Table of Contents Author Guidelines Submit a Manuscript
International Journal of Breast Cancer
Volume 2017, Article ID 4279724, 7 pages
https://doi.org/10.1155/2017/4279724
Review Article

Molecular Signatures of Radiation Response in Breast Cancer: Towards Personalized Decision-Making in Radiation Treatment

1Department of Radiation Oncology, Michigan Medicine, Ann Arbor, MI, USA
2Comprehensive Cancer Center, University of Michigan, Ann Arbor, MI, USA

Correspondence should be addressed to Corey Speers; ude.hcimu.dem@sreepsc

Received 28 July 2017; Accepted 25 October 2017; Published 26 November 2017

Academic Editor: Jennifer De Los Santos

Copyright © 2017 Corey Speers and Lori J. Pierce. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. A. C. Begg, K. Haustermans, A. A. Hart et al., “The value of pretreatment cell kinetic parameters as predictors for radiotherapy outcome in head and neck cancer: a multicenter analysis,” Radiotherapy & Oncology, vol. 50, no. 1, pp. 13–23, 1999. View at Publisher · View at Google Scholar
  2. B. Fertil and E.-P. Malaise, “Inherent cellular radiosensitivity as a basic concept for human tumor radiotherapy,” International Journal of Radiation Oncology, Biology, Physics, vol. 7, no. 5, pp. 621–629, 1981. View at Publisher · View at Google Scholar · View at Scopus
  3. G. G. Steel, Basic Clinical Radiobiology for Radiation Oncologists, Edward Arnold, London, UK, 1993.
  4. C. L. West, S. Davidson, J. Hendry, and R. Hunter, “Prediction of cervical carcinoma response to radiotherapy,” The Lancet, vol. 338, no. 8770, p. 818, 1991. View at Publisher · View at Google Scholar · View at Scopus
  5. N. G. Burnet, R. Wurm, J. R. Yarnold, J. H. Peacock, J. Nyman, and I. Turesson, “Prediction of normal-tissue tolerance to radiotherapy from in-vitro cellular radiation sensitivity,” The Lancet, vol. 339, no. 8809, pp. 1570-1571, 1992. View at Publisher · View at Google Scholar · View at Scopus
  6. F. B. Geara, L. J. Peters, K. Kian Ang, J. L. Wike, and W. A. Brock, “Prospective comparison of in vitro normal cell radiosensitivity and normal tissue reactions in radiotherapy patients,” International Journal of Radiation Oncology, Biology, Physics, vol. 27, no. 5, pp. 1173–1179, 1993. View at Publisher · View at Google Scholar · View at Scopus
  7. J. Johansen, S. M. Bentzen, J. Overgaard, and M. Overgaard, “Evidence for a positive correlation between in vitro radiosensitivity of normal human skin fibroblasts and the occurrence of subcutaneous fibrosis after radiotherapy,” International Journal of Radiation Biology, vol. 66, no. 4, pp. 407–412, 1994. View at Publisher · View at Google Scholar · View at Scopus
  8. S. A. Eschrich, J. Pramana, H. Zhang et al., “A gene expression model of intrinsic tumor radiosensitivity: prediction of response and prognosis after chemoradiation,” International Journal of Radiation Oncology, Biology, Physics, vol. 75, no. 2, pp. 489–496, 2009. View at Publisher · View at Google Scholar · View at Scopus
  9. J. G. Scott, A. Berglund, M. J. Schell et al., “A genome-based model for adjusting radiotherapy dose (GARD): a retrospective, cohort-based study,” The Lancet Oncology, vol. 18, no. 2, pp. 202–211, 2017. View at Publisher · View at Google Scholar
  10. N. Servant, M. A. Bollet, H. Halfwerk et al., “Search for a gene expression signature of breast cancer local recurrence in young women,” Clinical Cancer Research, vol. 18, no. 6, pp. 1704–1715, 2012. View at Publisher · View at Google Scholar · View at Scopus
  11. C. Speers, S. Zhao, M. Liu, H. Bartelink, L. J. Pierce, and F. Y. Feng, “Development and validation of a novel radiosensitivity signature in human breast cancer,” Clinical Cancer Research, vol. 21, no. 16, pp. 3667–3677, 2015. View at Publisher · View at Google Scholar · View at Scopus
  12. J. F. Torres-Roca, S. Eschrich, H. Zhao et al., “Prediction of radiation sensitivity using a gene expression classifier,” Cancer Research, vol. 65, no. 16, pp. 7169–7176, 2005. View at Publisher · View at Google Scholar · View at Scopus
  13. R. R. Weichselbaum, H. Ishwaran, T. Yoon et al., “An interferon-related gene signature for DNA damage resistance is a predictive marker for chemotherapy and radiation for breast cancer,” Proceedings of the National Acadamy of Sciences of the United States of America, vol. 105, no. 47, pp. 18490–18495, 2008. View at Publisher · View at Google Scholar · View at Scopus
  14. B. D. Yard, D. J. Adams, E. K. Chie et al., “A genetic basis for the variation in the vulnerability of cancer to DNA damage,” Nature Communications, vol. 7, p. 11428, 2016. View at Publisher · View at Google Scholar
  15. S. G. Zhao, S. L. Chang, D. E. Spratt et al., “Development and validation of a 24-gene predictor of response to postoperative radiotherapy in prostate cancer: a matched, retrospective analysis,” The Lancet Oncology, vol. 17, no. 11, pp. 1612–1620, 2016. View at Publisher · View at Google Scholar · View at Scopus
  16. K. S. Albain, W. E. Barlow, S. Shak et al., “Prognostic and predictive value of the 21-gene recurrence score assay in postmenopausal women with node-positive, oestrogen-receptor-positive breast cancer on chemotherapy: a retrospective analysis of a randomised trial,” The Lancet Oncology, vol. 11, no. 1, pp. 55–65, 2010. View at Publisher · View at Google Scholar · View at Scopus
  17. A. M. Glas, A. Floore, L. J. Delahaye et al., “Converting a breast cancer microarray signature into a high-throughput diagnostic test,” BMC Genomics, vol. 7, p. 278, 2006. View at Publisher · View at Google Scholar
  18. M. Knauer, S. Mook, E. J. T. Rutgers et al., “The predictive value of the 70-gene signature for adjuvant chemotherapy in early breast cancer,” Breast Cancer Research and Treatment, vol. 120, no. 3, pp. 655–661, 2010. View at Publisher · View at Google Scholar · View at Scopus
  19. G. Tang, S. Shak, S. Paik et al., “Comparison of the prognostic and predictive utilities of the 21-gene recurrence score assay and adjuvant! for women with node-negative, ER-positive breast cancer: Results from NSABP B-14 and NSABP B-20,” Breast Cancer Research and Treatment, vol. 127, no. 1, pp. 133–142, 2011. View at Publisher · View at Google Scholar · View at Scopus
  20. S. Paik, S. Shak, G. Tang et al., “A multigene assay to predict recurrence of tamoxifen-treated, node-negative breast cancer,” The New England Journal of Medicine, vol. 351, no. 27, pp. 2817–2826, 2004. View at Publisher · View at Google Scholar · View at Scopus
  21. M. J. van de Vijver, Y. D. He, L. J. van 'T Veer et al., “A gene-expression signature as a predictor of survival in breast cancer,” The New England Journal of Medicine, vol. 347, no. 25, pp. 1999–2009, 2002. View at Publisher · View at Google Scholar · View at Scopus
  22. L. J. van't Veer, H. Dai, M. J. van de Vijver et al., “Gene expression profiling predicts clinical outcome of breast cancer,” Nature, vol. 415, no. 6871, pp. 530–536, 2002. View at Publisher · View at Google Scholar · View at Scopus
  23. M. Dowsett, I. Sestak, E. Lopez-Knowles et al., “Comparison of PAM50 risk of recurrence score with oncotype DX and IHC4 for predicting risk of distant recurrence after endocrine therapy,” Journal of Clinical Oncology, vol. 31, no. 22, pp. 2783–2790, 2013. View at Publisher · View at Google Scholar · View at Scopus
  24. J. A. Sparano, R. J. Gray, D. F. Makower et al., “Prospective validation of a 21-gene expression assay in breast cancer,” The New England Journal of Medicine, vol. 373, no. 21, pp. 2005–2014, 2015. View at Publisher · View at Google Scholar · View at Scopus
  25. B. Kreike, H. Halfwerk, N. Armstrong et al., “Local recurrence after breast-conserving therapy in relation to gene expression patterns in a large series of patients,” Clinical Cancer Research, vol. 15, no. 12, pp. 4181–4190, 2009. View at Publisher · View at Google Scholar · View at Scopus
  26. M. Xiao-Jun, R. Salunga, S. Dahiya et al., “A five-gene molecular grade index and HOXB13.IL17BR are complementary prognostic factors in early stage breast cancer,” Clinical Cancer Research, vol. 14, no. 9, pp. 2601–2608, 2008. View at Publisher · View at Google Scholar · View at Scopus
  27. M. L. Whitfield, G. Sherlock, A. J. Saldanha et al., “Identification of genes periodically expressed in the human cell cycle and their expression in tumors,” Molecular Biology of the Cell (MBoC), vol. 13, no. 6, pp. 1977–2000, 2002. View at Publisher · View at Google Scholar · View at Scopus
  28. B. M. Müller, E. Keil, A. Lehmann et al., “The endopredict gene-expression assay in clinical practice—performance and impact on clinical decisions,” PLoS ONE, vol. 8, no. 6, Article ID e68252, 2013. View at Publisher · View at Google Scholar · View at Scopus
  29. S. A. Eschrich, W. J. Fulp, Y. Pawitan et al., “Validation of a radiosensitivity molecular signature in breast cancer,” Clinical Cancer Research, vol. 18, no. 18, pp. 5134–5143, 2012. View at Publisher · View at Google Scholar · View at Scopus
  30. T. Strom, S. E. Hoffe, W. Fulp et al., “Radiosensitivity index predicts for survival with adjuvant radiation in resectable pancreatic cancer,” Radiotherapy & Oncology, vol. 117, no. 1, pp. 159–164, 2015. View at Publisher · View at Google Scholar · View at Scopus
  31. B. D. Piening, P. Wang, A. Subramanian, and A. G. Paulovich, “A radiation-derived gene expression signature predicts clinical outcome for breast cancer patients,” Journal of Radiation Research, vol. 171, no. 2, pp. 141–154, 2009. View at Publisher · View at Google Scholar · View at Scopus
  32. D. S. A. Nuyten, B. Kreike, A. A. M. Hart et al., “Predicting a local recurrence after breast-conserving therapy by gene expression profiling,” Breast Cancer Research, vol. 8, no. 5, article no. R62, 2006. View at Publisher · View at Google Scholar · View at Scopus
  33. A. Eustace, N. Mani, P. N. Span et al., “A 26-gene hypoxia signature predicts benefit from hypoxia-modifying therapy in laryngeal cancer but not bladder cancer,” Clinical Cancer Research, vol. 19, no. 17, pp. 4879–4888, 2013. View at Publisher · View at Google Scholar · View at Scopus
  34. K. Toustrup, B. S. Sørensen, M. A. H. Metwally et al., “Validation of a 15-gene hypoxia classifier in head and neck cancer for prospective use in clinical trials,” Acta Oncologica, vol. 55, no. 9-10, pp. 1091–1098, 2016. View at Publisher · View at Google Scholar · View at Scopus
  35. L. Yang, J. Taylor, A. Eustace et al., “A gene signature for selecting benefit from hypoxia modification of radiotherapy for high-risk bladder cancer patients,” Clinical Cancer Research, vol. 23, no. 16, pp. 4761–4768, 2017. View at Publisher · View at Google Scholar
  36. D. S. Oh, M. C. U. Cheang, C. Fan, and C. M. Perou, “Radiation-induced gene signature predicts pathologic complete response to neoadjuvant chemotherapy in breast cancer patients,” Journal of Radiation Research, vol. 181, no. 2, pp. 193–207, 2014. View at Publisher · View at Google Scholar · View at Scopus
  37. H. S. Kim, S. C. Kim, S. J. Kim et al., “Identification of a radiosensitivity signature using integrative metaanalysis of published microarray data for NCI-60 cancer cells,” BMC Genomics, vol. 13, no. 1, article no. 348, 2012. View at Publisher · View at Google Scholar · View at Scopus
  38. F. Y. Feng, C. Speers, M. Liu et al., “Targeted radiosensitization with PARP1 inhibition: Optimization of therapy and identification of biomarkers of response in breast cancer,” Breast Cancer Research and Treatment, vol. 147, no. 1, pp. 81–94, 2014. View at Publisher · View at Google Scholar · View at Scopus
  39. M. Jonsson, H. B. Ragnum, C. H. Julin et al., “Hypoxia-independent gene expression signature associated with radiosensitisation of prostate cancer cell lines by histone deacetylase inhibition,” British Journal of Cancer, vol. 115, no. 8, pp. 929–939, 2016. View at Publisher · View at Google Scholar · View at Scopus
  40. S. Mori, J. T. Chang, E. R. Andrechek, A. Potti, and J. R. Nevins, “Utilization of genomic signatures to identify phenotype-specific drugs,” PLoS ONE, vol. 4, no. 8, Article ID e6772, 2009. View at Publisher · View at Google Scholar · View at Scopus
  41. E. Niméus-Malmström, M. Krogh, P. Malmström et al., “Gene expression profiling in primary breast cancer distinguishes patients developing local recurrence after breast-conservation surgery, with or without postoperative radiotherapy,” Breast Cancer Research, vol. 10, no. 2, article no. R34, 2008. View at Publisher · View at Google Scholar · View at Scopus
  42. B. Kreike, H. Halfwerk, P. Kristel et al., “Gene expression profiles of primary breast carcinomas from patients at high risk for local recurrence after breast-conserving therapy,” Clinical Cancer Research, vol. 12, no. 19, pp. 5705–5712, 2006. View at Publisher · View at Google Scholar · View at Scopus
  43. S. Darby, P. McGale, C. Correa et al., “Effect of radiotherapy after breast-conserving surgery on 10-year recurrence and 15-year breast cancer death: meta-analysis of individual patient data for 10 801 women in 17 randomised trials,” The Lancet, vol. 378, no. 9804, pp. 1707–1716, 2011. View at Publisher · View at Google Scholar · View at Scopus
  44. C. C. Kirwan, C. E. Coles, J. Bliss et al., “It's PRIMETIME. Postoperative Avoidance of Radiotherapy: Biomarker Selection of Women at Very Low Risk of Local Recurrence,” Clinical Oncology, vol. 28, no. 9, pp. 594–596, 2016. View at Publisher · View at Google Scholar · View at Scopus
  45. S. Eschrich, H. Zhang, H. Zhao et al., “Systems biology modeling of the radiation sensitivity network: a biomarker discovery platform,” International Journal of Radiation Oncology, Biology, Physics, vol. 75, no. 2, pp. 497–505, 2009. View at Publisher · View at Google Scholar · View at Scopus
  46. K. A. Ahmed, P. Chinnaiyan, W. J. Fulp, S. Eschrich, J. F. Torres-Roca, and J. J. Caudell, “The radiosensitivity index predicts for overall survival in glioblastoma,” Oncotarget , vol. 6, no. 33, pp. 34414–34422, 2015. View at Publisher · View at Google Scholar · View at Scopus
  47. S. A. Amundson, K. T. Do, L. C. Vinikoor et al., “Integrating global gene expression and radiation survival parameters across the 60 cell lines of the National Cancer Institute Anticancer Drug Screen,” Cancer Research, vol. 68, no. 2, pp. 415–424, 2008. View at Publisher · View at Google Scholar · View at Scopus