Abstract Background: Dual anti-HER2 blockade resulted in increased pathologic complete response rate (pCR) in the 3 arm NeoALTTO trial. High immune gene expression and the absence of PIK3CA pathway mutations are predictive of pCR in all treatment arms but no markers were identified that could predict which patients require dual HER2 targeted therapy. The goal of this analysis was to examine if TRBV expression could add to the predictive function of previously identified immune markers. Patients and Methods: We analyzed RNA and Whole Exome sequencing data from 245 cancers (54% of all patients) included in the trial. The TRBV reference sequences were obtained from the International ImMunoGeneTics information system. Reads were aligned using a custom BLAST mapping pipeline and normalized by the total number of aligned reads in each sample. We calculated 3 T cell receptor metrics for each tumor including (i) total TRBV chain expression level, (ii) Shannon entropy of the normalized unique TRBV-expression frequencies which reflect TCR diversity and (iii) we also used non-negative matrix factorization (NMF) to define TRBV co-expression metagenes (TRBVMG). We evaluated correlation between these metrics and immune and proliferation gene expression signatures and genomic features of the cancer including clonal heterogeneity and mutation load. We assessed association between TRBV and pCR using multivariate logistic regression. Results: 65 distinct TRBV variants showed heterogeneous expression levels across cancers with strong co-expression patterns. Total TRBV expression correlated strongly with immune metagene expression (Spearman's ρ=0.93, P<0.001), but entropy had a weaker, inverse correlation with immune metagene expression (Spearman's ρ=-0.40, P<0.001). Associations between TRBV metrics and mutation load and clonal heterogeneity were weak. pCR correlated with higher total TRBV expression (Spearman's ρ=0.17, P<0.05). Correlation between entropy and pCR was non-significant (odds ratio (OR) for regressing entropy with pCR was <1). NMF identified 4 distinct TRBVMGs that showed substantial expression variation within immune cell rich cancers. ER-status, proliferation and immune-gene expression adjusted logistic regression analysis including a treatment-arm interaction term revealed that TRBVMG-2, characterized by high expression of TRBV4.3, TRBV6.3 and TRBV7.2 variants, was associated with higher pCR rate in patients treated with trastuzumab plus lapatinib (Interaction OR=3.23 adjusted P=0.03). In immune-rich cancers, TRBVMG-2 expression above the median was associated with higher pCR rate in the dual HER2 targeted treatment arm compared to the other arms (68% vs 21%, Fisher exact test P<0.001). Patients with immune cell rich cancers but TRBVMG-2 expression below the median had similar pCR rates in all arms (42% monotherapy vs. 28% dual therapy, P=0.46). Conclusions: TRBV expression pattern can provide predictive information beyond known immune gene expression signatures. High expression of TRBV4.3, TRBV6.3 and TRBV7.2 variants is associated with higher pCR rate with dual HER2 targeted and paclitaxel neoadjuvant therapy. Citation Format: Powles R, Redmond D, Sotiriou C, Loi S, Fumagalli D, Nuciforo P, Harbeck N, de Azambuja E, Sarp S, Di Cosimo S, Huober J, Baselga J, Piccart-Gebhart M, Elemento O, Hatzis C, Pusztai L. T-cell receptor beta chain variable region (TRBV) expression patterns predict response to combined trastuzumab/lapatinib treatment in the NeoALTTO/BIG-1-06 trial [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr P2-09-01.