Maria Rossing1, Olga Østrup1, Wiktor W Majewski1, Savvas Kinalis1, Maj-Britt Jensen2, Ann Knoop3, Niels Kroman4, Maj-Lis Talman5, Thomas V O Hansen1, Bent Ejlertsen2,3, Finn C Nielsen1. 1. a Center for Genomic Medicine , Rigshospitalet, Copenhagen University Hospital , Copenhagen , Denmark. 2. b Danish Breast Cancer Cooperative Group , Rigshospitalet, Copenhagen University Hospital , Copenhagen , Denmark. 3. c Department of Clinical Oncology , Copenhagen University Hospital , Copenhagen , Denmark. 4. d Department of Breast Surgery , Rigshospitalet, Copenhagen University Hospital , Copenhagen , Denmark. 5. e Department of Pathology , Copenhagen University Hospital, Rigshospitalet, Copenhagen University Hospital , Copenhagen , Denmark.
Abstract
BACKGROUND: Transcriptome analysis enables classification of breast tumors into molecular subtypes that correlate with prognosis and effect of therapy. We evaluated the clinical benefits of molecular subtyping compared to our current diagnostic practice. MATERIALS AND METHODS: Molecular subtyping was performed on a consecutive and unselected series of 524 tumors from women with primary breast cancer (n = 508). Tumors were classified by the 256 gene expression signature (CIT) and compared to conventional immunohistochemistry (IHC) procedures. RESULTS: More than 99% of tumors were eligible for molecular classification and final reports were available prior to the multidisciplinary conference. Using a prognostic standard mortality rate index (PSMRi) developed by the Danish Breast Cancer Group (DBCG) 39 patients were assigned with an intermediate risk and among these 16 (41%) were furthermore diagnosed by the multi-gene signature assigned with a luminal A tumor and consequently spared adjuvant chemotherapy. There was overall agreement between mRNA derived and IHC hormone receptor status, whereas IHC Ki67 protein proliferative index proved inaccurate, compared to the mRNA derived index. Forty-one patients with basal-like (basL) subtypes were screened for predisposing mutations regardless of clinical predisposition. Of those 17% carried pathogenic mutations. CONCLUSION: Transcriptome based subtyping of breast tumors evidently reduces the need for adjuvant chemotherapy and improves identification of women with predisposing mutations. The results imply that transcriptome profiling should become an integrated part of current breast cancer management.
BACKGROUND: Transcriptome analysis enables classification of breast tumors into molecular subtypes that correlate with prognosis and effect of therapy. We evaluated the clinical benefits of molecular subtyping compared to our current diagnostic practice. MATERIALS AND METHODS: Molecular subtyping was performed on a consecutive and unselected series of 524 tumors from women with primary breast cancer (n = 508). Tumors were classified by the 256 gene expression signature (CIT) and compared to conventional immunohistochemistry (IHC) procedures. RESULTS: More than 99% of tumors were eligible for molecular classification and final reports were available prior to the multidisciplinary conference. Using a prognostic standard mortality rate index (PSMRi) developed by the Danish Breast Cancer Group (DBCG) 39 patients were assigned with an intermediate risk and among these 16 (41%) were furthermore diagnosed by the multi-gene signature assigned with a luminal A tumor and consequently spared adjuvant chemotherapy. There was overall agreement between mRNA derived and IHC hormone receptor status, whereas IHC Ki67 protein proliferative index proved inaccurate, compared to the mRNA derived index. Forty-one patients with basal-like (basL) subtypes were screened for predisposing mutations regardless of clinical predisposition. Of those 17% carried pathogenic mutations. CONCLUSION: Transcriptome based subtyping of breast tumors evidently reduces the need for adjuvant chemotherapy and improves identification of women with predisposing mutations. The results imply that transcriptome profiling should become an integrated part of current breast cancer management.
Authors: Dorte S Nørøxe; Christina W Yde; Olga Østrup; Signe R Michaelsen; Ane Y Schmidt; Savvas Kinalis; Mathias H Torp; Jane Skjøth-Rasmussen; Jannick Brennum; Petra Hamerlik; Hans S Poulsen; Finn C Nielsen; Ulrik Lassen Journal: Mol Oncol Date: 2020-09-18 Impact factor: 7.449