Exhausted T-cell signature in the TME can be inferred from the blood and the inferred exhausted T-cell score can further predict immunotherapy response in HNSCC. A, Correlation between the predicted and the measured exhausted T-cell signature scores in TME in the matched blood/tumor training dataset (n = 25) and validation dataset (n = 5). B, ROC curve for predicting ICB RECIST response (n = 16) and pathologic response (n = 26) by the predicted exhausted T-cell signature scores. C, OS and PFS analyses of ICB-treated patients in exhausted-high (exhausted score > quantile 50%) vs. exhausted-low (exhausted score ≤ quantile 50%) tumor groups using the predicted exhausted T-cell signature scores. D–F are the same as A–C, respectively, except that the predicted exhausted T-cell signature scores in the TME are replaced by the measured exhausted T-cell signature scores in the blood. r, Pearson correlation coefficient; ρ, Spearman correlation coefficient. FPR, false-positive rate; TPR, true-positive rate.
ARTICLE ABSTRACT
In this study, we explore the possibility of inferring characteristics of the tumor immune microenvironment from the blood. Specifically, we investigate two datasets of patients with head and neck squamous cell carcinoma with matched single-cell RNA sequencing (scRNA-seq) from peripheral blood mononuclear cells (PBMCs) and tumor tissues. Our analysis shows that the immune cell fractions and gene expression profiles of various immune cells within the tumor microenvironment can be inferred from the matched PBMC scRNA-seq data. We find that the established exhausted T-cell signature can be predicted from the blood and serve as a valuable prognostic blood biomarker of immunotherapy response. Additionally, our study reveals that the inferred ratio between tumor memory B- and regulatory T-cell fractions is predictive of immunotherapy response and is superior to the well-established cytolytic and exhausted T-cell signatures. These results highlight the promising potential of PBMC scRNA-seq in cancer immunotherapy and warrant, and will hopefully facilitate, further investigations on a larger scale. The code for predicting tumor immune microenvironment from PBMC scRNA-seq, TIMEP, is provided, offering other researchers the opportunity to investigate its prospective applications in various other indications.
Our work offers a new and promising paradigm in liquid biopsies to unlock the power of blood single-cell transcriptomics in cancer immunotherapy.
