Ceren Boyaci

Supplementary Figure S2: Probability for pathologic complete response in the four groups of the combined classification according to SUVmax at cycle 2 (median value 2.6 as cut-off) and baseline TIL (median value 10% as cut-off)

Supplementary Table S1. Representativeness of Study Participants

Supplementary Table S3. Hazard ratios for relapse-free survival estimated using univariate and multivariable proportional hazards regression. SUVmax at cycle 2 (C2) is included as continuous variable in the regression models.

Supplementary Figure S1: Bland-Altman plot depicting correlation between tumor infiltrating lymphocytes assessed manually and using digital image analysis

Supplementary Figure S3: Probability for pathologic complete response in the four groups of the combined classification according to SUVmax at cycle 2 (median value 2.6 as cut-off) and baseline DTIL (median value 8.7% as cut-off)

Supplementary Table S2. Distribution of clinical and pathologic characteristics according to baseline tumor infiltrating lymphocytes (median value as cut-off)

Purpose:PREDIX HER2 is a randomized Phase II trial that compared neoadjuvant docetaxel, trastuzumab, and pertuzumab (THP) with trastuzumab emtansine (T-DM1) for HER2-positive breast cancer. Rates of pathologic complete response (pCR) did not differ between the two groups. Here, we present the survival outcomes from PREDIX HER2 and investigate metabolic response and tumor-infiltrating lymphocytes (TIL) as prognostic factors.Patients and Methods:In total, 202 patients with HER2-positive breast cancer were enrolled and 197 patients received six cycles of either THP or T-DM1. Secondary endpoints included event-free survival (EFS), recurrence-free survival (RFS), and overall survival (OS). Assessment with PET/CT was performed at baseline, after two and six treatment cycles. TILs were assessed manually at baseline biopsies, while image-based evaluation of TILs [digital TILs (DTIL)] was performed in digitized full-face sections.Results:After a median follow-up of 5.21 years, there was no difference between the two treatment groups in terms of EFS [HR = 1.26; 95% confidence interval (CI), 0.54–2.91], RFS (HR = 0.69; 95% CI, 0.24–1.93), or OS (HR = 0.52; 95% CI, 0.09–2.82). Higher SUVmax at cycle 2 (C2) predicted lower pCR (ORadj = 0.65; 95% CI, 0.48–0.87; P = 0.005) and worse EFS (HRadj = 1.27; 95% CI, 1.12–1.41; P < 0.001). Baseline TILs and DTILs provided additional prognostic information to clinical parameters and C2 SUVmax.Conclusions:Long-term outcomes following neoadjuvant T-DM1 were similar to neoadjuvant THP. SUVmax after two cycles of neoadjuvant therapy for HER2-positive breast cancer may be an independent predictor of both short- and long-term outcomes. Combined assessment with TILs may facilitate early selection of poor responders for alternative treatment strategies.

Breast cancer (BC) represents a heterogeneous ecosystem and elucidation of tumor microenvironment components remains essential. Our study aimed to depict the composition and prognostic correlates of immune infiltrate in early BC, at a multiplex and spatial resolution. Pretreatment tumor biopsies from patients enrolled in the EORTC 10994/BIG 1-00 randomized phase III neoadjuvant trial (NCT00017095) were used; the CNN11 classifier for H&E-based digital TILs (dTILs) quantification and multiplex immunofluorescence were applied, coupled with machine learning (ML)-based spatial features. dTILs were higher in the triple-negative (TN) subtype, and associated with pathological complete response (pCR) in the whole cohort. Total CD4+ and intra-tumoral CD8+ T-cells expression was associated with pCR. Higher immune-tumor cell colocalization was observed in TN tumors of patients achieving pCR. Immune cell subsets were enriched in TP53-mutated tumors. Our results indicate the feasibility of ML-based algorithms for immune infiltrate characterization and the prognostic implications of its abundance and tumor-host interactions.