Longitudinal assessment of tumor-infiltrating lymphocytes in primary breast cancer following neoadjuvant radiotherapy

Background Tumor-infiltrating lymphocytes (TILs) have prognostic significance in several cancers, including breast. Despite interest in combining radiotherapy with immunotherapy, little is known about the effect of radiotherapy itself on the tumor-immune microenvironment, including TILs. Here, we interrogated longitudinal dynamics of tumor-infiltrating and systemic lymphocytes in patient samples taken before, during, and after neoadjuvant radiotherapy (NART), from XXX and XXX breast clinical trials. Methods We manually scored stromal TILs (sTILs) from longitudinal tumor samples using standardized guidelines, as well as deep learning-based scores at cell-level (cTIL) and cell- and tissue-level combination analysis (SuperTIL). In parallel, we interrogated absolute lymphocyte counts from routine blood tests at corresponding timepoints during treatment. Exploratory analyses studied the relationship between TILs and pathological complete response (pCR) and long-term outcomes. Results Patients receiving NART experienced a significant and uniform decrease in sTILs that did not recover at the time of surgery (P < 0.0001). This lymphodepletive effect was also mirrored in peripheral blood. Our “SuperTIL” deep learning score showed good concordance with manual sTILs, and importantly performed comparably to manual scores in predicting pCR from diagnostic biopsies. Analysis suggested an association between baseline sTILs and pCR, as well as sTILs at surgery and relapse, in patients receiving NART. Conclusions This study provides novel insights into TIL dynamics in the context of NART in breast cancer, and demonstrates the potential for artificial intelligence to assist routine pathology. We have identified trends which warrant further interrogation and have a bearing on future radio-immunotherapy trials.