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Published in: Annals of Surgical Oncology 13/2018

01-12-2018 | Translational Research and Biomarkers

Novel MicroRNA-Based Risk Score Identified by Integrated Analyses to Predict Metastasis and Poor Prognosis in Breast Cancer

Authors: Tstutomu Kawaguchi, MD, PhD, Li Yan, PhD, Qianya Qi, MS, Xuan Peng, MS, Stephen B. Edge, MD, Jessica Young, MD, Song Yao, PhD, Song Liu, PhD, Eigo Otsuji, MD, PhD, Kazuaki Takabe, MD, PhD, FACS

Published in: Annals of Surgical Oncology | Issue 13/2018

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Abstract

Background

The use of biomarkers that allow early therapeutic intervention or intensive follow-up evaluation is expected to be a powerful means for reducing breast cancer mortality. MicroRNAs (miRNAs) are known to play major roles in cancer biology including metastasis. This study aimed to develop a novel miRNA risk score to predict patient survival and metastasis in breast cancer.

Methods

An integrated unbiased approach was applied to derive a composite risk score for prognosis based on miRNA expression in primary breast tumors in 1051 breast cancer patients from The Cancer Genome Atlas (TCGA). Further analysis of the risk score with metastasis/recurrence was performed using the TCGA data set and validated in a separate patient population using small RNA sequencing.

Results

The three-miRNAs risk score (miR-19a, miR-93, and miR-106a) was developed using the TCGA cohort, which predicted poor prognosis (p = 0.0005) independently of known clinical risk factors. The prognostic value was validated in another three following independent cohorts: GSE19536 (p = 0.0009), GSE22220 (p = 0.0003), and the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) (p = 0.0023). The three-miRNAs risk score predicted bone recurrence in TCGA (p = 0.0052), and the findings were validated in another independent population of patients who experienced bone recurrence and age/stage-matched patients without any recurrence. The three-miRNAs risk score enriched multiple metastasis-related gene sets such as angiogenesis and epithelial mesenchymal transition in a gene-set-enrichment analysis.

Conclusions

The authors developed the novel miRNA-based risk score, which is a promising biomarker for prediction of worse survival and bone recurrence potential in breast cancer.
Appendix
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Literature
1.
go back to reference Perou CM, Sorlie T, Eisen MB, et al. Molecular portraits of human breast tumours. Nature. 2000;406:747–52.CrossRef Perou CM, Sorlie T, Eisen MB, et al. Molecular portraits of human breast tumours. Nature. 2000;406:747–52.CrossRef
2.
go back to reference Sparano JA, Gray RJ, Makower DF, et al. Prospective validation of a 21-gene expression assay in breast cancer. N Engl J Med. 2015;373:2005–14.CrossRef Sparano JA, Gray RJ, Makower DF, et al. Prospective validation of a 21-gene expression assay in breast cancer. N Engl J Med. 2015;373:2005–14.CrossRef
3.
go back to reference Sorlie T, Perou CM, Tibshirani R, et al. Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proc Natl Acad Sci U S A 2001;98:10869–74.CrossRef Sorlie T, Perou CM, Tibshirani R, et al. Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proc Natl Acad Sci U S A 2001;98:10869–74.CrossRef
5.
go back to reference DeSantis C, Ma J, Bryan L, Jemal A. Breast cancer statistics, 2013. CA Cancer J Clin. 2014;64:52–62.CrossRef DeSantis C, Ma J, Bryan L, Jemal A. Breast cancer statistics, 2013. CA Cancer J Clin. 2014;64:52–62.CrossRef
6.
go back to reference Lee RC, Feinbaum RL, Ambros V. The C. elegans heterochronic gene lin-4 encodes small RNAs with antisense complementarity to lin-14. Cell. 1993;75:843–54.CrossRef Lee RC, Feinbaum RL, Ambros V. The C. elegans heterochronic gene lin-4 encodes small RNAs with antisense complementarity to lin-14. Cell. 1993;75:843–54.CrossRef
7.
go back to reference Lee RC, Ambros V. An extensive class of small RNAs in Caenorhabditis elegans. Science. 2001;294:862–4.CrossRef Lee RC, Ambros V. An extensive class of small RNAs in Caenorhabditis elegans. Science. 2001;294:862–4.CrossRef
8.
go back to reference He L, Thomson JM, Hemann MT, et al. A microRNA polycistron as a potential human oncogene. Nature. 2005;435:828–33.CrossRef He L, Thomson JM, Hemann MT, et al. A microRNA polycistron as a potential human oncogene. Nature. 2005;435:828–33.CrossRef
9.
go back to reference Lu J, Getz G, Miska EA, et al. MicroRNA expression profiles classify human cancers. Nature. 2005;435:834–8.CrossRef Lu J, Getz G, Miska EA, et al. MicroRNA expression profiles classify human cancers. Nature. 2005;435:834–8.CrossRef
10.
go back to reference Calin GA, Croce CM. MicroRNA signatures in human cancers. Nat Rev Cancer. 2006;6:857–66.CrossRef Calin GA, Croce CM. MicroRNA signatures in human cancers. Nat Rev Cancer. 2006;6:857–66.CrossRef
11.
go back to reference He L, He X, Lim LP, et al. A microRNA component of the p53 tumour suppressor network. Nature. 2007;447:1130–4.CrossRef He L, He X, Lim LP, et al. A microRNA component of the p53 tumour suppressor network. Nature. 2007;447:1130–4.CrossRef
12.
go back to reference Iorio MV, Ferracin M, Liu CG, et al. MicroRNA gene expression deregulation in human breast cancer. Cancer Res. 2005;65:7065–70.CrossRef Iorio MV, Ferracin M, Liu CG, et al. MicroRNA gene expression deregulation in human breast cancer. Cancer Res. 2005;65:7065–70.CrossRef
13.
go back to reference Corcoran C, Friel AM, Duffy MJ, Crown J, O’Driscoll L. Intracellular and extracellular microRNAs in breast cancer. Clin Chem. 2011;57:18–32.CrossRef Corcoran C, Friel AM, Duffy MJ, Crown J, O’Driscoll L. Intracellular and extracellular microRNAs in breast cancer. Clin Chem. 2011;57:18–32.CrossRef
14.
go back to reference Koboldt DC, Fulton RS, McLellan MD, et al. Comprehensive molecular portraits of human breast tumours. Nature. 2012;490:61–70.CrossRef Koboldt DC, Fulton RS, McLellan MD, et al. Comprehensive molecular portraits of human breast tumours. Nature. 2012;490:61–70.CrossRef
15.
go back to reference Pereira B, Chin SF, Rueda OM, et al. The somatic mutation profiles of 2433 breast cancers refines their genomic and transcriptomic landscapes. Nat Commun. 2016;7:11479.CrossRef Pereira B, Chin SF, Rueda OM, et al. The somatic mutation profiles of 2433 breast cancers refines their genomic and transcriptomic landscapes. Nat Commun. 2016;7:11479.CrossRef
16.
go back to reference Curtis C, Shah SP, Chin SF, et al. The genomic and transcriptomic architecture of 2000 breast tumours reveals novel subgroups. Nature. 2012;486:346–52.CrossRef Curtis C, Shah SP, Chin SF, et al. The genomic and transcriptomic architecture of 2000 breast tumours reveals novel subgroups. Nature. 2012;486:346–52.CrossRef
17.
go back to reference Enerly E, Steinfeld I, Kleivi K, et al. miRNA-mRNA integrated analysis reveals roles for miRNAs in primary breast tumors. PLoS ONE. 2011;6:e16915.CrossRef Enerly E, Steinfeld I, Kleivi K, et al. miRNA-mRNA integrated analysis reveals roles for miRNAs in primary breast tumors. PLoS ONE. 2011;6:e16915.CrossRef
18.
go back to reference Buffa FM, Camps C, Winchester L, et al. MicroRNA-associated progression pathways and potential therapeutic targets identified by integrated mRNA and microRNA expression profiling in breast cancer. Cancer Res. 2011;71:5635–45.CrossRef Buffa FM, Camps C, Winchester L, et al. MicroRNA-associated progression pathways and potential therapeutic targets identified by integrated mRNA and microRNA expression profiling in breast cancer. Cancer Res. 2011;71:5635–45.CrossRef
19.
go back to reference Goldhirsch A, Wood WC, Coates AS, Gelber RD, Thurlimann B, Senn HJ. Strategies for subtypes: dealing with the diversity of breast cancer: highlights of the St. Gallen International Expert Consensus on the Primary Therapy of Early Breast Cancer 2011. Ann Oncol. 2011;22:1736–47.CrossRef Goldhirsch A, Wood WC, Coates AS, Gelber RD, Thurlimann B, Senn HJ. Strategies for subtypes: dealing with the diversity of breast cancer: highlights of the St. Gallen International Expert Consensus on the Primary Therapy of Early Breast Cancer 2011. Ann Oncol. 2011;22:1736–47.CrossRef
20.
go back to reference Sobin LH, Gospodarowicz MK, Wittekind C. TNM classification of malignant tumours. 7th ed. New York: John Wiley & Sons; 2009. Sobin LH, Gospodarowicz MK, Wittekind C. TNM classification of malignant tumours. 7th ed. New York: John Wiley & Sons; 2009.
21.
go back to reference Gendoo DM, Ratanasirigulchai N, Schroder MS, et al. Genefu: an R/Bioconductor package for computation of gene expression-based signatures in breast cancer. Bioinformatics. 2016;32:1097–9.CrossRef Gendoo DM, Ratanasirigulchai N, Schroder MS, et al. Genefu: an R/Bioconductor package for computation of gene expression-based signatures in breast cancer. Bioinformatics. 2016;32:1097–9.CrossRef
22.
go back to reference Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014;15:550.CrossRef Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014;15:550.CrossRef
23.
go back to reference Crowley JLM, Jacobson J, Salmon S. Proceedings of the First Seattle Symposium in Biostatistics Survival Analysis, vol 123. New York: Springer; 1997.CrossRef Crowley JLM, Jacobson J, Salmon S. Proceedings of the First Seattle Symposium in Biostatistics Survival Analysis, vol 123. New York: Springer; 1997.CrossRef
24.
go back to reference Kim SY, Kawaguchi T, Yan L, Young J, Qi Q, Takabe K. Clinical relevance of microRNA expressions in breast cancer validated using the Cancer Genome Atlas (TCGA). Ann Surg Oncol. 2017;24:2943–49.CrossRef Kim SY, Kawaguchi T, Yan L, Young J, Qi Q, Takabe K. Clinical relevance of microRNA expressions in breast cancer validated using the Cancer Genome Atlas (TCGA). Ann Surg Oncol. 2017;24:2943–49.CrossRef
25.
go back to reference Ramanathan R, Olex AL, Dozmorov M, Bear HD, Fernandez LJ, Takabe K. Angiopoietin pathway gene expression associated with poor breast cancer survival. Breast Cancer Res Treat. 2017;162:191–8.CrossRef Ramanathan R, Olex AL, Dozmorov M, Bear HD, Fernandez LJ, Takabe K. Angiopoietin pathway gene expression associated with poor breast cancer survival. Breast Cancer Res Treat. 2017;162:191–8.CrossRef
26.
go back to reference Young J, Kawaguchi T, Yan L, Qi Q, Liu S, Takabe K. Tamoxifen sensitivity-related microRNA-342 is a useful biomarker for breast cancer survival. Oncotarget. 2017;8:99978–89.PubMedPubMedCentral Young J, Kawaguchi T, Yan L, Qi Q, Liu S, Takabe K. Tamoxifen sensitivity-related microRNA-342 is a useful biomarker for breast cancer survival. Oncotarget. 2017;8:99978–89.PubMedPubMedCentral
27.
go back to reference Kawaguchi T, Yan L, Qi Q, et al. Overexpression of suppressive microRNAs, miR-30a, and miR-200c are associated with improved survival of breast cancer patients. Sci Rep. 2017;7:15945.CrossRef Kawaguchi T, Yan L, Qi Q, et al. Overexpression of suppressive microRNAs, miR-30a, and miR-200c are associated with improved survival of breast cancer patients. Sci Rep. 2017;7:15945.CrossRef
28.
go back to reference Hoerl AK. Ridge regression: biased estimation for nonorthogonal problems. Technometrics. 1970;12:55–67.CrossRef Hoerl AK. Ridge regression: biased estimation for nonorthogonal problems. Technometrics. 1970;12:55–67.CrossRef
29.
go back to reference Narayanan S, Kawaguchi T, Yan L, Peng X, Qi Q, Takabe K. Cytolytic activity score to assess anticancer immunity in colorectal cancer. Ann Surg Oncol. 2018;25:2323.CrossRef Narayanan S, Kawaguchi T, Yan L, Peng X, Qi Q, Takabe K. Cytolytic activity score to assess anticancer immunity in colorectal cancer. Ann Surg Oncol. 2018;25:2323.CrossRef
30.
go back to reference Terakawa T, Katsuta E, Yan L, et al. High expression of SLCO2B1 is associated with prostate cancer recurrence after radical prostatectomy. Oncotarget. 2018;9:14207–18.CrossRef Terakawa T, Katsuta E, Yan L, et al. High expression of SLCO2B1 is associated with prostate cancer recurrence after radical prostatectomy. Oncotarget. 2018;9:14207–18.CrossRef
31.
go back to reference Subramanian A, Tamayo P, Mootha VK, et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci U S A. 2005;102:15545–50.CrossRef Subramanian A, Tamayo P, Mootha VK, et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci U S A. 2005;102:15545–50.CrossRef
32.
go back to reference McShane LM, Altman DG, Sauerbrei W, Taube SE, Gion M, Clark GM. Reporting recommendations for tumor marker prognostic studies (REMARK). J Natl Cancer Inst. 2005;97:1180–4.CrossRef McShane LM, Altman DG, Sauerbrei W, Taube SE, Gion M, Clark GM. Reporting recommendations for tumor marker prognostic studies (REMARK). J Natl Cancer Inst. 2005;97:1180–4.CrossRef
33.
go back to reference McBryan J, Fagan A, McCartan D, et al. Transcriptomic profiling of sequential tumors from breast cancer patients provides a global view of metastatic expression changes following endocrine therapy. Clin Cancer Res. 2015;21:5371–9.CrossRef McBryan J, Fagan A, McCartan D, et al. Transcriptomic profiling of sequential tumors from breast cancer patients provides a global view of metastatic expression changes following endocrine therapy. Clin Cancer Res. 2015;21:5371–9.CrossRef
34.
go back to reference Liberzon A, Birger C, Thorvaldsdottir H, Ghandi M, Mesirov JP, Tamayo P. The Molecular Signatures Database (MSigDB) hallmark gene set collection. Cell Syst. 2015;1:417–25.CrossRef Liberzon A, Birger C, Thorvaldsdottir H, Ghandi M, Mesirov JP, Tamayo P. The Molecular Signatures Database (MSigDB) hallmark gene set collection. Cell Syst. 2015;1:417–25.CrossRef
35.
go back to reference Volinia S, Croce CM. Prognostic microRNA/mRNA signature from the integrated analysis of patients with invasive breast cancer. Proc Natl Acad Sci U S A. 2013;110:7413–7.CrossRef Volinia S, Croce CM. Prognostic microRNA/mRNA signature from the integrated analysis of patients with invasive breast cancer. Proc Natl Acad Sci U S A. 2013;110:7413–7.CrossRef
36.
go back to reference Peng F, Zhang Y, Wang R, et al. Identification of differentially expressed miRNAs in individual breast cancer patient and application in personalized medicine. Oncogenesis. 2016;5:e194.CrossRef Peng F, Zhang Y, Wang R, et al. Identification of differentially expressed miRNAs in individual breast cancer patient and application in personalized medicine. Oncogenesis. 2016;5:e194.CrossRef
37.
go back to reference Wu X, Zeng R, Wu S, Zhong J, Yang L, Xu J. Comprehensive expression analysis of miRNA in breast cancer at the miRNA and isomiR levels. Gene. 2015;557:195–200.CrossRef Wu X, Zeng R, Wu S, Zhong J, Yang L, Xu J. Comprehensive expression analysis of miRNA in breast cancer at the miRNA and isomiR levels. Gene. 2015;557:195–200.CrossRef
38.
go back to reference Zhou X, Wang X, Huang Z, Xu L, Zhu W, Liu P. An ER-associated miRNA signature predicts prognosis in ER-positive breast cancer. J Exp Clin Cancer Res. 2014;33:94.CrossRef Zhou X, Wang X, Huang Z, Xu L, Zhu W, Liu P. An ER-associated miRNA signature predicts prognosis in ER-positive breast cancer. J Exp Clin Cancer Res. 2014;33:94.CrossRef
39.
go back to reference Dews M, Homayouni A, Yu D, et al. Augmentation of tumor angiogenesis by a Myc-activated microRNA cluster. Nat Genet. 2006;38:1060–5.CrossRef Dews M, Homayouni A, Yu D, et al. Augmentation of tumor angiogenesis by a Myc-activated microRNA cluster. Nat Genet. 2006;38:1060–5.CrossRef
40.
go back to reference Dews M, Fox JL, Hultine S, et al. The myc-miR-17 ~ 92 axis blunts TGF{beta} signaling and production of multiple TGF{beta}-dependent antiangiogenic factors. Cancer Res. 2010;70:8233–46.CrossRef Dews M, Fox JL, Hultine S, et al. The myc-miR-17 ~ 92 axis blunts TGF{beta} signaling and production of multiple TGF{beta}-dependent antiangiogenic factors. Cancer Res. 2010;70:8233–46.CrossRef
41.
go back to reference Li Z, Yang CS, Nakashima K, Rana TM. Small RNA-mediated regulation of iPS cell generation. EMBO J 2011;30:823–34.CrossRef Li Z, Yang CS, Nakashima K, Rana TM. Small RNA-mediated regulation of iPS cell generation. EMBO J 2011;30:823–34.CrossRef
42.
go back to reference Stefani G, Slack FJ. Small non-coding RNAs in animal development. Nat Rev Mol Cell Biol. 2008;9:219–30.CrossRef Stefani G, Slack FJ. Small non-coding RNAs in animal development. Nat Rev Mol Cell Biol. 2008;9:219–30.CrossRef
43.
go back to reference Mendell JT. miRiad roles for the miR-17-92 cluster in development and disease. Cell. 2008;133:217–22.CrossRef Mendell JT. miRiad roles for the miR-17-92 cluster in development and disease. Cell. 2008;133:217–22.CrossRef
44.
go back to reference Petrocca F, Vecchione A, Croce CM. Emerging role of miR-106b-25/miR-17-92 clusters in the control of transforming growth factor beta signaling. Cancer Res. 2008;68:8191–4.CrossRef Petrocca F, Vecchione A, Croce CM. Emerging role of miR-106b-25/miR-17-92 clusters in the control of transforming growth factor beta signaling. Cancer Res. 2008;68:8191–4.CrossRef
45.
go back to reference O’Donnell KA, Wentzel EA, Zeller KI, Dang CV, Mendell JT. c-Myc-regulated microRNAs modulate E2F1 expression. Nature. 2005;435:839–43.CrossRef O’Donnell KA, Wentzel EA, Zeller KI, Dang CV, Mendell JT. c-Myc-regulated microRNAs modulate E2F1 expression. Nature. 2005;435:839–43.CrossRef
46.
go back to reference Dal Bo M, Bomben R, Hernandez L, Gattei V. The MYC/miR-17-92 axis in lymphoproliferative disorders: a common pathway with therapeutic potential. Oncotarget. 2015;6:19381–92.CrossRef Dal Bo M, Bomben R, Hernandez L, Gattei V. The MYC/miR-17-92 axis in lymphoproliferative disorders: a common pathway with therapeutic potential. Oncotarget. 2015;6:19381–92.CrossRef
47.
go back to reference Kim K, Chadalapaka G, Lee SO, et al. Identification of oncogenic microRNA-17-92/ZBTB4/specificity protein axis in breast cancer. Oncogene. 2012;31:1034–44.CrossRef Kim K, Chadalapaka G, Lee SO, et al. Identification of oncogenic microRNA-17-92/ZBTB4/specificity protein axis in breast cancer. Oncogene. 2012;31:1034–44.CrossRef
48.
go back to reference Yang J, Zhang Z, Chen C, et al. MicroRNA-19a-3p inhibits breast cancer progression and metastasis by inducing macrophage polarization through downregulated expression of Fra-1 proto-oncogene. Oncogene. 2014;33:3014–23.CrossRef Yang J, Zhang Z, Chen C, et al. MicroRNA-19a-3p inhibits breast cancer progression and metastasis by inducing macrophage polarization through downregulated expression of Fra-1 proto-oncogene. Oncogene. 2014;33:3014–23.CrossRef
49.
go back to reference Conley RB, Dickson D, Zenklusen JC, et al. Core clinical data elements for cancer genomic repositories: a multi-stakeholder consensus. Cell. 2017;171:982–6.CrossRef Conley RB, Dickson D, Zenklusen JC, et al. Core clinical data elements for cancer genomic repositories: a multi-stakeholder consensus. Cell. 2017;171:982–6.CrossRef
50.
go back to reference Manolio TA, Fowler DM, Starita LM, et al. Bedside back to bench: building bridges between basic and clinical genomic research. Cell. 2017;169:6–12.CrossRef Manolio TA, Fowler DM, Starita LM, et al. Bedside back to bench: building bridges between basic and clinical genomic research. Cell. 2017;169:6–12.CrossRef
51.
go back to reference Rodriguez H, Pennington SR. Revolutionizing precision oncology through collaborative proteogenomics and data sharing. Cell. 2018;173:535–9.CrossRef Rodriguez H, Pennington SR. Revolutionizing precision oncology through collaborative proteogenomics and data sharing. Cell. 2018;173:535–9.CrossRef
Metadata
Title
Novel MicroRNA-Based Risk Score Identified by Integrated Analyses to Predict Metastasis and Poor Prognosis in Breast Cancer
Authors
Tstutomu Kawaguchi, MD, PhD
Li Yan, PhD
Qianya Qi, MS
Xuan Peng, MS
Stephen B. Edge, MD
Jessica Young, MD
Song Yao, PhD
Song Liu, PhD
Eigo Otsuji, MD, PhD
Kazuaki Takabe, MD, PhD, FACS
Publication date
01-12-2018
Publisher
Springer International Publishing
Published in
Annals of Surgical Oncology / Issue 13/2018
Print ISSN: 1068-9265
Electronic ISSN: 1534-4681
DOI
https://doi.org/10.1245/s10434-018-6859-x

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