Combinatorial biomarker expression in breast cancer
- PMID: 20107892
- DOI: 10.1007/s10549-010-0746-x
Combinatorial biomarker expression in breast cancer
Abstract
Current clinical management of breast cancer relies on the availability of robust clinicopathological variables and few well-defined biological markers. Recent microarray-based expression profiling studies have emphasised the importance of the molecular portraits of breast cancer and the possibility of classifying breast cancer into biologically and molecularly distinct groups. Subsequent large scale immunohistochemical studies have demonstrated that the added value of studying the molecular biomarker expression in combination rather than individually. Oestrogen (ER) and progesterone (PR) receptors and HER2 are currently used in routine pathological assessment of breast cancer. Additional biomarkers such as proliferation markers and 'basal' markers are likely to be included in the future. A better understanding of the prognostic and predictive value of combinatorial assessment of biomarker expression could lead to improved breast cancer management in routine clinical practice and would add to our knowledge concerning the variation in behaviour and response to therapy. Here, we review the evidence on the value of assessing biomarker expression in breast cancer individually and in combination and its relation to the recent molecular classification of breast cancer.
Similar articles
-
Gene expression profiles of breast cancer obtained from core cut biopsies before neoadjuvant docetaxel, adriamycin, and cyclophoshamide chemotherapy correlate with routine prognostic markers and could be used to identify predictive signatures.Zentralbl Gynakol. 2006 Apr;128(2):76-81. doi: 10.1055/s-2006-921508. Zentralbl Gynakol. 2006. PMID: 16673249 Clinical Trial.
-
Molecular classification and molecular forecasting of breast cancer: ready for clinical application?J Clin Oncol. 2005 Oct 10;23(29):7350-60. doi: 10.1200/JCO.2005.03.3845. Epub 2005 Sep 6. J Clin Oncol. 2005. PMID: 16145060 Review.
-
Gene expression profiling in breast cancer: towards individualising patient management.Pathology. 2005 Aug;37(4):271-7. doi: 10.1080/00313020500169586. Pathology. 2005. PMID: 16194824 Review.
-
Microarray-based gene expression profiling as a clinical tool for breast cancer management: are we there yet?Int J Surg Pathol. 2009 Aug;17(4):285-302. doi: 10.1177/1066896908328577. Epub 2008 Dec 22. Int J Surg Pathol. 2009. PMID: 19103611 Review.
-
Clinical validation of a customized multiple signature microarray for breast cancer.Clin Cancer Res. 2008 Jan 15;14(2):461-9. doi: 10.1158/1078-0432.CCR-07-0999. Clin Cancer Res. 2008. PMID: 18223220
Cited by
-
Prediction of Overall Survival Among Female Patients With Breast Cancer Using a Prognostic Signature Based on 8 DNA Repair-Related Genes.JAMA Netw Open. 2020 Oct 1;3(10):e2014622. doi: 10.1001/jamanetworkopen.2020.14622. JAMA Netw Open. 2020. PMID: 33017027 Free PMC article.
-
An update on the pathological classification of breast cancer.Histopathology. 2023 Jan;82(1):5-16. doi: 10.1111/his.14786. Histopathology. 2023. PMID: 36482272 Free PMC article. Review.
-
Validation of the Prognostic Stage from the American Joint Committee on Cancer 8th Staging Manual in Luminal B-Like Human Epidermal Growth Factor Receptor 2-Negative Breast Cancer.Cancer Manag Res. 2022 Feb 21;14:719-728. doi: 10.2147/CMAR.S342918. eCollection 2022. Cancer Manag Res. 2022. PMID: 35221724 Free PMC article.
-
Fewer Reoperations After Lumpectomy for Breast Cancer with Neoadjuvant Rather than Adjuvant Chemotherapy: A Report from the National Cancer Database.Ann Surg Oncol. 2017 Jun;24(6):1507-1515. doi: 10.1245/s10434-016-5760-8. Epub 2017 Jan 6. Ann Surg Oncol. 2017. PMID: 28062931 Free PMC article.
-
Phosphorylation of estrogen receptor beta at serine 105 is associated with good prognosis in breast cancer.Am J Pathol. 2010 Sep;177(3):1079-86. doi: 10.2353/ajpath.2010.090886. Epub 2010 Aug 9. Am J Pathol. 2010. PMID: 20696772 Free PMC article.
Publication types
MeSH terms
Substances
LinkOut - more resources
Full Text Sources
Medical
Research Materials
Miscellaneous