Abstract P5-04-07: Defining T cell dysfunctionality in breast cancer by single cell analysis: Implications for immunotherapy

Media type: E-Article

Title: Abstract P5-04-07: Defining T cell dysfunctionality in breast cancer by single cell analysis: Implications for immunotherapy

Contributor: Losurdo, Agnese; Scirgolea, Caterina; Mazza, Emilia; Errico, Valentina; Fernandes, Bethania; Tommaso, Luca Di; Sagona, Andrea; Pilipow, Karolina; Torrisi, Rosalba; Masci, Giovanna; De Sanctis, Rita; Agostinetto, Elisa; Testori, Alberto; Tinterri, Corrado; Roncalli, Massimo; Santoro, Armando; Lugli, Enrico

imprint: American Association for Cancer Research (AACR), 2020

Language: English

DOI: 10.1158/1538-7445.sabcs19-p5-04-07

ISSN: 0008-5472; 1538-7445

Keywords: Cancer Research ; Oncology

Origination:

Footnote:

Description: Abstract Background Despite the well-known association between extensive lymphocytic infiltration in breast cancer (BC), good prognosis, and high response rates to neoadjuvant chemotherapy (CT), pathologic evaluation of tumor infiltrating lymphocytes (TILs) is currently not routine and a deep understanding of the properties of TILs, remain largely unfilled. So far, only in triple-negative (TN), PD-L1 positive BCs it has been possible to demonstrate a survival benefit with immunotherapy plus CT, thereby making the definition of possible immunotherapeutic targets across all biological subtypes a fundamental requirement. Material and methods Single-cell RNA-sequencing (scRNAseq) data from 8 BCs were downloaded from Gene Expression Omnibus dataset (GSE114725), obtaining CD45+ single cells only from the tumoral compartment. scRNAseq-guided high-dimensional profiling by 27-parameter FACS was then applied to a large cohort (n=54, including luminal-like, TN and HER2+ BCs) of early BC patients surgically treated at our Institution. We simultaneously profiled the peripheral blood, the normal and tumoral tissue from each patient and acquired using FACS Symphony A5 flow cytometer (BD Biosciences). Flow Cytometry Standard (FCS) 3.0 files were imported into FlowJo software v9, and analyzed by standard gating to remove aggregates and dead cells, and subsequently imported in FlowJo v10, biexponentially transformed, and exported for further analysis in R by a custom-made script, using an ad-hoc pipeline. Data were analyzed using the Phenograph unbiased algorithm coded in the cytofkit package. Data were further analyzed in FlowJo to determine the frequency of positive cells for each marker and the corresponding median fluorescence intensity (MFI). These values were multiplied to derive the integrated MFI; hierarchical metaclustering of all samples, based on the frequency of Phenograph clusters, was performed in R based on the Euclidean distance and Ward-linkage. Pearson correlation analysis was used to investigate the relationship between CD8+ and CD4+ clusters. Results Our scRNA-guided informative 27-colors flow cytometry panel included antibodies to define not only different lymphocyte subpopulations, but also different stages of T lymphocytes: differentiation and memory maturation (CCR7, CD45RA), activation status (HLA-DR), cytotoxicity (GZMK, GZMB), exhaustion (PD-1, TIGIT) and tissue residency (CD69, CD103). Focusing on CD8+ T cells, we observed, as expected, bona fide naïve T cells to be virtually absent at the tumor site and enriched in peripheral blood, while cytotoxic and effector memory cells were enriched in the tumor compartment. Of note, we identified a population of tissue resident memory T cells (Trm) CD69+ CD103+, CD39+, specifically enriched in the tumor, that could be further subdivided into a HLA-DR+ CD127- and a HLA-DR- CD127+ subpopulation. Interestingly, the HLA-DR+ subset exhibited more exhaustion markers (PD-1hi, TIGIT+, NKG2A+) and was significantly positively correlated with CD4+ regulatory T cells. We speculated, and deeply investigated by bulk RNA-seq, that these two subsets of Trm might represent different maturation states and that they could be reinvigorated targeting highly expressed inhibitory molecules using approved (e.g., PD-1) together with newly identified (e.g., NKG2A) immunotherapeutics. Moreover, as no difference was observed in the relative distribution of Phenograph clusters, our data may be applied to revert acquired immune escape mechanisms in all different BC biological subtypes. Conclusions We identified, among Trm CD69+ CD103+, tumor-specific CD39+, PD1+ exhausted population, novel dysfunctional NKG2A+ T cells previously not characterized in BC. This population is of extreme interest to characterize a novel potential immunotherapeutic target. Citation Format: Agnese Losurdo, Caterina Scirgolea, Emilia Mazza, Valentina Errico, Bethania Fernandes, Luca Di Tommaso, Andrea Sagona, Karolina Pilipow, Rosalba Torrisi, Giovanna Masci, Rita De Sanctis, Elisa Agostinetto, Alberto Testori, Corrado Tinterri, Massimo Roncalli, Armando Santoro, Enrico Lugli. Defining T cell dysfunctionality in breast cancer by single cell analysis: Implications for immunotherapy [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P5-04-07.

Access State: Open Access

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