, Fang J. The structure and clinical roles of MicroRNA in colorectal cancer. Gastroenterol Res Pract. 2016;2016:1360348.PubMedPubMedCentral Zhu L, Fang J. The structure and clinical roles of MicroRNA in colorectal cancer. Gastroenterol Res Pract. 2016;2016:1360348.PubMedPubMedCentral
9.
go back to reference Zhou L, Lim MYT, Kaur P, et al. Importance of miRNA stability and alternative primary miRNA isoforms in gene regulation during Drosophila development. Elife. 2018;7:e38389.PubMedPubMedCentralCrossRef Zhou L, Lim MYT, Kaur P, et al. Importance of miRNA stability and alternative primary miRNA isoforms in gene regulation during Drosophila development. Elife. 2018;7:e38389.PubMedPubMedCentralCrossRef
10.
go back to reference Jiang H, Zhang G, Wu JH, Jiang CP. Diverse roles of miR-29 in cancer (review). Oncol Rep. 2014;31(4):1509–16.PubMedCrossRef Jiang H, Zhang G, Wu JH, Jiang CP. Diverse roles of miR-29 in cancer (review). Oncol Rep. 2014;31(4):1509–16.PubMedCrossRef
11.
go back to reference Wang Y, Zhang X, Li H, Yu J, Ren X. The role of miRNA-29 family in cancer. Eur J Cell Biol. 2013;92(3):123–8.PubMedCrossRef Wang Y, Zhang X, Li H, Yu J, Ren X. The role of miRNA-29 family in cancer. Eur J Cell Biol. 2013;92(3):123–8.PubMedCrossRef
12.
go back to reference Brunet Vega A, Pericay C, Moya I, et al. microRNA expression profile in stage III colorectal cancer: circulating miR-18a and miR-29a as promising biomarkers. Oncol Rep. 2013;30(1):320–6.PubMedCrossRef Brunet Vega A, Pericay C, Moya I, et al. microRNA expression profile in stage III colorectal cancer: circulating miR-18a and miR-29a as promising biomarkers. Oncol Rep. 2013;30(1):320–6.PubMedCrossRef
13.
go back to reference Whiting PF, Rutjes AW, Westwood ME, et al. QUADAS-2: a revised tool for the quality assessment of diagnostic accuracy studies. Ann Intern Med. 2011;155(8):529–36.PubMedCrossRef Whiting PF, Rutjes AW, Westwood ME, et al. QUADAS-2: a revised tool for the quality assessment of diagnostic accuracy studies. Ann Intern Med. 2011;155(8):529–36.PubMedCrossRef
14.
go back to reference Stang A. Critical evaluation of the Newcastle–Ottawa scale for the assessment of the quality of nonrandomized studies in meta-analyses. Eur J Epidemiol. 2010;25(9):603–5.PubMedCrossRef Stang A. Critical evaluation of the Newcastle–Ottawa scale for the assessment of the quality of nonrandomized studies in meta-analyses. Eur J Epidemiol. 2010;25(9):603–5.PubMedCrossRef
15.
go back to reference Reitsma JB, Glas AS, Rutjes AW, Scholten RJ, Bossuyt PM, Zwinderman AH. Bivariate analysis of sensitivity and specificity produces informative summary measures in diagnostic reviews. J Clin Epidemiol. 2005;58(10):982–90.PubMedCrossRef Reitsma JB, Glas AS, Rutjes AW, Scholten RJ, Bossuyt PM, Zwinderman AH. Bivariate analysis of sensitivity and specificity produces informative summary measures in diagnostic reviews. J Clin Epidemiol. 2005;58(10):982–90.PubMedCrossRef
16.
go back to reference Jones CM, Athanasiou T. Summary receiver operating characteristic curve analysis techniques in the evaluation of diagnostic tests. Ann Thorac Surg. 2005;79(1):16–20.PubMedCrossRef Jones CM, Athanasiou T. Summary receiver operating characteristic curve analysis techniques in the evaluation of diagnostic tests. Ann Thorac Surg. 2005;79(1):16–20.PubMedCrossRef
18.
go back to reference Zhao JG. Identifying and measuring heterogeneity across the studies in meta-analysis. J Hand Surg Am. 2013;38(7):1449–50.PubMedCrossRef Zhao JG. Identifying and measuring heterogeneity across the studies in meta-analysis. J Hand Surg Am. 2013;38(7):1449–50.PubMedCrossRef
19.
20.
go back to reference Chou CH, Shrestha S, Yang CD, et al. miRTarBase update 2018: a resource for experimentally validated microRNA-target interactions. Nucleic Acids Res. 2018;46(D1):D296–302.PubMedCrossRef Chou CH, Shrestha S, Yang CD, et al. miRTarBase update 2018: a resource for experimentally validated microRNA-target interactions. Nucleic Acids Res. 2018;46(D1):D296–302.PubMedCrossRef
21.
go back to reference Gene Ontology C, Blake JA, Dolan M, et al. Gene Ontology annotations and resources. Nucleic acids research. 2013;41(Database issue):D530–5. Gene Ontology C, Blake JA, Dolan M, et al. Gene Ontology annotations and resources. Nucleic acids research. 2013;41(Database issue):D530–5.
22.
go back to reference Kanehisa M, Furumichi M, Tanabe M, Sato Y, Morishima K. KEGG: new perspectives on genomes, pathways, diseases and drugs. Nucleic Acids Res. 2017;45(D1):D353–61.PubMedCrossRef Kanehisa M, Furumichi M, Tanabe M, Sato Y, Morishima K. KEGG: new perspectives on genomes, pathways, diseases and drugs. Nucleic Acids Res. 2017;45(D1):D353–61.PubMedCrossRef
23.
go back to reference Sherman BT, da Huang W, Tan Q, et al. DAVID Knowledgebase: a gene-centered database integrating heterogeneous gene annotation resources to facilitate high-throughput gene functional analysis. BMC Bioinformatics. 2007;8:426.PubMedPubMedCentralCrossRef Sherman BT, da Huang W, Tan Q, et al. DAVID Knowledgebase: a gene-centered database integrating heterogeneous gene annotation resources to facilitate high-throughput gene functional analysis. BMC Bioinformatics. 2007;8:426.PubMedPubMedCentralCrossRef
24.
go back to reference Szklarczyk D, Morris JH, Cook H, et al. The STRING database in 2017: quality-controlled protein-protein association networks, made broadly accessible. Nucleic Acids Res. 2017;45(D1):D362–8.PubMedCrossRef Szklarczyk D, Morris JH, Cook H, et al. The STRING database in 2017: quality-controlled protein-protein association networks, made broadly accessible. Nucleic Acids Res. 2017;45(D1):D362–8.PubMedCrossRef
25.
go back to reference Shannon P, Markiel A, Ozier O, et al. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res. 2003;13(11):2498–504.CrossRefPubMedPubMedCentral Shannon P, Markiel A, Ozier O, et al. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res. 2003;13(11):2498–504.CrossRefPubMedPubMedCentral
26.
go back to reference Tang Y, Li M, Wang J, Pan Y, Wu FX. CytoNCA: a cytoscape plugin for centrality analysis and evaluation of protein interaction networks. Biosystems. 2015;127:67–72.PubMedCrossRef Tang Y, Li M, Wang J, Pan Y, Wu FX. CytoNCA: a cytoscape plugin for centrality analysis and evaluation of protein interaction networks. Biosystems. 2015;127:67–72.PubMedCrossRef
27.
go back to reference Huang Z, Huang D, Ni S, Peng Z, Sheng W, Du X. Plasma microRNAs are promising novel biomarkers for early detection of colorectal cancer. Int J Cancer. 2010;127(1):118–26.PubMedCrossRef Huang Z, Huang D, Ni S, Peng Z, Sheng W, Du X. Plasma microRNAs are promising novel biomarkers for early detection of colorectal cancer. Int J Cancer. 2010;127(1):118–26.PubMedCrossRef
28.
go back to reference Giraldez MD, Lozano JJ, Ramirez G, et al. Circulating microRNAs as biomarkers of colorectal cancer: results from a genome-wide profiling and validation study. Clin Gastroenterol Hepatol. 2013;11(6):681–8.PubMedCrossRef Giraldez MD, Lozano JJ, Ramirez G, et al. Circulating microRNAs as biomarkers of colorectal cancer: results from a genome-wide profiling and validation study. Clin Gastroenterol Hepatol. 2013;11(6):681–8.PubMedCrossRef
29.
go back to reference Luo X, Stock C, Burwinkel B, Brenner H. Identification and evaluation of plasma microRNAs for early detection of colorectal cancer. PLoS ONE. 2013;8(5):e62880.PubMedPubMedCentralCrossRef Luo X, Stock C, Burwinkel B, Brenner H. Identification and evaluation of plasma microRNAs for early detection of colorectal cancer. PLoS ONE. 2013;8(5):e62880.PubMedPubMedCentralCrossRef
30.
go back to reference Basati G, Razavi AE, Pakzad I, Malayeri FA. Circulating levels of the miRNAs, miR-194, and miR-29b, as clinically useful biomarkers for colorectal cancer. Tumour Biol. 2016;37(2):1781–8.PubMedCrossRef Basati G, Razavi AE, Pakzad I, Malayeri FA. Circulating levels of the miRNAs, miR-194, and miR-29b, as clinically useful biomarkers for colorectal cancer. Tumour Biol. 2016;37(2):1781–8.PubMedCrossRef
31.
go back to reference Li L, Guo Y, Chen Y, et al. The diagnostic efficacy and biological effects of microRNA-29b for colon cancer. Technol Cancer Res Treat. 2016;15(6):772–9.PubMedCrossRef Li L, Guo Y, Chen Y, et al. The diagnostic efficacy and biological effects of microRNA-29b for colon cancer. Technol Cancer Res Treat. 2016;15(6):772–9.PubMedCrossRef
32.
go back to reference Zhu Y, Xu A, Li J, et al. Fecal miR-29a and miR-224 as the noninvasive biomarkers for colorectal cancer. Cancer Biomark. 2016;16(2):259–64.PubMedCrossRef Zhu Y, Xu A, Li J, et al. Fecal miR-29a and miR-224 as the noninvasive biomarkers for colorectal cancer. Cancer Biomark. 2016;16(2):259–64.PubMedCrossRef
33.
go back to reference Liu HN, Liu TT, Wu H, et al. Serum microRNA signatures and metabolomics have high diagnostic value in colorectal cancer using two novel methods. Cancer Sci. 2018;109(4):1185–94.PubMedPubMedCentralCrossRef Liu HN, Liu TT, Wu H, et al. Serum microRNA signatures and metabolomics have high diagnostic value in colorectal cancer using two novel methods. Cancer Sci. 2018;109(4):1185–94.PubMedPubMedCentralCrossRef
34.
go back to reference Ramzy I, Hasaballah M, Marzaban R, Shaker O, Soliman ZA. Evaluation of microRNAs-29a, 92a and 145 in colorectal carcinoma as candidate diagnostic markers: an Egyptian pilot study. Clin Res Hepatol Gastroenterol. 2015;39(4):508–15.PubMedCrossRef Ramzy I, Hasaballah M, Marzaban R, Shaker O, Soliman ZA. Evaluation of microRNAs-29a, 92a and 145 in colorectal carcinoma as candidate diagnostic markers: an Egyptian pilot study. Clin Res Hepatol Gastroenterol. 2015;39(4):508–15.PubMedCrossRef
35.
go back to reference Yamada A, Horimatsu T, Okugawa Y, et al. Serum miR-21, miR-29a, and miR-125b are promising biomarkers for the early detection of colorectal neoplasia. Clin Cancer Res. 2015;21(18):4234–42.PubMedPubMedCentralCrossRef Yamada A, Horimatsu T, Okugawa Y, et al. Serum miR-21, miR-29a, and miR-125b are promising biomarkers for the early detection of colorectal neoplasia. Clin Cancer Res. 2015;21(18):4234–42.PubMedPubMedCentralCrossRef
36.
go back to reference Wang Q, Huang Z, Ni S, et al. Plasma miR-601 and miR-760 are novel biomarkers for the early detection of colorectal cancer. PLoS ONE. 2012;7(9):e44398.PubMedPubMedCentralCrossRef Wang Q, Huang Z, Ni S, et al. Plasma miR-601 and miR-760 are novel biomarkers for the early detection of colorectal cancer. PLoS ONE. 2012;7(9):e44398.PubMedPubMedCentralCrossRef
37.
go back to reference Tang W, Zhu Y, Gao J, et al. MicroRNA-29a promotes colorectal cancer metastasis by regulating matrix metalloproteinase 2 and E-cadherin via KLF4. Br J Cancer. 2014;110(2):450–8.PubMedCrossRef Tang W, Zhu Y, Gao J, et al. MicroRNA-29a promotes colorectal cancer metastasis by regulating matrix metalloproteinase 2 and E-cadherin via KLF4. Br J Cancer. 2014;110(2):450–8.PubMedCrossRef
38.
go back to reference Inoue A, Yamamoto H, Uemura M, et al. MicroRNA-29b is a novel prognostic marker in colorectal cancer. Ann Surg Oncol. 2015;22(Suppl 3):S1410–8.PubMedCrossRef Inoue A, Yamamoto H, Uemura M, et al. MicroRNA-29b is a novel prognostic marker in colorectal cancer. Ann Surg Oncol. 2015;22(Suppl 3):S1410–8.PubMedCrossRef
39.
go back to reference Ulivi P, Canale M, Passardi A, et al. Circulating plasma levels of miR-20b, miR-29b and miR-155 as predictors of bevacizumab efficacy in patients with metastatic colorectal cancer. Int J Mol Sci. 2018;19(1):307.PubMedCentralCrossRef Ulivi P, Canale M, Passardi A, et al. Circulating plasma levels of miR-20b, miR-29b and miR-155 as predictors of bevacizumab efficacy in patients with metastatic colorectal cancer. Int J Mol Sci. 2018;19(1):307.PubMedCentralCrossRef
40.
go back to reference Yuan Z, Baker K, Redman MW, et al. Dynamic plasma microRNAs are biomarkers for prognosis and early detection of recurrence in colorectal cancer. Br J Cancer. 2017;117(8):1202–10.PubMedPubMedCentralCrossRef Yuan Z, Baker K, Redman MW, et al. Dynamic plasma microRNAs are biomarkers for prognosis and early detection of recurrence in colorectal cancer. Br J Cancer. 2017;117(8):1202–10.PubMedPubMedCentralCrossRef
41.
go back to reference Conev NV, Donev IS, Konsoulova-Kirova AA, Chervenkov TG, Kashlov JK, Ivanov KD. Serum expression levels of miR-17, miR-21, and miR-92 as potential biomarkers for recurrence after adjuvant chemotherapy in colon cancer patients. Biosci Trends. 2015;9(6):393–401.PubMedCrossRef Conev NV, Donev IS, Konsoulova-Kirova AA, Chervenkov TG, Kashlov JK, Ivanov KD. Serum expression levels of miR-17, miR-21, and miR-92 as potential biomarkers for recurrence after adjuvant chemotherapy in colon cancer patients. Biosci Trends. 2015;9(6):393–401.PubMedCrossRef
42.
go back to reference Weissmann-Brenner A, Kushnir M, Lithwick Yanai G, et al. Tumor microRNA-29a expression and the risk of recurrence in stage II colon cancer. Int J Oncol. 2012;40(6):2097–103.PubMed Weissmann-Brenner A, Kushnir M, Lithwick Yanai G, et al. Tumor microRNA-29a expression and the risk of recurrence in stage II colon cancer. Int J Oncol. 2012;40(6):2097–103.PubMed
43.
go back to reference Wang LG, Gu J. Serum microRNA-29a is a promising novel marker for early detection of colorectal liver metastasis. Cancer Epidemiol. 2012;36(1):e61–7.PubMedCrossRef Wang LG, Gu J. Serum microRNA-29a is a promising novel marker for early detection of colorectal liver metastasis. Cancer Epidemiol. 2012;36(1):e61–7.PubMedCrossRef
44.
go back to reference Mayer IA, Arteaga CL. The PI3K/AKT pathway as a target for cancer treatment. Annu Rev Med. 2016;67:11–28.PubMedCrossRef Mayer IA, Arteaga CL. The PI3K/AKT pathway as a target for cancer treatment. Annu Rev Med. 2016;67:11–28.PubMedCrossRef
45.
go back to reference Kang DW, Lee BH, Suh YA, et al. Phospholipase D1 inhibition linked to upregulation of ICAT blocks colorectal cancer growth hyperactivated by Wnt/beta-catenin and PI3K/Akt signaling. Clin Cancer Res. 2017;23(23):7340–50.PubMedCrossRef Kang DW, Lee BH, Suh YA, et al. Phospholipase D1 inhibition linked to upregulation of ICAT blocks colorectal cancer growth hyperactivated by Wnt/beta-catenin and PI3K/Akt signaling. Clin Cancer Res. 2017;23(23):7340–50.PubMedCrossRef
46.
go back to reference Joerger AC, Fersht AR. The p53 Pathway: origins, inactivation in cancer, and emerging therapeutic approaches. Annu Rev Biochem. 2016;85:375–404.PubMedCrossRef Joerger AC, Fersht AR. The p53 Pathway: origins, inactivation in cancer, and emerging therapeutic approaches. Annu Rev Biochem. 2016;85:375–404.PubMedCrossRef
47.
go back to reference Bykov VJN, Eriksson SE, Bianchi J, Wiman KG. Targeting mutant p53 for efficient cancer therapy. Nat Rev Cancer. 2018;18(2):89–102.PubMedCrossRef Bykov VJN, Eriksson SE, Bianchi J, Wiman KG. Targeting mutant p53 for efficient cancer therapy. Nat Rev Cancer. 2018;18(2):89–102.PubMedCrossRef
49.
go back to reference Ma J, Matkar S, He X, Hua X. FOXO family in regulating cancer and metabolism. Semin Cancer Biol. 2018;50:32–41.PubMedCrossRef Ma J, Matkar S, He X, Hua X. FOXO family in regulating cancer and metabolism. Semin Cancer Biol. 2018;50:32–41.PubMedCrossRef
50.
go back to reference Schaefer L, Tredup C, Gubbiotti MA, Iozzo RV. Proteoglycan neofunctions: regulation of inflammation and autophagy in cancer biology. FEBS J. 2017;284(1):10–26.PubMedCrossRef Schaefer L, Tredup C, Gubbiotti MA, Iozzo RV. Proteoglycan neofunctions: regulation of inflammation and autophagy in cancer biology. FEBS J. 2017;284(1):10–26.PubMedCrossRef
51.
go back to reference Aldo P, Elisabetta C. Role of HIF-1 in cancer progression: novel insights. A review. Curr Mol Med. 2018;18(6):343–51. Aldo P, Elisabetta C. Role of HIF-1 in cancer progression: novel insights. A review. Curr Mol Med. 2018;18(6):343–51.
52.
go back to reference Wu JB, Tang YL, Liang XH. Targeting VEGF pathway to normalize the vasculature: an emerging insight in cancer therapy. Oncol Targets Ther. 2018;11:6901–9.CrossRef Wu JB, Tang YL, Liang XH. Targeting VEGF pathway to normalize the vasculature: an emerging insight in cancer therapy. Oncol Targets Ther. 2018;11:6901–9.CrossRef
Metadata
Title
Integrated analyses of microRNA-29 family and the related combination biomarkers demonstrate their widespread influence on risk, recurrence, metastasis and survival outcome in colorectal cancer
Authors
Qiliang Peng
Zhengyang Feng
Yi Shen
Jiahao Zhu
Li Zou
Yuntian Shen
Yaqun Zhu
Publication date
01-12-2019
Publisher
BioMed Central
Published in
Cancer Cell International / Issue 1/2019
Electronic ISSN: 1475-2867
DOI
https://doi.org/10.1186/s12935-019-0907-x

Other articles of this Issue 1/2019

Cancer Cell International 1/2019 Go to the issue
Webinar | 19-02-2024 | 17:30 (CET)

Keynote webinar | Spotlight on antibody–drug conjugates in cancer

Antibody–drug conjugates (ADCs) are novel agents that have shown promise across multiple tumor types. Explore the current landscape of ADCs in breast and lung cancer with our experts, and gain insights into the mechanism of action, key clinical trials data, existing challenges, and future directions.

Dr. Véronique Diéras
Prof. Fabrice Barlesi
Developed by: Springer Medicine