Abstract LB248: Interrogating the cancer-immunity cycle through the lens of a large-scale single-cell atlas of immune checkpoint inhibition response and resistance
Authors: Topolewski Piotr , Kochańska Zofia , Osipowicz Marlena , Ronen Roy , Dutkowski Janusz 
Published: April 2024

Abstract
Introduction. The cancer-immunity cycle (CIC; Chen et al. 2013; Mellman et al. 2023) systematizes the current understanding of the factors (both suppressive and promoting) that together determine the anticancer immune responses. While the CIC is not limited to any single therapeutic modality, the framework is useful for understanding the mechanisms of immune checkpoint inhibition (ICI) response and resistance. Given its importance in the field, it is critical to be able to systematically examine and expand the CIC (or related frameworks) using new high-throughput data. Here we intersect the CIC framework with a large-scale atlas of single-cell RNA-seq data to provide a window into the CIC factors supported across multiple tumor types.
Approach. We have previously developed the Single-Cell Immune Checkpoint Inhibition Atlas (ICI Atlas) which in its original version spanned 27 datasets and 1.9 million cells across a range of tumor types and ICI therapies. Motivated by rapid growth of data in the field, here we develop version 2 of the Atlas, over twice as large and consisting of 55 datasets and 4.4 million cells with cross-dataset integration via a transformer-based deep learning model. Of the 55 datasets, 47 contain both pre- and post-treatment samples, 2 contain only pre-treatment samples, and 6 contain only post-treatment samples. The Atlas spans 124 cell types and covers 19 different cancer types as well as 31 treatment strategies including 19 ICI therapies.
Results. To determine the ICI Atlas support for each factor in the CIC, we analyzed the percent of studies where the factor’s cell type-specific pre-treatment expression was significantly higher in ICI responders (for promoting factors) or in non-responders (for inhibiting factors). We found that 16 cell type-specific CIC factors (12 promoting and 4 inhibiting) had strong support in the ICI Altas (supported in ≥ 50% of relevant studies). Specific steps of the CIC were associated with well-supported promoting factors, e.g. Step 2: interferon alpha/beta signaling pathway (dendritic cells/APCs, 50-100% of studies); Step 3: TCR signaling pathway (T cells; 58%); Step 5: CXCL9/10/11 (macrophages, 50-75%) and CCL5 (T cells, 58%); Step 5a: SELL (T cells, 68%); or inhibiting factors, e.g. Step 5b: IL10 (T cells, 53%). For some factors the support is tissue-specific, e.g. in tumor samples type-I IFN signaling was higher in dendritic cells and monocytes of responders while in blood this was reversed. Interestingly, certain co-stimulatory factors showed higher expression in non-responders (e.g. OX40 in T-cells, 53% of analyses, and 4-1BBL in macrophages, 50%). Our analysis also identifies a number of new factors whose expression is associated with response to ICI across the majority of ICI Atlas studies, providing opportunities for expanding current knowledge of cancer-immune system interplay and ICI response.
Citation Format: Piotr Topolewski, Zofia Kochańska, Marlena Osipowicz, Roy Ronen, Janusz Dutkowski. Interrogating the cancer-immunity cycle through the lens of a large-scale single-cell atlas of immune checkpoint inhibition response and resistance [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr LB248.