Molecular subtyping of breast cancer improves identification of both high and low risk patients
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Molecular subtyping of breast cancer improves identification of both high and low risk patients. / Rossing, Maria; Østrup, Olga; Majewski, Wiktor W.; Kinalis, Savvas; Jensen, Maj Britt; Knoop, Ann; Kroman, Niels; Talman, Maj Lis; Hansen, Thomas V.O.; Ejlertsen, Bent; Nielsen, Finn C.
I: Acta Oncologica, Bind 57, Nr. 1, 2018, s. 58-66.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
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TY - JOUR
T1 - Molecular subtyping of breast cancer improves identification of both high and low risk patients
AU - Rossing, Maria
AU - Østrup, Olga
AU - Majewski, Wiktor W.
AU - Kinalis, Savvas
AU - Jensen, Maj Britt
AU - Knoop, Ann
AU - Kroman, Niels
AU - Talman, Maj Lis
AU - Hansen, Thomas V.O.
AU - Ejlertsen, Bent
AU - Nielsen, Finn C.
PY - 2018
Y1 - 2018
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85034623647&partnerID=8YFLogxK
U2 - 10.1080/0284186X.2017.1398416
DO - 10.1080/0284186X.2017.1398416
M3 - Journal article
C2 - 29164972
AN - SCOPUS:85034623647
VL - 57
SP - 58
EP - 66
JO - Acta Oncologica
JF - Acta Oncologica
SN - 1100-1704
IS - 1
ER -
ID: 188721150