Display options
Cite
Kenn M, Schlangen K, Castillo-Tong DC, et al. Gene expression information improves reliability of receptor status in breast cancer patients. Oncotarget. 2017;8(44):77341-77359doi: 10.18632/oncotarget.20474.
Kenn, M., Schlangen, K., Castillo-Tong, D. C., Singer, C. F., Cibena, M., Koelbl, H., & Schreiner, W. (2017). Gene expression information improves reliability of receptor status in breast cancer patients. Oncotarget, 8(44), 77341-77359. https://doi.org/10.18632/oncotarget.20474
Kenn, Michael, et al. "Gene expression information improves reliability of receptor status in breast cancer patients." Oncotarget vol. 8,44 (2017): 77341-77359. doi: https://doi.org/10.18632/oncotarget.20474
Kenn M, Schlangen K, Castillo-Tong DC, Singer CF, Cibena M, Koelbl H, Schreiner W. Gene expression information improves reliability of receptor status in breast cancer patients. Oncotarget. 2017 Aug 24;8(44):77341-77359. doi: 10.18632/oncotarget.20474. eCollection 2017 Sep 29. PMID: 29100391; PMCID: PMC5652334.
Copy Download .nbib Format: NLM
Share it on

Oncotarget. 2017 Aug 24;8(44):77341-77359. doi: 10.18632/oncotarget.20474. eCollection 2017 Sep 29.

Gene expression information improves reliability of receptor status in breast cancer patients.

Oncotarget

Michael Kenn, Karin Schlangen, Dan Cacsire Castillo-Tong, Christian F Singer, Michael Cibena, Heinz Koelbl, Wolfgang Schreiner

Affiliations

  1. Section of Biosimulation and Bioinformatics, Center for Medical Statistics, Informatics and Intelligent Systems (CeMSIIS), Medical University of Vienna, A-1090 Vienna, Austria.
  2. Translational Gynecology Group, Department of Obstetrics and Gynecology, Comprehensive Cancer Center, Medical University of Vienna, A-1090 Vienna, Austria.
  3. Department of General Gynecology and Gynecologic Oncology, Medical University of Vienna, A-1090 Vienna, Austria.

PMID: 29100391 PMCID: PMC5652334 DOI: 10.18632/oncotarget.20474

Abstract

Immunohistochemical (IHC) determination of receptor status in breast cancer patients is frequently inaccurate. Since it directs the choice of systemic therapy, it is essential to increase its reliability. We increase the validity of IHC receptor expression by additionally considering gene expression (GE) measurements. Crisp therapeutic decisions are based on IHC estimates, even if they are borderline reliable. We further improve decision quality by a responsibility function, defining a critical domain for gene expression. Refined normalization is devised to file any newly diagnosed patient into existing data bases. Our approach renders receptor estimates more reliable by identifying patients with questionable receptor status. The approach is also more efficient since the rate of conclusive samples is increased. We have curated and evaluated gene expression data, together with clinical information, from 2880 breast cancer patients. Combining IHC with gene expression information yields a method more reliable and also more efficient as compared to common practice up to now. Several types of possibly suboptimal treatment allocations, based on IHC receptor status alone, are enumerated. A 'therapy allocation check' identifies patients possibly miss-classified. Estrogen: false negative 8%, false positive 6%. Progesterone: false negative 14%, false positive 11%. HER2: false negative 2%, false positive 50%. Possible implications are discussed. We propose an 'expression look-up-plot', allowing for a significant potential to improve the quality of precision medicine. Methods are developed and exemplified here for breast cancer patients, but they may readily be transferred to diagnostic data relevant for therapeutic decisions in other fields of oncology.

Keywords: breast cancer; data science; gene expression; mathematical oncology; receptor status

Conflict of interest statement

CONFLICTS OF INTEREST The authors declare that there are no conflicts of interest regarding the publication of this paper.

References

  1. J Histochem Cytochem. 2011 Feb;59(2):146-57 - PubMed
  2. J Cancer Res Clin Oncol. 2010 Nov;136(11):1709-18 - PubMed
  3. Nat Rev Clin Oncol. 2011 Dec 06;9(1):48-57 - PubMed
  4. Pharm Stat. 2017 Jan;16(1):55-63 - PubMed
  5. Cancer Sci. 2012 May;103(5):913-20 - PubMed
  6. Breast Cancer Res. 2010;12 (1):R1 - PubMed
  7. PLoS One. 2013 Aug 19;8(8):e66848 - PubMed
  8. J Clin Pathol. 2000 Apr;53(4):292-301 - PubMed
  9. Methods Enzymol. 2006;411:352-69 - PubMed
  10. PLoS One. 2011;6(11):e27656 - PubMed
  11. Oncotarget. 2015 Dec 8;6(39):42197-221 - PubMed
  12. Cancer Res. 2008 Jul 1;68(13):5405-13 - PubMed
  13. Breast Cancer Res Treat. 2010 Feb;119(3):685-99 - PubMed
  14. J Clin Oncol. 2011 Apr 20;29(12):1578-86 - PubMed
  15. Cancer Res. 2016 Apr 1;76(7):1942-53 - PubMed
  16. Mol Cancer Ther. 2015 Nov;14 (11):2473-85 - PubMed
  17. BMC Med Genomics. 2009 Jul 02;2:40 - PubMed
  18. Clin Cancer Res. 2011 Sep 15;17(18):6012-20 - PubMed
  19. Cancer Biol Ther. 2015;16(2):317-24 - PubMed
  20. Nature. 2002 Jan 31;415(6871):530-6 - PubMed
  21. J Clin Oncol. 2007 Jan 1;25(1):118-45 - PubMed
  22. Ann Oncol. 2007 May;18(5):845-50 - PubMed
  23. Bioinformatics. 2003 Jan 22;19(2):185-93 - PubMed
  24. Breast Cancer Res. 2015 Mar 20;17:43 - PubMed
  25. Virchows Arch. 2004 Aug;445(2):119-28 - PubMed
  26. EMBO Mol Med. 2011 Dec;3(12):726-41 - PubMed
  27. Cancer. 1950 Jan;3(1):32-5 - PubMed
  28. Bioinformatics. 2004 Feb 12;20(3):307-15 - PubMed
  29. BMC Genomics. 2008 Aug 06;9:375 - PubMed
  30. BMC Cancer. 2014 Mar 19;14:211 - PubMed
  31. Breast Cancer Res Treat. 2011 Oct;129(3):767-76 - PubMed
  32. Clin Cancer Res. 2014 Jan 15;20(2):511-21 - PubMed
  33. Carcinogenesis. 2013 Oct;34(10):2300-8 - PubMed
  34. Genome Biol. 2012 Dec 10;13(12):R112 - PubMed
  35. J Clin Oncol. 2010 Mar 1;28(7):1145-53 - PubMed
  36. BMC Cancer. 2011 Apr 18;11:143 - PubMed
  37. Nucleic Acids Res. 2007 Jan;35(Database issue):D760-5 - PubMed
  38. Clin Cancer Res. 2009 Jul 15;15(14):4649-64 - PubMed
  39. PLoS One. 2016 Feb 19;11(2):e0148957 - PubMed
  40. PLoS One. 2013 Oct 03;8(10):e76421 - PubMed
  41. Clin Cancer Res. 2012 Feb 15;18(4):1004-14 - PubMed
  42. Nucleic Acids Res. 2002 Jan 1;30(1):207-10 - PubMed
  43. N Engl J Med. 2004 Dec 30;351(27):2817-26 - PubMed
  44. Lancet Oncol. 2007 Mar;8(3):203-11 - PubMed
  45. Clin Cancer Res. 2015 Apr 1;21(7):1688-98 - PubMed
  46. J Natl Cancer Inst. 2006 Nov 1;98(21):1571-81 - PubMed
  47. BMC Cancer. 2011 Jun 01;11:215 - PubMed
  48. J Oncol Pract. 2010 Jul;6(4):195-7 - PubMed
  49. Cancer Inform. 2012;11:147-56 - PubMed
  50. Cancer Res. 2009 Sep 1;69(17):6871-8 - PubMed
  51. Oncotarget. 2015 Nov 3;6(34):36652-74 - PubMed
  52. Nat Med. 2010 Feb;16(2):214-8 - PubMed
  53. Cancer. 2011 Apr 15;117(8):1575-82 - PubMed
  54. Clin Cancer Res. 2008 Aug 15;14(16):5158-65 - PubMed
  55. Breast Cancer Res Treat. 2008 Mar;108(2):191-201 - PubMed
  56. Med Biol Eng Comput. 2012 Sep;50(9):981-90 - PubMed
  57. Nucleic Acids Res. 2003 Feb 15;31(4):e15 - PubMed
  58. NPJ Breast Cancer. 2016;2:null - PubMed

Publication Types