Abstract PO-024: Tumor-specific cell populations in clear cell renal carcinoma associated with clinical outcome identified using single-cell protein activity inference
Authors: Aleksandar Obradovic, Nivedita Showdhury, Casey Ager, Vinson Wang, Lukas Vlahos, Xinzheng V. Guo, David H. Aggen, James McKiernan, Andrea Califano, Charles G. Drake
Journal: Cancer Research (2020)

Abstract Primary Clear Cell Renal Carcinoma (ccRCC) is a highly heterogenous disease with a variable disease course post-surgery, and ccRCC tumor micro-environment has thus far not been characterized at the single-cell level with the whole-transcriptome resolution enabled by single-cell RNA Sequencing (scRNASeq). To elucidate the cellular and transcriptional mechanisms driving disease recurrence, we performed scRNASeq on both hematopoietic and non-hematopoietic populations from tumor and tumor-adjacent tissue from primary resections of treatment-naïve ccRCC patients (n=11), thus producing a complete atlas of the ccRCC tumor microenvironment. Furthermore, in order to mitigate gene dropout inherent to scRNASeq and commonly preventing detection of &amp;gt;80% of genes, we leveraged the VIPER algorithm, which quantitates protein activity, to infer the proteomic regulators of cell state. Clustering at the gene expression level enabled construction of lineage-specific gene regulatory networks applying ARACNe, the Algorithm for Reconstruction of Accurate Cellular Networks, from which protein activity of upstream regulatory molecules could be inferred by VIPER. Comparison with protein-level expression data from antibody-based, high-parameter spectral flow cytometry in the same patients shows that VIPER-measured protein activity systematically abrogated gene dropout effects on a repertoire of &amp;gt;6,000 regulatory proteins, comparing favorably with antibody-based measurements. 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, as validated by spatially-resolved, quantitative multispectral immunofluorescence (qmIF). These tumor-specific macrophages were statistically significantly over-represented in a separate validation cohort of patients who recurred following surgery (n=4) compared to patients who did not recur (n=4). This study highlights the substantial resolution increase afforded by VIPER and identifies TREM2/APOE/C1Q-positive macrophage infiltration as a potential biomarker for ccRCC recurrence and a candidate target for intervention. Furthermore, it provides a highly-generalizable methodology to study the role of rare subpopulations by leveraging VIPER on scRNASeq data. Citation Format: Aleksandar Obradovic, Nivedita Showdhury, Casey Ager, Vinson Wang, Lukas Vlahos, Xinzheng V. Guo, David H. Aggen, James McKiernan, Andrea Califano, Charles G. Drake. Tumor-specific cell populations in clear cell renal carcinoma associated with clinical outcome identified using single-cell protein activity inference [abstract]. In: Proceedings of the AACR Virtual Special Conference on Tumor Heterogeneity: From Single Cells to Clinical Impact; 2020 Sep 17-18. Philadelphia (PA): AACR; Cancer Res 2020;80(21 Suppl):Abstract nr PO-024.