Multimodal delineation of a layer of effector function among exhausted CD8 T cells in tumors [CITE-seq]

The anti-tumor function of CD8 T cells is limited through well-established pathways of T cell exhaustion (TEX). Strategies to capture emergent functional states amongst this dominant trajectory of dysfunction are necessary to find pathways to durable anti-tumor immunity. By leveraging transcriptional reporting (by the fluorescent protein TFP) of the T cell activation marker Cd69, related to upstream AP-1 transcription factors, we define a classifier for potent versus sub-optimal CD69+ activation states arising from T cell stimulation. In tumors, this delineation acts an additional functional readout along the TEX differentiation trajectory, within and across TEX subsets, marked by enhanced effector cytokine and granzyme B production. The more potent state remains differentially prominent in a T cell-mediated tumor clearance model, where they also show increased engagement in the microenvironment and are superior in tumor cell killing. Employing multimodal CITE-Seq in human head and neck tumors enables a similar strategy to identify Cd69RNAhiCD69+ cells that also have enhanced functional features in comparison to Cd69RNAloCD69+ cells, again within and across intratumoral CD8 T cell subsets. Refining the contours of the T cell functional landscape in tumors in this way paves the way for the identification of rare exceptional effectors, with imminent relevance to cancer treatment. Live CD45+ and CD45- cells were sorted on a BD FACSAria Fusion. CD45+ and CD45- cells were pelleted and resuspended at 1x10^3 cells/ml in 0.04%BSA/PBS buffer before mixing in an 8:2 CD45+:CD45- ratio and loaded onto the Chromium Controller (10X Genomics) to generate 5′ v1.1 gel beads-in-emulsions (GEM). Pooled 8:2 CD45+:CD45- cells were resuspended in Cell Staining Buffer (BioLegend) and stained with a pool of 137 TotalSeq-C antibodies (Table) according to the manufacturer’s protocol before loading onto the Chromium Controller (10X Genomics) for GEM generation. The cDNA libraries were generated using all or a subset of Chromium Next GEM Single Cell 5′ Library Kit for gene expression (GEX), Chromium Single Cell V(D)J Enrichment kit (10X Genomics) for T cell receptor (TCR), and Chromium Single Cell 5′ Feature Barcode Library kit for antibody derived tag (ADT) according to the manufacturer’s instructions. The libraries were subsequently sequenced on a Novaseq S4 sequencer (Illumina) to generate fastqs with the following mean reads per cell: 42,000 (GEX), 34,000 (TCR), and 5,700 (ADT). Please note that the records have been updated with the re-analysis data on May 21, 2025 as detailed below: In addition, GSM6552605, GSM6552607, GSM6552609, GSM6552613 from GSE212797 were included in this analysis. The sequencing and processing of these previous samples were the same as the new ones identified here. Identical analysis pipelines were used to analyze these data. IPIHNSC126_T1_scrna_CD45_enriched_filtered_feature_bc_matrix.h5 (generated from re-analysis of GSM6552605, GSM6552607) IPIPOOL004_P1_scrna_CD45_enriched_filtered_feature_bc_matrix.h5 (generated from re-analysis of GSM6552609, GSM6552613) *************************************************************** The table below lists GEO accessions reused/reanalyzed for this study. ***************************************************************