Neutrophil–lymphocyte ratio reflects tumour-infiltrating lymphocytes and tumour-associated macrophages and independently predicts poor outcome in breast cancers with neoadjuvant chemotherapy

Abstract

Aims: The neutrophil–lymphocyte ratio (NLR) is a systemic reflection of cancer-associated inflammation and a prognostic marker for breast cancer. For the local tumour microenvironment, tumour-infiltrating lymphocytes (TILs) and tumour-associated macrophages (TAMs) are also highly correlated with breast cancer survival. This study aimed to explore the relationship between the circulating and local immune microenvironment, and to further delineate the prognostic role of NLR in breast cancer patients receiving neoadjuvant chemotherapy (NAC). Methods: A cohort of breast cancer patients receiving NAC with subsequent surgery was retrieved. Clinical data were reviewed. Histological slides and CD8 immunohistochemistry from biopsy (pre-chemotherapy) and excision (postchemotherapy) specimens were assessed for TILs and TAMs. Results: A total of 146 patients were included. There was a significant positive correlation between pre- and postsurgery NLR at a cut-off of 2.6 (median pre-chemotherapy NLR) (P < 0.001). NLR pre-chemotherapy was associated positively with necrosis on biopsy (P = 0.027) and excision (P = 0.021) and TAMs on excision (P = 0.049). NLR 1 year postsurgery was associated with high tumour stage (P = 0.050) and low histological grade (P = 0.008). TIL count was lower in NLR-high cases at almost all time-points by histological assessment and CD8 immunostaining (P < 0.050). In multivariate analysis, postsurgery NLR is an independent predictor for overall survival [OS; hazard ratio (HR) = 9.524, P < 0.001], breast cancer-specific survival (BCSS) (HR = 10.059, P = 0.001) and disease-free survival (DFS; HR = 2.824, P = 0.016). Conclusions: The association between NLR with tumour necrosis, TAMs and TILs illustrates an interaction between the circulating and local immune microenvironment. Late NLR is a strong indicator of outcome and may be useful for prognostication and disease monitoring.