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AbstractA deeper understanding of pathophysiology, from the initiation of tumors of epithelial cells to the outcomes associated with it, is imperative to test potential interventions for these diseases. However, few models can accomplish this because of the complexity of origin cells and their transformation. We established an epithelial cell original tumor mouse model by conditional KrasG12D activation and tumor suppressor gene p53 deletion specifically in epithelial cells of the whole body using Cytokeratin 19 (CK19) promoter via Cre‐ERT mediation. Multiple tumors derived from epithelial cells developed in this novel model. This model can recapitulate the progress of intestinal, pancreatic, liver, lung, and subcutaneous tumors which derive from epithelial cells. This model is suitable for studying the pathophysiology of tumors derived from epithelial cells and may have the potential to test interventions.

ABSTRACT Understanding lung cancer evolution can identify tools for intercepting its growth. In a landscape analysis of 1024 lung adenocarcinomas (LUAD) with deep whole-genome sequencing integrated with multiomic data, we identified 542 LUAD that displayed diverse clonal architecture. In this group, we observed an interplay between mobile elements, endogenous and exogenous mutational processes, distinct driver genes, and epidemiological features. Our results revealed divergent evolutionary trajectories based on tobacco smoking exposure, ancestry, and sex. LUAD from smokers showed an abundance of tobacco-related C:G>A:T driver mutations in KRAS plus short subclonal diversification. LUAD in never smokers showed early occurrence of copy number alterations and EGFR mutations associated with SBS5 and SBS40a mutational signatures. Tumors harboring EGFR mutations exhibited long latency, particularly in females of European-ancestry (EU_N). In EU_N, EGFR mutations preceded the occurrence of other driver genes, including TP53 and RBM10. Tumors from Asian never smokers showed a short clonal evolution and presented with heterogeneous repetitive patterns for the inferred mutational order. Importantly, we found that the mutational signature ID2 is a marker of a previously unrecognized mechanism for LUAD evolution. Tumors with ID2 showed short latency and high L1 retrotransposon activity linked to L1 promoter demethylation. These tumors exhibited an aggressive phenotype, characterized by increased genomic instability, elevated hypoxia scores, low burden of neoantigens, propensity to develop metastasis, and poor overall survival. Re-activated L1 retrotransposition-induced mutagenesis can contribute to the origin of the mutational signature ID2, including through the regulation of the transcriptional factor ZNF695 , a member of the KZFP family. The complex nature of LUAD evolution creates both challenges and opportunities for screening and treatment plans.

Key Points The Standard versus Accelerated Initiation of Renal Replacement Therapy in AKI trial found that starting dialysis earlier for AKI resulted in a 74% higher risk of still receiving dialysis at 90 days. Among patients who likely would have started dialysis under usual practice, the risks of dialysis dependence were similar. This suggests much of the risk observed may have been due to starting dialysis (versus never starting) rather than starting slightly earlier. Background The Standard versus Accelerated Initiation of Renal Replacement Therapy in AKI Trial showed that among critically ill patients with AKI, an accelerated KRT initiation strategy resulted in more KRT dependence at 90 days, as compared with a standard strategy. However, it is unclear whether this difference exists among participants who likely would have been treated with KRT in usual practice. Methods Secondary analysis of the Standard versus Accelerated Initiation of Renal Replacement Therapy in AKI randomized controlled trial, analyzing participants who received more than the median number of days of KRT, which served as a proxy for high probability of requiring KRT under usual practice. Two sensitivity analyses redefined the cohort as ( 1 ) those with ≥24 hours of oliguria who received KRT and ( 2 ) those who received any KRT. Using the same statistical approach as the original trial, we calculated unadjusted relative risks with 95% confidence intervals (CIs) for the exposure of randomized KRT initiation strategy (accelerated versus standard) on the outcome of KRT dependence at 90 days among survivors. Results Among the 1184 participants who received ≥6 days of KRT (670 and 514 in the accelerated and standard arms, respectively), baseline characteristics remained balanced between treatment arms. The relative risk of KRT dependence at 90 days was attenuated and nonsignificant: 1.21 (95% CI, 0.84 to 1.78), compared with 1.74 (95% CI, 1.24 to 2.43) in the overall trial. The results were similar in sensitivity analyses. Conclusions Among patients who likely would have been treated with KRT in usual practice, there was no significant difference in 90-day KRT dependence among survivors between those randomized to the accelerated and standard KRT initiation strategies. These results suggest that the harm of long-term KRT dependence may be largely due to KRT initiation (versus never initiation) rather than earlier initiation. Clinical Trial registry name and registration number: NCT02568722.

BACKGROUND: Pharmacological treatments for fibrocalcific aortic valve stenosis (FCAVS) have been elusive for >50 years. Here, we tested the hypothesis that reactivation of oxidized sGC (soluble guanylate cyclase), the primary receptor for nitric oxide, with ataciguat is a safe and efficacious strategy to slow progression of FCAVS. METHODS: We used quantitative real-time reverse transcription polymerase chain reaction, Western blotting, and immunohistochemistry to characterize sGC signaling and the biological effects of ataciguat on signaling cascades related to nitric oxide, calcification, and fibrosis in excised human aortic valve tissue, aortic valve interstitial cells, and mouse aortic valves. We then conducted randomized, placebo-controlled phase I (14-day safety/tolerance) and phase II (6-month efficacy) trials in patients with moderate aortic valve stenosis. RESULTS: In excised human tissue, we found robust losses in sGC signaling despite upregulation of sGC subunits. In vitro, ataciguat increased sGC signaling and reduced BMP2 (bone morphogenetic protein 2) signaling in aortic valve interstitial cells. In mice with established FCAVS, treatment with ataciguat attenuated BMP signaling and slowed progression of valve calcification and dysfunction. In a phase I, randomized, placebo-controlled trial, treatment with ataciguat for 2 weeks was safe and well tolerated in patients with moderate FCAVS ( https://www.clinicaltrials.gov ; Unique identifier: NCT02049203). In a separate phase II, randomized, placebo-controlled trial, treatment with ataciguat for 6 months slowed the progression of aortic valve calcification and tended to slow the progression of valvular and ventricular dysfunction in patients with moderate FCAVS ( https://www.clinicaltrials.gov ; Unique identifier: NCT02481258). CONCLUSIONS: Collectively, this study highlights the therapeutic potential of the targeted restoration of the diseased/inactive form of sGC for treatment of FCAVS. REGISTRATION: URL: https://www.clinicaltrials.gov ; Unique identifier: NCT02049203. URL: https://www.clinicaltrials.gov ; Unique identifier: NCT02481258.

261 Background: Clinicians use next-generation sequencing (NGS) to tailor targeted treatments for PCa patients. However, the results are often available in unstructured formats and are saturated with technical jargon, making them inaccessible for patients. Therefore, we aimed to assess the efficacy of LLMs to accurately extract genomic characteristics from unstructured reports and generate patient-friendly summaries for ease of variant interpretation in PCa patients. Methods: This retrospective study included patients with PCa who underwent NGS from 2023-2024. The GPT4 model was utilized using structured zero-shot prompts to extract genomic characteristics from unstructured reports in a non-decomposed manner. Prompt development was conducted iteratively using a 2% random sample of the dataset. Genomic characteristics ascertained by LLM were assessed against held out vendor-curated test dataset for evaluation. Performance was assessed using weighted evaluation metrics (precision, recall, and F1-score). Additionally, the extracted variables were organized using rule-based criterion and presented as a separate prompt to GPT4 to generate summaries for interpretation at the level of each biologically relevant variant. Mean Flesch-Kincaid scores and Vocd-D statistic with standard deviations were computed to assess readability and lexical diversity of LLM-generated variant interpretation summaries. Results: A total of 331 patients (370 NGS reports) were included in the study. Evaluation on the held-out test dataset (Table) showed that the weighted average precision ranged from 80% for extracting tumor mutational burden to 100% for extracting the CtDNA fraction from unstructured reports. The weighted average recall ranged from 85% for extracting CtDNA tumor fraction to 99% for ascertaining variant/alteration. The weighted average F1-scores varied from 0.83 for extracting tumor mutational burden to 1.0 for extracting specimen site from NGS reports. The mean Flesch-Kincaid score was 8.29 ± 1 indicating average/standard readability ease. The mean Vocd-D statistic was 7.55 ± 1 indicating focused summaries, however, with limited lexical diversity. Conclusions: This study suggests that large language models can effectively extract genomic characteristics from unstructured reports and can potentially improve genomic literacy among prostate cancer patients by providing easy-to-interpret variant summaries. However, targeted prompting may be required to increase lexical diversity for improved engagement. Performance across different genomic characteristics. Category Precision Recall F1-Score Altered gene 0.86 0.97 0.89 Variant/alteration type 0.98 0.99 0.98 Variant allele fraction 0.96 0.96 0.96 Test name/type 1 0.99 1 Specimen site 1 0.99 1 Tumor mutational burden 0.8 0.93 0.83 CtDNA tumor fraction 1 0.85 0.92 MSI status 0.99 0.97 0.98

454 Background: Limited data exist on outcomes in mRCC patients with major venous involvement (MVI). Assessment of impact of a given variable on prognosis in cancer patients is challenging given competing causes of death (PMID: 25417239). This analysis aims to estimate cancer prognosis in mRCC patients with MVI, considering death from competing causes. Methods: Data from the Surveillance Epidemiology and End Results (SEER) database (2010-2020) were analyzed for survival and mortality in mRCC patients with MVI. 5-year (y) overall survival (OS) and 5-y probability of cancer death were calculated using the actuarial method in SEER*Stat 8.4.4, reported as percentages with 95% confidence intervals (CI). Results were based on the site of MVI (renal vein, inferior vena cava [IVC]) and stratified by age (<65, >65 years), gender (male, female), and race/ethnicity (Non-Hispanic [NH] White, NH Black, NH Asian/Pacific Islander [API], Hispanic). Results: A total of 89047 mRCC patients were included in our analysis of whom 10785 (12%) had major venous involvement (MVI). Overall, patients who experienced MVI had worse prognosis as compared to those who did not have MVI (5-y OS: 53.2% vs 84.4% and 5-y cancer death: 38.6% vs 8.2% respectively). Among cohort with MVI, prognosis was poor with IVC involvement as compared to involvement of renal vein (5-y OS: 36% vs 57%; 5-y cancer death: 56% vs 35% respectively). Patients who had the worst prognosis with MVI included older adults (>65 y) (5-y OS: 47.8%; 5-y cancer death: 40.8%) and NH Black (5-y OS: 41.5%; 5-y cancer death: 49.8%) (Table). Conclusions: Prognosis in mRCC with MVI, especially with IVC involvement, was poor, particularly for older adults (>65 y) and NH Black patients. Further research is needed for better prognostication and risk stratification to improve outcomes for high-risk patients. Subgroup No MVI MVI N 5-year OS (%), 95% CI 5-year Cancer death (%), 95% CI N 5-year OS (%), 95% CI 5-year Cancer death (%), 95% CI Overall population 78,262 84.4 (84.1-84.7) 8.2 (8.0-8.4) 10,785 53.2 (52.0-54.3) 38.6 (37.5-39.7) Age <65 y 49,217 89.0 (88.6-89.2) 6.5 (6.3-6.8) 5,897 57.5 (56.0-59.0) 36.8 (35.4-38.3) >65 y 29,045 77.0 (76.1-77.2) 10.9 (10.5-11.4) 4,888 47.8 (46.0-49.5) 40.8 (39.2-42.4) Gender Male 49,221 83.0 (82.7-83.5) 8.9 (8.6-9.2) 7,503 53.2 (51.8-54.6) 38.3 (37.0-39.6) Female 29,041 86.5 (86.0-86.9) 7.0 (6.7-7.4) 3,282 53.0 (51.0-55.0) 39.4 (37.4-41.3) Race/ethnicity NH White 49,520 84.0 (83.7-84.4) 8.3 (8.0-8.5) 7,182 53.5 (52.1-54.8) 38.0 (36.7-39.3) NH Black 8,878 82.0 (81.0-82.9) 8.1 (7.5-8.8) 685 41.5 (37.1-45.9) 49.8 (45.4-54.1) NH API 4,747 86.0 (85.1-87.4) 8.5 (7.6-9.4) 713 52.9 (48.2-57.3) 39.9 (35.5-44.1) Hispanic (All Races) 13,826 86.5 (85.8-87.2) 7.9 (7.4-8.4) 2,014 56.2 (53.4-58.8) 36.7 (34.1-39.2) N: number of cases; OS: overall survival; CI: confidence interval; NH: Non-Hispanic; API: Asian/Pacific Islander; MVI: major venous involvement.

270 Background: Inconsistent reporting of subgroup data across clinical trials makes interpretation and application of the evidence from trials challenging. We conducted a living systematic review to summarize evidence for American Society of Clinical Oncology (ASCO) guidelines for management of metastatic castration resistant prostate cancer (mCRPC). Here, we provide an overview of reporting patterns of subgroup data across mCRPC trials. Methods: MEDLINE and EMBASE were systematically searched from each database's inception through September 20 th , 2024, to identify phase II/III/IV randomized clinical trials assessing the efficacy and safety of treatment options in mCRPC. For outcomes of overall survival (OS) and progression free survival (PFS), data from the subgroup analyses was collected and compared across trials to assess heterogeneity in the reporting of subgroups. Results: This analysis included 141 trials (phase II: 83; phase III: 56; phase IV: 2). OS was reported by 113 (80%) trials; 32 (28%) reported OS by any subgroups with 95 unique subgroup categories. PFS was reported by 110 (78%) trials; 23 (21%) reported PFS by any subgroups with 63 unique subgroup categories. Even among consistently reported subgroups, such as age, ECOG performance status, race, geographical area, and Gleason score, considerable heterogeneity in different subgroup levels/thresholds was observed across trials. Top ten most commonly reported subgroups are summarized (Table). Conclusions: Lack of consistent reporting for subgroup analysis in mCRPC trials preclude meaningful conclusions about clinically relevant subgroup and synthesizing evidence for clinical guidelines. A standardized framework for consistent reporting of subgroup data across trials can help inform clinical practice and clinical practice guidelines. OS PFS Number of trials 113 110 Reporting subgroup analysis – N (%) 32 (28) 23 (21) Commonly reported subgroups – (N) Age (26)ECOG-PS (26)LDH (21)PSA (18)Geographic area (15)Alkaline phosphatase (14)Visceral disease (14)Gleason score (9)Race (9)Brief pain inventory level (8) Age (21) ECOG-PS (19)PSA (18)LDH (14)Geographic area (13)Visceral disease (11)Gleason score (10)Alkaline phosphatase (9)Bone metastasis (9)Disease location (9) Age – (N) <65 (14); ≥65 (9); ≤68 (1); ≥69 (1); <70 (5); ≥70 (5); ≤74 (4); 65-75 (5); ≤ 71 (1); >71 (1); ≥75 (11); >Median (1); <Median (1) <65 (12); 65-74 (6); ≥65 (6); <70 (5); ≥70 (5); <75 (4); ≥75 (10); 76-80 (1); >80 (1) ECOG-PS – (N) 0 (15); 0-1 (11), 1 (11); 1-2 (5); 2 (12) 0 (15); 0-1 (5), 1 (12); 1-2 (2); 2 (6) Race – (N) White (9)Non-white (6)African American/black (2)Asian (2) White (8)Non-white (5)African American/black (2)Asian (4) Geographic Area – (N) Europe (8)North America (14)United States (1)Australia (1)Asia (2) Europe (11)North America (13)United States (1)Australia (1)Asia (2)North and South America (2) Gleason Score – (N) 2-6 (1); 7 (1); 8 (1); <8 (8); ≥ 8 (8); 9-10 (1) <8 (10); ≥ 8 (10)

773 Background: BCG-unresponsive High-risk non-muscle invasive bladder cancer (HRNMIBC) tumours have an ominous prognosis and require effective, tolerable treatments. Uptake remains low for FDA approved agents (including systemic pembrolizumab, nogapendekin alfa inbakicept-pmln or N-803) due to toxicity concerns. We hypothesize direct intravesical administration of a PDL1 inhibitor could be effective with less systemic toxicity. However, it is unknown whether antibodies delivered via this route can reach tumor vasculature. INVEST is a phase Ib window of opportunity study investigating the safety and preliminary activity of passive instillation and direct injection of intravesical atezolizumab into the tumour/bladder wall. Methods: Eligible participants (ECOG performance status 0-2) are awaiting radical cystectomy (RC) for any stage urothelial cell carcinoma. Participants with muscle invasive bladder cancer, must be ineligible for/ refuse cisplatin based neo-adjuvant chemotherapy. Atezolizumab (600mg or 1200mg) is administered via direct injection into the tumour/bladder or by instillation into the bladder. The 3+3 design is utilised in the dose confirmation stages where participants receive either Single or Multiple (between 3 and 6) dose(s) of treatment before RC. Efficacy signals are derived from pathological complete response at RC and progression-free survival at 2 years. Primary endpoint, Dose confirmation stage: The number of dose-limiting toxicities (DLTs) observed from first dose of trial treatment to RC. Results: Enrolment began in May 2023. 13 participants were recruited to the single dose cohorts: 11 male, and 2 female. Age (Range; 43-86); median 70y, 9 NMIBC, 4 MIBC. 7 for direct injection (4 at 600mg and 3 at 1200mg dose) and 6 for passive instillation (3 at 600mg and 3 at 1200mg). Due to technical issues (syringe size) the first direct injection participant did not receive the full 600mg and were replaced. 12 participants received trial treatment as planned. There were no DLTs; 5 participants experienced non-trial treatment related SAEs (4 infections, 2 ileus, 2 renal impairment; 7/8 events occurred post-RC and all SAEs resolved). All participants underwent planned RC within the protocol stipulated timeline. Median time from last treatment to RC was18 days. 5 of 13 participants had downstaging of tumour in cystectomy specimen. Following independent Safety Review Committee review, recruitment is now open for the dose confirmation phase (Multiple 1200mg dose) in both treatment routes. Conclusions: Single dose atezolizumab treatment at a dose of 600mg and 1200mg in passive instillation and direct injection cohorts was well tolerated. Early efficacy data is encouraging. Multiple weekly doses of 1200mg in each treatment route are now being investigated within the INVEST trial. Clinical trial information: ISRCTN15842444 .

524 Background: Antiangiogenic tyrosine kinase inhibitors (TKIs) play a key role in treating renal cell carcinoma and other solid organ malignancies, but TKIs cause bothersome side effects that frequently necessitate dose reductions or treatment holds. Olanzapine has been useful for palliating symptoms from classical chemotherapies and advanced cancer, but its effect on TKI-related symptoms is largely unknown. This retrospective study aimed to estimate the efficacy of olanzapine for TKI-induced nausea, vomiting, anorexia, weight loss, and insomnia. Methods: All patients prescribed olanzapine with lenvatinib, cabozantinib, axitinib, or tivozanib at Mayo Clinic between January 1, 2018, and June 30, 2024 were assessed for inclusion. For baseline symptom assessment, clinical care team notes documenting the presence or absence of symptoms and indication(s) for starting olanzapine were reviewed. For response assessment, clinical notes and patient portal messages from the first three months after starting olanzapine were evaluated for qualitative descriptions of change in symptom burden. Relevant data were extracted as direct quotations, which were reviewed by the research team and categorized as “improved,” “worsened,” “stable,” or “missing data.” Each symptom domain was analyzed independently when olanzapine was prescribed for multiple interrelated symptoms. Results: A total of 60 patients who received olanzapine for the treatment of TKI-related adverse effects were included. The most common documented indication for olanzapine was nausea without vomiting (n=35), followed by anorexia (n=25), nausea with vomiting (n=16), weight loss (n=16), and insomnia (n=11). In 32 cases (53%), olanzapine was prescribed for multiple, simultaneous symptoms. Response rates for each symptom domain are shown in the table. In addition, prior to olanzapine, 34 patients (57%) had documented weight loss. Following olanzapine, 50% (n=17) gained weight (median increase: 6.1 kg; range: 2.0 - 10.7 kg), 26% (n=9) stabilized their weight (±1 kg), and 24% (n=8) continued to lose weight. Clinicians utilized a TKI dose reduction within one week of olanzapine initiation in 5 cases (8.3%), and 3 of these patients could resume the higher dose of TKI after starting olanzapine. Only 4 patients (7%) discontinued olanzapine within 3 months due to perceived side effects. Conclusions: Olanzapine appears to be effective in treating TKI-induced nausea, vomiting, anorexia, insomnia, and weight loss. Prospective randomized placebo-controlled studies are needed to confirm these findings. Improvedn (%) Worsened n (%) Stablen (%) Missing Datan (%) Nausea without emesis 32 (84) 3 (8) 1 (3) 2 (5) Nausea with emesis 13 (93) 0 (0) 0 (0) 1 (7) Anorexia 26 (74) 2 (6) 4 (11) 3 (9) Insomnia 11 (85) 0 (0) 2 (15) 0 (0)

520 Background: The annual incidence of renal cancer is 0.02% among the general United States population. End stage renal disease (ESRD) and exposure to dialysis are thought to be the primary drivers of increased risk of renal cancer in renal transplant patients rather than immunosuppression. This has been evidenced by how the incidence of RCC in heart transplant recipients is no different than the normal population. In this study, we aim to characterize RCC incidence among kidney transplant patients (usually exposed to ESRD/dialysis) versus other solid organ transplant patients (usually unexposed to ESRD/dialysis). Methods: We used CPT codes to search for patients who had received a solid organ transplant (kidney, liver, heart, lung, pancreas) at all Mayo Clinic sites from 1/1/2018 to 1/1/2024. Within this cohort, we identified those who had been diagnosed with kidney cancer after initiating dialysis or receiving a transplant, and retrospectively extracted data related to demographics, cancer diagnosis, and transplant details. Results: We identified 10873 patients who had received a solid organ transplant (Table 1). Of these, 178 (1.76%) were diagnosed with kidney cancer after either starting dialysis or receiving a transplant. These 178 patients were of median age 56 years at time of cancer diagnosis (STD 12), 71% male, 70% white, 20% black, 4.5% Asian, 2.8% American Native. Of 5792 patients who had received a kidney transplant (with or without another solid organ transplant), 172 (2.97%) were diagnosed with kidney cancer after having started dialysis or receiving a kidney transplant. Of these 172, 156 (91%) were exposed to dialysis (107 primarily hemodialysis and 48 peritoneal). Of 4392 patients who had received a solid organ transplant other than kidney (liver, heart, lung, and/or pancreas), 6 (0.14%) were diagnosed with kidney cancer after having received a kidney transplant. Of these 6, none underwent dialysis. Conclusions: Patients with kidney transplants are at increased risk of kidney cancer compared to patients with non-kidney solid organ transplants (2.97% vs 0.14%). This supports prior evidence showing ESRD plays a significant role in the pathogenesis of kidney cancer. Patients who received solid organ transplants at Mayo Clinic from 2018-2024 and were subsequently diagnosed with kidney cancer. n % With RCC after TXP 178 1.7587% Cancer Diagnosis after Kidney HD/TXP 172 2.9696% Cancer Diagnosis after Other TXP 6 0.1386% Patients who received solid organ transplants at Mayo Clinic from 2018-2024 n % Unique Patients 10121 100% Kidney Transplant 5792 57.23% Alone 5088 50.27% &Liver 332 3.28% &Heart 119 1.18% &Lung 8 0.08% &Pancreas 245 2.42% Non-kidney Transplant (Liver, Heart, Lung, or Pancreas) 4329 42.77% TXP: Transplant, HD: Hemodialysis.