breast cancer; metastasis; prognosis; tumor biology
Abstract :
[en] Prognostic classifiers conceivably comprise biomarker genes that functionally contribute to the oncogenic and metastatic properties of cancer, but this has not been investigated systematically. The transcription factor Fra-1 not only has an essential role in breast cancer, but also drives the expression of a highly prognostic gene set. Here, we systematically perturbed the function of 31 individual Fra-1-dependent poor-prognosis genes and examined their impact on breast cancer growth in vivo. We find that stable shRNA depletion of each of nine individual signature genes strongly inhibits breast cancer growth and aggressiveness. Several factors within this ninegene set regulate each other’s expression, suggesting that together they form a network. The ninegene set is regulated by estrogen, ERBB2 and EGF signaling, all established breast cancer factors. We also uncover three transcription factors, MYC, E2F1 and TP53, which act alongside Fra-1 at the core of this network. ChIP-Seq analysis reveals that a substantial number of genes are bound, and regulated, by all four transcription factors. The nine-gene set retains significant prognostic power and includes several potential therapeutic targets, including the bifunctional enzyme PAICS, which catalyzes purine biosynthesis. Depletion of PAICS largely cancelled breast cancer expansion, exemplifying a prognostic gene with breast cancer activity. Our data uncover a core genetic and prognostic network driving human breast cancer. We propose that pharmacological inhibition of components within this network, such as PAICS, may be used in conjunction with the Fra-1 prognostic classifier towards personalized management of poor prognosis breast cancer.
Disciplines :
Oncology
Author, co-author :
Gallenne, Tristan ✱; The Netherlands Cancer Institute, Plesmanlaan, CX, Amsterdam, The Netherlands > Department of Molecular Oncology
Ross, Kenneth N. ✱; Massachusetts General Hospital Cancer Center, Boston, MA, USA
Visser, Nils L. ✱; The Netherlands Cancer Institute, Plesmanlaan, CX, Amsterdam, The Netherlands > Department of Molecular Oncology
Salony, - ✱; Massachusetts General Hospital Cancer Center, Boston, MA, USA
Desmet, Christophe ; ULiège, Département des sciences fonctionnelles (DSF), GIGA-R : Biochimie et biologie moléculaire > Department of Molecular Oncology, The Netherlands Cancer Institute, Plesmanlaan, CX, Amsterdam, The Netherlands
Wittner, Ben S.; Massachusetts General Hospital Cancer Center, Boston, MA, USA
Wessels, Lodewyk F.A.; The Netherlands Cancer Institute, Plesmanlaan, CX, Amsterdam, The Netherlands > Department of Molecular Carcinogenesis
Ramaswamy, Sridhar; Massachusetts General Hospital Cancer Center, Boston, MA, USA
Peeper, Daniel Simon; The Netherlands Cancer Institute, Plesmanlaan, CX, Amsterdam, The Netherlands > Department of Molecular Oncology
✱ These authors have contributed equally to this work.
Language :
English
Title :
Systematic functional perturbations uncover a prognostic genetic network driving human breast cancer
van de Vijver MJ, He YD, Van't Veer LJ, Dai H, Hart AAM, Voskuil DW, Schreiber GJ, Peterse JL, Roberts C, Marton MJ, Parrish M, Atsma D, Witteveen A, et al. A gene-expression signature as a predictor of survival in breast cancer. N Engl J Med. 2002; 347: 1999-2009. doi: 10.1056/NEJMoa021967.
van t Veer LJ, Dai H, van de Vijver MJ, He YD, Hart AAM, Mao M, Peterse HL, van der Kooy K, Marton MJ, Witteveen AT, Schreiber GJ, Kerkhoven RM, Roberts C, et al. Gene expression profiling predicts clinical outcome of breast cancer. Nature. 2002; 415: 530-6. doi: 10.1038/415530a.
Paik S, Shak S, Tang G, Kim C, Baker J, Cronin M, Baehner FL, Walker MG, Watson D, Park T, Hiller W, Fisher ER, Wickerham DL, et al. A multigene assay to predict recurrence of tamoxifen-treated, node-negative breast cancer. N Engl J Med. 2004; 351: 2817-26. doi: 10.1056/NEJMoa041588.
Sotiriou C, Neo S-Y, McShane LM, Korn EL, Long PM, Jazaeri A, Martiat P, Fox SB, Harris AL, Liu ET. Breast cancer classification and prognosis based on gene expression profiles from a population-based study. Proc Natl Acad Sci USA. 2003; 100: 10393-8. doi: 10.1073/pnas.1732912100.
Wang Y, Klijn JGM, Zhang Y, Sieuwerts AM, Look MP, Yang F, Talantov D, Timmermans M, Meijer-van Gelder ME, Yu J, Jatkoe T, Berns EMJJ, Atkins D, et al. Geneexpression profiles to predict distant metastasis of lymphnode-negative primary breast cancer. Lancet. 2005; 365: 671-9. doi: 10.1016/S0140-6736(05)17947-1.
Ramaswamy S, Ross KN, Lander ES, Golub TR. A molecular signature of metastasis in primary solid tumors. Nat Genet. 2002nd ed. 2003; 33: 49-54. doi: 10.1038/ng1060.
Cardoso F, Van't Veer LJ, Bogaerts J, Slaets L, Viale G, Delaloge S, Pierga J-Y, Brain E, Causeret S, Delorenzi M, Glas AM, Golfinopoulos V, Goulioti T, et al. 70-Gene Signature as an Aid to Treatment Decisions in Early-Stage Breast Cancer. N Engl J Med. 2016; 375: 717-29. doi: 10.1056/NEJMoa1602253.
Sparano JA, Gray RJ, Makower DF, Pritchard KI, Albain KS, Hayes DF, Geyer CE, Dees EC, Perez EA, Olson JA, Zujewski J, Lively T, Badve SS, et al. Prospective Validation of a 21-Gene Expression Assay in Breast Cancer. N Engl J Med. 2015; 373: 2005-14. doi: 10.1056/NEJMoa1510764.
Desmet CJ, Gallenne T, Prieur A, Reyal F, Visser NL, Wittner BS, Smit MA, Geiger TR, Laoukili J, Iskit S, Rodenko B, Zwart W, Evers B, et al. Identification of a pharmacologically tractable Fra-1/ADORA2B axis promoting breast cancer metastasis. Proc Natl Acad Sci USA. 2013; 110: 5139-44. doi: 10.1073/pnas.1222085110.
Tam WL, Lu H, Buikhuisen J, Soh BS, Lim E, Reinhardt F, Wu ZJ, Krall JA, Bierie B, Guo W, Chen X, Liu XS, Brown M, et al. Protein kinase C a is a central signaling node and therapeutic target for breast cancer stem cells. Cancer Cell. 2013; 24: 347-64. doi: 10.1016/j.ccr.2013.08.005.
van t Veer LJ, Bernards R. Enabling personalized cancer medicine through analysis of gene-expression patterns. Nature. 2008; 452: 564-70. doi: 10.1038/nature06915.
Minn AJ, Gupta GP, Siegel PM, Bos PD, Shu W, Giri DD, Viale A, Olshen AB, Gerald WL, Massagué J. Genes that mediate breast cancer metastasis to lung. Nature. 2005; 436: 518-24. doi: 10.1038/nature03799.
Li J, Lenferink AEG, Deng Y, Collins C, Cui Q, Purisima EO, O'Connor-McCourt MD, Wang E. Identification of high-quality cancer prognostic markers and metastasis network modules. Nature Communications. 2010; 1: 34. doi: 10.1038/ncomms1033.
Tian S, Roepman P, Van't Veer LJ, Bernards R, de Snoo F, Glas AM. Biological functions of the genes in the mammaprint breast cancer profile reflect the hallmarks of cancer. Biomark Insights. 2010; 5: 129-38. doi: 10.4137/BMI.S6184.
Wolfer A, Wittner BS, Irimia D, Flavin RJ, Lupien M, Gunawardane RN, Meyer CA, Lightcap ES, Tamayo P, Mesirov JP, Liu XS, Shioda T, Toner M, et al. MYC regulation of a "poor-prognosis" metastatic cancer cell state. Proc Natl Acad Sci USA. 2010; 107: 3698-703. doi: 10.1073/pnas.0914203107.
Skobe M, Hawighorst T, Jackson DG, Prevo R, Janes L, Velasco P, Riccardi L, Alitalo K, Claffey K, Detmar M. Induction of tumor lymphangiogenesis by VEGF-C promotes breast cancer metastasis. Nat Med. 2001; 7: 192-8. doi: 10.1038/84643.
Adorno M, Cordenonsi M, Montagner M, Dupont S, Wong C, Hann B, Solari A, Bobisse S, Rondina MB, Guzzardo V, Parenti AR, Rosato A, Bicciato S, et al. A Mutant-p53/Smad complex opposes p63 to empower TGFbetainduced metastasis. Cell. 2009; 137: 87-98. doi: 10.1016/j. cell.2009.01.039.
Zhang Y, Liu T, Meyer CA, Eeckhoute J, Johnson DS, Bernstein BE, Nusbaum C, Myers RM, Brown M, Li W, Liu XS. Model-based analysis of ChIP-Seq (MACS). Genome Biol. BioMed Central Ltd; 2008; 9: R137. doi: 10.1186/gb-2008-9-9-r137.
Rhie SK, Hazelett DJ, Coetzee SG, Yan C, Noushmehr H, Coetzee GA. Nucleosome positioning and histone modifications define relationships between regulatory elements and nearby gene expression in breast epithelial cells. BMC Genomics. BioMed Central Ltd; 2014; 15: 331. doi: 10.1186/1471-2164-15-331.
Subramanian A, Tamayo P, Mootha VK, Mukherjee S, Ebert BL, Gillette MA, Paulovich A, Pomeroy SL, Golub TR, Lander ES, Mesirov JP. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci USA. 2005; 102: 15545-50. doi: 10.1073/pnas.0506580102.
Mootha VK, Lindgren CM, Eriksson K-F, Subramanian A, Sihag S, Lehár J, Puigserver P, Carlsson E, Ridderstråle M, Laurila E, Houstis N, Daly MJ, Patterson N, et al. PGC-1alpha-responsive genes involved in oxidative phosphorylation are coordinately downregulated in human diabetes. Nat Genet. 2003; 34: 267-73. doi: 10.1038/ng1180.
Douma S, van Laar T, Zevenhoven J, Meuwissen R, van Garderen E, Peeper DS. Suppression of anoikis and induction of metastasis by the neurotrophic receptor TrkB. Nature. 2004; 430: 1034-9. doi: 10.1038/nature02765.
Liotta LA, Kohn E. Anoikis: cancer and the homeless cell. Nature. 2004; 430: 973-4. doi: 10.1038/430973a.
Cardoso F, Veer LV, Rutgers E, Loi S, Mook S, Piccart-Gebhart MJ. Clinical Application of the 70-Gene Profile: The MINDACT Trial. J Clin Oncol. 2008; 26: 729-35. doi: 10.1200/JCO.2007.14.3222.
Sparano JA, Paik S. Development of the 21-Gene Assay and Its Application in Clinical Practice and Clinical Trials. J Clin Oncol. 2008; 26: 721-8. doi: 10.1200/JCO.2007.15.1068.
Bueno-de-Mesquita JM, Linn SC, Keijzer R, Wesseling J, Nuyten DSA, van Krimpen C, Meijers C, de Graaf PW, Bos MMEM, Hart AAM, Rutgers EJT, Peterse JL, Halfwerk H, et al. Validation of 70-gene prognosis signature in nodenegative breast cancer. Breast Cancer Res Treat. 2009; 117: 483-95. doi: 10.1007/s10549-008-0191-2.
Stagg J, Divisekera U, McLaughlin N, Sharkey J, Pommey S, Denoyer D, Dwyer KM, Smyth MJ. Anti-CD73 antibody therapy inhibits breast tumor growth and metastasis. Proc Natl Acad Sci USA. 2010; 107: 1547-52. doi: 10.1073/pnas.0908801107.
Cekic C, Sag D, Li Y, Theodorescu D, Strieter RM, Linden J. Adenosine A2B Receptor Blockade Slows Growth of Bladder and Breast Tumors. J Immunol. 2012; 188: 198-205. doi: 10.4049/jimmunol.1101845.
Guo K, Tang JP, Tan CPB, Wang H, Zeng Q. Monoclonal antibodies target intracellular PRL phosphatases to inhibit cancer metastases in mice. Cancer Biol Ther. 2008; 7: 750-7.
Crea F, Fornaro L, Bocci G, Sun L, Farrar WL, Falcone A, Danesi R. EZH2 inhibition: targeting the crossroad of tumor invasion and angiogenesis. Cancer Metastasis Rev. Springer US; 2012; 31: 753-61. doi: 10.1007/s10555-012-9387-3.
Loi S, Haibe-Kains B, Desmedt C, Lallemand F, Tutt AM, Gillet C, Ellis P, Harris A, Bergh J, Foekens JA, Klijn JGM, Larsimont D, Buyse M, et al. Definition of Clinically Distinct Molecular Subtypes in Estrogen Receptor-Positive Breast Carcinomas Through Genomic Grade. J Clin Oncol. 2007; 25: 1239-46. doi: 10.1200/JCO.2006.07.1522.
Miller LD, Smeds J, George J, Vega VB, Vergara L, Ploner A, Pawitan Y, Hall P, Klaar S, Liu ET, Bergh J. An expression signature for p53 status in human breast cancer predicts mutation status, transcriptional effects, and patient survival. Proc Natl Acad Sci USA. 2005; 102: 13550-5. doi: 10.1073/pnas.0506230102.
Pawitan Y, Bjöhle J, Amler L, Borg A-L, Egyhazi S, Hall P, Han X, Holmberg L, Huang F, Klaar S, Liu ET, Miller L, Nordgren H, et al. Gene expression profiling spares early breast cancer patients from adjuvant therapy: derived and validated in two population-based cohorts. Breast Cancer Res. 2005; 7: R953-64. doi: 10.1186/bcr1325.
Desmedt C, Piette F, Loi S, Wang Y, Lallemand F, Haibe-Kains B, Viale G, Delorenzi M, Zhang Y, d'Assignies MS, Bergh J, Lidereau R, Ellis P, et al. Strong Time Dependence of the 76-Gene Prognostic Signature for Node-Negative Breast Cancer Patients in the TRANSBIG Multicenter Independent Validation Series. Clin Cancer Res. 2007; 13: 3207-14. doi: 10.1158/1078-0432.CCR-06-2765.
Minn AJ, Gupta GP, Padua D, Bos P, Nguyen DX, Nuyten D, Kreike B, Zhang Y, Wang Y, Ishwaran H, Foekens JA, van de Vijver M, Massagué J. Lung metastasis genes couple breast tumor size and metastatic spread. Proc Natl Acad Sci USA. 2007; 104: 6740-5. doi: 10.1073/pnas.0701138104.
Freeman PR, Hedges LV, Olkin I. Statistical Methods for Meta-Analysis. Biometrics. 1986; 42: 454. doi: 10.2307/2531069.
Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014; 30: 2114-20. doi: 10.1093/bioinformatics/btu170.
Langmead B, Trapnell C, Pop M, Salzberg SL. Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol. 2009; 10: R25. doi: 10.1186/gb-2009-10-3-r25.
Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, Marth G, Abecasis G, Durbin R, Subgroup 1GPDP. The Sequence Alignment/Map format and SAMtools. Bioinformatics. 2009; 25: 2078-9. doi: 10.1093/bioinformatics/btp352.
Shen L, Shao N, Liu X, Nestler E. ngs.plot: Quick mining and visualization of next-generation sequencing data by integrating genomic databases. BMC Genomics. 2014. p.284. doi: 10.1186/1471-2164-15-284.
Salmon-Divon M, Dvinge H, Tammoja K, Bertone P. PeakAnalyzer: Genome-wide annotation of chromatin binding and modification loci. BMC Bioinformatics. 2010. p. 415. doi: 10.1186/1471-2105-11-415.
Trapnell C, Pachter L, Salzberg SL. TopHat: discovering splice junctions with RNA-Seq. Bioinformatics. 2009; 25: 1105-11. doi: 10.1093/bioinformatics/btp120.
Benjamini Y, Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. Journal of the Royal Statistical Society Series B. 1995. doi: 10.2307/2346101.
Ciriello G, Gatza ML, Beck AH, Wilkerson MD, Rhie SK, Pastore A, Zhang H, McLellan M, Yau C, Kandoth C, Bowlby R, Shen H, Hayat S, et al. Comprehensive Molecular Portraits of Invasive Lobular Breast Cancer. Cell. 2015; 163: 506-19. doi: 10.1016/j.cell.2015.09.033.
