T. Choueiri

8 Single Cell Transcriptomic Investigation of Renal Cell Carcinoma (RCC) Reveals Tissue Resident Memory Exhausted CD8+ T Cell Signature Associated with Resistance to Immune Checkpoint Inhibition (ICI)

Abstract Background The current standard of care for advanced RCC is ICI-based combination therapies. However, most patients with advanced RCC develop disease progression despite ICI treatment, suggesting a lack of durable immune response. Although a lack of T cell infiltration or the presence of non-tumor-reactive “bystander” T cells are hypothesized mechanisms of ICI resistance across tumor types, therapeutic resistance in RCC may still occur in the presence of abundant infiltration of tumor-specific CD8+ T cells. We therefore investigated whether CD8+ T cell phenotype in the RCC tumor microenvironment (TME) impacts ICI response or resistance. Methods 70 tumor samples from 63 RCC patients were collected before (n = 48) or after (n = 22) therapies (VEGFi, n = 9; ICI monotherapy, n = 20; ICI combination, n = 26; others, n = 15). 11 samples were collected from patients without tumors. RCC variants included 59 clear cell and 11 non-clear cell samples. 18 were labeled as clinical benefit and 11 as no-clinical benefit. Single-cell RNA sequencing (10x Genomics) was performed on these samples to generate a transcriptome of the RCC TME. Graph-based clustering identified cell type populations, which were annotated with known lineage genes. Non-negative matrix factorization (NMF) identified gene programs within exhausted CD8+ T cells (Tex). Differential gene expression analysis determined the most differentially expressed genes between resident memory Tex and other cell populations. Results Within CD8+ T cells, Tex cells were identified through expression of TOX, PDCD1 (PD-1), and HAVCR2 (TIM-3). NMF generated 4 gene programs within Tex cells, expressing markers for immediate early genes (JUNB, FOS), exhaustion/activation (GZMK, CD74, LAG3), tissue residency (GZMH, ITGAE, IL7R), and stress response (HSPA1A, HSPA6). The tissue residency program was associated with resistance to ICI therapy (p = 0.05); this association was only found in samples with abundant tumor-specific CD8+ T cells. Differential expression between resident memory Tex (Tex-RM) and other cell types generated a signature of 10 markers that were most highly expressed in Tex-RM. Response and survival data of external bulk RNA-seq cohorts were analyzed. A signature score subtracting for Tex-RM signature was calculated (normalized to overall abundance of Tex cells by signature analysis), which was significantly higher in patients with progressive disease than those with complete/partial response (p = 0.0046), specifically for patients receiving ICI-based therapies. Additionally, survival analysis revealed that ICI-based patients with a higher (top 25%) signature score had significantly worse progression free survival (PFS; p = 0.0048) as well as overall survival (p = 0.0069) with ICI. For ICI-treated patients, the Tex-RM signature score was associated with worse PFS, with a hazard ratio of 2.1 (90% CI [1.3, 3.25]). There was no significant impact on patients receiving TKI monotherapy. Conclusions Through scRNA-seq analysis, we identify a tissue residency gene program in Tex cells associated with non-response to immunotherapy. A signature derived from this program was additionally shown to predict significantly worse response and outcomes for patients receiving ICI-based therapies within a group of bulk RNA-seq clinical trial cohorts. This study provides a framework for using scRNA-seq to identify mechanisms of ICI resistance in RCC and nominates resident memory exhausted CD8+ T cells as a targetable subset of cells to improve CD8+ T cell-mediated anti-tumor immunity. DOD CDMRP Funding yes

50 Tumor–Myeloid Multicellular Programs Reveal ECM-Associated Macrophage Polarization in ccRCC

Abstract Background Clear cell renal cell carcinoma (ccRCC) is characterized by a highly heterogeneous tumor immune microenvironment. However, how tumor-intrinsic programs shape immune cell states remains incompletely understood. We aimed to identify multicellular programs (MCPs) linking tumor and immune compartments and to define tumor-derived signals that modulate immune phenotypes. Methods We applied DIALOGUE to identify MCPs across tumor and non-tumor compartments, including CD8+ T cells, CD4+ T cells, regulatory T cells, myeloid cells, endothelial cells, and fibroblasts. A total of 189,999 cells from 26 patients with sufficient tumor cell representation (>100 cells) were analyzed from our previously reported cohort (Kashima, ASCO 2024). MCP scores were derived from DIALOGUE and summarized at the sample level by averaging single-cell MCP scores. Cell–cell interactions were evaluated using CellChat and NicheNet. Spatial relationships were assessed using G4X spatial transcriptomic data (Yochum, AACR Kidney 2026). Spatial niches were defined using Seurat v5 based on k-nearest neighbor composition, and annotated as stromal, sarcomatoid, or clear cell according to cell-type composition and gene expression features. Results We identified two major MCPs, including tumor–myeloid (MCP1) and tumor–CD4+ T cell (MCP2) programs. The tumor component of MCP1 was enriched for mesenchymal and extracellular matrix (ECM)-related genes, including structural components and remodeling factors (COL5A2, MMP2, MRC2), as well as integrin-associated adhesion and cytoskeletal genes (ITGA3, ITGB1, VCL). Expression of HMGA2 further supported a dedifferentiated, EMT-like state. Clinically, a high MCP1 score was associated with sarcomatoid features (p = 0.04). In the myeloid compartment, MCP1 was characterized by immunoregulatory and tissue-remodeling markers (MRC1, MARCO, VSIG4, MS4A4A), chemokines (CCL13, CCL18, CCL23), and complement-related genes (C2, CFH, CR1), consistent with an M2-like macrophage phenotype. Cell–cell interaction analysis revealed increased communication between MCP1-high tumor cells and MARCO+ and CXCL9+ macrophage populations. Mechanistically, ECM-related signaling pathways, particularly collagen and laminin interactions, were predicted to activate CD44-mediated signaling in macrophages. These findings suggest an ECM–CD44 axis linking tumor mesenchymal programs to M2-like polarization. Spatial transcriptomic analysis further demonstrated preferential accumulation of macrophages in stromal-rich regions. Quantitative comparison across stromal, sarcomatoid, and clear cell regions showed increased macrophage infiltration in stromal and sarcomatoid areas compared to clear cell regions (3900 and 1920 vs 830 cells/mm², respectively). Differential expression analysis of macrophages across these regions showed that macrophages in sarcomatoid areas upregulated immunoregulatory and M2-associated markers, including CD163, MRC1, CSF1R, and TGFB1. CD44 expression was also significantly increased, supporting activation of ECM–CD44-associated signaling. Response to immune checkpoint inhibitors (ICIs) was evaluable in 13 patients. Although MCPs were not significantly associated with response, patients with higher myeloid MCP1 score (> mean), but not tumoral MCP1 score, showed a numerically higher response rate compared to those with low MCP1 score (4/4 vs 5/9 patients). Of note, all 4 responders in the myeloid MCP1-high group received combination therapy with CTLA-4 and PD-1 blockade. This suggests myeloid MCP1 may be associated with response to combination ICI therapy. Conclusions Our study identifies a tumor–immune MCP in which mesenchymal and ECM remodeling programs in tumor cells are associated with M2-like macrophage polarization. These findings highlight an ECM–CD44-associated signaling axis as a potential mechanism by which tumor cells shape an immunosuppressive microenvironment in ccRCC.

51 Discovery of Exhausted CD8+ T-cell States Associated with Clinical Outcomes in Renal Cell Carcinoma

Abstract Background Therapeutic resistance to immune checkpoint inhibitors (ICIs) and antiangiogenic therapies remains a significant clinical challenge in advanced renal cell carcinoma (RCC). The prognostic value of CD8+ T-cell infiltration—a central player in cancer immunity—is often equivocal across RCC studies, supporting the need for a systematic characterization of response-associated T cell states. Here, we used a machine learning-based approach that integrated bulk RNA-sequencing (RNA-seq) data from multiple ICI-based clinical trials with an in-house single-cell RNA-sequencing (scRNA-seq) dataset to identify CD8+ T-cell states associated with progression-free survival (PFS), providing novel prognostic insights for advanced RCC. Methods We collected bulk RNA-seq data of baseline tumor samples and patient outcomes from four major clinical trials of advanced RCC with at least one treatment arm receiving ICI monotherapy or ICI combined with tyrosine kinase inhibitors (ICI+TKI): HCRN GU16-260, JAVELIN Renal 101, COSMIC-313, and CheckMate 9ER. An in-house scRNA-seq dataset of tumor-infiltrating CD8+ T cells from 70 advanced RCC patients was used as a cellular reference. Our analysis focused on the CD8+ exhausted T cells (Tex), which generally overlap with tumor-specific T-cell population. Using non-negative matrix factorization (NMF), we classified the Tex into four functional states. To link the scRNA-seq-derived T-cell states with the PFS and bulk RNA-seq data, we applied Scissor (Sun et al., 2022), a machine learning model that identifies phenotype-associated cell subsets through cell-sample correlations. For the bulk cohort meta-analysis, shared genes were normalized, scaled, and batch-corrected using ComBat (Johnson et al., 2007). Statistical significance was established via a permutation test of the PFS data, and calculating empirical p-values based on the concordance index (C-index). Results Our final bulk dataset comprised 1,527 RNA-seq tumor samples from four clinical trials of RCC, including 1,004 tumor samples from patients receiving ICI or ICI+TKI regimens. We first applied Scissor to each treatment arm of each trial individually, and found that worse PFS-associated Tex cells exhibited elevated expression of tissue-resident markers, such as ZNF683 and ITGAE, consistently across all ICI and ICI+TKI arms. These markers represent one specific NMF program defined in Tex, which we have termed the resident-memory-like exhausted state (Tex-rm). Notably, the Tex-rm population was enriched among worse PFS-associated cells in all ICI-based treatment arms (ratio of observed to expected [Ro/e] = 1.37-2.33) but not in any TKI monotherapy arms. Subsequently, we combined all ICI-based treatment arms and applied Scissor to the batch-corrected bulk dataset. This again identified Tex-rm as associated with worse PFS. Such a correlation was supported by a permutation test with p-value < 0.001. Conclusions Through machine learning-based integration of bulk and single-cell RNA-seq datasets, we found that baseline tumor infiltration by exhausted T cells with a resident memory phenotype (Tex-rm) is significantly associated with worse PFS in advanced RCC patients receiving ICI monotherapy or ICI+TKI combination therapy. This finding highlights the Tex-rm state as a potential predictive biomarker for ICI efficacy. DOD CDMRP Funding no

20 PF-08634404 (SSGJ-707), a Tetravalent PD-1/VEGF Bispecific Antibody for the Treatment of Renal Cell Carcinoma (NCT07227415)

Abstract Background Renal cell carcinoma (RCC) is characterized by an immunogenic tumor microenvironment and frequent activation of angiogenic pathways. Therefore, combining immune checkpoint blockade with VEGF pathway inhibition is a rational therapeutic approach. PF‑08634404 is an investigational anti–PD‑1 and anti‑VEGF bispecific antibody that effectively binds both targets. PF‑08634404 uses a tetravalent (2 + 2) structure that enables binding cooperativity between PD-1 and VEGF-A, increasing the avidity for and functional inhibition of PD-1 and resulting in enhanced target engagement. This enhancement differentiates PF‑08634404 from combinations of separate PD‑1 and VEGF inhibitors. PF‑08634404 has shown promising clinical activity in patients with non-small cell lung cancer (NSCLC) or colorectal cancer (CRC), with no dose-limiting toxicities observed up to 45 mg/kg Q3W, highlighting the wide therapeutic margin. Here, we present preclinical data demonstrating high-affinity binding to and functional inhibition of both PD‑1 and VEGF‑A by PF‑08634404, including evidence of VEGF‑mediated cooperative binding. Methods Assays include: 1) flow cytometry to measure binding affinity on PD-1–expressing cells; 2) size exclusion chromatography to measure PF-08634404/VEGF-A multimerization; 3) flow cytometry using pH dye to assess internalization of cell surface PD-1/PF-08634404 complexes; 4) reporter cell assay to determine PD-1 signal blockade; 5) surface plasmon resonance (SPR) to measure affinity for soluble VEGF-A; and 6) in vitro proliferation assays to examine inhibition of VEGF-induced proliferation. Results PF‑08634404 binds PD‑1 and VEGF‑A with sub‑nanomolar affinity and can engage both targets simultaneously. Its affinity for soluble VEGF‑A is approximately 30-fold and 60-fold higher than that of ivonescimab and bevacizumab, respectively, resulting in deeper and more potent VEGF inhibition in vitro. Consistent with the bispecific mechanism, PF‑08634404 multimerizes in the presence of VEGF‑A, increasing avidity for PD‑1 (>100-fold), promoting rapid internalization of PD‑1, and enhancing functional PD‑1 inhibition (>10-fold). Conclusions Collectively, these encouraging preclinical data that define the core mechanistic features of PF‑08634404, the preliminary safety and antitumor activity, and the importance of targeting PD-(L)1 and VEGF support the investigation of PF‑08634404 in pivotal trials across multiple tumor types, including RCC. A phase 1b/2 study (Symbiotic-GU-08) in patients with newly diagnosed advanced or metastatic RCC is being conducted to evaluate the efficacy and safety of PF‑08634404, either as monotherapy or in combination with ipilimumab (anti–CTLA‑4) or axitinib (VEGF tyrosine kinase inhibitor) (NCT07227415). Symbiotic-GU-08 enables a novel “tripartite” approach to frontline treatment of RCC through combination therapy. PD‑1 blockade in combination with ipilimumab-mediated CTLA‑4 inhibition produces complementary immune activation. Adding PF‑08634404’s VEGF neutralization to a PD‑1/CTLA‑4 backbone would be expected to further enhance the immune response by reducing VEGF-driven immunosuppression and abnormal vasculature and by improving T‑cell infiltration and function. PF‑08634404 in combination with axitinib, a potent VEGFR1–3 tyrosine kinase inhibitor, creates dual VEGF-pathway blockade on top of PD‑1 inhibition. This strategy could more thoroughly shut down tumor angiogenesis, in addition to leveraging the immunomodulatory effects of axitinib that may further complement PD‑1 blockade. PF‑08634404 has demonstrated clinical proof of concept in other cancers. Together, these data provide a strong scientific rationale to evaluate PF‑08634404, alone or in combination regimens, in alignment with established effective RCC treatment paradigms. Previously presented in part at the 2026 AACR Annual Meeting.

Tertiary lymphoid structures harbour stem-like tumour-specific T cells

Abstract PR006: Target discovery in rare cancers enabled by transcriptome-based virtual CRISPR screening

It is demonstrated that machine learning applied to transcriptomic data can uncover novel cancer vulnerabilities and actionable targets in individual tumors, even in the absence of functional screening, which may represent a scalable approach to advance precision oncology in rare and/or under-characterized cancer types.