The expression levels of 17% to 47% of the genes expressed in TME immune cells can be predicted from the blood. A, Distribution of correlations between the predicted and true expression values of all expressed genes in each immune cell type in the TME, with and without clinical information. B, Number of expressed genes and predictable genes in each cell type with and without the consideration of clinical variables. The gray bars represent the number of genes that can be predicted using expression alone, whereas the colored bars indicate the additional number of genes that can be predicted by incorporating clinical variables (see the corresponding colored labels). Statistical notation: ***, FDR < 0.001; **, FDR < 0.01; *, FDR < 0.05. The FDRs are calculated using the Benjamini–Hochberg correction method. info., information.
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.
