Abstract PO009: Single-cell protein activity inference identifies tumor-enriched macrophages associated with early post-surgical disease recurrence

Abstract

Abstract Primary Clear Cell Renal Carcinoma (ccRCC) is a highly heterogenous disease with a variable disease course post-surgery. To elucidate the cellular and transcriptional mechanisms driving disease recurrence, we aimed in this study to transcriptionally profile single-cell populations enriched in the Tumor Micro-Environment (TME) and assess their key regulatory proteins as biomarkers of recurrence. We performed scRNASeq on immune and non-immune populations from tumor compared to tumor-adjacent tissue in primary resections of treatment-naïve ccRCC patients (n=11), thus producing a complete atlas of the ccRCC tumor microenvironment. In order to mitigate gene dropout inherent to scRNASeq and commonly preventing detection of >80% of genes, we leveraged the VIPER algorithm to infer proteomic regulators of cell state. This approach relies on construction of lineage-specific gene regulatory networks with ARACNe, the Algorithm for Reconstruction of Accurate Cellular Networks, and infers protein activity from expression of hundreds of downstream transcriptional targets. By VIPER, we recover key regulatory proteins not significantly detected by gene expression alone, and improve resolution of cell subtypes. VIPER-inferred protein activity systematically abrogated gene dropout effects on a repertoire of >6,000 regulatory proteins, comparing favorably with antibody-based measurements for a subset of proteins profiled by spectral flow cytometry. This helped comprehensively characterize the individual cellular sub-populations comprising the ccRCC tumor and peri-tumor microenvironment, as well as their specific master regulators and candidate cell-cell interactions, revealing several populations undetectable by gene expression analysis. Specifically, we uncovered a novel tumor-specific macrophage subpopulation characterized by significant upregulation of TREM2, APOE, and C1Q, further validated by spatially-resolved quantitative multispectral immunofluorescence (qmIF). These tumor-specific macrophages were significantly over-represented in an exploratory cohort of patients who recurred following surgery compared to patients who did not recur (n=8), predictive of time-to-recurrence with a p-value of 0.0067. In a larger validation cohort (n=157), enrichment of tumor-specific macrophage population markers was associated with early post-surgical recurrence with a p-value of 0.0029. This study highlights the substantial increase in resolution of scRNASeq analysis afforded by VIPER and identifies TREM2/APOE/C1Q-positive macrophage infiltration as a potential biomarker for ccRCC recurrence and a candidate target for intervention to reduce post-surgical recurrence rates. Citation Format: Aleksandar Obradovic, Nivedita Chowdhury, Casey Ager, Vinson Wang, Lukas Vlahos, Xinzheng Guo, David Aggen, Andrea Califano, Charles Drake. Single-cell protein activity inference identifies tumor-enriched macrophages associated with early post-surgical disease recurrence [abstract]. In: Proceedings of the AACR Virtual Special Conference on the Evolving Tumor Microenvironment in Cancer Progression: Mechanisms and Emerging Therapeutic Opportunities; in association with the Tumor Microenvironment (TME) Working Group; 2021 Jan 11-12. Philadelphia (PA): AACR; Cancer Res 2021;81(5 Suppl):Abstract nr PO009.