Molecular stratification of early breast cancer identifies drug targets to drive stratified medicine

• Published in: NPJ breast cancer Vol. 3; no. 1; pp. 3 - 10
• Main Authors: Bayani, Jane, Yao, Cindy Q., Quintayo, Mary Anne, Yan, Fu, Haider, Syed, D’Costa, Alister, Brookes, Cassandra L., van de Velde, Cornelis J. H., Hasenburg, Annette, Kieback, Dirk G., Markopoulos, Christos, Dirix, Luc, Seynaeve, Caroline, Rea, Daniel, Boutros, Paul C., Bartlett, John M. S.
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 15.02.2017; Nature Publishing Group; Nature Portfolio
• Subjects: 631/67/1347; 692/53/2422; Biomedical and Life Sciences; Biomedicine; Breast cancer; Cancer Research; Cancer therapies; Cell Biology; Cell cycle; Chemotherapy; Endocrine therapy; Gene expression; Human Genetics; Oncology
• DOI: 10.1038/s41523-016-0003-5
• ISSN: 2374-4677

Many women with hormone receptor-positive early breast cancer can be managed effectively with endocrine therapies alone. However, additional systemic chemotherapy treatment is necessary for others. The clinical challenges in managing high-risk women are to identify existing and novel druggable targets, and to identify those who would benefit from these therapies. Therefore, we performed mRNA abundance analysis using the Tamoxifen and Exemestane Adjuvant Multinational (TEAM) trial pathology cohort to identify a signature of residual risk following endocrine therapy and pathways that are potentially druggable. A panel of genes compiled from academic and commercial multiparametric tests as well as genes of importance to breast cancer pathogenesis was used to profile 3825 patients. A signature of 95 genes, including nodal status, was validated to stratify endocrine-treated patients into high-risk and low-risk groups based on distant relapse-free survival (DRFS; Hazard Ratio = 5.05, 95% CI 3.53–7.22, p  = 7.51 × 10 −19 ). This risk signature was also found to perform better than current multiparametric tests. When the 95-gene prognostic signature was applied to all patients in the validation cohort, including patients who received adjuvant chemotherapy, the signature remained prognostic (HR = 4.76, 95% CI 3.61-6.28, p  = 2.53× 10 −28 ). Functional gene interaction analyses identified six significant modules representing pathways involved in cell cycle control, mitosis and receptor tyrosine signaling; containing a number of genes with existing targeted therapies for use in breast or other malignancies. Thus the identification of high-risk patients using this prognostic signature has the potential to also prioritize patients for treatment with these targeted therapies. Genetics: Expression signature identifies high-risk patients A gene expression signature identifies breast cancer patients who do poorly after endocrine therapy and might benefit from extra treatment. A team led by John Bartlett and Paul Boutros from the Ontario Institute for Cancer Research in Toronto, Canada, measured the activity levels of 165 genes known to be involved in breast cancer development in tumor samples from 3825 patients with early estrogen receptor-positive disease. The patients received either endocrine therapies (tamoxifen or an aromatase inhibitor) alone or additional chemotherapy as well. The researchers identified a 95-gene expression signature that, when combined with a determination of whether the cancer has spread into the lymph nodes, can help predict which patients are at high risk of disease progression, regardless of whether they received chemotherapy or not. These patients could be prioritized for additional drug therapies.