Background: DAPHNe was a prospective trial designed to assess adherence to de-escalated antibody doublet therapy in the adjuvant setting among HER2+ breast cancer patients experiencing a pathologic complete response (pCR) following neoadjuvant taxol (T), trastuzumab (H) and pertuzumab (P). Peripheral blood mononuclear cells (PBMC), were collected from all patients at baseline and after THP completion. The goal of this study was to determine if a patient’s peripheral blood immune profile at baseline, or the longitudinal change with treatment, could predict response to THP. Methods: Blood samples were subjected to high dimensional (28-30 parameter) flow cytometry with comprehensive T- and NK-cell panels. A fully automated computational analysis strategy was undertaken consisting of unsupervised clustering of the high dimensional data into groups of cells with similar immunophenotypic signatures. Clustering was performed using 2 algorithms: Fingerprint-based clustering (Fluster) and High Throughput Mapper (HiTMapper). Clusters were tested using the Wilcoxon rank-sum test for correlation with the clinical response. Responders were those with pCR (=residual cancer burden [RCB] 0) or RCB 1; non-responders were those with RCB 2/3 disease. P values were adjusted with the Benjamini-Hochberg method to control for FDR. In addition to P values, effect size was evaluated using the nonparametric Cliff’s Delta measure. An effect was determined to be large if the magnitude of Delta was >0.4 which corresponded to one cohort coming ahead 70% of the time. In addition, groups of clusters were evaluated using multivariate statistical modeling or dimensionality reduction to determine if there was an association with pCR. Results: Matched baseline and pre-op PBMC were available to perform the NK panel in 66 patients and the T cell panel in 40. In both groups 70% were responders and 30% were non-responders. No cluster produced by Fluster or HiTMapper differed significantly between responders and non-responders however, in the T cell panel, several clusters had a large effect size (table) suggesting the clusters are good at differentiating some, responders from non-responders. Both algorithms agreed that the median responder has more CD4 naïve and CD8 naïve cells than the median non-responder. While no individual cluster differed significantly between responders and non-responders, cross-validated logistic regression analyses showed that 2 clusters, activated CD4 central memory clusters, and activated CD4 naïve clusters, predicted responder status with AUC of 0.70 and 0.68 respectively. Numerous clusters showed robust and significant longitudinal changes between baseline and pre-op samples. Stratifying longitudinal changes by response status revealed no significant differences between responders and non-responders, however evaluation of effect size suggested a naïve CD4 cluster that increased in non-responders and decreased in responders. The latter could be explained as naïve T cells acquiring a memory phenotype in response to treatment in responders. Conclusion: High dimensional flow cytometry suggested a potential role for monitoring several T cell subsets to predict response in HER2+ patients receiving THP. Additional analyses to include cyTOF evaluation of PBMCs are ongoing to further characterize the peripheral immune profile of these HER2+ patients.

T cell clusters with high effect size
Major PhenotypeOther markersMethodp-valueeffect size
CD4 CM.act CD38, CD226 HiTMapper 0.351 -0.469 
CD4 Naive.act.2 CD38, CD226 HiTMAPPER 0.4 -0.413 
CD4 Naive.act.4 CD226 HiTMapper 0.351 -0.490 
CD4 Naive.act.5 CD38 HiTMapper 0.351 -0.524 
CD8 Naive 1 CD226 HiTMapper 0.396 -0.427 
CD3 Neg Fluster 0.319 0.476 
CD3 Neg3 CD45RA, CD185, CD197 Fluster 0.319 0.476 
CD3 Neg4 CD45RA, Eomes,tBET Fluster 0.424 0.413 
CD4 Naive Fluster 0.319 -0.517 
CD8 Naive1 Fluster 0.319 -0.469 
Unassigned 20 (CD4) CD45RA, CD27-, CD28- Fluster 0.364 -0.441 
T cell clusters with high effect size
Major PhenotypeOther markersMethodp-valueeffect size
CD4 CM.act CD38, CD226 HiTMapper 0.351 -0.469 
CD4 Naive.act.2 CD38, CD226 HiTMAPPER 0.4 -0.413 
CD4 Naive.act.4 CD226 HiTMapper 0.351 -0.490 
CD4 Naive.act.5 CD38 HiTMapper 0.351 -0.524 
CD8 Naive 1 CD226 HiTMapper 0.396 -0.427 
CD3 Neg Fluster 0.319 0.476 
CD3 Neg3 CD45RA, CD185, CD197 Fluster 0.319 0.476 
CD3 Neg4 CD45RA, Eomes,tBET Fluster 0.424 0.413 
CD4 Naive Fluster 0.319 -0.517 
CD8 Naive1 Fluster 0.319 -0.469 
Unassigned 20 (CD4) CD45RA, CD27-, CD28- Fluster 0.364 -0.441 

Citation Format: Esther R Ogayo, Adrienne Waks, Wade Rogers, Matei Ionita, Kenechukwu Adigwe, Jillian Alberti, Sapana Kadel, Jonni Moore, Tari King, Ian Krop, Sara Tolaney, Eric Winer, Jennifer Guerriero, Elizabeth Mittendorf. High dimensional flow cytometric analysis or the peripheral immune profile and response to HER2-targeted antibody therapy [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P5-13-15.