Annals of Oncology 23 (Supplement 6): vi13 vi18, 2012 doi:10.1093/annonc/mds188 Understanding the biology of triple-negative breast cancer C. Criscitiello 1 *,, H. A. Azim, Jr 1,, P. C. Schouten 2, S. C. Linn 2, & C. Sotiriou 1, 1 Breast Cancer Translational Research Laboratory J.C. Heuson, Université Libre de Bruxelles, Institut Jules Bordet, Brussels, Belgium; 2 Divisions of Molecular Biology and Medical Oncology, Netherlands Cancer Institute Anotoni van Leeuwenhoek Hospital, Amsterdam, The Netherlands Greater understanding of the biology of triple-negative breast cancer (TNBC) is needed to discern the roughly 60% of node-negative patients who are already cured with locoregional therapy from the 40% who need adjuvant systemic therapy to be cured. Recent evidence suggests that patients with TNBC whose tumours have an activated immune response gene signature have a more favourable outcome than TNBC patients without this signature. For the group who needs additional systemic therapy, the challenge remains to choose the right systemic drug combination for the right TNBC sub-type. Significant heterogeneity exists within the TNBC class that is exemplified by differing chemotherapeutic sensitivity observed for some sub-types. This heterogeneity establishes the need for identifying differentiating molecular markers within the overall class of TNBC disease, which may help refine therapeutic management. In this review, we discuss some of these promising predictive molecular markers for tailoring therapy. In addition, several gene expression profiling and functional studies employing genetic screens that help to establish TNBC sub-groups with varying sensitivities to a variety of targeted therapies currently under clinical investigation are conferred. It is anticipated that a greater understanding of the biology of TNBC and its complex heterogeneity will reveal novel targets or identify markers around which clinical trials in molecularly well-defined sub-groups can be designed. Key words: gene expression, molecular markers, triple-negative breast cancer introduction Breast cancer is a heterogeneous disease encompassing a variety of entities, which are morphologically and clinically distinct. Immunohistochemical methods define the triplenegative breast cancer (TNBC) sub-type as staining negative for oestrogen receptor (ER) and progesterone receptor (PR), and not overexpressing human epidermal growth factor receptor 2 (HER2) [1]. Perou et al. [2] described the identification of five intrinsic sub-types of breast cancer determined by their different gene expression profiles. Despite their morphological and clinical heterogeneity, several of these intrinsic sub-types show a TNBC phenotype [3]. In general, patients with TNBC are at high risk of early relapse compared with other breast cancer sub-types [4]. However, chemotherapy treatment gives rise to a more favourable outcome in a subset of patients with TNBC compared with other breast cancer subtypes [5]. The lack of obvious targets is a major challenge in treating patients with TNBC. Thus, there is a need to elucidate targets specific to TNBC on which to base future therapies. In this *Correspondence to: Dr C. Sotiriou, Breast Cancer Translational Research Laboratory J.C. Heuson, Université Libre de Bruxelles, Institut Jules Bordet, Boulevard de Waterloo, 125 1000 Brussels, Belgium. Tel: +32-2-541-34-57; Fax: +32-2-541-33-39; E-mail: christos.sotiriou@bordet.be Co-first authors. Co-last authors. review, we discuss the biology of TNBC at both the pathological and the molecular level. We also highlight the potential role of gene expression signatures in predicting outcome in this very challenging disease. natural history of TNBC TNBC represents around 15% 20% of newly diagnosed breast cancer cases [1]. It is associated with young age at diagnosis (<40 years), advanced disease, and African American ethnicity [6 9]. Furthermore, TNBC is characterised by an early peak of recurrence between the first and third year after diagnosis followed by a sharp decrease in subsequent years with relapses seldom reported after 8 or 10 years [4]. Unlike other sub-types, TNBC outcome is less clearly related to stage [10]. Metastases tend to be more aggressive than other breast cancer sub-types and more likely to occur in the viscera, particularly in the lungs and brain [11], but less likely to spread to the bones [5]. heterogeneity of TNBC and overlap between TNBC and basal-like breast cancer Although there is a substantial overlap between TNBC tumours and basal-like breast cancer, these breast cancer subtypes are not synonymous [3, 12]. To gain more insight into the heterogeneity of TNBC, researchers from the Netherlands research article The Author 2012. Published by Oxford University Press on behalf of the European Society for Medical Oncology. All rights reserved. For permissions, please email: journals.permissions@oup.com.
Cancer Institute examined the histopathological features and gene expression profiles of 97 TNBCs [13, 14]. They found that all TNBCs were classified as basal-like tumours at the gene expression level; however, hierarchical cluster analysis revealed five distinct sub-groups of TNBC. Turner et al. [15] also found considerable heterogeneity of TNBC tumours resulting from gene expression profiling. Hence, this study suggests that although TNBC and basal-like tumours are frequently considered to be the same, there is significant heterogeneity within these largely overlapping sub-types. Very recently, Lehmann et al. [16] corroborated this concept by analysing gene expression profiles from 21 breast cancer datasets. They identified six different TNBC sub-types displaying unique gene expression patterns including two basal-like (BL1 and BL2), an immunomodulatory, a mesenchymal (M), a mesenchymal stem-like (MSL), and a luminal androgen receptor (LAR) subtype. BL1 and BL2 showed higher expression of cell cycle and DNA damage response genes whereas M and MSL were enriched with epithelial mesenchymal transition genes. The LAR sub-type was characterised by higher expression of genes involved in androgen receptor signalling. Interestingly, the investigators identified breast cancer cell lines representative of each of these molecular sub-types. These showed different sensitivities to various targeted therapies currently under clinical investigation, providing an attractive platform for future drug development in TNBC. From the histological perspective, the majority of TNBCs are unsurprisingly of the invasive duct carcinoma, not otherwise specified (IDC-NOS) histology [17 19]. However, a significant proportion (40% 100%) of other relatively rare histotypes (medullary and metaplastic carcinomas [20 22], adenoid cystic carcinoma, and apocrine carcinoma [23, 24]) also shows negative expression for ER, PR, and HER2. Interestingly, the prognosis of each appears to be distinct despite sharing the triple-negative phenotype. Table 1 summarises the proportion, molecular characteristics, and prognosis of TNBC according to the different histologic sub-types. Annals of Oncology Both TNBC and basal-like breast cancer show considerable overlap with BRCA1-mutated tumours [3]. BRCA1 is an important tumour suppressor gene that plays a vital role in DNA repair [25]. BRCA1 deficiency [as assessed by mutation, methylation, and BRCA1-like comparative genomic hybridisation (CGH) profile analysis] is observed in 50% of patients with TNBC (Figure 1). Apart from the basal-like sub-type, other relatively rare molecular entities have been claimed to exhibit the triplenegative phenotype. These include the recently described claudin-low molecular sub-type [17], which lacks expression of many of the claudin genes, such as cell cell junction proteins. These tumours are highly immune cell infiltrated and show stem-cell and epithelial mesenchymal transition characteristics [26, 27]. However, its exact nature at the molecular level as well as its clinical relevance requires further validation [28]. It should be also highlighted that molecular markers, such as androgen receptor, EGFR, C-KIT, and interferon/ immunoglobulin-related genes, have been identified in TNBC by differential gene expression [29, 30]. In addition, other groups have also observed low expression of Bcl-2 and PTEN loss [31, 32]. However, the results in this area are too premature to draw solid conclusions at present. Apart from gene expression and pathway deregulations associated with TNBC, copy number alterations have also been observed in a higher proportion than in the other breast cancer sub-types, suggesting gross genomic instability in this group [33 35]. Two specific copy number alterations were described; gene amplification and chromosomal deletion [34, 35]. In one study, amplification of the nuclear factor 1/B was observed and further validated by RT-PCR; however, the exact oncogenic function of this gene is not clear [35]. Hu et al. [34] showed deletion of chromosome 5q13-14 in TNBC, which harbours the RASA1 gene and regulates the RAS oncogene. Moreover, Andre et al. [33] found that TNBC is characterised by high frequency of copy number anomalies of PTEN, EGFR, Table 1. Incidence and prognosis of TNBC according to histology Histology Molecular hallmarks Proportion TNBC (%) Prognosis References IDC-NOS HER1+and/or CK5/6+ 12 17 Reference group: [17 19] 5-year DFS: 60% 65% 10-year DFS: 55% 60% Metaplastic Squamous epithelium differentiation; mesenchymal 90 Adverse in comparison with IDC-NOS [20 22, 30, 46] carcinoma elements; EGFR+, CK5/6+, CK14+, p63+ Medullary carcinoma Lymphoplasmacytic infiltrate; P53 mutation; BRCA1 mutation 95 Favourable in comparison with IDC- NOS [50] Adenoid cystic carcinoma Apocrine carcinoma Low grade; resembles tumours found in salivary glands; c-kit+; fusion gene MYB-NFIB+; MYB overexpression 90 100 Favourable in comparison with IDC- NOS; 10-year OS: >90% Androgen receptor overexpression 40 60 Favourable in comparison with IDC- NOS CK, cytokeratin; DFS, disease-free survival; EGFR, epidermal growth factor receptor; HER, human epidermal growth factor receptor; IDC-NOS, invasive duct carcinoma, not otherwise specified; OS, overall survival; TNBC, triple-negative breast cancer. [24, 51] [23, 52] vi14 Criscitiello et al. Volume 23 Supplement 6 August 2012
Annals of Oncology research article Figure 1. Clinical characteristics of 60 patients with triple-negative breast cancer (TNBC) [45]. Medium grey boxes: negative for the corresponding characteristic; dark grey: positive for the corresponding characteristic; light grey: characteristic unknown. Comparisons: Bloom Richardson (BR) grade I + II versus grade III; BRCA1-like comparative genomic hybridisation (CGH) profile negative versus positive; BRCA1 promotor hypermethylation negative versus positive; BRCA1 mutation (hotspot mutations; explaining approximately two-third of Dutch BRCA1-related cases) negative versus positive. The figure was generated using the ggplot2 package in R version 2.12.1. and vascular endothelial growth factor A (VEGFA), the latter being gained in >30% of TNBCs. prognostic and predictive values of gene expression signatures in TNBC In recent years, gene expression profiles have been used to identify several prognostic and predictive signatures, including MammaPrint w, Oncotype Dx w, MapQuant Dx w, and Theros w [36]. These first-generation gene signatures are mainly informative in determining the risk of relapse in ER-positive/ HER2-negative breast cancer. They show similar prognostic performance with proliferation genes being the main denominator [37]. As basal-like breast cancers are highly proliferative, the vast majority of these tumours are assigned as high risk [38]. Several investigators have tried to improve the prognostic performance of gene expression profiles by interrogating the role of breast cancer microenvironment. Teschendorff et al. [39] were the first to report a signature based on seven immune-related genes, prognostic for a subset of breast cancer tumours (Table 2). Overexpression of these immune response genes was associated with a better prognosis in this high-risk population irrespective of other clinical prognostic parameters [38]. Building on these findings, Teschendorff et al. [40] used mixture discriminant analysis to develop a novel statistical tool capable of accurately identifying breast cancer patients with a good prognosis [average predictive value = 94% (range 85% 100%), average hazard ratio = 0.15 (range 0.07 0.36), P < 0.000001]. The classifier was tested across a total of 469 tumours, representing untreated and partially untreated patient cohorts. Rody et al. [41] demonstrated that up-regulation of the lymphocyte-specific kinase metagene, which includes numerous T-cell-specific genes, was also predictive for a better outcome in patients. Additionally, using a previously published 368-gene expression signature associated with medullary breast cancer, Sabatier et al. [42] found that immune-related genes are able to identify a sub-group of ERnegative patients associated with good prognosis. A metaanalysis performed by Desmedt et al. [38] further confirmed the prognostic power of immune response genes in ERnegative/HER2-negative tumours. On the other hand, several gene-expression studies have shown that immune modules are predictive of pathological complete response to neoadjuvant chemotherapy in ERnegative/HER2-negative breast cancers; particularly anthracycline-based regimens [38, 43, 44]. Hence, these results suggest that immune-related gene expression signatures, unlike the first-generation signatures, have potential in refining prognosis and response to chemotherapy in / HER2-negative patients, with concomitant implications for patients diagnosed with TNBC. Another aspect that deserves further attention is whether outcome in vaccination studies of patients with TNBC would be different between those having a tumour with an activated immune response gene signature versus those who have not. Stratification according to this feature in vaccination trials might shed more light on this issue. future directions A better understanding of the tumourigenesis and tumour progression of TNBC, and the causes of phenotypic Volume 23 Supplement 6 August 2012 doi:10.1093/annonc/mds188 vi15
Annals of Oncology Table 2. Summary of the prognostic value of immune gene signatures in TNBC Study and breast cancer population breast cancer [38] General breast cancer [37] and HER2-positive breast cancer [39] Medullary breast cancer [40] Neoadjuvant TOP [41] Gene cluster name Prognostic value Overexpressed genes Relevant breast cancer subtypes IR+ Best prognosis Immune response genes C1QA, Basal-like IGLC2, LY9, TNFRSF17, SPP1, HER2-positive # XCL2, HLA-F CC+/IR+ Cell cycle and proliferation Basal-like pathways and immune Medullary response genes BRCA1-mutated ECM+ Extracellular matrix genes Basal-like Normal breast-like ERnegative Luminal A SR+ Worst prognosis Steroid response genes Non-TNBC (large majority HER2-positive) CC+ Cell cycle and proliferation pathways Large majority basal-like STAT1 Immune responses module T-cell metagene SVM sub-group 1 (resembling MBC) SVM sub-group 2 (not resembling MBC) Anthracycline-based A score Predicts favourable prognosis of ERnegative tumours and HER2- positive tumours Predicts favourable prognosis of ERnegative tumours Predicts better response to neoadjuvant therapy Less risk of relapse Increased risk of relapse High negative predictive value LCK metagene LCK and IgG metagenes Immune response, apoptosis, metastasis-inhibiting factors; low levels of metastasispromoting factors Cell migration systems TOP2A amplification, tumour invasion, immune response HER2-positive HER2-positive Basal-like HER2-negative ER, estrogen receptor; HER, human epidermal growth factor receptor; LCK, lymphocyte-specific kinase; MBC, medullary breast cancer; SVM, support vector machine; TNBC, triple-negative breast cancer; TOP, trial of principle; IR, immune response; CC, cell cycle; ECM, extracellular matrix; SR, steroid response. heterogeneity, may allow improvement in planning and designing novel, individualised treatments for this disease. An efficient way to move forward in this field is by testing potential hypotheses on tumour material from patients who have participated in randomised controlled trials. This would allow efficient progress in a field that is desperate to identify novel management strategies. A good example for this approach was recently demonstrated by Vollebergh et al. [45], who retrospectively tested a CGH classifier derived from BRCA1-mutated tumours as a predictive tool for patients who had received an adjuvant anthracycline-based regimen with or without one cycle of high-dose, platinum-based chemotherapy in the context of a prospective randomised trial [45]. In this study, it was found that patients with BRCA1-like breast cancers had a better disease-free and overall survivals when treated with the high-dose, platinum-based regimen compared with those treated with conventional chemotherapy. However, no difference was found in patients with non-brca1-like tumours. Another method to find the Achilles heel of a tumour is to perform functional studies, such as genetic screens [46]. Using this approach, Sun et al. [46] identified the PTPN12 tyrosine phosphatase as a tumour suppressor in TNBC, which acts by inhibiting multiple oncogenic pathways including HER2 and EGFR. The tumourigenic and metastatic potential of PTPN12- deficient TNBC cells was found to be severely impaired upon restoration of PTPN12 function or combined inhibition of PTPN12-regulated tyrosine kinases. In the same study, around 60% of TNBCs were found to have negative expression at the protein level compared with only 9% in HER2-amplified tumours, suggesting that PTPN12 could represent a key driver of oncogenesis of TNBC. A second example of this approach was recently reported by Possemato et al. [47], who identified phosphoglycerate dehydrogenase (PHGDH) as a potential cancer target, specifically in and TNBC. PHGDH catalyses the first step in the serine biosynthesis pathway. Breast cancer cells with increased expression of PHGDH have increased serine synthesis flux. Suppression of PHGDH overexpression in these cells results in a strong decrease in cell proliferation and a decrease in serine synthesis [47]. In our opinion, there is a continuous need for further molecular subdivision of the TNBC sub-type. The vi16 Criscitiello et al. Volume 23 Supplement 6 August 2012
Annals of Oncology identification of TNBC-specific molecular markers will allow reinvention of existing drugs and the development of new targeted drugs that can be used against TNBC [48]. Hence, this will enable the clever design of randomised phase III clinical trials in well-defined molecular sub-groups, where fewer patients will be needed, to demonstrate superiority of the targeted approach over the standard treatment [48, 49]. acknowledgements CC is supported by a TRANSBIG Fellowship. HAA Jr is supported by an ESMO Translational Research Fellowship. PCS is supported by a grant from A Sister s Hope. SCL is supported by a grant from the Dutch Cancer Society (NKI 2006-3706). Editorial assistance was provided by ArticulateScience Ltd. funded by Sanofi. The authors retain full control of content. disclosures CS is co-inventor of the Gene Expression Grade Index and the Immune, Stroma, Topo II Signatures. SCL is a named inventor on a provisional patent application for the BRCA-like CGH classifier. references 1. Bauer KR, Brown M, Cress RD et al. Descriptive analysis of estrogen receptor (ER)-negative, progesterone receptor (PR)-negative, and HER2-negative invasive breast cancer, the so-called triple-negative phenotype: a population-based study from the California cancer Registry. Cancer 2007; 109: 1721 1728. 2. Perou CM, Sorlie T, Eisen MB et al. Molecular portraits of human breast tumours. Nature 2000; 406: 747 752. 3. Oakman C, Viale G, Di Leo A. Management of triple negative breast cancer. Breast 2010; 19: 312 321. 4. Blows FM, Driver KE, Schmidt MK et al. Subtyping of breast cancer by immunohistochemistry to investigate a relationship between subtype and short and long term survival: a collaborative analysis of data for 10,159 cases from 12 studies. PLoS Med 2010; 7: e1000279. 5. Liedtke C, Mazouni C, Hess KR et al. Response to neoadjuvant therapy and longterm survival in patients with triple-negative breast cancer. J Clin Oncol 2008; 26: 1275 1281. 6. Carey LA, Perou CM, Livasy CA et al. Race, breast cancer subtypes, and survival in the Carolina Breast Cancer Study. JAMA 2006; 295: 2492 2502. 7. Cancello G, Maisonneuve P, Rotmensz N et al. Prognosis and adjuvant treatment effects in selected breast cancer subtypes of very young women (<35 years) with operable breast cancer. Ann Oncol 2010; 21: 1974 1981. 8. Azim HA, Jr, Michiels S, Bedard PL et al. Elucidating prognosis and biology of breast cancer arising in young women using gene expression profiling. Clin Cancer Res 2012; 18: 1341 1351. 9. Lund MJ, Trivers KF, Porter PL et al. Race and triple negative threats to breast cancer survival: a population-based study in Atlanta, GA. Breast Cancer Res Treat 2009; 113: 357 370. 10. Park YH, Lee SJ, Cho EY et al. Clinical relevance of TNM staging system according to breast cancer subtypes. Ann Oncol 2011; 22: 1554 1560. 11. Heitz F, Harter P, Lueck HJ et al. Triple-negative and HER2-overexpressing breast cancers exhibit an elevated risk and an earlier occurrence of cerebral metastases. Eur J Cancer 2009; 45: 2792 2798. 12. Reis-Filho JS, Tutt AN. Triple negative tumours: a critical review. Histopathology 2008; 52: 108 118. research article 13. Kreike B, van Kouwenhove M, Horlings H et al. Gene expression profiling and histopathological characterization of triple-negative/basal-like breast carcinomas. Breast Cancer Res 2007; 9: R65. 14. Kreike B, Halfwerk H, Kristel P et al. Gene expression profiles of primary breast carcinomas from patients at high risk for local recurrence after breast-conserving therapy. Clin Cancer Res 2006; 12: 5705 5712. 15. Turner N, Lambros MB, Horlings HM et al. Integrative molecular profiling of triple negative breast cancers identifies amplicon drivers and potential therapeutic targets. Oncogene 2010; 29: 2013 2023. 16. Lehmann BD, Bauer JA, Chen X et al. Identification of human triple-negative breast cancer subtypes and preclinical models for selection of targeted therapies. J Clin Invest 2011; 121. 17. Foulkes WD, Smith IE, Reis-Filho JS. Triple-negative breast cancer. N Engl J Med 2010; 363: 1938 1948. 18. Dent R, Hanna WM, Trudeau M et al. Time to disease recurrence in basal-type breast cancers: effects of tumour size and lymph node status. Cancer 2009; 115: 4917 4923. 19. Hernandez-Aya LF, Chavez-Macgregor M, Lei X et al. Nodal status and clinical outcomes in a large cohort of patients with triple-negative breast cancer. J Clin Oncol 2011; 29: 2628 2634. 20. Bae SY, Lee SK, Koo MY et al. The prognoses of metaplastic breast cancer patients compared to those of triple-negative breast cancer patients. Breast Cancer Res Treat 2011; 126: 471 478. 21. Jung SY, Kim HY, Nam BH et al. Worse prognosis of metaplastic breast cancer patients than other patients with triple-negative breast cancer. Breast Cancer Res Treat 2010; 120: 627 637. 22. Reis-Filho JS, Milanezi F, Steele D et al. Metaplastic breast carcinomas are basal-like tumours. Histopathology 2006; 49: 10 21. 23. Honma N, Saji S, Kurabayashi R et al. Oestrogen receptor-beta1 but not oestrogen receptor-betacx is of prognostic value in apocrine carcinoma of the breast. APMIS 2008; 116: 923 930. 24. Constantinidou A, Jones RL, Reis-Filho JS. Beyond triple-negative breast cancer: the need to define new subtypes. Expert Rev Anticancer Ther 2010; 10: 1197 1213. 25. Anders CK, Carey LA. Biology, metastatic patterns, and treatment of patients with triple-negative breast cancer. Clin Breast Cancer 2009; 9(Suppl 2): S73 S81. 26. Creighton CJ, Li X, Landis M et al. Residual breast cancers after conventional therapy display mesenchymal as well as tumour-initiating features. Proc Natl Acad Sci U S A 2009; 106: 13820 13825. 27. Hennessy BT, Gonzalez-Angulo AM, Stemke-Hale K et al. Characterization of a naturally occurring breast cancer subset enriched in epithelial-to-mesenchymal transition and stem cell characteristics. Cancer Res 2009; 69: 4116 4124. 28. Herschkowitz JI, Simin K, Weigman VJ et al. Identification of conserved gene expression features between murine mammary carcinoma models and human breast tumours. Genome Biol 2007; 8: R76. 29. Bertucci F, Finetti P, Cervera N et al. How basal are triple-negative breast cancers? Int J Cancer 2008; 123: 236 240. 30. Nielsen TO, Hsu FD, Jensen K et al. Immunohistochemical and clinical characterization of the basal-like subtype of invasive breast carcinoma. Clin Cancer Res 2004; 10: 5367 5374. 31. Rodriguez-Pinilla SM, Sarrio D, Honrado E et al. Vimentin and laminin expression is associated with basal-like phenotype in both sporadic and BRCA1-associated breast carcinomas. J Clin Pathol 2007; 60: 1006 1012. 32. Saal LH, Gruvberger-Saal SK, Persson C et al. Recurrent gross mutations of the PTEN tumour suppressor gene in breast cancers with deficient DSB repair. Nat Genet 2008; 40: 102 107. 33. Andre F, Job B, Dessen P et al. Molecular characterization of breast cancer with high-resolution oligonucleotide comparative genomic hybridization array. Clin Cancer Res 2009; 15: 441 451. 34. Hu X, Stern HM, Ge L et al. Genetic alterations and oncogenic pathways associated with breast cancer subtypes. Mol Cancer Res 2009; 7: 511 522. 35. Han W, Jung EM, Cho J et al. DNA copy number alterations and expression of relevant genes in triple-negative breast cancer. Genes Chromosomes Cancer 2008; 47: 490 499. Volume 23 Supplement 6 August 2012 doi:10.1093/annonc/mds188 vi17
36. Sotiriou C, Pusztai L. Gene-expression signatures in breast cancer. N Engl J Med 2009; 360: 790 800. 37. Fan C, Oh DS, Wessels L et al. Concordance among gene-expression-based predictors for breast cancer. N Engl J Med 2006; 355: 560 569. 38. Desmedt C, Haibe-Kains B, Wirapati P et al. Biological processes associated with breast cancer clinical outcome depend on the molecular subtypes. Clin Cancer Res 2008; 14: 5158 5165. 39. Teschendorff AE, Miremadi A, Pinder SE et al. An immune response gene expression module identifies a good prognosis subtype in estrogen receptor negative breast cancer. Genome Biol 2007; 8: R157. 40. Teschendorff AE, Caldas C. A robust classifier of high predictive value to identify good prognosis patients in breast cancer. Breast Cancer Res 2008; 10: R73. 41. Rody A, Holtrich U, Pusztai L et al. T-cell metagene predicts a favourable prognosis in estrogen receptor-negative and HER2-positive breast cancers. Breast Cancer Res 2009; 11: R15. 42. Sabatier R, Finetti P, Cervera N et al. A gene expression signature identifies two prognostic subgroups of basal breast cancer. Breast Cancer Res Treat 2011; 126: 407 420. 43. Desmedt C, Di Leo A, de Azambuja E et al. Multifactorial approach to predicting resistance to anthracyclines. J Clin Oncol 2011; 29: 1578 1586. 44. Hess KR, Anderson K, Symmans WF et al. Pharmacogenomic predictor of sensitivity to preoperative chemotherapy with paclitaxel and fluorouracil, doxorubicin, and cyclophosphamide in breast cancer. J Clin Oncol 2006; 24: 4236 4244. Annals of Oncology 45. Vollebergh MA, Lips EH, Nederlof PM et al. An acgh classifier derived from BRCA1-mutated breast cancer and benefit of high-dose platinum-based chemotherapy in HER2-negative breast cancer patients. Ann Oncol 2011; 22: 1561 1570. 46. Sun T, Aceto N, Meerbrey KL et al. Activation of multiple proto-oncogenic tyrosine kinases in breast cancer via loss of the PTPN12 phosphatase. Cell 2011; 144: 703 718. 47. Possemato R, Marks KM, Shaul YD et al. Functional genomics reveal that the serine synthesis pathway is essential in breast cancer. Nature 2011; 476: 346 350. 48. Linn SC, Van t Veer LJ. Clinical relevance of the triple-negative breast cancer concept: genetic basis and clinical utility of the concept. Eur J Cancer 2009; 45 (Suppl 1): 11 26. 49. Dancey JE, Freidlin B. Targeting epidermal growth factor receptor-are we missing the mark? Lancet 2003; 362: 62 64. 50. Bertucci F, Finetti P, Cervera N et al. Gene expression profiling shows medullary breast cancer is a subgroup of basal breast cancers. Cancer Res 2006; 66: 4636 4644. 51. Marchio C, Weigelt B, Reis-Filho JS. Adenoid cystic carcinomas of the breast and salivary glands (or The strange case of Dr Jekyll and Mr Hyde of exocrine gland carcinomas). J Clin Pathol 2010; 63: 220 228. 52. Niemeier LA, Dabbs DJ, Beriwal S et al. Androgen receptor in breast cancer: expression in estrogen receptor-positive tumours and in estrogen receptornegative tumours with apocrine differentiation. Mod Pathol 2010; 23: 205 212. vi18 Criscitiello et al. Volume 23 Supplement 6 August 2012