title: The value of tumor infiltrating lymphocytes (TILs) for predicting response to neoadjuvant chemotherapy in breast cancer: a systematic review and meta-analysis.
abstract: BACKGROUND
  We carried out a systematic review and meta-analysis to evaluate the predictive roles of tumor infiltrating lymphocytes (TILs) in response to neoadjuvant chemotherapy (NAC) in breast cancer.
  
  
  METHODS
  A PubMed and Web of Science literature search was designed. Random or fixed effect models were adopted to estimate the summary odds ratio (OR). Heterogeneity and sensitivity analyses were performed to explore heterogeneity among studies and to assess the effects of study quality. Publication bias was evaluated using a funnel plot, Egger's test and Begg's test. We included studies where the predictive significance of TILs, and/or TILs subset on the pathologic complete response (pCR) were determined in NAC of breast cancer.
  
  
  RESULTS
  A total of 13 published studies (including 3251 patients) were eligible. In pooled analysis, the detection of higher TILs numbers in pre-treatment biopsy was correlated with better pCR to NAC (OR = 3.93, 95% CI, 3.26-4.73). Moreover, TILs predicted higher pCR rates in triple negative (OR = 2.49, 95% CI: 1.61-3.83), HER2 positive (OR = 5.05, 95% CI: 2.86-8.92) breast cancer, but not in estrogen receptor (ER) positive (OR = 6.21, 95%CI: 0.86-45.15) patients. In multivariate analysis, TILs were still an independent marker for high pCR rate (OR = 1.41, 95% CI: 1.19-1.66). For TILs subset, higher levels of CD8+ and FOXP3+ T-lymphocytes in pre-treatment biopsy respectively predicted better pathological response to NAC (OR = 6.44, 95% CI: 2.52-16.46; OR = 2.94, 95% CI: 1.05-8.26). Only FOXP3+ lymphocytes in post-NAC breast tissue were a predictive marker for low pCR rate in univariate (OR = 0.41, 95% CI: 0.21-0.80) and multivariate (OR = 0.36, 95% CI: 0.13-0.95) analysis.
  
  
  CONCLUSIONS
  Higher TILs levels in pre-treatment biopsy indicated higher pCR rates for NAC. TILs subset played different roles in predicting response to NAC.
authors.affiliation: Comprehensive Breast Health Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
authors.forename: Yan
authors.initials: Y
authors.lastname: Mao
authors.affiliation: Department of Oncology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
authors.forename: Qing
authors.initials: Q
authors.lastname: Qu
authors.affiliation: Comprehensive Breast Health Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
authors.forename: Yuzi
authors.initials: Y
authors.lastname: Zhang
authors.affiliation: Comprehensive Breast Health Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
authors.forename: Junjun
authors.initials: J
authors.lastname: Liu
authors.affiliation: Comprehensive Breast Health Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
authors.forename: Xiaosong
authors.initials: X
authors.lastname: Chen
authors.affiliation: Comprehensive Breast Health Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
authors.forename: Kunwei
authors.initials: K
authors.lastname: Shen
mesh_terms: D000970:Antineoplastic Agents / Q000627:therapeutic use*; D001943:Breast Neoplasms / Q000188:drug therapy* / Q000276:immunology*; D005260:Female; D006801:Humans; D016246:Lymphocytes, Tumor-Infiltrating / Q000276:immunology*; D015233:Models, Statistical; D020360:Neoadjuvant Therapy / Q000009:adverse effects*; D016017:Odds Ratio; D011237:Predictive Value of Tests; D016896:Treatment Outcome
chemical_list: D000970:Antineoplastic Agents