NKG2D ligand tumor expression and association with clinical outcome in early breast cancer patients: an observational study

Our study population (n = 677) consisted of all breast cancer patients primarily treated with surgery in our center between 1985 and 1994. Formalin-fixed paraffin-embedded tumor tissue was immunohistochemically stained with antibodies directed against MIC-A/MIC-B (MIC-AB), ULBP-1, ULBP-2, ULBP-3, ULBP-4, and ULBP-5.NKG2DL were frequently expressed by tumors (MIC-AB, 50% of the cases; ULBP-1, 90%; ULBP-2, 99%; ULBP-3, 100%; ULBP-4, 26%; ULBP-5, 90%) and often showed co-expression: MIC-AB and ULBP-4 (p = 0.043), ULBP-1 and ULBP-5 (p = 0.006), ULBP-4 and ULBP-5 (p < 0.001). MIC-AB (p = 0.001) and ULBP-2 (p = 0.006) expression resulted in a statistically significant longer relapse free period (RFP). Combined expression of these ligands showed to be an independent prognostic parameter for RFP (p < 0.001, HR 0.41). Combined expression of all ligands showed no associations with clinical outcome.We demonstrated for the first time that NKG2DL are frequently expressed and often co-expressed in breast cancer. Expression of MIC-AB and ULBP-2 resulted in a statistically significant beneficial outcome concerning RFP with high discriminative power. Combination of all NKG2DL showed no additive or interactive effect of ligands on each other, suggesting that similar and co-operative functioning of all NKG2DL can not be assumed. Our observations suggest that among driving forces in breast cancer outcome are immune activation on one site and tumor immune escape on the other site.Breast cancer is the most commonly diagnosed female cancer and is the leading cause of death from cancer in women in the western world [1]. Decisions regarding use of systemic therapy are mainly based on prognostic and predictive factors like lymph node status, tumor size, grade, hormone receptor and human epidermal growth factor receptor 2 (HER2) expression [2,3]. However, current prognostic and predictive factors still do not provide optimal risk-stratification. Therefore, additional prognostic and predictive