Karger Publishers, Breast Care, 1(13), p. 8-14, 2018
DOI: 10.1159/000486949
Abstracts of the 10th Scientific Symposium of the Comission for Translational Research of the Working group for Gynecologic Oncology AGO e.V., 2018
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<b><i>Background:</i></b> Despite advancements in the treatment of primary and metastatic breast cancer, many patients lack a durable response to these treatments. Patients with triple-negative breast cancer (TNBC) and human epidermal growth factor receptor 2(HER2)-positive breast cancer who do not have a pathological complete response (pCR) after neoadjuvant chemotherapy (NACT) have a very poor prognosis. Tumor-infiltrating lymphocytes (TILs) have been identified as a predictive marker for pCR after NACT in TNBC and HER2-positive breast cancer. These patient populations could also be suitable for novel treatment strategies including neoepitope-based therapies. This work analyses the effect of TILs on the pCR in neoadjuvantly treated patients in the TILGen study and presents the procedures aimed at establishing neoepitope-based therapies in this study. <b><i>Methods:</i></b> Neoadjuvantly treated HER2-positive and TNBC patients were eligible for the presented analysis concerning the association between TILs and pCR. A total of 146 patients could be identified within the TILGen study. TILs were evaluated as percentage of stromal tumor tissue in core biopsies at primary diagnosis. The phenotype ‘lymphocyte-predominant breast cancer' (LPBC) was associated with pCR by logistic regression adjusted for estrogen receptor status, progesterone receptor status, HER2 status, age at diagnosis, and grading. <b><i>Results:</i></b> LPBC was seen in 24 (16.4%) patients. In this patient group, 66.7% achieved a pCR, while the pCR rate was 32.8% in patients with a low TIL count. The adjusted odds ratio was 6.60 (95% confidence interval 2.02-21.56; p < 0.01). <b><i>Conclusion:</i></b> TILs are a strong predictor of pCR in TNBC and HER2-positive breast cancer patients. Implications for the use of this information including the effect on prognosis might help to identify patients most likely to benefit from a neoepitope-based therapy approach.