A gene signature to predict high tumor-infiltrating lymphocytes after neoadjuvant chemotherapy and outcome in patients with triple-negative breast cancer
A gene signature to predict high tumor-infiltrating lymphocytes after neoadjuvant chemotherapy and outcome in patients with triple-negative breast cancer
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DOI：
10.1093/annonc/mdx691
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发表时间：
2018-01-01
影响因子：
50.5
通讯作者：
Andre, F.
中科院分区：
文献类型：
--
作者：
Criscitiello, C.;Bayar, M. A.;Andre, F.
Background: In patients with triple-negative breast cancer (TNBC), the extent of tumor-infiltrating lymphocytes (TILs) in the residual disease after neoadjuvant chemotherapy (NACT) is associated with better prognosis. Our objective was to develop a gene signature from pretreatment samples to predict the extent of TILs after NACT and then to test its prognostic value on survival.Patients and methods: Using 99 pretreatment samples, we generated a four-gene signature associated with high post-NACT TILs. Prognostic value of the signature on distant relapse-free survival (DRFS) was first assessed on the training set (n = 99) and then on an independent validation set (n = 115).Results: A four-gene signature combining the expression levels of HLF, CXCL13, SULT1E1, and GBP1 was developed in baseline samples to predict the extent of lymphocytic infiltration after NACT. In a multivariate analysis performed on the training set, this signature was associated with DRFS [hazard ratio (HR): 0.28, for a one-unit increase in the value of the four-gene signature, 95% confidence interval (CI): 0.13-0.63)]. In a multivariate analysis performed on an independent validation set, the four-gene signature was significantly associated with DRFS (HR: 0.17, 95% CI: 0.06-0.43). The four-gene signature added significant prognostic information when compared with the clinicopathologic pretreatment model (likelihood ratio test in the training set P = 0.004 and in the validation set P = 0.002).Conclusions: A four-gene signature predicts high levels of TILs after anthracycline-containing NACT and outcome in patients with TNBC and adds prognostic information to a clinicopathological model at diagnosis.
