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Evaluation of malignancy-risk gene signature in breast cancer patients

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Abstract

We recently developed a malignancy-risk gene signature that was shown to identify histologically-normal tissues with a cancer-like profile. Because the signature was rich with proliferative genes, we postulated it might also be prognostic for existing breast cancers. We evaluated the malignancy risk gene signature to see its clinical association with cancer relapse/progression, and cancer prognosis using six independent external datasets. Six independent external breast cancer datasets were collected and analyzed using the malignancy risk gene signature designed to assess normal breast tissues. Evaluation of the signature in external datasets suggested a strong clinical association with cancer relapse/progression, and prognosis with minimal overlap of signature gene sets. These results suggest a prognostic role for the malignancy risk gene signature in the assessment of existing cancer. Proliferative biology dominates not only the earliest stages of tumor development but also later stages of tumor progression and metastasis.

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References

  1. Chen D-T, Nasir A, Culhane A, Venkataramu C, Fulp W, Rubio R et al (2009) Proliferative genes dominate malignancy-risk signature in histologically normal breast tissue. Breast Cancer Res Treat. doi:10.1007/s10549-009-0344-y

  2. Bair E, Tibshirani R (2004) Semi-supervised methods to predict patient survival from gene expression data. PLoS Biol 2(4):E108. doi:10.1371/journal.pbio.0020108

    Article  PubMed  Google Scholar 

  3. Miller RG (1981) Simultaneous statistical inference. Springer, New York

    Google Scholar 

  4. Turashvili G, Bouchal J, Baumforth K, Wei W, Dziechciarkova M, Ehrmann J, Klein J, Fridman E, Skarda J, Srovnal J, Hajduch M, Murray P, Kolar Z (2007) Novel markers for differentiation of lobular and ductal invasive breast carcinomas by laser microdissection and microarray analysis. BMC Cancer 7:55

    Article  PubMed  Google Scholar 

  5. Chanrion M, Negre V, Fontaine H, Salvetat N, Bibeau F, Mac Grogan G et al (2008) A gene expression signature that can predict the recurrence of tamoxifen-treated primary breast cancer. Clin Cancer Res 14(6):1744–1752. doi:10.1158/1078-0432.CCR-07-1833

    Article  CAS  PubMed  Google Scholar 

  6. Ma XJ, Salunga R, Tuggle JT, Gaudet J, Enright E, McQuary P et al (2003) Gene expression profiles of human breast cancer progression. Proc Natl Acad Sci USA 100(10):5974–5979. doi:10.1073/pnas.0931261100

    Article  CAS  PubMed  Google Scholar 

  7. van de Vijver MJ, He YD, van ‘t Veer LJ, Dai H, Hart AAM, Voskuil DW et al (2002) A gene-expression signature as a predictor of survival in breast cancer. N Engl J Med 347(25):1999–2009. doi:10.1056/NEJMoa021967

    Article  PubMed  Google Scholar 

  8. Wang Y, Klijn JG, Zhang Y, Sieuwerts AM, Look MP, Yang F et al (2005) Gene-expression profiles to predict distant metastasis of lymph-node-negative primary breast cancer. Lancet 365(9460):671–679

    CAS  PubMed  Google Scholar 

  9. Huang E, Cheng SH, Dressman H, Pittman J, Tsou MH, Horng CF et al (2003) Gene expression predictors of breast cancer outcomes. Lancet 361(9369):1590–1596. doi:10.1016/S0140-6736(03)13308-9

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgments

This work was supported by grants from the National Institutes of Health (RO1CA098522, R01CA112215, and P30CA76292). We thank Magaly Mendez for assistance in manuscript preparation. The authors gratefully acknowledge the helpful comments by anonymous referees.

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Correspondence to Timothy Yeatman.

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Chen, DT., Nasir, A., Venkataramu, C. et al. Evaluation of malignancy-risk gene signature in breast cancer patients. Breast Cancer Res Treat 120, 25–34 (2010). https://doi.org/10.1007/s10549-009-0357-6

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  • DOI: https://doi.org/10.1007/s10549-009-0357-6

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