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Serum biomarkers in metastatic castration-resistant prostate cancer (mCRPC) patients receiving [ <sup>177</sup> Lu]Lu-PSMA-617 therapy: Post hoc analysis of a phase II clinical trial.
190 Background: [ 177 Lu]Lu-PSMA-617 ( 177 Lu-PSMA-617) has been recently approved for metastatic castration-resistant prostate cancer (mCRPC). Several clinical trials have assessed the efficacy of 177 Lu-PSMA-617, but only half of the eligible patients seem to obtain a clear benefit from it. Currently, there is a lack of validated biomarkers that could help find the best candidates for this radioligand therapy. Methods: In the IRST185.03, a single-arm monocentric phase II clinical trial, 142 mCRPC patients received 177 Lu-PSMA-617 at a dose of 3.7-5.5 Gbq every 8-12 weeks for a maximum of 4 cycles. Baseline blood samples were collected within 7 days from the first dose of 177 Lu-PSMA-617. Hemoglobin (Hb), alkaline phosphatase (ALP), prostate-specific antigen (PSA), carcinoembryonic Antigen (CEA), chromogranin A (CgA), and neuron-specific Enolase (NSE), as well as neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR), were analyzed at both uni- and multivariate levels to evaluate their correlation to progression-free survival (PFS). Results: At the time of data cut-off, after a median follow-up time of 44.0 months, the median PFS in the global cohort was 7.0 months. At univariate analysis, among serum biomarkers, lower PLR (cut-off: 210, HR: 0.66, 95% CI: 0.44-0.99, p=0.04), lower ALP (cut-off: upper limit of normal, HR: 0.51, 95% CI: 0.34-0.75, p<0.01), lower PSA (cut-off: median value, HR: 0.51, 95% CI: 0.35-0.74, p<0.01), and lower CEA (cut-off: upper limit of normal, HR: 0.55, 95% CI: 0.32-0.95, p=0.03) were associated with longer PFS. Among clinical characteristics, the previous use of docetaxel (HR: 1.48, 95% CI: 1.04-2.10, p=0.03) was associated with shorter PFS. At multivariate analysis, only PSA and CEA remained prognostic for PFS (p=0.01 and 0.02. respectively). Conclusions: High PSA and CEA levels appeared the only serum predictors of poor clinical outcome to 177 Lu-PSMA-617 therapy in mCRPC. The role of CEA as potential biomarker associated with 177 Lu-PSMA-617 needs to be confirmed since it could be linked to aggressive prostate cancer variant. Clinical trial information: 2016-002732-32 .
Association between vascular patterns of clear cell renal cell carcinoma and immune cell infiltration and therapeutic response.
575 Background: Clear cell renal cell carcinoma (ccRCC) is a highly vascularized tumor with histological heterogenous appearance. We explored whether vascular pattern (VP) are predictive to response of therapy. Methods: We defined three categories of VP in the publicly available TCGA cohort: high-branching (HB), low-branching (LB) and sinusoid. VP-based gene signatures were generated by integrating the transcriptomes of matched ccRCC samples. We developed a learning-based (AI) algorithm for the classification of VP based on CD31 immunohistochemistry and analyzed histology specimens from patients treated with tyrosine kinase inhibitors +/- immunotherapy (TKI) (University Clinic Dresden, retrospective cohort n=38, and NivoSwitch trial NCT: NCT03013946 , n=38 respectively) as well as the publicly available transcriptome datasets from two phase III clinical trials (JAVELIN Renal 101; IMmotion 151). Multiplex immunofluorescence (CODEX) was used for spatial mapping. Outcome measures employed KM-plots and log-rank analyses. Results: We identified a trajectory from a HB to LB vascular phenotype, paralleled by a decline in the expression of proximal tubule cell lineage traits. Applying the VP gene signatures to the transcriptome datasets from JR101 and IM151 we found that the progression-free survival (PFS) benefit from adding immunotherapy to anti-angiogenic therapy (IMmotion151: Bevacizumab; JAVELIN Renal 101: Axitinib) was limited to low-branching ccRCC (IM151: HR (95% CI): 0.64 (0.51-0.80), JR101: HR (95% CI): 0.45 (0.33-0.61, both p < 0.001), respectively) and linked to an immune cell infiltrated microenvironment. Patients with a HB ccRCC demonstrated prolonged PFS in the Dresden TKI cohort (p = 0.026) and in the NivoSwitch trial (p = 0.01). CODEX analysis using the SPACEc pipeline revealed profound differences in cellular neighborhoods, characterized by dense immune cell infiltration of ccRCC with LB compared to HB vascular patterns. Using 30 ccRCC patient-derived organoid in air-liquid interface (ALI) cultures, we confirmed the association between LB pattern and higher T cell infiltration, resulting in reduced viability of LB ccRCC organoids under immune-stimulating conditions. Conclusions: Vascular pattern can reliably predict therapy response in advanced ccRCC. Tumors with high branching phenotype respond better to anti-angiogenic TKI therapy. Low branching pattern was associated with improved response to immunotherapy.
Systemic therapy clinical trial participation in patients with bladder and kidney cancers.
451 Background: Patient participation in clinical trials has led to numerous treatment advances in renal cell carcinoma (RCC) and urothelial carcinoma (UC) over the past decade. The rate of patient participation in RCC and UC trials and factors influencing participation are unknown. This study evaluates patient participation rates in RCC and UC clinical trials at a major United Kingdom cancer centre. Methods: All referrals to St Bartholomew’s Hospital (SBH) Genitourinary Cancer Department between Jan 2020 to Sept 2022 were reviewed. Patients with RCC or UC of any stage were included. Dates of consultation and follow up visits were cross-referenced with a list of systemic therapy clinical trials open at SBH from Jan 2020 to Oct 2024. The proportion of patients who a) had a trial available to them, b) entered trial screening, and c) were eligible for a trial, was determined. Multilevel mixed-effects logistic regression models were used to assess the likelihood of clinical trial screening and enrolment with adjustment for relevant baseline variables (age, cancer type, gender, line of therapy, and performance status [PS]). Results: 403 patients were included in the analysis: 215 RCC (44% stage I-III and 60% had or developed metastatic disease) and 188 UC (41% stage I-III and 69% had or developed metastatic disease). 63% (254/403) of patients had at least one eligibility opportunity to be screened for a trial during the follow up. 40% (161/403) consented to trial screening, and 30% (118/403) were enrolled into at least one trial. The table shows trial availability, screening, and enrolment by line of therapy (rates were similar between RCC and UC, data not shown). Variables associated with increased odds of entering trial screening were line of therapy (second line odds ratio (OR) 8.6 (2.3-31.8), p<0.01, third line OR 3.4 (1.3-9.0) p=0.02, compared to adjuvant) and UC vs RCC trials OR 2.4 (1.3-4.3) p<0.01. Poor PS decreased the odds of entering trial screening (OR 0.21 (0.1-0.5) p<0.01). Gender and age were not associated with screening rates. No variables were associated with trial enrolment after a patient had consented to screening. Conclusions: At a major UK clinical trial centre, 40% of patients with RCC or UC entered clinical trial screening and 30% participated. Most patient characteristics were not associated with increased screening except for PS. Screening rates were higher in later line treatment studies. The effect of ethnicity and randomisation will be presented at the meeting. These data highlight patient willingness to screen for trials when they are available. Clinical trial availability, screening rates, and enrollment rates by line of therapy for patients with RCC and UC. Neo/Adjuvant 1L 2L 3/4L Trial Available 45% (86/248) 58% (151/259) 34% (35/104) 66% (40/60) Screened 56% (48/86) 52% (78/151) 91% (32/35) 83% (33/40) Enrolled 73% (35/48) 68% (53/78) 63% (20/32) 82% (27/33)
Treatment of low-grade intermediate-risk non-muscle-invasive bladder cancer with UGN-102: Results of the phase 3 ATLAS and ENVISION studies.
777 Background: The ATLAS and ENVISION phase 3 studies (NCT04688931/NCT05243550) treated patients with low-grade intermediate-risk non-muscle-invasive bladder cancer (LG-IR-NMIBC) with UGN-102, a reverse thermal hydrogel containing mitomycin. Primary efficacy and safety results were previously reported for the individual studies; here we report additional data. Methods: In the randomized controlled ATLAS study, patients with newly diagnosed or recurrent LG-IR-NMIBC were randomized to 6 weekly intravesical instillations of UGN-102 (n=142) or transurethral resection of bladder tumor (TURBT) (n=140). In the single-arm ENVISION study, patients with recurrent LG-IR-NMIBC received 6 weekly intravesical instillations of UGN-102 (n=240). In both trials, patients were examined for recurrence of bladder cancer using cystoscopy, urine cytology testing, and for-cause biopsy at 3 months, and in those with a complete response (CR), at regular intervals thereafter. Duration of response (DOR) was calculated using the Kaplan–Meier method. Results: In both studies (ATLAS, ENVISION) patients were mostly aged ≥65 years (60%, 68%), white (99%, 98%), and male (70%, 61%). In the ATLAS study, 89 patients (63.6%) in the TURBT arm and 92 patients (64.8%) in the UGN-102 arm had a CR at 3 months. Among patients achieving a CR at 3 months in ATLAS, 79.7% in the UGN-102 arm vs 67.7% in the TURBT arm remained event free 12 months later; the majority with recurrence had low-grade (LG) disease (Table). In ENVISION, 79.6% had a CR at 3 months, and 82.3% remained event free 12 months later, again with the majority of recurrence being LG disease (Table). Median DOR was not estimable in any arm due to low recurrence rates, with a between arms hazard ratio in ATLAS of 0.46 (95% CI 0.24–0.86) favoring the UGN-102 arm. The most common adverse event with UGN-102 in both studies was dysuria, occurring in 30.4% in ATLAS and 22.5% in ENVISION. Conclusions: In both studies, CR rate in patients initially treated with UGN-102 was robust, with the majority of patients remaining event-free at 12 months follow-up. These results demonstrate that treatment with UGN-102 results in a high and clinically meaningful durable CR rate in patients with newly diagnosed or recurrent LG-IR-NMIBC. UGN-102 may represent a valuable non-surgical treatment option for these patients. Clinical trial information: NCT04688931 / NCT05243550 . ATLAS ENVISION UGN-102 TURBT UGN-102 CR at 3 months 92/142 (64.8%) 89/140 (63.6%) 191/240 (79.6%) CR rate (95% CI) 64.8 (56.3–72.6) 63.6 (55.0–71.5) 79.6 (73.9–84.5) Follow-up time for DORMedian (95% CI) 12.45 (12.02–14.13) 12.16 (11.89–12.75) 13.86 (12.19–14.52) Any recurrence 18/92 (19.6%) 24/89 (27.0%) 33/191 (17.3%) LG disease 15/92 (16.3%) 17/89 (19.1%) 27/191 (14.1%) HG disease 3/92 (3.3%) 6/89 (6.7%) 4/191 (2.1%) Death 0 1/89 (1.1%) 2/191 (1.0%) HG, high grade.
Application of canary histology classifier in prostate biopsies for risk stratification.
412 Background: Nguyen et al recently proposed an outcome-based radical prostatectomy (RP) histologic classifier (PMID 38828674, “Canary histology risk group”), combining all high-risk carcinoma histology patterns into “unfavorable histology,” versus absence as “favorable histology.” We examine whether this classifier, with additional stratification of favorable, is applicable to prostate biopsies for risk stratification. Methods: Archival databases of one single institution were searched for patients with long term clinical follow-up after RP and available prostate biopsy slides. Most recent biopsies underwent blinded re-review. Canary risk group was assigned based on highest risk patterns in any core. Unfavorable histology encompasses all Gleason pattern 5, large cribriform/intraductal carcinoma (>0.25 mm), anastomosing cords of carcinoma, grade 3 stromogenic carcinoma, and complex intraluminal papillary architecture. To capture patterns potentially predictive of unsampled unfavorable histology, “biopsy borderline” combines small cribriform/glomeruloid (≤0.25 mm), simple glomerulations, predominance of extensive poorly formed glands, equivocal small anastomosing cords, grade 2 stromal response, and epithelial complexity associated with mucin (beyond mucinous fibroplasia). “Biopsy favorable” is defined as void of any unfavorable or biopsy borderline histology. Biopsy and RP Gleason Grade Group (GG), pT stage, and pN stage were recorded from original reports. Biochemical recurrence (BCR) was defined as consecutive PSA of ≥0.2 ng/mL 8 weeks after RP or receipt of salvage treatment. RP stage and GG were analyzed using chi-square. BCR-free survival was analyzed using Kaplan-Meier curve. Results: 360 patients were identified (median, IQR): Age at diagnosis 61 years (56, 66), PSA at diagnosis 5.38 ng/mL (4.2, 7.6), post-RP follow-up 9 years, (7, 12). The patients were classified as histologically unfavorable (n=63; 17.8%), biopsy borderline (n=92; 25.6%), and biopsy favorable (n=205; 56.9%). The three-tiered classification is significantly associated with earlier BCR (log-rank p-value <.01), RP GG (<.01), pT stage (<.01), and pN stage (<.01) (Table). Conclusions: Unfavorable histology on biopsy was associated with highest risk of BCR after RP, compared to “biopsy borderline” and “biopsy favorable” groups. This proof-of-principle study demonstrates the three-tiered histology-based classifier could be applicable in biopsies for risk stratification. Canary Histology Risk Group N (%) GG3+ at RP pT3a at RP pT3b at RP pN1 BCR event within 7 years of RP Unfavorable 63 (18%) 46 (73%) 30 (48%) 11 (17%) 11 (17%) 53 (84%) Biopsy Borderline 92 (26%) 21 (23%) 32 (35%) 5 (5%) 1 (1%) 60 (63%) Biopsy Favorable 205 (57%) 22 (11%) 69 (34%) 3 (1%) 0 (0%) 110 (54%) All patients 360 (100%) 89 (25%) 131 (36%) 19 (5%) 12 (3%) 223 (62%)
A prospective, single-center, single-arm clinical study of adjuvant toripalimab combined with axitinib in non-clear renal cell carcinoma (nccRCC) patients with high-risk recurrence factors (IUNU-RC-102).
TPS613 Background: Non-clear cell renal cell carcinoma (nccRCC) accounts for approximately 25–30% of all renal cell carcinoma (RCC) cases and is associated with a poor prognosis. While early-stage treatment typically involves surgery, there is a significant risk of postoperative recurrence. Once recurrence or distant metastasis occurs, management becomes more challenging. Current clinical trial results for metastatic advanced nccRCC have shown variability, and no standard treatment protocol has been established. For advanced clear cell renal cell carcinoma (ccRCC), however, the combination of immunotherapy and targeted therapy has become the standard of care. The RENOTORCH study demonstrated the efficacy and safety of toripalimab combined with axitinib as a first-line treatment for advanced ccRCC[1]. This study aims to investigate the efficacy and safety of toripalimab combined with axitinib as adjuvant therapy in postoperative patients with high-risk nccRCC. Methods: IUNU-RC-102 (NCT05768464) is a single-center, prospective, single-arm clinical trial. The study plans to enroll 30 patients. Key inclusion criteria include: a clinical diagnosis of high-risk recurrent nccRCC following nephrectomy, age between 18 and 75 years, an ECOG performance status of 0–1, no prior systemic therapy for renal cancer, and confirmed pathological histology of nccRCC following partial or radical nephrectomy, with exclusions for clear cell carcinoma, chromophobe carcinoma, and eosinophilic renal cell carcinoma. All participants will receive axitinib (5 mg twice daily) for 4 weeks, along with toripalimab (240 mg intravenously on the first day of each 21-day cycle). The treatment duration will extend up to 52 cycles. The study follows Simon’s minimax two-stage design. In the first stage, three patients will be enrolled and will receive two treatment cycles to assess safety. If dose-limiting toxicity (DLT) occurs in one or more of the three patients, the study will be paused. Investigators will then determine whether to terminate or amend the study protocol after further deliberation. In the second stage, the primary endpoint will be 2-year disease-free survival (DFS). Secondary endpoints will include 3-year overall survival (OS), disease recurrence-specific survival (DRSS), and safety. The first participant was enrolled in IUNU-RC-102 in October 2023. We anticipate that the combination of toripalimab and axitinib will offer a promising new treatment option for these patients. Clinical trial information: NCT05768464 .
Automated risk stratification in localized prostate cancer using an AI-assisted framework.
341 Background: Specialist clinicians (oncologists, urologists, radiation oncologists) read through free text reports of prostate MRI and biopsy reports to risk stratify patients during initial consultation of localized PCa. This laborious and time-consuming process is repeated for each day during the clinic. Herein, we propose a hybrid stratification framework utilizing a combination of large language model (LLM) and rule-based programming to automate this process. Methods: This retrospective study included patients with localized PCa (2004-2024) presenting to care at Mayo Clinic with at least one positive prostate biopsy and MRI report available. The state-of-the-art LLM – GPT4 – was utilized using a structured zeroshot prompt to extract relevant phenotypic variables (clinical T stage, Gleason patterns, grade group, extent of specimen/cores involved, prostate size/volume) from unstructured MRI and biopsy reports. Using a rule-based algorithm, the extracted variables and PSA at PCa diagnosis were used to categorize each patient into one of the six NCCN risk categories (very low [VL], low [L], favorable intermediate [FInt], unfavorable intermediate [UFInt], high risk (HR), very high risk [VHR]). Prompts were iteratively developed using ~5% of the total dataset and validated on ~10% of the dataset. Final performance was assessed against a held-out expert annotated test dataset using evaluation metrics (accuracy, F1-score, precision, recall). Additionally, manual annotation was conducted by two independent novice reviewers to compare machine annotated and novice-human annotated risk categorization. Results: A total of 397 patients were included in the evaluation. The median age at diagnosis was 64.8 (IQR: 59.7-68.5); majority of the men were White (n: 366; 92%) and non-Hispanic (n: 371; 94%). The most prevalent risk category was UFint (n: 151; 38%) followed by FInt (n: 80; 20.2%), HR (n: 76; 19.1%), VHR (n: 64; 16.1%), L (21: 5.3%), and VL (n: 5; 1.3%). Novice reviewers achieved an accuracy of 79%, precision of 80%, recall of 82% and a F1-score of 0.81. The hybrid stratification framework using GPT4 achieved an accuracy of 89%, precision of 89%, recall of 88% and a F1-score of 0.88. Among 43 errors by GPT4 risk stratification, majority of the errors were due to miscategorization of clinical T-stage (n: 21; 49%) followed by erroneous number of positive cores (n: 13; 30%). However, additional evaluation showed that GPT4 achieved numerically higher performance (accuracy: 90%; precision: 91%; recall: 90%; F1: 0.90) compared to novice reviewers (accuracy: 77%; precision: 89%; recall: 77%; F1: 0.82) for ascertaining clinical T-stage. Conclusions: Large language models exhibited superior performance than novice clinicians for risk stratification in patients with localized PCa. As the next step, we intend to validate our framework for automated risk classification in a prospective manner.
Computational pathology–based classifier for predicting Gleason grade group upgrading on radical prostatectomy from diagnostic biopsies.
329 Background: Prostate biopsy is the gold standard for diagnosing and risk stratification of prostate cancer. As therapeutic options expand, detailed biopsy analysis becomes critical. However, discrepancies between biopsy samples and radical prostatectomy (RP) Gleason grade groups occur, with about 30% of patients experiencing an upgrade. This inconsistency can lead clinicians to underestimate disease severity, impacting patient management and outcomes. This study aimed to identify patients likely to experience a Gleason grade group upgrade (GGU) at RP by utilizing an AI-based computational pathology model that analyzes spatial architecture of lymphocytes from baseline diagnostic biopsies. Methods: We retrospectively analyzed whole-slide images from diagnostic biopsies of 128 patients who underwent RP (29 upgraded) at Helsinki University Hospital. Patients were randomly divided into training (D 1 ) and test (D 2 ) sets, comprising 89 and 39 patients, respectively. Nuclei segmentation and classification were performed using a deep learning model, followed by the extraction of 350 features representing the spatial interactions between lymphocytes and other nuclei. Feature selection and hyperparameter tuning were conducted on D 1 using cross-validated decision trees. The top five features and optimal parameters were then used to fit a final model GUP (Gleason Upgrade Predictor) on D 1 . GUP was subsequently used to predict GGU on D 2 . For comparative analysis, we developed models M c , M p and M cp using clinical variables (age, blood PSA level, PSA doubling time, T-stage, comorbidity index), data on proportion of Gleason grade patterns in the biopsies, and their combination. Finally, we integrated clinical variables into GUP (GUP c ) to evaluate whether this combination would enhance predictive performance and improve explainability. Results: The top five features measure lymphocyte cluster irregularity and their interactions with other cells. GUP achieved an AUC of 0.83 (±0.08), outperforming models trained exclusively on clinical data, Gleason pattern proportions, or their combination. Notably, GUP’s performance further improved when it was integrated with clinical variables (AUC 0.87 ± 0.1; Table). Conclusions: Our AI-driven computational pathology model shows strong predictive performance for GGU. Although external validation is still required, this model holds promise for improving the accuracy of Gleason group assessments at diagnosis. Model performance comparison. Model AUC ± std Balanced ACC GUP: Top 5 features of lymphocyte spatial architecture 0.83 ± 0.08 0.83 M c : Clinical variables 0.58* ± 0.08 0.58 M p : Pathological annotations of Gleason patterns 0.55* ± 0.10 0.52 M cp : M c + M p 0.72* ± 0.11 0.72 GUP c : GUP + clinical data 0.87 ± 0.10 0.87 *Indicates a statistically significant value at p < 0.05 comparing the model to GUP c .
Genome-scale metabolic reconstruction of urinary microbiome: Pathway for personalized medicine.
822 Background: The human microbiome significantly influences the efficacy and safety of various medications. To integrate microbial metabolism into precision medicine, it is crucial to develop strain- and molecule-specific computational models that can predict a patient's microbiome's ability to metabolize chemotherapy drugs. This study evaluates the potential of urine, pellet, and supernatant samples to identify microbial profiles and metabolizing genes in patients with bladder cancer. Methods: Catheterized urine, pellet, and supernatant samples from six patients (5 males and 1 female) with bladder cancer were analyzed to identify microbial species and strains, assess drug gene abundance, and predict drug metabolism. Whole-genome sequencing (WGS) was performed, and gene annotation was conducted using the PubSEED platform. Biosynthetic pathways were identified following the KEGG PATHWAY resource, and AGORA2 reconstruction was used for final metabolic reactions. Results: WGS revealed a diverse microbial community, with 1,024 species unique to urine, 386 unique to pellet, and 1,861 species common to both. The most prevalent species, Enterococcus faecalis and Staphylococcus epidermidis, accounted for over 60% of the microbial population in both urine and pellet samples. A detailed comparison of OTU abundance between paired urine and pellet samples showed significant variations in microbial composition, yet a strong correlation between the two sample types. The net metabolizing capacity of 13 chemotherapy-drug metabolites was assessed among the six patients. Mean flux calculations indicated highly variable metabolism of gemcitabine (median 773.57, IQR 380-1056), SN38 (irinotecan) (median 770.24, IQR 10.1-2234.5), and bile salt hydrolase (median 130.80, IQR 9.8-318.2). These findings highlight the microbiome's extensive role in influencing chemotherapy drug pharmacokinetics. Conclusions: This study demonstrates the potential of microbiome profiling in informing precision medicine, suggesting that microbiome modification could enhance chemotherapy drug pharmacokinetics and improve patient outcomes. Further research is needed to validate these findings and refine microbiome-based precision medicine in oncology.
Neoadjuvant pembrolizumab (pembro) and accelerated methotrexate, vinblastine, doxorubicin, cisplatin (aMVAC) in non-urothelial (non-UC) histologic subtype muscle invasive bladder cancer (MIBC): A phase 2 trial.
769 Background: Cisplatin-based chemotherapy (CT) prior to radical cystectomy (RC) + perioperative anti-PDL1 improves pathologic complete response rates (pCR) and survival in MIBC with predominant UC. Outcomes are poorer in the 5-10% of MIBC with pure/predominant non-UC histology. Thus, optimizing neoadjuvant therapy for these patients (pts) is critical. Pembro monotherapy has induced promising pCR rates in histologic subtypes (PURE-01 trial). We hypothesized that aMVAC + pembro would be safe and effective for non-UC MIBC and conducted a single-center trial testing this combination in pts with pure/predominant non-UC MIBC. Methods: Pts with resectable MIBC (cT2-4a/N0-1) with pure/predominant non-UC histology and fit for CT and RC were treated with neoadjuvant pembro (200mg q3 weeks x 3) + aMVAC (q2 weeks x 4) with G-CSF. Primary endpoint was pCR rate. Secondary endpoints included toxicity, pathologic downstaging (<ypT2N0), and event-free and overall survival (EFS, OS) from initiation of neoadjuvant therapy. EFS/OS were estimated using Kaplan-Meier method. A single arm phase II trial with 91% exact power to rule out 8% pCR rate at 1-sided 4% level, if true pCR rate was 36%, required 17 pts. If ≥4/17 had pCR, then an 8% pCR rate was rejected. Results: 17 pts were enrolled from 3/2020 to 3/2024 (Table). Median age was 60 (range 39-74); 12 were male, 5 female. Predominant histologies at TURBT were squamous (5), plasmacytoid (3), micropapillary (3), poorly differentiated (3), glandular (2), and sarcomatoid (1). 4 pts discontinued treatment (2 toxicity, 1 patient choice, 1 unrelated illness), of whom 2 completed 3 planned pembro doses. Median time to RC from completing neoadjuvant therapy was 6 weeks (range 4-24); 2/17 pts did not proceed to RC, 1 (squamous) due to clinical status (achieved clinical CR and remained recurrence-free) and 1 (micropapillary) deemed to have unresectable MIBC. 9/17 patients (53%) achieved pCR; 1 patient achieved ypTisN0 (downstaging 59%). With median follow-up of 29 months the estimated 2-year OS was 75% (95%CI: 40-91) and estimated 2-year EFS was 69% (95%CI: 36-88). Median OS was not reached; estimated median EFS was 38 months (95%CI: 12, NR). Conclusions: The primary endpoint was met: pCR and downstaging rates with neoadjuvant aMVAC + pembro were significantly higher than reported historically in pts with pure/predominant non-UC MIBC. EFS/OS were also encouraging. No new safety signal was noted; all but 2 pts underwent RC. Correlative analysis for putative biomarkers, using tissue, blood and urine biospecimens, is ongoing. Clinical trial information: NCT04383743 . Baseline and Treatment Characteristics N(%) Clinical T-Stage at diagnosis T2 10 (59) T3-4 * 7 (41) aMVAC Cycles 4 cycles + 13 (76) <4 cycles 4 (24) Pembro Cycles 3 cycles 15 (88) <3 cycles 2 (12) * 1 patient with cN1 (T4a); + 1 patient had dose reduction.
First preliminary results of artificial intelligence-generated, explainable treatment recommendations for renal cell cancer based on multidisciplinary cancer conferences.
465 Background: The expert panel in multidisciplinary cancer conferences (MCC) decides on the best available treatment for the individual cancer patient. To support these complex evidence-based decisions, an artificial intelligence (AI) was developed to generate treatment recommendations for renal cell cancer (RCC) patients to support decision-making in MCC. Methods: We have transformed comprehensive patient data (99 individual machine-readable features) of 880 MCC recommendations for RCC from the years 2015 - 2022 into representations that can be used in software development. We developed a two-step process in order to train classifiers to mimic MMC recommendations. First, we identified superordinate categories of the recommendations. Afterwards, we specified the detailed recommendation. For this purpose, we used different machine learning (CatBoost, XGBoost, Random Forest) and deep learning (SoftOrdering-1d-CNN) approaches with 787 training cases and 93 test set cases. Accuracy weights are determined by F1-Score. Results: The KITTU-AI is able to generate fully automated treatment recommendations for patients with histologically confirmed RCC in MCC. First, the AI can decide which kind of superordinate recommendation should be applied, e.g. surgery or anticancer-drugs (Table). Second, our AI system is able to suggest the specific surgical treatment as well as the correct drugs (Table). The AI-generated recommendation is presented explainable based on the clinical features and their importance score. Conclusions: To our knowledge, we present the first time data for fully automated AI-based treatment recommendations for MMC in RCC with promising accuracy rates.Our selected AI architecture is able to learn and to generate medically comprehensible and explainable treatment recommendations. Small numbers of recommended therapies hamper AI training but this will improve with increasing numbers over time. Next, clinical trial data will be implemented to enable a higher level of explainability. Meanwhile, the first prospective validation is ongoing. Accuracy rates for AI-generated treatment recommendations of renal cell cancer based on F1-scores (test set of 93 cases). Task (number) F1-Score ↑ #Classes Class (number) F1-Score High Level Prediction (93) 0.76 (CatBoost) 5 Surgery (10)Medication (45)Aftercare (22)Best supportive care (4)Radiotherapy (12) 0.450.920.880.000.47 Low Level Surgical Prediction (10) 0.81(Soft Ordering) 3 Primary tumor resection (4)Resection of recurrent tumor (1)Metastases resection (5) 0.670.000.73 Low LevelDrug Prediction (45) 0.73 (XGBoost) 8 Sunitinib (8)Nivolumab (7)Cabozantinib (6)Pembrolizumab/Axitinib (5)Nivolumab/Ipilimumab (4)Pazopanib (3)Pembrolizumab (3)Other (9) 0.520.780.400.890.601.001.000.67
Investigating clinical associations between genomic alterations and prostate cancer lineage states using circulating tumor cell RNA sequencing.
256 Background: Resistance to Androgen Receptor Pathway Inhibitors (ARPI) in metastatic prostate cancer (mPC) is universal and can be driven by complex genomic alterations. The evolution of lineage state transitions from adenocarcinomas to neuroendocrine prostate cancer (NEPC) has also been shown to drive treatment resistance and poor survival. Identifying the timing and association of genomic mutations with lineage state transitions has been limited by the need for serial tumor biopsies. We report an integrated analysis of clinical next-generation sequencing (NGS) data and mPC lineage states with a novel circulating tumor cell (CTC) RNA sequencing methodology. Methods: We collected 273 samples from 117 unique patients with mPC in a prospective biomarker trial. CTCs were purified via immunomagnetic capture on an automated microfluidic technology and analyzed via RNA-seq. A subset of patients had a clinical grade genetic test performed on a contemporary metastatic tissue biopsy. We compared CTC gene expression for lineage states (luminal A, luminal B, NEPC) with somatic gene mutation subtypes known to confer resistance to ARPIs (AR, p53, RB, PTEN, HRR genes) and overall survival (OS). Results: Single sample pathway analysis of high CTC purity samples identified four transcriptional phenotypes: luminal A-like (LumA), luminal B-like (LumB), low proliferation (LP), and neuroendocrine (NE). Compared to patients with low CTC burden/purity (median OS not reached), patients with LumA and LP phenotypes had similar survival, patients with LumB and NE CTC phenotypes had shorter survival (LumB: median OS 6m, HR 9.1 [3.8-21.8], p<0.0001, NE: median OS 3.7m, HR 11.8 [2.4-57.2], p=0.0019). AR alterations were found in samples with prior ARPI exposure and at similar frequencies across all CTC phenotypes but NE where they were absent. RB mutations were enriched in the unfavorable CTC phenotypes (LumB, NE; p=0.0288). Integrating CTC phenotype with presence or absence of at least one high risk genomic alteration (AR, RB, TP53, PTEN), patients with favorable CTC phenotype (Low burden, LP and LumA) and no high risk alterations had the longest median survival (median OS NR), followed by patients with favorable phenotype but a high risk alteration (median OS 12.7m), patients with an unfavorable phenotype (LumB, NE) but no high risk alteration (median OS 8m), and unfavorable phenotype with a high risk alteration (median OS 4m). Conclusions: Somatic mutations in mCRPC influence lineage state acquisitions and treatment resistance. Lineage state transitions themselves are associated with poor outcomes and decreased survival which is worsened in the presence of high-risk genetic mutations including RB. This data presents potentially targetable patient populations that would benefit from treatment intensification and early disease monitoring for more aggressive mCRPC subtypes.
Safety of combining radiotherapy and antibody drug conjugates in advanced urothelial and other cancers.
758 Background: Antibody drug conjugates (ADCs) such as enfortumab vedotin (EV) and sacituzumab govitecan (SG) are novel treatments increasingly used for metastatic urothelial carcinoma (mUC). SG is also utilized in metastatic breast cancer (mBC). Radiotherapy (RT) is used for palliation or consolidation of metastatic sites in mUC and for bladder preservation in localized disease. There is limited data evaluating the safety of ADCs when combined with RT. We sought to characterize the safety of RT in patients with mUC or mBC cancer receiving EV or SG. Methods: A bi-institutional retrospective analysis was performed. Eligible patients had a diagnosis of mUC or mBC and received RT within 6 months of EV or SG receipt. Patients were stratified by intensity of RT (higher vs. lower), site of RT (pelvis with bladder, pelvis without bladder, outside pelvis), and RT timing relative to ADC (prior to, within 4 weeks of, or after ADC infusion). ADC status was categorized as discontinued for progression of disease, discontinued for toxicity, or continued therapy. Those who discontinued ADC for toxicity were further evaluated to assess attribution to RT vs. expected treatment-limited toxicity of ADC. Results: Between January 1, 2020 and January 31, 2024, 103 patients received 166 RT courses within 6 months of ADC. RT courses were of mostly lower intensity (66%) vs. higher intensity (34%), using a cutoff of biologically equivalent dose (a/b=10) of 35Gy after assessing the distribution of RT regimens. RT location was extra-pelvic (58%), pelvis without bladder (16%), brain (14%), and pelvis with bladder (11%). RT delivery occurred prior to ADC (30%), concurrent with ADC (46%), or after ADC completion (24%). Of 77 RT courses concurrent with ADC, 10 (13%) patients experienced grade 3-5 toxicity. All of these were attributed to known ADC toxicities and only one possibly influenced by addition of RT. No patients receiving RT to the bladder experienced high-grade toxicity. Conclusions: This real world, retrospective study thus found no added safety events for patients receiving RT with ADCs, even when administered concurrently. Further data to validate these findings is needed as the use of both ADCs and RT increases in patients with urothelial carcinoma. Concurrent ADC–RT and toxicity. Patient # Toxicity Grade Toxicity History Relationship to RT 1 G3 skin Out of RT field Unlikely 2 G3 neuropathy Out of RT field Unlikely 3 G3 neuropathy Out of RT field Unlikely 4 G3 neuropathy Out of RT field Unlikely 5 G3 neuropathy Out of RT field Unlikely 6 G3 pneumonitis Out of RT field Unlikely 7 G3 skin Out of RT field Unlikely 8 G3 thrombocytopenia Began prior to RT Unlikely 9 G3 oral mucositis Out of RT field Unlikely 10 G5 neutropenia vs. pneumonitis 1 week after completing craniospinal irradiation, ADC infusions resumed; two weeks later, the patient was admitted for pneumonia Possible ADC: Antibody-drug conjugate; RT: Radiotherapy.
Choice of androgen receptor pathway inhibitors (ARPi) by disease volume and timing of metastases in metastatic hormone sensitive prostate cancer (mHSPC).
184 Background: We update evidence on mHSPC when new evidence becomes available (PMID: 36862387). ARANOTE trial prompted us to assess the comparative efficacy of darolutamide (DARO) with other ARPi agents in mHSPC using the living network meta-analysis (LNMA). Methods: This LNMA is conducted using the living interactive evidence (LIvE) synthesis framework. Phase III trials assessing systemic treatments in mHSPC are included. Mixed treatment comparisons were made using a frequentist network meta-analysis. P-scores were computed to assess relative treatment rankings with higher values indicating potentially better efficacy. Results: This report of LNMA includes a total 11 trials (12628 patients; 12 unique treatment options) as of October 1 st , 2024. Overall results were consistent with prior updates. Analysis limited to the ARPi trials showed that inhigh volume, abiraterone acetate (AAP)+androgen deprivation therapy (ADT) (HR: 0.46; 95% CI: 0.40-0.53; rank 1), apalutamide (APA)+ADT (0.53; 0.41-0.68; rank 3), DARO+ADT (0.60; 0.44-0.81; rank 4) and enzalutamide (E)+ADT (0.48; 0.41-0.56; rank 2) significantly improved radiographic progression-free survival (rPFS) compared to ADT alone. No statistically significant differences were observed with DARO+ADT compared to AAP+ADT (1.30; 0.94-1.82), APA+ADT (1.14; 0.77-1.67) and E+ADT (1.24; 0.89-1.79). Inlow volume, AAP+ADT (0.48; 0.37-0.63; rank 4), APA+ADT (0.36; 0.22-0.58; rank 3), DARO+ADT (0.30; 0.15-0.60; rank 1) and E+ADT (0.32; 0.25-0.41; rank 2) significantly improved rPFS compared to ADT. E+ADT significantly improved rPFS compared to AAP+ADT (0.67; 0.47-0.96) in low volume. No statistically significant differences were observed with DARO+ADT compared to AAP+ADT (0.62; 0.30-1.30), APA+ADT (0.83; 0.36-1.92) and E+ADT (0.93; 0.45-1.94). In synchronous disease, AAP+ADT (0.58; 0.51-0.67; rank 4), APA+ADT (0.49; 0.39-0.62; rank 2), DARO+ADT (0.59; 0.44-0.79; rank 3) and E+ADT (0.42; 0.36-0.50; rank 1) significantly improved rPFS compared to ADT. E+ADT significantly improved rPFS compared to AAP+ADT (0.73; 0.59-0.89) in synchronous disease. In metachronous disease, DARO+ADT (0.34; 0.17-0.67; rank 1), APA+ADT (0.41; 0.22-0.77; rank 2) and E+ADT (0.44; 0.35-0.57; rank 3) significantly improved rPFS compared to ADT. No statistically significant differences were observed with DARO+ADT compared to APA+ADT (0.83; 0.33-2.08) and E+ADT (0.76; 0.37-1.57) in metachronous disease. The results were consistent for overall survival. Conclusions: Current evidence suggests no significant differences for darolutamide as compared to other ARPi agents. Enzalutamide may be preferred over AAP in low-volume or synchronous disease. Given similar efficacy, choice of ARPi requires careful consideration of patient-specific factors including cost, accessibility and toxicity.
A comprehensive evaluation of gene expression-based signatures for detecting tertiary lymphoid structures (TLS) in metastatic renal cell carcinoma (mRCC).
591 Background: TLS are organized lymphoid aggregates linked to improved response to immunotherapy in multiple cancers, including mRCC. Traditionally, TLS assessment relies on pathological staining of tumor sections. In this study, we evaluated the performance of TLS gene-expression signatures as an alternative diagnostic tool. Methods: Primary tumors from treatment-naïve patients with mRCC in the HCRN GU16-260 trial were analyzed using multiparametric immunofluorescence (IF), staining for CD3, CD20 (TLS), CD21 (mature TLS), and CD8. The counts and densities of total and mature TLS were calculated. Bulk RNA sequencing was performed on the same specimens, and 4 gene signature scores (Meylan, Cabrita, Coppola, and Ng) were estimated using gene set variation analysis (GSVA). Spearman's correlations between signature scores and TLS IF parameters, as well as the area under the receiver operator characteristic (AUROC) curve, were computed. Results: Our cohort included 78 patients with matched IF and RNA-seq data. All 4 TLS signatures demonstrated strong predictive performance for detecting the presence (vs. absence) of TLS by IF in each sample (AUROC 0.8 to 0.85). Quantitatively, the 4 TLS signature scores, measured as continuous variables, correlated with IF-based counts and densities of total TLS, and to a lesser extent, mature TLS (Table). In terms of comparative performance, Meylan’s signature showed the highest correlation with IF TLS features, while Ng’s was the least correlated (Table). Furthermore, Meylan’s signature achieved the best predictive ability to stratify high vs. low TLS (AUROC 0.83) and was more specifically correlated with TLS compared to CD8 density (Table). Conclusions: Expression-based signatures exhibit robust predictive ability for TLS detection and quantification, similar to previously established CD8 signatures, and represent valid surrogate tools to complement pathological diagnosis. Spearman’s correlations between IF parameters and TLS signatures. Parameter Meylan Cabrita Coppola Ng Total TLS count ρ=0.65, P= 1.1x10 -10 ρ=0.58, P= 2.9x10 -8 ρ=0.56, P= 7.1x10 -8 ρ=0.42, P= 1.4x10 -4 Mature TLS count ρ=0.51, P= 2.1x10 -6 ρ=0.41, P= 1.8x10 -4 ρ=0.34, P= 2.3x10 -3 ρ=0.39, P= 5.0x10 -4 Total TLS density ρ=0.63, P= 6.1x10 -10 ρ=0.58, P= 3.4x10 -8 ρ=0.55, P= 2.2x10 -7 ρ=0.42, P= 1.4x10 -4 Mature TLS density ρ=0.49, P= 5.1x10 -6 ρ=0.39, P= 3.5x10 -3 ρ=0.32, P= 4.3x10 -3 ρ=0.38, P= 6.8x10 -4 CD8 density ρ=0.42, P= 3.1x10 -4 ρ=0.62, P= 2.1x10 -8 ρ=0.67, P <2.2x10 -16 ρ=0.35, P= 2.9x10 -3
Upstaging and risk migration with blue light cystoscopy for non–muscle-invasive bladder cancer: Results from a prospective multi-center registry.
686 Background: Blue-light cystoscopy (BLC) is an established procedure for use in the diagnosis and surveillance of patients with non-muscle-invasive bladder cancer (NMIBC). It is associated with improved detection rates compared to white light cystoscopy (WLC); however, limited data is available regarding its role in upstaging and/or upgrading when used alongside WLC. The aim of this study is to assess the incidence and features of patients undergoing upstaging and/or risk-group migration with the implementation of BLC. Methods: Using data from the prospective multi-institutional Cysview Registry (2014-2024), patients with NMIBC who underwent transurethral resection or biopsy of bladder tumors were identified. The patients in whom malignant lesions were exclusively detected by BLC, as well as those experiencing an upward change in risk category (as defined by the American Urological Association [AUA] classification) based on BLC findings, were documented. The clinical features of these patients were subsequently reviewed. Results: In this study, 2,854 patients were enrolled, who collectively underwent 4,158 resections and provided 6,432 separate pathology samples. A total of 201 (7%) patients had at least one malignant lesion detected exclusively by BLC while having negative WLC. These lesions (total 335) included carcinoma in-situ (CIS) in 145 (43%), low-grade Ta in 53 (16%), high-grade Ta in 95 (28%), high-grade T1 in 37 (11%), and high-grade T2 in 5 (1%). In patients with multifocal disease, BLC resulted in AUA risk-group upward migration in 66 (2.3%) patients.Theclinical features of these two groups are presented in the table. Taken together, the total rate of upgrading or upstaging using BLC was 9.3%, including migration to low-risk in 1.2%, intermediate-risk in 2.1%, and high-risk in 6%. Conclusions: Using BLC during transurethral resection or biopsy of bladder tumors results in risk group migration in over 9% of patients with NMIBC. This impacts patient management, including the administration of intravesical therapy when it was not initially planned, an extension in the duration of therapy, or the decision to proceed with radical cystectomy. Clinical features of patients with malignant lesions detected by BLC only (A) and those with risk group migration (B). Clinical features A B Age, median (IQR), year 71 (63-76) 71 (61-77) Gender, n (%) Male Female 140 (74)49 (26) 54 (82)12 (18) History of smoking, n (%) 117 (62) 40 (61) Primary occurrence, n (%) 65 (34) 14 (21) History on intravesical therapy, n (%) 92 (49) 40 (61) Urine cytology * , n (%) Positive Suspicious Atypical Negative/NA 33 (17)21 (10)41 (20)106 (53) 13 (20)7 (11)10 (15)36 (54) IQR: interquartile range; NA: not available. *Detected by either voided urine or bladder wash.
Clinical and radiographic trends in patients with renal angiomyolipomas (AML).
458 Background: Renal angiomyolipoma (AML) is a common benign solid tumor of the kidney, typically found incidentally through imaging. These tumors can also present with symptoms like flank pain, hematuria, or retroperitoneal bleeding. AMLs are usually monitored and treated when they reach sizes between 4 and 6 cm based on clinical judgment, although the timing for intervention remains debated. This study aimed to investigate growth rates, assess radiographic features, and evaluate trends in clinical presentation. Methods: This multicenter, single-institution retrospective study reviewed patients diagnosed with renal AML at three Mayo Clinic locations (Rochester, Arizona, Jacksonville) from 1997 to 2021. Eligible patients had at least three abdominal scans over a minimum of two years and 36 months of follow-up. We reviewed radiologic reports, images, and charts to record demographics, tumor characteristics, imaging modalities, intervention rates, tumor sizes, and growth rates. The Mann-Whitney and Fisher exact tests were used for comparisons. Results: Among 839 patients, most were female (81.6%), with a median age of 58.55 years. Bleeding patients had significantly larger initial tumors (median 6.50 cm) compared to non-bleeding patients (median 1.20 cm), p < 0.001. Treatment with everolimus was more common in bleeding patients (12.2% vs. 2.1%), and the prevalence of tuberous sclerosis was higher in the bleeding group (19.5% vs. 6.3%). All bleeding patients underwent intervention, while 22.3% of the overall cohort received treatment. Follow-up duration and total scans did not differ significantly between groups. Over 12 months, non-bleeding patients had a median growth change of 0.00 cm [IQR: 0.00, 0.30], whereas bleeding patients showed a median growth change of 0.40 cm [IQR: 0.15, 1.00], p = 0.002. Conclusions: This study reveals significant differences in characteristics and growth patterns of renal angiomyolipomas between bleeding and non-bleeding patients. Bleeding patients had larger initial tumors and greater growth changes over time. Further studies on radiographic features may help identify lesions needing earlier intervention. Demographic and clinical characteristics of patients with renal AML: Comparison bleeding vs non-bleeding groups. Overall Non-bleeding Bleeding P-Value N 839 798 41 Gender (%) Female 685 (81.6) 650 (81.5) 35 (85.4) 0.793 Male 152 (18.1) 146 (18.3) 6 (14.6) Unknown 2 (0.2) 2 (0.3) 0 (0.0) Age (median [IQR]) 58.55 [47.04, 66.95] 58.72 [47.32, 67.19] 53.84 [42.88, 60.82] 0.015 Follow up (months) (median [IQR]) 45.30 [37.12, 89.15] 46.45 [36.32, 89.52] 39.70 [36.30, 61.63] 0.233 Total scans (median [IQR]) 3.00 [3.00, 5.00] 4.00 [3.00, 5.00] 3.00 [3.00, 4.00] 0.282 Initial size (cm) (median [IQR]) 1.30 [0.80, 2.70] 1.20 [0.70, 2.50] 6.50 [3.00, 9.30] <0.001 Everolimus (%) Yes 22 (2.6) 17 (2.1) 5 (12.2) 0.001 Tuberous sclerosis (%) Yes 58 (6.9) 50 (6.3) 8 (19.5) 0.003 Intervention (%) Yes 187 (22.3) 147 (18.4) 41 (100) <0.001
A retrospective real-world study of disitamab vedotin combined with tislelizumab versus chemotherapy in patients with previously untreated metastatic urothelial carcinoma.
733 Background: Eligible patients with metastatic urothelial carcinoma (mUC) typically receive platinum-based chemotherapy as first-line therapy. Recently, antibody-drug conjugates (ADCs) combined with PD-1 antibody have shown good efficacy and safety in metastatic urothelial carcinoma (mUC). And HER2-positive thought to be an unfavorable prognostic factor and associated with poor outcomes but can benefit from anti-HER2 ADCs such as Disitamab Vedotin (RC48-ADC). The aim of this retrospective study is to evaluate the efficacy and safety of RC48-based therapy in real-world untreated mUC, especially in comparison to standard chemotherapy. Methods: We retrospectively collected data from 70 consecutive patients with mUC who received routine care between July 2022 and December 2023 including 30 received RC48-ADC plus Tislelizumab (DT-group) and 40 received the conventional regimen of Gemcitabine plus Cisplatin (GC-group). Last follow-up on 30 March 2024. The primary endpoints were objective response rate (ORR), disease control rate (DCR), median progression-free survival (PFS), overall survival (OS), and treatment-related adverse events (TRAEs). Results: The median age of the DT-group and GC-group patients were 67-y and 64-y, with 66.7% (n=20) and 82.5% (n=33) HER-2 negative (identified as IHC 0 or 1+). Baseline characteristics of the two groups, including age, gender, pathological grading, ECOG score, tumour location, metastasis and HER-2 expression showed no statistically difference (P > 0.05). The ORR in DT-group was 1.5 times higher than in GC-group, reaching 73.3% (22/30) versus 47.5% (19/40) with a higher CR rate (20% vs 0%). Even in HER-2 negative subgroup from DT-group, the RC48-ADC plus Tislelizumab therapy achieved impressive outcomes (ORR 55% (11/20)) comparable to chemotherapy. For survival analyses, PFS was longer in the DT-group than in GC-group (median, 10.98 months vs. 7.67 months; P<0.005), as was OS (median, not reached vs. 11.34 months). Two groups showed a similar safety profile (p > 0.05). The most reported TRAEs were bone marrow suppression, gastrointestinal and hepatobiliary disorders, malaise, alopecia and rash, and no ≥ grade 3 TRAEs or treatment-related deaths were reported. Conclusions: This retrospective study of patients with treatment-naïve mUC demonstrated administration of RC48 for real-world patients is both effective and safe. Several global clinical trials (DV-001, RC48-G001) evaluating efficacy and safety of RC48-ADC in combination with immunotherapy are ongoing. These data further solidify the benefit of anti-HER2 ADC combined with checkpoint inhibitors for frontline treatment of patients with mUC.
Impact of relative dose intensity on efficacy of enfortumab vedotin monotherapy in platinum and ICI resistant metastatic urothelial carcinoma: A multi-institutional real-world analysis.
728 Background: The treatment paradigm for metastatic or locally advanced urothelial carcinoma (mUC) has shifted towards combination therapies with Enfortumab Vedotin (EV) and Pembrolizumab. Understanding EV's characteristics is crucial for optimizing treatment. The EV-101 trial showed a correlation between exposure and efficacy, but few real-world studies explore how relative dose intensity (RDI) impacts outcomes. This study examines RDI's effect on efficacy using real-world data. Methods: We retrospectively analyzed 123 mUC patients treated with EV monotherapy as third-line or later, following progression after platinum-based chemotherapy and resistance to immune checkpoint inhibitors (ICIs). Data were collected from five institutions. We evaluated overall response rate (ORR), progression-free survival (PFS), and overall survival (OS). Patients were grouped into full dose on-schedule (FDO) and dose/schedule adjusted (DSA) based on EV dose and timing until best response (BR). On DSA group, relative dose intensity (RDI) until BR (BRRDI) was measured, and patients were classified into High (BRRDI > 80), Intermediate (80 ≥ BRRDI > 70), and Low (BRRDI ≤ 70) groups for comparison. Results: Among the 123 patients, median OS (mOS) was 14.8 Ms, median PFS (mPFS) was 7.1 Ms, and ORR was 48%, with a complete response (CR) rate of 9%. In the FDO group (31 patients), mOS was 9.3 Ms, mPFS was 4.5 Ms, and ORR was 29% (CR: 0%). In the DSA group (93 patients), mOS was 17.1 Ms (p=0.002), mPFS was 8.8 Ms (p=0.019), and ORR was 56% (CR: 12.1%) (p=0.0029 for ORR, p=0.017 for CR). In the BRRDI analysis, median time to BR was 2.6 Ms. ORR for High, Intermediate, and Low groups were 50% (CR: 20%), 58% (CR: 3.4%), and 63% (CR: 9.4%), respectively, with significant differences in CR (p=0.026). Conclusions: Patients requiring dose or schedule adjustments before best response showed better ORR, OS, and PFS than those on full dose. Higher BRRDI correlated with better CR, emphasizing the need to manage adverse events while maintaining dose intensity until BR.
Association of statin use with overall survival and cardiac adverse events in patients with advanced prostate cancer treated with apalutamide: A pooled analysis of TITAN and SPARTAN.
137 Background: The impact of statins on overall survival (OS) in patients (pts) with advanced prostate cancer is not fully understood. We performed a pooled analysis of the TITAN and SPARTAN trials to determine if exposure to statins had an independent effect on OS and grade ≥3 cardiac adverse events (AE) in pts treated with androgen deprivation therapy (ADT) with/without apalutamide (APA). Methods: TITAN and SPARTAN randomized pts to receive ADT with/without APA either in metastatic hormone-sensitive or in non-metastatic castration-resistant prostate cancer, respectively. Pts had at least some duration of statin exposure during the assigned treatment which could have started before and ended during or after the assigned treatment. A stratified (for the trial) multivariable Cox proportional hazard model was applied to determine the association of statin use with OS. Adjusted (adj) OS was estimated for pts in each trial, separately. A multivariable stratified logistic regression model was applied to determine the association of statin exposure with grade ≥3 cardiac AE. Results: Out of 2190 pts included in this study, 1288 received APA (TITAN 517; SPARTAN 771) and 484 were exposed to statins. Statin exposure was associated with significantly superior OS among all APA-treated pts (adjusted hazard ratio [HR]: 0.58; 95% CI: 0.45-0.75) while the OS benefit was not significant among ADT-treated pts (adjusted HR: 0.83 [0.62-1.11]). Adjusted 3-year OS in pts with and without statins were 82% and 67% (adjusted difference: 15%; 95% CI: 6-24) in the APA arm of TITAN and 86% and 78% (adjusted difference: 8% [3-13]) in the APA arm of SPARTAN. Adjusted 3-year OS among pts with and without statins was 71% and 58% (adjusted difference: 13% [3-24]) in the ADT arm of TITAN and 77% and 75% (adjusted difference: -2% [-10 to 6]) in the ADT arm of SPARTAN. Statin exposure was associated with a higher risk of grade ≥3 cardiac AE in pts treated with APA (adjusted odds ratio [OR]: 2.92 [1.56-5.47]) and ADT (adjusted OR: 3.06 [1.18-7.89]). Conclusions: In this exploratory analysis, exposure to statins was associated with significantly improved OS in all APA-treated patients but not in ADT-treated patients. Statin exposure was also associated with a higher risk of grade ≥3 cardiac AE in all pts (APA and ADT), which could be attributed to pre-existing cardiac comorbidities requiring these patients to start statin.