Immune cell composition and functional marker dynamics from multiplexed immunohistochemistry to predict response to neoadjuvant chemotherapy in the WSG-ADAPT-TN trial

Abstract

BackgroundThe association of early changes in the immune infiltrate during neoadjuvant chemotherapy (NACT) with pathological complete response (pCR) in triple-negative breast cancer (TNBC) remains unexplored.MethodsMultiplexed immunohistochemistry was performed in matched tumor biopsies obtained at baseline and after 3 weeks of NACT from 66 patients from the West German Study Group Adjuvant Dynamic Marker-Adjusted Personalized Therapy Trial Optimizing Risk Assessment and Therapy Response Prediction in Early Breast Cancer - Triple Negative Breast Cancer (WSG-ADAPT-TN) trial. Association between CD4, CD8, CD73, T cells, PD1-positive CD4 and CD8 cells, and PDL1 levels in stroma and/or tumor at baseline, week 3 and 3-week change with pCR was evaluated with univariable logistic regression.ResultsCompared with no change in immune cell composition and functional markers, transition from ‘cold’ to ‘hot’ (below-median and above-median marker level at baseline, respectively) suggested higher pCR rates for PD1-positive CD4 (tumor: OR=1.55, 95% CI 0.45 to 5.42; stroma: OR=2.65, 95% CI 0.65 to 10.71) and PD1-positive CD8 infiltrates (tumor: OR=1.77, 95% CI 0.60 to 5.20; stroma: OR=1.25, 95% CI 0.41 to 3.84; tumor+stroma: OR=1.62, 95% CI 0.51 to 5.12). No pCR was observed after ‘hot-to-cold’ transition in PD1-positive CD8 cells. pCR rates appeared lower after hot-to-cold transitions in T cells (tumor: OR=0.26, 95% CI 0.03 to 2.34; stroma: OR=0.35, 95% CI 0.04 to 3.25; tumor+stroma: OR=0.00, 95% CI 0.00 to 1.04) and PD1-positive CD4 cells (tumor: OR=0.60, 95% CI 0.11 to 3.35; stroma: OR=0.22, 95% CI 0.03 to 1.92; tumor+stroma: OR=0.32, 95% CI 0.04 to 2.94). Higher pCR rates collated with ‘altered’ distribution (levels below-median and above-median in tumor and stroma, respectively) of T cell (OR=3.50, 95% CI 0.84 to 14.56) and PD1-positive CD4 cells (OR=4.50, 95% CI 1.01 to 20.14).ConclusionOur exploratory findings indicate that comprehensive analysis of early immune infiltrate dynamics complements currently investigated predictive markers for pCR and may have a potential to improve guidance for individualized de-escalation/escalation strategies in TNBC.

Gene signatures in patients with early breast cancer and relapse despite pathologic complete response

“…5h ) in recurrent tumors. A number of recent studies postulate that such alterations in the tumor immune microenvironment are in response to NST and are likely to have predictive value in treatment outcomes 43 – 45 . Secondly, our findings suggest that the immunologically quiescent primary tumors which are at risk of post-pCR relapse could benefit from the early use of immune-oncologic agents either alone or in combination with NST.…”

Dissecting Tumor-Immune Microenvironment in Breast Cancer at a Spatial and Multiplex Resolution

“…Treatment with either chemotherapy or HER2 targeted therapies lead to increase of markers associated with cellular immunity, except for a study [75], which demonstrated that chemotherapy globally downregulated the expression of immune markers. Compared with baseline, increased infiltration of CD8+ [60,77], FOXP3+ [60], CD8+PD1+ [61] and PD-L1+ [61] was noted, while CD3+KI67+ [60] cells decreased. Interestingly, intra-tumoral spatial distribution of T cells also changed, with CD3+ and CD8+ T cells being recruited closer to cancer cells, either in tumoral [60,61,77] or proximal stromal compartments [60].…”

“…Compared with baseline, increased infiltration of CD8+ [60,77], FOXP3+ [60], CD8+PD1+ [61] and PD-L1+ [61] was noted, while CD3+KI67+ [60] cells decreased. Interestingly, intra-tumoral spatial distribution of T cells also changed, with CD3+ and CD8+ T cells being recruited closer to cancer cells, either in tumoral [60,61,77] or proximal stromal compartments [60]. In summary, these studies demonstrate that multiplex methods can be used to evaluate the dynamic changes of TIME, under the pressure of neoadjuvant therapy.…”

“…At first, lineage specific markers can be used such as T cell (CD3+, CD4+, or CD8+), B-cell (CD20+), NK-cell (CD56+), myeloid (MPO+, CD11c+), endothelial (CD31+) or fibroblastic (FAP+, SMA+, vimentin+), among others. Intriguingly, despite the fact that T cells comprise the most abundant immune population in BC TIME, TILs rates by mIHC/IF seem to modestly to strongly correlate with H&E TILs findings, in part due to panel selection and the scoring algorithm [60][61][62][63][64][65]. Furthermore, combinations of different markers have been used as surrogates for function, and include proliferative cells (CD3+Ki67+ [60], CD20+ki67+ [66]), tissue resident memory effector T cells (CD8+CD103+) [67], cytotoxic T cells (GZMB+CD8+) [66], regulatory T cells (CD4+FoxP3+) [68] and follicular helper T cells (CD4+CXCL13+CXCR5-) [66].…”

“…A dynamic, longitudinal evaluation of inflammatory changes within BC TIME is of utmost importance to better understand anti-tumor immune response. Some studies have used mIF/IHC and DSP to longitudinally evaluate immune response under the pressure of neoadjuvant therapy [60,61,75,77]. Treatment with either chemotherapy or HER2 targeted therapies lead to increase of markers associated with cellular immunity, except for a study [75], which demonstrated that chemotherapy globally downregulated the expression of immune markers.…”