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454 Background: Immune checkpoint inhibitor (ICI)-based combination therapy has become the standard of care for advanced renal cell carcinoma (RCC). A pathologic complete response (pCR) in the primary tumor may be observed in up to one-third of patients; however, data on the outcomes of these patients remain limited. This study aimed to evaluate the clinical outcomes of patients who achieved a pCR following ICI therapy. Methods: Patients with advanced RCC who underwent nephrectomy following ICI therapy were evaluated across five high-volume U.S. academic centers between 2015 and 2023. Clinical characteristics and outcomes were compared between those with and without a pCR in the primary tumor (ypT0N0/Nx). Multivariable logistic regression models were used to identify factors associated with pCR. Recurrence-free (RFS) and overall survival (OS) rates were estimated using the Kaplan-Meier (KM) method. Results: A total of 182 patients were included (Table 1). Among all patients, downstaging to ≤ypT1N0/Nx was observed in 45 patients (25%), of whom 21 (11%) achieved a pCR. In multivariable analysis, the presence of clinical thrombus was marginally associated with a lower likelihood of achieving pCR (odds ratio [95% CI]: 0.39 [0.15–1.00], p=0.06). During a median follow-up of 25 months, 70 patients (38%) experienced recurrence, including 4 (2%) in the pCR group. Median time to recurrence was 7.5 months. KM analysis demonstrated a higher estimated 5-year RFS in the pCR group compared to those with residual disease; however, the difference was not statistically significant (68% vs. 54%, p=0.2). In addition, OS rates were comparable between the two groups. Conclusions: In our cohort, 11% of patients who underwent nephrectomy following ICI therapy for advanced RCC showed pCR, which correlated with improved oncologic outcomes. Despite the lower recurrence rates observed in the pCR group, sustained long-term surveillance remains necessary due to the continued, albeit reduced, risk of disease recurrence. Clinical characteristics of patients who underwent post-ICI nephrectomy, stratified by their pathologic complete response (pCR). Variable pCR (n=21) No pCR (n=161) p-value Median (IQR) age, year 61 (56 – 70) 64 (56 – 71) 0.46 Gender (male), n (%) 15 (71) 118 (73) 0.8 Tumor advancement, n (%) Locally advanced Metastatic 2 (10)19 (90) 36 (22)125 (78) 0.26 Risk group (for metastatic), n (%) Favorable Intermediate Poor 3 (25)6 (50)3 (25) 38 (34)59 (54)13 (12) 0.42 ICI regimen, n (%) ICI monotherapy ICI+ICI ICI+TKI 4 (19)9 (43)8 (38) 46 (28)64 (40)51 (32) 0.64 Immunotherapy cycles (>4), n (%) 8 (50) 49 (37) 0.42 Median (IQR) clinical tumor size, cm 9.3 (6.7 – 11.9) 8.4 (6.6 – 12) 0.68 Clinical nodal involvement, n (%) 8 (38) 53 (33) 0.63 Clinical thrombus, n (%) 12 (57) 60 (37) 0.1 ICI: immune checkpoint inhibitor; TKI: tyrosine kinase inhibitor.

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.

214 Background: 177 Lu-PSMA-617 (LuPSMA) has revolutionized care for patients (pts) with metastatic castrate-resistant prostate cancer (mCRPC), but only half achieves PSA decline ≥50%. Biomarkers are urgently needed to improve pt selection. EVs and ctDNA released by cancer cells into the blood are emerging biomarkers to estimate overall tumor burden and capture tumor heterogeneity in mCRPC. Here, we analyzed pre-treatment plasma levels of tumor EVs and ctDNA in a pilot cohort of 35 pts with mCRPC treated with LuPSMA. Methods: Blood samples were collected pre-cycle 1 of LuPSMA at Tulane Cancer Center between 12/2018-1/2025. Plasma-derived small and large EVs were incubated with fluorescently conjugated antibodies and enumerated using nanoscale flow cytometry. ctDNA fraction was estimated from plasma cfDNA methylation WGS (∼10×) with ichorCNA. We also analyzed EVs from blood samples of male healthy donors (HD) and pts with localized prostate cancer (LPC) collected 1 day to 8 months after radical prostatectomy (post-RP) from 6/2020-8/2024 at Mayo Clinic as controls. Results: Median age at collection for 10 HD was 55 yrs and for 36 pts with LPC post-RP was 65 yrs. Median PSMA+ EV level was 2.0 x 10 6 /mL for post-RP and 1.4 x 10 6 /mL for HD. For 35 pts with mCRPC, 25 pts had complete data for analysis. Median PSMA+ EV level was 1.4 x 10 7 /mL, significantly higher than post-RP (p<0.001) and HD (p<0.001). At LuPSMA start, median age was 69 yrs (range 54-83), PSA was 82 ng/mL (range 0.8-503), median time from CRPC diagnosis to start was 50 months (range 6.9-285), median time from plasma collection to treatment initiation was 0.5 months (range 0-7.3). Median number of prior lines of life-extending therapy was 4 (range 1-11), including 100% androgen receptor pathway inhibitor and 75% docetaxel. Pts received median 4 cycles of LuPSMA. Median ctDNA fraction was 14.0% (range 0-51.1). Median time to reach nadir PSA for pts with any decline was 2.6 months. 15 pts (60%) achieved PSA40 (defined ≥40% decline in PSA from start to nadir) (range -99% to -42%) compared to 10 pts (40%) who did not (range -16% to rise), which predicted better median overall survival (OS) after LuPSMA start (40.7 v 6.0 months; HR 0.23, 95% CI, 0.07-0.71; p=0.0001). Pts were classified as LuPSMA responders using PSA40. Responders had a lower ratio of large to small PSMA+ EVs (0.30 v 0.53, p=0.0042) with an area under the receiver operating characteristic curve (AUC) of 0.83 (95% CI, 0.68-0.99), and a lower median ctDNA fraction (6.1% v 26.2%, p=0.0044) with an AUC of 0.83 (95% CI, 0.68-1.00). Incorporating both PSMA+ EV and ctDNA fraction together predicted PSA40 response with an AUC of 0.93 (95% CI, 0.84-1.00, p=0.0003). Conclusions: Using pre-LuPSMA plasma samples from a heavily pre-treated historical cohort, we integrated non-invasive liquid biopsy methods to successfully predict response to LuPSMA using PSA decline. Prospective validation is underway.

ABSTRACT We report a case of significant clinical improvement after starting odevixibat in a 27-year-old patient with refractory pruritus due to progressive familial intrahepatic cholestasis type 1. He had poor response to multiple therapies and experienced profound decline in quality of life, describing his symptoms as emotionally exhausting and difficult to endure. He was evaluated for liver transplantation in March 2020 but was denied due to preserved liver function. Odevixibat was started in November 2021, resulting in biochemical improvement and dramatic sustained resolution of pruritus. He resumed normal activities, achieving excellent quality of life.

INTRODUCTION: Despite the widespread use of ursodeoxycholic acid (UDCA) in primary biliary cholangitis (PBC), many patients remain at risk of progression. Emerging data suggest that normalization of alkaline phosphatase (ALP) and total bilirubin (TB)—particularly when TB < 0.6 times the upper limit of normal (× ULN)—is associated with improved outcomes compared with ALP reduction to < 1.5 × ULN. This study investigated the association between ALP normalization in response to UDCA and long-term clinical outcomes in a real-world cohort of patients with PBC. METHODS: We compared complication-free survival in patients achieving an ALP > ULN and < 1.5 × ULN (adequate response) with those with an ALP ≤ ULN on UDCA monotherapy. Complication-free survival was defined as the absence of serious liver-related clinical events. Restricted mean survival time was used to quantify survival time gained. RESULTS: Patients achieving normal ALP and/or TB ≤ 0.6 × ULN demonstrated significantly improved complication-free survival compared with those with an adequate ALP response. Event-free survival was extended by 1.34 years (95% CI: 0.56, 2.11; P = 0.001) for ALP normalization alone, 3.7 years (95% CI: 3.11, 4.29; P < 0.001) for TB ≤ 0.6 × ULN, and 4.51 years (95% CI: 4.13, 4.88; P < 0.001) for those meeting both criteria. The risk of severe clinical events was reduced in patients achieving ALP normalization (hazard ratio [HR] 0.34; 95% CI: 0.15, 0.80; P = 0.01), TB ≤ 0.6 × ULN (HR 0.23; 95% CI: 0.09, 0.55; P = 0.001), or both (HR 0.14; 95% CI: 0.05, 0.38; P < 0.001). High-risk patients, defined by liver stiffness measurement ≥ 10 kPa or clinical, histological, or laboratory evidence of cirrhosis or portal hypertension, derived the greatest benefit. DISCUSSION: Achieving normal ALP and TB ≤ 0.6 × ULN is associated with significantly improved complication-free survival, particularly in high-risk patients. These findings highlight the potential of biochemical thresholds as a meaningful therapeutic goal in PBC management.