Abstract P5-04-03: Deconvoluting immune cell populations using ‘in silico flow cytometry’ with CIBERSORT: Association with neoadjuvant therapy response and genomic instability in TNBC
Authors: Vinayak Shaveta , Newman Aaron , Adams Sylvia , Afghahi Anosheh , Jensen Kristin C , Badve Sunil S , Ford James M , Alizadeh Ash A , Telli Melinda L 
Published: May 2015

Abstract
Background: Increased tumor infiltrating lymphocytes (TILs) are prognostic and predictive of therapy response in TNBC. CIBERSORT, a highly novel ‘in silico flow cytometry’ gene expression-based method, can assess the overall immune content and relative levels of distinct leukocyte subsets in tumors.
Methods: We applied CIBERSORT to PrECOG 0105, a neoadjuvant trial of carboplatin, gemcitabine and iniparib for patients with clinical stage I-IIIA TN or BRCA1/2 mutation-associated BC. H&E tumor sections from pre-therapy biopsies were evaluated for density of stromal (sTILs) and intratumoral (iTILs) lymphocytes. Pathologic response was assessed at definitive surgery. Overall immune content and fractions of 23 distinct leukocyte subsets were derived from Affymetrix U133 plus 2.0 arrays, using CIBERSORT. Using an input matrix of reference gene expression signatures of 23 purified leukocytes, this methodology can infer an unknown fraction of each cell type from tissue expression profiling, yielding a p value for deconvolution. All patients had BRCA1/2 genotyping and levels of tumor genomic instability were assessed by the homologous recombination deficiency (HRD) assay.
Results: 57 pts had gene expression and TILs assessment. TILs, sTILs, and iTILs were significantly associated with a measure of absolute immune content determined by CIBERSORT, termed an ‘immune score’ (R 0.73, p&lt;0.0001; R 0.70, p&lt;0.0001; R 0.57, p&lt;0.0001 respectively). Both iTILs and the CIBERSORT immune score were significantly associated with pathologic complete response (pCR; ypT0/is N0) in independent models. Specific leukocyte subsets significantly associated with pCR, included activated memory CD4 T cells, CD8 T cells, and M1 macrophages (all p&lt;0.05). Regarding genomic instability measures, BRCA1/2 germline mutation status was not associated with TILs or immune score, whereas a high HRD assay score was significantly associated with the CIBERSORT immune score (p=0.038). Individual leukocyte subsets significantly associated with a high HRD assay score, included plasma cells, activated memory CD4 T cells, M1 macrophages, and unstimulated mast cells (all p&lt;0.05).
Conclusions: Neoadjuvant platinum-based therapy response significantly associates with both iTILs and CIBERSORT immune score. A measure of global genomic instability (HRD score) significantly associates with immune score alone. Enumeration of 23 leukocyte subsets in therapy-naïve TNBC by CIBERSORT revealed three distinct cell types that significantly predict pCR, two of which also associate with genomic instability. These results suggest an intimate interplay between genomic instability and immune infiltration, potentially shaping adaptive anti-tumor humoral immune responses, and thereby affecting neoadjuvant response in TNBC.
Citation Format: Shaveta Vinayak, Aaron Newman, Sylvia Adams, Anosheh Afghahi, Kristin C Jensen, Sunil S Badve, James M Ford, Ash A Alizadeh, Melinda L Telli. Deconvoluting immune cell populations using ‘in silico flow cytometry’ with CIBERSORT: Association with neoadjuvant therapy response and genomic instability in TNBC [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P5-04-03.