Abstract Immuno-oncology (IO) represents a significant paradigm shift in cancer treatment, focused on leveraging and mobilizing a patient’s own immune response and anti-tumor capabilities. Despite accounting for the majority of available treatment options, there are currently no diagnostic tests capable of predicting combination immunotherapy response in kidney cancer. We have developed a fully human 3D IO model for clinical drug efficacy prediction through multivariate analysis of the tumor-immune microenvironment (TiME) combining functional assays, artificial intelligence and multi-omics. These immune-microtumors recapitulate a patient’s unique pathophysiology and allow 3D spatio-temporal analyses of functional metrics at both bulk and single-cell resolutions. Renal cell carcinoma (RCC) resections and matched blood were collected and processed for single cell isolation of tumor and PBMCs (N=20, ISRCTN10001405). Flow cytometry (FC) and immunofluorescence (IF) were used to characterize TiME cell subpopulations (cancer, immune, stromal etc.) in pellets and 3D cultures, and to deconvolute bulk RNAseq data. Target (tumor) and effector cells (PBMCs and CD8+) were stained with fluorescent probes, activated using ɑCD3 and encapsulated in TiME-mimicking 3D matrices. 3D immune-microtumors were treated with FDA-approved regimens including immunotherapies (ipilimumab, nivolumab, pembrolizumab) and receptor-tyrosine kinase inhibitors (TKIs)(cabozantinib, lenvatinib, axitinib) as monotherapies or combination therapies. Differential drug efficacies were functionally quantified over 4 days using 3D confocal microscopy and computer vision pipelines to extract cell behavior metrics such as immune cell infiltration, immune/tumor cell migration speed, and tumor killing/viability. We devised a specialized RCC hydrogel formulation with superior viability compared to MatrigelTM alone (N=7). FC/IF/RNAseq were used to quantify relative cell subpopulations after isolation and show protein/transcriptional signature retention after 3D culture (N=7). The platform was conducive to the testing of various drugs with varying MoAs including immunotherapies, TKIs, targeted therapies and cell therapies. Treatment with pembrolizumab led to 26% higher PBMC infiltration, 14% higher CD8+ infiltration and 15% increased tumor cell death compared to control. When in combination, pembrolizumab reduced cell viability by 10% and 19% with lenvatinib and axitinib respectively (N=1). Population analyses revealed intra-patient response heterogeneity (N=7). In conclusion, we showed MoA-agnostic, patient-dependent responses to FDA-approved clinical treatment regimens via molecular and functional spatio-temporal analyses. Clinical outcome correlation is currently underway in our advanced RCC study PEAR-TREE2 as well as in breast NCT05435352 and brain NCT06038760 tumors. Citation Format: Eleonora Peerani, Keqian Nan, Demi A. Wiskerke, Thomas D. Richardson, Polina Maximchick, Jay Kearney, George R. de Fraine, Kerrie L. Loughrey, Jonathan Ient, Jessica A. Hudson, Andreas Kaffa, Aston M. Crawley, Nourdine K. Bah, Edgar G. Lopez Molina, Elli Tham, Francesco Iori, Matthew H. Williams, Maxine G. Tran, Duleek N. Ranatunga. Multivariate analysis of ex vivo kidney 3D immune-microtumors for functional precision medicine [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6767.
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