Background: Prostate cancer is a heterogeneous disease with variable clinical outcomes. If localized, the patient may be cured. However, prostate cancer is lethal if recurrence/progression to metastatic castrate resistant disease occurs. Thus, there is an unmet need to further understand the molecular underpinnings of this progression. Epidemiologic studies show that increased risk of developing and dying from prostate cancer has been associated with elevated serum IGF-1 levels, hyperinsulinemia and metabolic syndrome. Alterations in insulin pathway genes, such as PTEN, FOXO, and PIK3CA, are mutated in up to 32%, 15%, and 11% of localized prostate tumors, respectively. We aimed to further characterize expression of insulin pathway genes in localized prostate cancers in an effort to (1) provide insights into potential mechanisms of progression to metastatic disease and (2) try to further enrich for those prostate tumors that portend worse survival outcomes. Methods: Using the multi-institutional Oncology Research Information Exchange Network (ORIEN) database, gene expression data was analyzed from localized prostate cancer tumors. The raw counts were first normalized, and 176 genes related to the insulin receptor and its downstream pathways were then subset and used for clustering using the non-negative matrix factorization (NMF). The NMF cluster analysis was performed in an attempt to separate gene expression into two groups. Gene Set Enrichment Analysis (GSEA) was then performed between the two groups that had been separated by cluster analysis to determine homology between other GSEA sets. Kaplan-Meier curves were used to assess median overall survival. Cox analysis was performed to generate the adjusted KM curve. Mediation analysis was conducted to determine the relationship between cluster status, TN stage, and survival. Results: Cluster analysis revealed two distinct groups of insulin gene expression, cluster 1 (n = 96) and cluster 2 (n = 337). Compared with cluster 2, cluster 1 consisted of decreased expression of PTEN (p < 0.001) and PIK3R1 (p < 0.001), along with increases in the expression of AKT1 (p < 0.001), IRS1/2 (p < 0.001), FASN (p < 0.001), IGFBP2 (p < 0.001), and MTOR (p < 0.001). GSEA analysis revealed changes in lipid metabolism and WNT secretion pathways in cluster 1. Cluster 2 GSEA showed pathway changes related to DNA damage repair and testosterone. Patient characteristics between clusters differed significantly in the T and N stages of tumor but not in other ways. In unadjusted analysis, median overall survival was estimated at 117 months and 232 months for cluster 1 and cluster 2, respectively (p < 0.05). The proportion of patients who went on to develop metastases (p < 0.05) or need chemotherapy (p < 0.05) was increased in cluster 1 compared to cluster 2. Repeat survival analysis adjusted for confounders (T stage, N stage, age at diagnosis, pathologic grade) showed no difference in survival between clusters. Mediation analysis showed that the contribution of cluster status to survival was independent of T or N stage. Conclusions: A subset of localized prostate cancer patients demonstrated linked insulin pathway changes that are consistent with prior studies describing a pattern of insulin dysregulation. Though the group characterized by insulin dysregulation initially showed worse survival outcomes, this difference disappeared when controlling for confounders. Though baseline differences in tumor stage seemed to most readily explain the difference in survival between clusters, mediation analysis showed that the effect of cluster status on survival was independent of tumor stage. This suggests that other confounders, such as pathologic grade or baseline age, may explain the survival difference.

INTRODUCTION:Nearly 81,000 new cases of renal cell carcinoma are expected to be diagnosed in 2025, with more than one-third of patients presenting with or eventually developing metastatic disease. Some patients develop oligoprogressive disease, defined by limited metastatic progression. AREAS COVERED:We discuss current data evaluating the treatment approaches to patients with oligoprogressive disease. This includes active surveillance, systemic therapy, and metastasis-directed therapy such as surgical resection, stereotactic ablative radiotherapy, and percutaneous thermal ablation. We also describe the disease characteristics that we consider when deciding on the appropriate therapy for patients with oligoprogressive disease. We searched databases such as PubMed and ClinicalTrials.gov from 2000 to 2026 for trials related to these treatment options. EXPERT OPINION:Patients with oligoprogressive RCC with favorable or intermediate-risk disease and limited metastases may benefit from metastasis-directed therapy. Patients that progress on immunotherapy and require subsequent therapy should consider a tyrosine kinase inhibitor. Biomarkers are being explored to better risk-stratify patients for metastasis directed therapy.

Renal cell carcinoma (RCC) accounts for the majority of kidney cancers, with approximately 80,000 new diagnoses and over 14,000 deaths annually in the United States. Risk stratification is essential for prognostication, treatment selection, and clinical trial design across all disease stages. In localized and locally advanced RCC, pathological stage, histology, and grade remain the primary prognostic factors, while the International Metastatic Renal Cell Carcinoma Database Consortium (IMDC) criteria serve as the standard risk stratification tool in the metastatic setting. However, current models rely predominantly on clinical and pathologic variables that act as indirect surrogates of tumor biology and do not account for the molecular heterogeneity inherent to RCC. This narrative review synthesizes and compares established and emerging risk stratification and prognostic models across all stages of RCC. Established models such as the IMDC criteria and the stage, size, grade, and necrosis (SSIGN) score demonstrate robust prognostic performance but are limited by their reliance on clinical and pathologic variables alone. Emerging biomarkers-including circulating tumor DNA, methylated DNA, artificial intelligence-based radiomics, and tissue-based molecular signatures-show promise for improving risk discrimination. The molecular heterogeneity of RCC underscores an urgent need for integrated molecular-clinical-pathologic prognostic tools tailored to specific histologic subtypes to enable more precise, individualized care.

4561 Background: Belzutifan, a hypoxia-inducible factor–2α inhibitor, is an emerging therapy for advanced renal cell carcinoma (RCC) that demonstrated significant benefit over everolimus in the LITESPARK-005 trial. We aimed to validate these findings in a real-world setting and identify clinical prognostic factors within a large, multi-institutional cohort. Methods: We conducted a retrospective cohort study, using Epic Cosmos, of adults with RCC who initiated Belzutifan on or after the FDA Approval date (December 14, 2023) to Dec 20, 2025, ensuring at least one month of follow-up prior to the query date. Overall survival (OS) was measured from the treatment start date to death, with censoring at the last clinical encounter. Survival was estimated using Kaplan–Meier methods. Associations between baseline clinical and laboratory variables and OS were evaluated using univariable Cox proportional hazards models with false discovery rate (FDR) correction. Results: A total of 2,844 patients were included; the median age was 66 years, 72% were male, and 51.2% had documented tobacco use. The OS probabilities were 80.9%, 68.1%, 58.3%, and 53.2% at 6, 12, 18, and 24 months, respectively, and comparable to the LITESPARK-005 trial. Among clinical variables, tobacco use was associated with worse survival (HR 1.24 [95% CI 1.08–1.44], FDR = 0.014), whereas female sex (HR 0.78 [0.66–0.92], FDR = 0.014) and higher BMI (HR 0.96 [0.95–0.98], FDR <0.001) were associated with improved outcomes. Markers of nutritional and hematologic reserve were strongly protective, including higher Albumin (HR 0.46 [0.41–0.52], FDR <0.001), Total Protein (HR 0.77 [0.70–0.89], FDR <0.001), Hemoglobin (HR 0.90 [0.87–0.93], FDR <0.001), RBC (HR 0.69 [0.62–0.75], FDR <0.001), and MPV (HR 0.90 [0.84–0.96], FDR = 0.002). Inflammatory and immune markers demonstrated divergent effects: higher Lymphocytes (HR 0.53 [0.46–0.61], FDR <0.001) and Lymphocyte-to-Monocyte Ratio (HR 0.75 [0.71–0.80], FDR <0.001) predicted favorable outcomes. Conversely, worse survival was associated with elevated RDW (HR 1.14 [1.11–1.17], FDR <0.001), Monocytes (HR 1.71 [1.34–2.20], FDR <0.001), Basophil-to-Lymphocyte Ratio (HR 2.39 [1.20–4.77], FDR = 0.019) and Neutrophils (HR 1.06 [1.04–1.07], FDR <0.001),.Higher Corrected Calcium (HR 1.43 [1.30–1.57], FDR <0.001) and Total Bilirubin (HR 1.13 [1.04–1.22], FDR = 0.005) were associated with inferior outcomes. Conclusions: In the largest real-world cohort to date, overall survival after belzutifan initiation mirrored LITESPARK-005, supporting its effectiveness in routine practice. Baseline nutritional, hematologic, and immune markers were associated with improved survival, while systemic inflammation and metabolic dysfunction predicted worse outcomes, highlighting the prognostic value of routine clinical variables.

PURPOSE OF REVIEW:To summarize recent updates in the classification, clinical trial evidence, and evolving treatment strategies for nonclear cell renal cell carcinoma (nccRCC). RECENT FINDINGS:The 2022 WHO classification eliminated the type 1/2 papillary paradigm, refined molecularly defined tumors such as fumarate hydratase (FH)-deficient and anaplastic lymphoma kinase-rearranged RCC, while acknowledging indolent tumors like clear cell papillary renal cell tumors. Prospective and retrospective data increasingly support the use of immune checkpoint inhibitor (ICI)-based regimens, particularly ICI/ tyrosine kinase inhibitor (TKI) combinations. KEYNOTE-B61 and ARON-1 demonstrated consistent activity of pembrolizumab + lenvatinib across nccRCC subtypes, while the randomized SUNNIFORECAST trial validated ipilimumab + nivolumab as a first-line option with overall survival (OS) benefit over standard therapy. Subtype-specific approaches are also emerging: bevacizumab + erlotinib and sintilimab + axitinib showed high response rates in FH-deficient RCC, and prognostic tools such as VENUSS remain valuable for papillary RCC risk stratification. Despite progress, many studies remain limited by histologic heterogeneity and small sample sizes. Multiple ongoing trials, including ICONIC, SAMETA, and PAPMET2, are expected to further clarify optimal management strategies in 2026. SUMMARY:Therapeutic advances are reshaping the management of nccRCC, with IO/TKI regimens and histology-specific therapies showing promise. Continued integration of molecular classification, rare subtype-specific trials, and international collaboration will be essential to establish evidence-based treatment standards for this diverse and understudied population.

5033 Background: After FDA approval on March 23, 2022, lutetium (Lu 177 ) vipivotide tetraxetan became an established treatment option for advanced prostate cancer, but real-world survival outcomes and prognostic factors remain incompletely described. Methods: We conducted a retrospective cohort study in Epic Cosmos with the largest to date reported cohort of patients with prostate cancer who initiated lutetium Lu 177 vipivotide tetraxetan after FDA approval to Dec 20, 2025, ensuring at least one month of follow-up prior to the query date. OS was measured from the medication start date to death, or censoring at last encounter. Kaplan–Meier methods were used for survival analysis. Univariable Cox proportional hazards models, adjusted for false discovery rate (FDR), were used to assess associations between OS and clinical variables. Results: The cohort included 6464 patients with a median age of 74.0 years (IQR: 38–100). The cohort was predominantly White (75.2%) and Black/African American (19.9%). Kaplan-Meier analysis showed OS probabilities of 85.4%, 67.2%, 42.8%, and 23.8% at 6, 12, 24, and 36 months, respectively, comparable to results reported in the Phase 3 VISION trial. Worse survival was significantly associated with a history of tobacco use (HR 1.22 [1.11–1.33], FDR <0.01) and higher Charlson Comorbidity Index scores (HR 1.04 [95% CI 1.02–1.06], FDR <0.01). Conversely, higher BMI (HR 0.98 [0.97–0.99], FDR <0.01) was associated with improved survival. Baseline laboratory markers of nutritional and hematologic reserve were strongly protective, including higher Albumin (HR 0.39 [0.35–0.43], FDR <0.01), Total Protein (HR 0.81 [0.74–0.89], FDR <0.01), Hemoglobin (HR 0.77 [0.75–0.79], FDR <0.01), RBC count (HR 0.53 [0.49–0.57], FDR <0.01), and MCHC (HR 0.88 [0.86–0.91], FDR <0.01). Inflammatory and immune markers showed distinct prognostic value: higher Eosinophils (HR 0.38 [0.25–0.58], FDR <0.01) and Lymphocytes (HR 0.69 [0.64–0.76], FDR <0.01) were associated with better outcomes, while higher Basophil-to-Lymphocyte Ratio (HR 2.10 [1.17–3.78], FDR = 0.02), RDW (HR 1.16 [1.14–1.19], FDR <0.01), and Neutrophils (HR 1.06 [1.04–1.08], FDR <0.01) were associated with worse survival. Higher electrolytes (Sodium, Chloride, Potassium, Bicarbonate) were generally associated with lower hazard, likely reflecting better physiologic homeostasis. Conclusions: In this large real-world cohort of prostate cancer patients treated with Lu 177 vipivotide tetraxetan, overall survival was strongly influenced by tobacco use, comorbidity burden, and baseline laboratory markers reflecting nutritional status, hematological reserves, and immunity. These findings highlight the importance of physiologic reserve and inflammatory state in shaping outcomes with this radioligand therapy and may inform risk stratification and care strategies in routine clinical practice.

4526 Background: Despite available tyrosine kinase inhibitors (TKIs) and immune checkpoint inhibitors (ICIs), reliable biomarkers guiding frontline advanced RCC treatment remain limited. Existing signatures lack generalizability across therapeutic regimens. We developed a data-driven machine learning (ML) framework to predict survival outcomes and therapeutic response. Methods: Transcriptomic and clinical data were analyzed from 733 patients across two frontline treatment cohorts, sunitinib (n = 376) and avelumab plus axitinib (n = 357), derived from JAVELIN Renal 101. A multi-algorithm feature selection framework was applied to identify transcriptomic signatures associated with progression-free survival (PFS) and overall survival (OS). Prognostic performance was evaluated using the concordance index (C-index). Predictive models for therapeutic response, including disease control, were developed using PFS-derived gene signatures and assessed by area under the curve (AUC). External validation was performed in an independent cohort from The Ohio State University Total Cancer Care (OSU TCC) (n = 114). Results: ML-derived transcriptomic models consistently stratified patients into distinct risk groups with improved prognostic discrimination compared with standard clinical classifiers. In the sunitinib cohort, the best-performing models achieved C-indices of 0.72 for PFS and 0.81 for OS, outperforming IMDC (0.59 and 0.66). In the validation set of the sunitinib cohort, high-risk patients exhibited worse outcomes, with hazard ratios of 3.00 for PFS (P < 0.001, 95% CI, 2.06–4.39) and 13.42 for OS (P < 0.001, 95% CI, 7.78–23.13). In the avelumab plus axitinib cohort, C-indices reached 0.70 for PFS and 0.79 for OS. Consistent risk stratification was observed in the validation set, with hazard ratios of 3.16 for PFS (P < 0.001, 95% CI, 2.07–4.83) and 4.69 for OS (P < 0.001, 95% CI, 2.65–8.30). For response prediction, the models demonstrated predictive performance, with the Naive Bayes model achieving a validation AUC of 0.83 for disease control in both sunitinib and avelumab plus axitinib cohorts. The model showed significant risk stratification in an external validation cohort (OSU TCC). Conclusions: This study presents a multi-cohort transcriptomic framework with prognostic and predictive utility in advanced RCC. By outperforming established clinical risk classifiers and enabling prediction of regimen-specific therapeutic responses, this ML-based approach supports biomarker-informed frontline treatment selection.

Active surveillance (AS) management for patients with small renal masses (SRMs) is increasing globally, but questions remain regarding optimal AS practice. This review provides an evidence-based perspective on current controversies in SRM AS management. Considerable variation in AS utilization likely reflects non-standardization of patient selection criteria and differences among providers and healthcare settings. While most expert-consensus guidelines still restrict AS candidacy to patients with very small (< 1-2cm) renal tumors or significant health issues, increasing research supports AS to be an acceptable option for tumors up to 4 cm and a preferred option for many tumors up to 2 cm. For younger patients, AS appears oncologically safe but efficacy for long-term avoidance of delayed intervention (DI) remains unknown. Progression definitions for triggering DI still lack standardization, but there is general consensus for including thresholds based on some or all “GLASS” criteria [Growth rate; Longest tumor diameter; Adverse biopsy histology; Stage (≥ cT3a); Symptomatology]. SRM biopsy during AS can diagnose benign neoplasm with high accuracy to negate the need for DI, particularly when corroborated by computed tomography (CT) enhancement-based approaches such as tumor:cortex Peak Early Enhancement Ratio (PEER) scoring. In contrast, the value for biopsy in adverse histology detection remains more controversial. Advanced imaging modalities, including 99mTc-sestamibi single photon emission computed tomography (SPECT)/CT and [89Zr]Zr-girentuximab positron emission tomography (PET)/CT, may serve as useful adjuncts to biopsy during AS, while providing limited accuracy alone when biopsy is deferred. Future investigative efforts should focus on standardizing AS protocols, refining progression criteria for intervention, and addressing uncertainties about longer-term outcomes, particularly in younger patients.

Decisions regarding the use of adjuvant systemic therapy in genitourinary (GU) malignancies—including bladder, kidney, and prostate cancers—are currently driven by clinicopathologic risk factors, which incompletely capture individual risk of residual disease. Consequently, patient selection for adjuvant treatment remains imprecise, leading to both overtreatment of cancers unlikely to recur and undertreatment of those with occult residual disease. Circulating tumor DNA (ctDNA), a minimally invasive liquid biopsy biomarker for minimal residual disease, has emerged as a promising tool to refine adjuvant treatment decision-making. Detection of ctDNA reflects persistent tumor-derived genomic material and often precedes radiographic recurrence, whereas ctDNA negativity is consistently associated with favorable oncologic outcomes. In this review, we summarize the evolving evidence supporting the use of ctDNA to guide adjuvant therapy decisions in bladder, kidney, and prostate cancers. This is not a comprehensive review on all of the potential applications of ctDNA in these malignancies. Rather, we aim to highlight disease-specific, adjuvant-guiding applications, including post-neoadjuvant and post-cystectomy decision-making in bladder cancer and emerging proof-of-concept data in renal cell carcinoma, and explore the potential application of ctDNA in the post-prostatectomy setting. Collectively, these data suggest that ctDNA may enable a paradigm shift toward biologically informed escalation and de-escalation of adjuvant therapy across GU malignancies, while underscoring the need for prospective validation in biomarker-driven clinical trials.

e23447 Background: Adjuvant pembrolizumab improves overall and disease-free survival in high-risk renal cell carcinoma (RCC) patients; however, treatment-related toxicity remains a serious concern. We evaluated toxicity patterns and associated survival outcomes among patients receiving adjuvant pembrolizumab following nephrectomy in a large real-world cohort. Methods: We conducted a retrospective cohort study in Epic Cosmos, identifying the largest-to-date RCC cohort undergoing nephrectomy who received post-nephrectomy adjuvant pembrolizumab. The study period spanned from the FDA approval date (Nov 17, 2021) to Dec 20, 2025, ensuring at least one month of follow-up prior to the query date. Patients were excluded if they had metastatic systemic therapy exposure and/or metastatic diagnosis codes at any time before or within 90 days after nephrectomy. Overall survival (OS) was estimated using the Kaplan–Meier method. Logistic regression models with false discovery rate (FDR) correction were used to identify factors associated with toxicity (initiation of post-adjuvant high-dose systemic corticosteroids was used as a proxy for clinically significant immune-related adverse events). Results: The cohort included 2,656 patients with a median age of 64 years; 67.8% were male, and 86.5% were White. During follow-up, 400 patients (15.1%) initiated high-dose systemic corticosteroids, which was higher than reported in the KEYNOTE-564 trial (7.4%). Steroid use was associated with significantly worse OS compared with no steroid use (OR 1.99, 95% CI 1.21–3.27; p < 0.01). Laboratory factors significantly associated with toxicity requiring high-dose steroids included high eosinophils (OR: 2.44 [1.51-3.95], FDR < 0.01), eosinophil-to-lymphocyte ratio (OR: 2.44 [1.33-4.35], FDR = 0.02), RDW (OR: 1.07 [1.02-1.22], FDR = 0.01), and BUN (OR: 1.02 [1.003-1.03], FDR = 0.03). Higher values of albumin (OR: 0.62 [0.47-0.81], FDR < 0.01), hemoglobin (OR: 0.90 [0.84-0.96], FDR < 0.01), MCHC (OR: 0.89 [0.82-0.96], FDR = 0.02), and hematocrit (OR: 0.97 [0.94-0.99], FDR = 0.03) were associated with lower toxicity risk. None of the baseline clinical/ demographic features were significant, including age, sex, or BMI. Conclusions: In this large real-world cohort of patients with RCC receiving adjuvant pembrolizumab following nephrectomy, treatment-related toxicity requiring high-dose corticosteroids occurred in approximately 15.1% of patients and was associated with significantly worse overall survival. Baseline inflammatory and hematologic markers were associated with toxicity risk. These findings highlight the importance of early toxicity risk stratification and proactive management in the adjuvant immunotherapy setting.

4556 Background: There is an unmet need to develop rapidly deployable and reliable biomarkers to guide treatment decisions in clear cell renal cell carcinoma (ccRCC). Transcriptome-based molecular classification is promising in predicting differential clinical outcomes to angiogenesis blockade alone or with an immune checkpoint inhibitor (ICI), but these approaches require molecular profiling that is costly and time-consuming. This study evaluates whether explainable artificial intelligence (AI) can accurately predict molecular classes of ccRCC from diagnostic H&E slides. This approach enables scalable, pathology-based assessment of treatment response–related biology without the need for additional tissue or sequencing. Methods: We acquired digital whole slide images of H&E stained primary ccRCC tumors from TCGA, OSU Total Cancer Care Alliance, and an in-house built set of selected biopsies. RNA-Seq cluster assignments from IMmotion151 study were reconstructed from published gene log-fold-change cluster enrichment scores and non-negative least squares regression on matching RNA-Seq of our samples. After assigning samples to their highest scoring group, we trained a multi-group attention-based multiple-instance learning (ABMIL) classifier to predict RNA-Seq groups from digital whole slide images broken into 112um patches and encoded using UNI foundation model embeddings. Results: A total of 555 cases with both H&E and RNA-seq data were included. Class prediction from RNA-Seq were 40% Angio-Stromal, 30% Complement-Ox, 16% Angio, 8% Teff-Prolif, 4% Prolif, 2% Stromal-Prolif and 0% snoRNA. Predicting these classes from H&E-stained images, showed AUROC values of 0.76 (Angio-Stromal), 0.78 (Complement-Ox), 0.83 (Angio), 0.85 (Teff-Prolif), 1.00 (Prolif) and 0.91 (Stromal-Prolif) respectively. Similar AUROC values with more modest curves were seen on a hold-out set (10%) where Angio-Stromal/Complement-Ox (0.61/0.61) and Teff-Prolif (0.59) were the lowest AUROC values and Prolif (0.99) was the highest. Importantly, incorrect predictions most often yielded a group prediction where the predicted group shared some biological identity with the ground truth group label (eg. Angio-Stromal and Angio). We also utilized the attention values from ABMIL to evaluate spatial prediction saliency, which showed the model focused primarily on tumor regions, even for predictions of primarily stromal defined classes. Conclusions: Our results demonstrate that diagnostic H&E slides contain histologic features that can predict ccRCC molecular subsets using explainable AI. Supporting scalable pathology-based inference of tumor biology linked to treatment response.

TPS4629 Background: Immunotherapy doublet combinations (+/- vascular endothelial growth factor receptor-tyrosine kinase inhibitor [VEGFR-TKI]) are established for front-line treatment of metastatic, clear cell renal cell carcinoma (ccRCC). However, their role in the perioperative setting for locoregional ccRCC remains to be defined. We designed the EXPLORE-RCC trial to evaluate neoadjuvant ZANZA (novel, next generation VEGFR-TKI with short half-life) plus NIVO (PD-1 inhibitor) in patients with locally advanced ccRCC, where the combination has the potential to shrink the primary tumor, increase resectability, and/or allow a partial nephrectomy or minimally invasive approach. Methods: In this multisite, phase 2, open-label, single-arm trial coordinated by the Hoosier Cancer Research Network, subjects will receive ZANZA 60mg orally once daily plus NIVO intravenously per standard of care (SOC) dosing for 12 weeks (w), followed by restaging scans and an adaptive approach: (1) subjects who are deemed operable will undergo resection (Cohort A); (2) subjects who remain inoperable can receive up to 48w total of ZANZA plus NIVO (Cohort B1) with the option to undergo resection when deemed operable; or (3) subjects who have disease progression will stop protocol mandated therapy and receive subsequent SOC treatment (Cohort B2). The main inclusion criteria include age ≥ 18 years, ECOG Performance Status of 0-1, histologically confirmed ccRCC, and locally advanced (cT3/4, N0-1, with or without tumor thrombus) disease and/or deemed surgically challenging per surgeon discretion. Non-measurable metastasis per RECIST 1.1 criteria, including soft tissue metastasis with longest diameter <10mm or distant lymph nodes <15 mm in short axis are allowed. Main exclusion criteria are non-clear cell histology, measurable metastatic disease per RECIST 1.1 criteria, and prior systemic treatment for ccRCC. The primary endpoint is overall response rate (ORR) after 12w of therapy. This single arm trial is powered to detect an improvement in ORR from a historical rate of 30% to 45%, with 80% power and a 0.05 one-sided type I error. Estimating 10% drop out, 69 subjects will be enrolled. Key secondary/exploratory endpoints include efficacy outcomes (conversion to operable, disease free survival, overall survival, pathologic response), safety, surgery-related complications (including Clavien-Dindo), and biomarker correlatives. The trial is actively enrolling (ClinicalTrials.gov NCT06794229) at UT Southwestern and opening at Ohio State, Fox Chase Cancer Center, Virginia Commonwealth, Northwestern University, and Washington University in St Louis. Clinical trial information: NCT06794229 .