A score based in toll-like receptors expression to predict prognostic in molecular subtypes of breast cancer treated with neoadjuvant chemotherapy (NAC).

Abstract

e22165 Background: To evaluate toll-like receptors (TLRs1-9) and IRAK 1,3 and 4 expression in a breast cancer patients dataset that were treated with NAC as prognostic factors in terms of recurrence-free survival (RFS). Methods: Weretrieved normalized gene expression data from a public database (GEO: GSE25066) that includes 253 samples of breast cancer patients treated with NAC (antracyclines/taxanes) profiled with the U133A microarray. The median of RFS was 3.2 years (52 relapses observed). Distribution of molecular subtypes was: Luminal A (31.2%), Luminal B (17.4%), HER2 (7.1%), Basal (36.4%) and Normal (7.9%). We build a ratio of target gene/reference gen (ATCB) with to obtain replicable cut-points in other datasets. Levels of Gene expression were divided in three cut-points (Q1, Q2, and Q3). A cox-model was used to select gene expression cut-points with significant effects in the RFS. Results: According to molecular subtypes, there were significant differences in expression of TLR5 (higher in basal and Luminal A), TLR6 and IRAK1 (higher in basal and HER2). There were not differences of expression according to the pathologic response. The multivariate analysis shown that genes associated with the RFS were: TLR5 (HR=2.1 for the lower quartile), TLR6 (HR=2.4 for upper Q2), IRAK1 (HR=2.0 for upper quartile) and IRAK 3 (HR=2.2 for upper Q2). A TLR-Score was constructed (1 point added for each unfavorable gene-group). Cases were grouped in two categories (score 0-1 as good prognostic and score ≥ 2 as poor prognostic). There were and overall significant differences in both score-groups (poor prognostic: HR=4.9). In Basal and luminal B tumors there were significant differences (logrank test: P<0.001 and P=0.014, respectively), in HER2 tumors there were differences although not significant (P=0.143). There were not differences in Luminal A tumors. Conclusions: These data support the exploration of a TLR expression-based score to predict for RFS in breast cancer treated with NAC.