Pathological Response in a Triple-Negative Breast Cancer Cohort Treated with Neoadjuvant Carboplatin and Docetaxel According to Lehmann's Refined Classification
Por:
Echavarria, I, Lopez-Tarruella, S, Picornell, A, Garcia-Saenz, JA, Jerez, Y, Hoadley, K, Gomez, HL, Moreno, F, Del Monte-Millan, M, Marquez-Rodas, I, Alvarez, E, Ramos-Medina, R, Gayarre, J, Massarrah, T, Ocana, I, Cebollero, M, Fuentes, H, Barnadas, A, Ballesteros, AI, Bohn, U, Perou, CM, Martin, M
Publicada:
15 abr 2018
Resumen:
Purpose: Triple-negative breast cancer (TNBC) requires the identification of reliable predictors of response to neoadjuvant chemotherapy (NACT). For this purpose, we aimed to evaluate the performance of the TNBCtype-4 classifier in a cohort of patients with TNBC treated with neoadjuvant carboplatin and docetaxel (TCb).
Methods: Patients with TNBC were accrued in a nonrandomized trial of neoadjuvant carboplatin AUC 6 and docetaxel 75 mg/m(2) for six cycles. Response was evaluated in terms of pathologic complete response (pCR, ypT0/is ypN0) and residual cancer burden by Symmans and colleagues. Lehmann's subtyping was performed using the TNBC type online tool from RNAseq data, and germline sequencing of a panel of seven DNA damage repair genes was conducted.
Results: Ninety-four out of the 121 patients enrolled in the trial had RNAseq available. The overall pCR rate was 44.7%. Lehmann subtype distribution was 34.0% BL1, 20.2% BL2, 23.4% M, 14.9% LAR, and 7.4% were classified as ER+. Response to NACT with TCb was significantly associated with Lehmann subtype (P = 0.027), even in multivariate analysis including tumor size and nodal involvement, with BL1 patients achieving the highest pCR rate (65.6%), followed by BL2 (47.4%), M (36.4%), and LAR (21.4%). BL1 was associated with a significant younger age at diagnosis and higher ki67 values. Among our 10 germline mutation carriers, 30% were BL1, 40% were BL2, and 30% were M.
Conclusions: TNBCtype-4 is associated with significantly different pCR rates for the different subtypes, with BL1 and LAR displaying the best and worse responses to NACT, respectively. (C) 2018 AACR.
Filiaciones:
Echavarria, I:
CiberOnc, IiSGM, Madrid, Spain
Lopez-Tarruella, S:
CiberOnc, IiSGM, Madrid, Spain
Picornell, A:
CiberOnc, IiSGM, Madrid, Spain
Garcia-Saenz, JA:
Hosp Univ Clin San Carlos, Madrid, Spain
Jerez, Y:
CiberOnc, IiSGM, Madrid, Spain
Hoadley, K:
Univ N Carolina, Dept Genet, Chapel Hill, NC USA
Gomez, HL:
INEN, Med Oncol, Lima, Peru
Moreno, F:
Hosp Univ Clin San Carlos, Madrid, Spain
Del Monte-Millan, M:
CiberOnc, IiSGM, Madrid, Spain
Marquez-Rodas, I:
CiberOnc, IiSGM, Madrid, Spain
Alvarez, E:
CiberOnc, IiSGM, Madrid, Spain
Ramos-Medina, R:
CiberOnc, IiSGM, Madrid, Spain
Gayarre, J:
CiberOnc, IiSGM, Madrid, Spain
Massarrah, T:
CiberOnc, IiSGM, Madrid, Spain
Ocana, I:
CiberOnc, IiSGM, Madrid, Spain
Cebollero, M:
Hosp Gen Univ Gregorio Maranon, Dept Pathol, Madrid, Spain
Fuentes, H:
INEN, Med Oncol, Lima, Peru
Barnadas, A:
Hosp Santa Creu & Sant Pau, Dept Med Oncol, Barcelona, Spain
Ballesteros, AI:
Hosp Univ La Princesa, Med Oncol, Madrid, Spain
Bohn, U:
Hosp Gran Canaria Dr Negrin, Med Oncol, Las Palmas Gran Canaria, Spain
Perou, CM:
Univ N Carolina, Lineberger Comprehens Canc Ctr, Chapel Hill, NC USA
Martin, M:
Univ Complutense, GEICAM, CiberOnc, IiSGM, Madrid, Spain
Green Accepted, Bronze
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