Zakharia, Yousef

464 Background: Based on LITESPARK-005 trail, Belzutifan was FDA-approved to treat advanced RCC following ICI and a VEGF-TKI. We conducted a retrospective cohort study to report the real-world outcomes of Belzutifan in pre-treated RCC patients. Methods: A retrospective chart review of all patients who received Belzutifan at the Mayo Clinic Comprehensive Cancer Center between Dec 2023 and Sep 2025 was conducted. Patients treated for sporadic RCC were eligible; those with von Hippel–Lindau disease, non-RCC pathologies (e.g., Pheochromocytoma, ovarian cancer) were excluded. Radiologic response was assessed by trained curators using RECIST-defined criteria, approximated through systematic review of radiology reports with clinician adjudication when needed. Progression-free survival (PFS), defined as the time from treatment initiation to radiographic progression or death, was estimated using the Kaplan–Meier method. Non-progressors were censored at the last radiology assessment. Patients who discontinued therapy for non-progression reasons were censored at the last radiology assessment prior to discontinuation. Any-cause hypoxia and anemia were reported using CTCAEv5 definitions. Results: A total of 158 patients were identified; 83 (52.5%) who received Belzutifan for sporadic RCC were included. The remaining were excluded for VHL disease (68, 43%) or other pathologies (7, 4.4%). Median follow up was 12 months, 67% were male, median age was 70 (range 39, 94) with 57 patients (69%) were ≥ 65. 28 patients (34%) had a poor IMDC score at baseline. The cohort received a median of 3 previous lines of therapy (range 1,8). Median treatment duration was 3 months (IQR: 1-9.5). Median PFS was 5.7 months (95% CI, 3.8–8.7). At 12 and 18 months, 23.1% and 13.9% of patients, respectively, remained alive and progression-free. Corresponding OS rates at these time points were 60.2% and 51.5%. A confirmed ORR occurred in 12 patients (14.4%). Hypoxia occurred in 44 (53%) patients, median onset 31 days (range 1–270) and 29 (34.9%) required hospitalizations. Median hemoglobin (Hb) levels at baseline were 12.65 g/dl (range, 7.2-15.5), and 68 (82%) patients developed Hb decline on Belzutifan, 27 (32.5%) required transfusions. Conclusions: In an older, high-risk cohort with higher number of prior lines of therapy, Belzutifan yielded PFS/OS and ORR landmarks comparable to the trial supporting its effectiveness in the real world. Outcomes compared with LITESPARK-005 trial. Variable Real world cohort (Mayo Clinic) LITESPARK-005, Belzutifan arm Median PFS (months, 95% CI) 5.7 (3.8-8.7) 5.6 (3.9-7) 12-month PFS rate (%, 95% CI) 23.1% (14.4-33.4) 33.4% (28.4-33.5) 18-month PFS rate (%, 95% CI) 13.9% (7.7-23.9) 24% (19-29.4) 12-month OS rate (%, 95% CI) 60.2% (48.9-70.8) 67.9% (62.9-72.4) 18-month OS rate (%, 95% CI) 51.5% (40.6-62.9) 55.2% (50-60.1) ORR (%, 95% CI) 14.4% (7.7-23.9) 21.9% (17.8-26.5)

405 Background: Clinical trials are critical to advancing prostate cancer treatment, yet patient enrollment remains a major bottleneck. Despite strong interest in AI for trial matching, real-world use remains limited due to reasons such as complex infrastructure requirements. To address this, we developed a lightweight, scalable AI framework leveraging the Google Healthcare Search API—requiring minimal technical expertise—to automate trial eligibility screening. Methods: We used a pre-trained GPT-5 large language model (LLM) to decompose the eligibility criteria of 13 prostate cancer clinical trials into 269 YES/NO questions, such that for an eligible patient of a given trial, the chart review would yield YES for inclusion and NO for exclusion questions. From 348 patients enrolled in one of the trials, we built a dataset linking each eligibility question to each patient, resulting in 4,947 patient–question pairs (2,034 inclusion pairs with YES labels and 2,913 exclusion pairs with NO labels). The task was framed as binary classification. During evaluation, for each patient–question pair, the LLM extracted search phrases from the question to retrieve relevant EHR information via the Google Healthcare Search API, then used the question and retrieved information to predict YES or NO responses. Performance was measured using accuracy, precision, recall, specificity, and F1 score. Results: Across 4,947 question–patient pairs, our framework achieved 0.81 accuracy, 0.85 precision, 0.65 recall, 0.92 specificity and a F1 score of 0.74. Results for different phases of trials is reported in Table 1, which demonstrates the approach’s robustness across trial phases. Predictions for exclusion criteria were highly precise, while inclusion criteria were more challenging. Most errors were observed in criteria involving complex nested logical conditions, interpretable clinical definitions and data not explicitly measurable or recorded in the EHR (e.g., planned treatments or clinician-assessed scores). Conclusions: This work demonstrates a practical AI framework to support clinical trial matching. The system can identify complex disease states (biochemical recurrence vs radiographic metastasis), castration status (sensitive, resistant) and genomics. Future work should focus on developing human-in-the-loop supervision and improving question decomposition to reduce errors in complex eligibility criteria. Screening performance of the proposed framework across different phases of trials. Trial Phase #Patient-Question Pairs #YES/NO labels Accuracy Precision Recall Specificity F1 score I, II, I/II 4,227 Yes: 1,735 No: 2,492 0.80 0.84 0.66 0.92 0.74 III 720 Yes: 299 No: 421 0.82 0.90 0.63 0.95 0.74 All 4,947 Yes: 2,034 No: 2,913 0.81 0.85 0.65 0.92 0.74 #YES/NO labels: The number of patient-question pairs that are labeled YES/NO among total patient-question pairs of the same row.

Abstract Background: Clear cell renal cell carcinoma (ccRCC), metastatic castration-resistant prostate cancer (mCRPC), and glioblastoma (GBM) are highly treatment-refractory tumors characterized by elevated TGF-β1, a key suppressor of antitumor immunity and antigen presentation. Because CAR-T cells infiltrating these tumors experience persistent physiologic TGF-β exposure, assessing CAR-T functional resilience across increasing TGF-β concentrations is critical for determining therapeutic feasibility. Methylseleninic acid (MSA), a pharmacologic selenium compound, potently inhibits TGF-β1, PD-L1, and VEGF with minimal off-target toxicity. FN14, the TWEAK receptor and a metastasis driver, is selectively overexpressed in these malignancies, making it a high-specificity CAR target. Methods: We developed second-generation anti-FN14 CARs containing CD28 or 4-1BB costimulatory domains and a CD3ζ signaling motif, then lentivirally transduced into primary human CD4+ and CD8+ T cells. Cytotoxicity against FN14+ ccRCC, mCRPC, GBM lines and patient-derived cells was assessed using LDH release and xCELLigence assays. Effector function was evaluated through intracellular cytokine profiling, multiplex analysis, and phenotypic characterization by flow cytometry. CAR-T persistence in TGF-β-rich conditions was measured using CCK-8 proliferation assays, and Ki-67 and activation/exhaustion markers (PD-1, CXCR3) in the presence of 0-10 ng/mL TGF-β. MSA’s immunomodulatory and synergistic effects were tested at physiologically concentrations to measure impacts on CAR-T viability, metabolic activity, cytokine secretion, and tumor cell susceptibility. Results: Anti-FN14 CAR-T cells mediated rapid, antigen-specific lysis across all tumor types, achieving >50% specific killing at a 1:1 E:T ratio. MSA (2.5-5 µM) reduced tumor PD-L1 and TGF-β expression by >40% and enhanced CAR-T metabolic activity, IL-2, and IFN-γ secretion. CAR-T cells maintained comparable proliferation and activation in 0-5 ng/mL TGF-β, indicating that antigen-driven signaling counteracted low-to-moderate TGF-β-mediated suppression. Ex vivo CAR-T manufacturing with MSA (2.5 µM) improved cytotoxicity and persistence versus untreated CAR-T cells (p < 0.01). MSA’s effects were dose- and schedule-dependent and remained within human-relevant exposure ranges without detectable toxicity. Conclusion: MSA enhances anti-FN14 CAR-T cytotoxicity, metabolic fitness, and sustained effector activity by suppressing tumor-derived TGF-β1 and PD-L1 and by directly improving CAR-T functional capacity. Consistent with this mechanism, physiological TGF-β levels (0-5 ng/mL) did not significantly impair CAR-T proliferation or activation, demonstrating intrinsic resilience of FN14 CAR-T cells in TGF-β-rich environments. As a clinically relevant TGF-β1 inhibitor and active metabolite of seleno-L-methionine, MSA represents a readily translatable strategy to reduce CAR-T exhaustion and enhance efficacy in TGF-β-rich solid tumors including ccRCC, mCRPC, and GBM. Citation Format: Obed B. Amissah, Casey Ager, Yousef Zakharia, Youcef M. Rustum, Gloria B. Kim. Anti-FN14 CAR-T cells overcome TGF-β-mediated suppression, and their synergy with methylseleninic acid enhances cytotoxicity and effector function in kidney, prostate, and brain tumors [abstract]. In: Proceedings of the AACR Immuno-Oncology Conference (AACR IO): Discovery and Innovation in Cancer Immunology: Revolutionizing Treatment through Immunotherapy; 2026 Feb 18-21; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Immunol Res 2026;14(2 Suppl):Abstract nr C010.

Abstract Background Pembrolizumab is approved for advanced cutaneous melanoma (aCM). Cabozantinib, an oral multi‐tyrosine kinase inhibitor, has demonstrated antitumor activity as monotherapy or in combination with anti‐PD‐1 therapy in malignancies. The objective of this study was to determine the safety and efficacy of cabozantinib and pembrolizumab for patients with aCM. Methods This phase 1b/2 study enrolled 28 patients with unresectable aCM. In phase 1b, escalating dose levels of cabozantinib (20 mg, 40 mg, and 60 mg) were administered concurrently with pembrolizumab 200 mg intravenously every 3 weeks using a 3 + 3 design to determine recommended phase 2 dose (RP2D). In phase 2, patients received cabozantinib at RP2D in combination with pembrolizumab using a Simon 2 stage design. Primary end point of phase 2 was overall response rate (ORR). Secondary end points included disease control rate, progression‐free survival (PFS), and overall survival (OS). Results Phase 1b enrolled eight patients, cabozantinib 40 mg daily dose level was selected as RP2D. Response rate in stage 1 exceeded predefined criteria for proceeding to expansion phase; however, phase 2 was terminated after 20 patients due to low accrual in the setting of evolving standard of care. Among all treated patients, the most common grade ≥3 toxicities were hypertension ( n = 10, 36%), hypokalemia ( n = 5, 18%), hypophosphatemia ( n = 4, 14%), and ALT elevation ( n = 4, 14%). Among 20 patients treated in phase 2, ORR was 45%, median PFS was 6.6 months, and median OS was 29.5 months. Conclusions Cabozantinib and pembrolizumab combination was explored in treatment‐naive aCM. Toxicity was consistent with known profiles, but discontinuation rates were notable.

Non-muscle-invasive bladder cancer (NMIBC) comprises approximately 75% of new bladder cancer cases and generally carries a favorable prognosis, yet high rates of recurrence and progression necessitate close surveillance with frequent cystoscopies and repeated transurethral resections. Upfront treatment for high-risk disease is typically Bacillus Calmette-Guérin (BCG), although combinations with immune checkpoint inhibitors have reported results. Patients with BCG-unresponsive, intolerant, or refractory disease represent a subset of patients with high risk of progression, with early radical cystectomy being the standard approach for this setting. Global BCG shortages and the substantial impact of cystectomy on quality of life underscore the need for therapeutic alternatives. Over the past decade, investigational trials in immunotherapy have expanded treatment options for BCG-unresponsive NMIBC with CIS, leading to FDA approval of intravesical nadofaragene firadenovec, nogapendekin alfa-inbakicept, and systemic pembrolizumab. This narrative review summarizes developments in intravesical and systemic immunotherapies for NMIBC, highlights ongoing trials, and addresses controversies in trial design, treatment sequencing, comparative efficacy, and safety.

PURPOSE Previous studies suggest that SPOP mutations result in increased sensitivity to androgen receptor pathway inhibitors (ARPIs) but are limited by lack of granular data. We hypothesize that SPOP mutations are associated with improved outcomes across the spectrum of advanced prostate cancer (PC). METHODS Using the real-world clinicogenomic Prostate Cancer Precision Medicine Multi-Institutional Collaborative Effort database, we analyzed outcomes based on SPOP mutation status. The primary end point was overall survival (OS) from the diagnosis of metastatic disease. Secondary end points included real-world progression-free survival (PFS) and PSA90 response. RESULTS Among 2,097 patients with metastatic PC, 5.5% (N = 115) had SPOP -mutated tumors. Compared with SPOP wild-type, patients with SPOP mutations were older at diagnosis (median 65 v 63 years; P = .001) and had higher (≥8) Gleason sum (68% v 54%; P = .02), higher incidence of lung metastasis (17% v 6%; P = .001), and increased frequency of intraductal features (13% v 5%; P < .001). SPOP mutations were associated with improved PSA90 response with first ARPI exposure in the castrate-resistant setting (60% v 40.6%; OR, 2.20 [95% CI, 1.15 to 4.19]; P = .02) but not in the castrate-sensitive setting (78.9% v 71.5%; OR, 1.49 [95% CI, 0.66 to 3.37]; P = .43). Median PFS with first ARPI did not differ in SPOP- mutated versus wild-type group in both the castrate-sensitive (24.2 v 19.2 months; hazard ratio [HR], 0.80 [95% CI, 0.49 to 1.32]; P = .39) and castrate-resistant settings (15.0 v 12.4 months; HR, 0.81 [95% CI, 0.58 to 1.12]; P = .20). In multivariable analysis, SPOP mutations were associated with improved OS (HR, 0.65, P = .02). CONCLUSION SPOP mutations were associated with longer OS despite the presence of aggressive clinical features. The distinct clinical and molecular features of SPOP -mutated PC support its consideration as a unique molecular subtype with prognostic implications.

Background Immune-related adverse events (irAEs) remain largely unpredictable, potentially affecting multiple organ systems and occurring at almost any point during and even occasionally after immune checkpoint inhibitor (ICI) treatment. To identify populations at risk for these immune-mediated toxicities, we analyzed genetic characteristics and immune markers associated with clinically significant irAEs. Methods We carried out a genome-wide association study on 373 white patients receiving ICI treatment. We identified single nucleotide polymorphisms associated with irAEs. Blood cytokine profiling and peripheral blood mononuclear cell RNA sequencing were performed at pretreatment baseline and 6–8 weeks after ICI initiation. Findings were validated in two external cohorts. Results We identified genetic haplotypes in VWA8 (Von Willebrand Factor A Domain Containing 8) , OSBPL6 (Oxysterol Binding Protein Like 6), and ADAMTS9-AS2 (ADAM Metallopeptidase With Thrombospondin Type 1 Motif 9 Antisense RNA 2) associated with grade ≥2 irAEs. Patients carrying risk haplotypes for one or more genes exhibited significantly greater rates of grade ≥2 (OR 3.02; 95% CI 1.83 to 5.02; p<0.001), grade ≥3 (OR 3.59; 95% CI 1.93 to 6.64; p<0.001), and multiple type irAE (OR 2.60; 95% CI 1.53 to 4.39; p<0.001). Serum CCL3 levels were significantly elevated in individuals carrying risk haplotypes (p=0.03). Gene expression analysis demonstrated activated autoimmune and inflammatory pathways in the genetic risk group. Conclusions Novel polymorphisms in VWA8, OSBPL6, and ADAMTS9-AS2 may impact immune pathways, promote inflammation, potentiate autoimmune phenotypes, and convey risk of irAE in ICI-treated patients.

5108 Background: We previously proposed a hybrid framework combining LLMs and rule based algorithm (RBA) for automating risk stratification in locPCa. Herein, we aim to validate the risk stratification agent (RSA) in a prospective cohort, develop & evaluate the treatment recommendation agent (TRA) based on NCCN guidelines, and develop an interactive interface to facilitate clinicians for accurate risk stratification and treatment recommendations at the point of care. Methods: This study included pts with locPCa (2004-2024) presenting at Mayo Clinic with at least 1 positive prostate biopsy and MRI report available. For RSA prospective validation, GPT4 extracted key phenotypic variables (PSA, T stage, prostate volume, number of cores, Gleason patterns, grade group) from unstructured MRI and biopsy reports using a zeroshot prompt. An RBA then classified pts into NCCN risk groups. The agent performance was compared with the treating clinician's documentation and evaluated against gold-standard labels manually annotated by two independent clinicians. For development of TRA, two experiments were performed using GPT4 with and without retrieval-augmented generation (RAG) to generate treatment plans. Generated treatment plans were evaluated using NCCN guideline-informed treatment decision tree based algorithm (DTA). Evaluation metrics, weighted – accuracy (acc) and F1, were computed. A clinician facing interface (lisr.org/risk) was developed to provide accurate risk stratification and treatment plans. Results: A total of 858 pts were included (500 for prospective validation, 358 for treatment recommendations). Prospective validation for RSA demonstrated a higher F1 score of 0.89 compared to the treating clinician (F1: 0.58). Treatment recommendation experiments showed that GPT4 with RAG achieved higher acc (64% full – all correct treatment options and 36% partial – at least 1 correct treatment option) compared to GPT4 alone (35% and 65%, respectively). Sensitivity analysis using DTA-informed GPT4 note generation achieved 94% full acc and 6% partial acc. GPT4 alone generated hallucinated treatment options in 71% of cases, while GPT4 with RAG reduced this to 32%. Conclusions: The multi-agent framework based on LLM and RBA achieves high accuracy in risk stratification and treatment recommendation for locPCa. A multi-agent framework with an interactive interface holds high promise to enable efficient, accurate decision-making, and improve locPCa management at the point of care Performance evaluation. RSA(acc; F1) % TRA(full acc; partial acc) % Clinician RSA* GPT4 RAG+GPT4 DTA+GPT4 Overall 60; 58 89; 89 29; 71 64; 36 94; 6 V. High 94; 33 96; 96 55; 45 69; 31 93; 7 High 46; 52 92; 89 - - - Int. Unf 80; 61 91; 90 5; 95 38; 62 93; 7 Int. Fav 57; 64 84; 87 0; 100 98; 2 100; 0 Low 57; 65 87; 80 100; 0 95; 5 90; 10 V. Low 8; 13 50; 67^ - - - *Statistical significance (p<0.01) except for ^V. Low.

e17155 Background: Localized PCa is classified into six NCCN risk categories, each with specific treatment recommendations. However, treatment concordance across these categories and its variation by race in clinical practice remain unexplored. Therefore, we aim to describe patterns of guideline-concordant treatment receipt for localized PCa across risk groups and race. Methods: Surveillance, Epidemiology, and End Results (SEER) database (2018–2020) was queried to identify patients with localized PCa from 17 registries. Data regarding clinical T stage, Gleason patterns, PSA level, biopsy cores and initial treatment received (radiation, radical prostatectomy, systemic therapy) was obtained. Each patient was then stratified into one of six NCCN-based risk categories using a rule-based algorithm. Using the stratified risk category of each patient, treatment recommendations were obtained from the NCCN guidelines. Concordance was assessed by comparing the received treatment and guideline-recommended treatment. A focused bi-variate logistic regression analysis was performed adjusting for risk groups, and race. Odds ratio (OR) with 95% confidence intervals (CI) were computed to quantify the magnitude of guideline-discordant treatment receipt. Results: This analysis included 69,584 patients with localized PCa (White: 53,875 [77.4%]; Black: 11,265 [16.2%]; Asian/Pacific Islander: 4,133 [5.9%]; American Indian/Alaska Native: 311 0.5%]). In terms of risk groups, patients in higher risk categories had increased odds of discordance compared to the lower risk groups (Table). In terms of race, Black men had significantly higher odds of receiving guideline-discordant therapy (OR:1.67, 95% CI:1.58–1.76), while no statistically significant difference was observed with American Indian/Alaska Native men (OR:1.21, 95% CI: 0.92–1.61) and Asian/Pacific Islander men (OR:1.05, 95% CI:0.97–1.14) compared to White men. Conclusions: Population level data, based on limited sample size in some groups, suggests that treatment concordance with NCCN guidelines varies by risk group and race in localized PCa. Black patients, and those with higher risk groups were more likely to receive guideline-discordant therapy. These findings highlight the need for strategies and prospective studies at individual patient level to evaluate and enhance guideline adherence to promote personalized care for these patients. Variable Discordant Treatment (%) OR (95% CI) White 22168 (41.1) REF Black 5653 (47.5) 1.67 (1.58-1.76) * Asian/Pacific Islander 1822 (44.1) 1.05 (0.97-1.14) American Indian/Alaska Native 191 (61.4) 1.22 (0.92- 1.61) Very Low Risk 770 (9) REF Low Risk 146 (2) 0.16 (0.13-0.19) * Favorable Risk 35 (0.4) 0.03 (0.02-0.04) * Unfavorable Risk 15125 (83.2) 36.30 (33.72-39.25) * High/Very High Risk 13441 (50) 7.32 (6.83-7.86) * * p <0.05.