Abstract 2039: Predicting abundance and expression of immune cells in patients’ head & neck tumor microenvironment from blood single-cell transcriptomics

Abstract The tumor microenvironment (TME) is a key determinant of immunotherapy efficacy, yet, not readily accessible. Here, we ask if the immune cell fractions (ICFs) and gene expression patterns in the TME can be predicted from the blood single-cell RNA sequencing (scRNA-Seq) data. To the best of our knowledge, the immune status of the TME has not been comprehensively evaluated and predicted from the blood previously. Addressing this challenge, we analyzed 26 paired head and neck squamous cell carcinoma (HNSCC) patients matched blood and tumor samples with CD45+ scRNA-Seq data and clinical information. We developed a machine learning predictor of ICFs and gene expression levels of major immune cell types in the TME from the matching blood transcriptomics and pertaining clinical information, termed the Tumor Immune MicroEnvironment Predictor (TIMEP). We find that the ICFs, all 11 major immune cell types in the TME were predictable from the blood. 17-47% genes expressed in different immune cells were predictable from the blood, with the highest coverage in dendritic cells and helper, cytotoxic and regulatory T cells. Furthermore, the ICF ratio (ICFR) signature of (Treg - Bmemory)/(Treg + Bmemory) in the TME, as predicted from the blood, can robustly predict the response to immune checkpoint blockade (AUC > 0.72 on three independent single-cell and bulk expression datasets). These results are the first to demonstrate the feasibility of employing single-cell transcriptomics liquid biopsy to predict the immune status in patients TME in patients, facilitating future personalized cancer precision therapy. Citation Format: Yingying Cao, Tiangen Chang, Fiorella Schischlik, Sanju Sinha, Kun Wang, Peng Jiang, Eytan Ruppin. Predicting abundance and expression of immune cells in patients’ head & neck tumor microenvironment from blood single-cell transcriptomics [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 2039.