Citations

TPS5127 Background: Androgen deprivation therapy (ADT) ± androgen receptor pathway inhibitor therapy is a primary treatment for metastatic hormone-sensitive prostate cancer, but is noncurative and has significant toxicities when used long-term. In patients with OMPC for whom delaying ADT is appropriate, metastasis-directed therapy such as stereotactic body radiation therapy (SBRT) has been shown to provide local disease control. However, many patients do not experience a complete prostate-specific antigen (PSA) response and develop poly-metastatic disease. [ 177 Lu]Lu-PSMA-617 ( 177 Lu-PSMA-617) is a prostate-specific membrane antigen (PSMA)-targeted radioligand therapy with demonstrated efficacy and a manageable safety profile in patients with PSMA-positive metastatic castration-resistant prostate cancer in the VISION and PSMAfore trials. PSMA-DC (NCT05939414) is an ongoing, international, randomized phase 3 trial to evaluate the efficacy of 177 Lu-PSMA-617 versus observation after SBRT in delaying castration and disease progression in patients with PSMA-positive OMPC. Methods: Eligible patients have histologically confirmed prostate cancer, biochemical recurrence post-definitive treatment, OMPC with ≤ 5 PSMA-positive metastatic lesions including ≥ 1 distant metastasis on PSMA PET/CT scans (all must be amenable to SBRT), PSA doubling time < 10 months and non-castration testosterone levels (> 100 ng/dL). Exclusion criteria include distant metastasis by conventional imaging (CI; CT/MRI and bone scans) at screening, prior ADT (except adjuvant ADT completed > 12 months before randomization), or other systemic therapy for metastatic prostate cancer. Patients (N = ~450) will be randomized 2:1 to 177 Lu-PSMA-617 or observation and will receive SBRT to all metastatic lesions within 14 days, completed within 3 weeks. Patients will then receive either intravenous 177 Lu-PSMA-617 (7.4 GBq/6 weeks; 4 cycles), starting 7–21 days after SBRT, or undergo observation only. Additional SBRT for new lesions is allowed. ADT is allowed after a metastasis-free survival (MFS) event by CI confirmed by blinded independent review committee (BIRC). Safety follow-up will occur 42 days after the last 177 Lu-PSMA-617 dose and at the week 24 visit for the observational arm. Long-term follow-up for the 177 Lu-PSMA-617 arm will include safety assessments every ~32 weeks. The primary endpoint is MFS by CI as assessed by BIRC using RECIST v1.1, or death. To provide 90% power to detect a hazard ratio of 0.6, 187 MFS events are required. The key secondary endpoint is time to next hormonal therapy. Additional secondary endpoints include time to PSA progression, radiographic progression-free survival, symptomatic progression, patient-reported health-related quality of life, overall survival and safety. Shore et al. PSMA-delay castration (DC): an open-label, multicenter, randomized phase 3 study of [ 177 Lu]Lu-PSMA-617 versus observation in patients with metachronous PSMA-positive oligometastatic prostate cancer (OMPC). J Urol 2025;213 (5S2_suppl):e28. https://www.auajournals.org/doi/10.1097/01.JU.0001110444.53548.eb . Reused with permission; ©American Urological Association, 2025. This abstract previously presented at 2025 AUA Annual Meeting. Clinical trial information: NCT05939414 .

7023 Background: Axi-cel is an autologous chimeric antigen receptor (CAR) T-cell therapy approved for adults with R/R LBCL after ≥ 1 prior line of therapy (LoT). Adverse events, such as cytokine release syndrome (CRS) and neurologic events (NEs), may deter centers from using axi-cel in an outpatient (OPT) setting, though individual centers have observed comparable safety and effectiveness in OPT and inpatient (IPT) care (Furqan et al. Blood Adv . 2024). Here, we present safety and effectiveness outcomes of axi-cel by intention to treat in OPT and IPT settings in a multicenter real-world dataset. Methods: Pts receiving axi-cel for R/R LBCL in the US from 01/2021-07/2023 with data in the Center for International Blood and Marrow Transplant Research (CIBMTR) registry were eligible for analysis. Pts with prior allogeneic transplant or unknown intended care setting were excluded. Of potential pts, 119 OPT pts were identified from 29 centers where an increasing trend was seen (9.6% of pts in 2021 were OPT, 13.5% in 2022, 22.8% in 2023). Pts were matched to 119 IPT pts by propensity score matching on age, sex, comorbidities, lactate dehydrogenase (LDH), bulky disease, prior LoT, chemosensitivity, and infusion year (see table). Results: OPT pts had median age of 63 y (25% ≥ 70), 66% were male, and 67% had ≥ 1 comorbidity. Half (50%) had elevated LDH and 73% had 1 prior LoT. Bulky disease was reported in 3%, and 60% had chemo-resistant disease. Outcomes were analyzed at median follow-up of 12 mo. Safety and effectiveness outcomes were similar between OPT and IPT pts (see table). In multivariate analyses, no differences were found between intended care setting and CRS (odds ratio [OR] 1.09 [95% CI 0.51-2.35]), CRS Gr ≥ 3 (OR 0.57 [0.12-2.60]), NEs (OR 1.14 [0.65-2.00]), or NEs Gr ≥ 3 (OR 0.98 [0.48-2.00]). Among OPT pts, 24% and 50% did not require hospital admission within 30 d and 3 d, respectively. In pts aged ≥ 70 y, only any Gr NEs were higher in the OPT group. Conclusions: After matching on key factors that may be used to select pts for OPT infusion, outcomes were comparable between intended care settings. These findings corroborate prior results and support the consideration of axi-cel in appropriate OPT care settings. Outcomes between matched pts with R/R LBCL receiving axi-cel intended for OPT or IPT. OPT (n=119) a IPT (n=119) a CRS any Gr / Gr ≥ 3 83 (75−89) / 3 (<1−7) 83 (74−89) / 4 (1−10) NE any Gr / Gr ≥ 3 47 (38−57) / 19 (12−27) 46 (37−56) / 21 (14−30) Overall / complete response rates 78 (69−85) / 68 (59−76) 76 (67−83) / 62 (52-70) Duration of response @ 12 mo 64 (52−74) 69 (58−78) Progression-free survival @ 12 mo 53 (43−62) 53 (43−61) Overall survival @ 12 mo 71 (61−78) 72 (62−79) Non-relapse mortality @ 12 mo 6 (2−11) 4 (1−8) Hospital admission within 30 days of infusion / median duration (range), d 76 (67−83) / 9 (2−53) Not Applicable a Percent (95% CI) unless otherwise specified.

Significance Statement Why are there so few biomarkers accepted by health authorities and implemented in clinical practice, despite the high and growing number of biomaker studies in medical research ? In this meta-epidemiological study, including 804 studies that were critically appraised by expert reviewers, the authors have identified all prognostic kidney transplant biomarkers and showed overall suboptimal study designs, methods, results, interpretation, reproducible research standards, and transparency. The authors also demonstrated for the first time that the limited number of studies challenged the added value of their candidate biomarkers against standard-of-care routine patient monitoring parameters. Most biomarker studies tended to be single-center, retrospective studies with a small number of patients and clinical events. Less than 5% of the studies performed an external validation. The authors also showed the poor transparency reporting and identified a data beautification phenomenon. These findings suggest that there is much wasted research effort in transplant biomarker medical research and highlight the need to produce more rigorous studies so that more biomarkers may be validated and successfully implemented in clinical practice. Background Despite the increasing number of biomarker studies published in the transplant literature over the past 20 years, demonstrations of their clinical benefit and their implementation in routine clinical practice are lacking. We hypothesized that suboptimal design, data, methodology, and reporting might contribute to this phenomenon. Methods We formed a consortium of experts in systematic reviews, nephrologists, methodologists, and epidemiologists. A systematic literature search was performed in PubMed, Embase, Scopus, Web of Science, and Cochrane Library between January 1, 2005, and November 12, 2022 (PROSPERO ID: CRD42020154747). All English language, original studies investigating the association between a biomarker and kidney allograft outcome were included. The final set of publications was assessed by expert reviewers. After data collection, two independent reviewers randomly evaluated the inconsistencies for 30% of the references for each reviewer. If more than 5% of inconsistencies were observed for one given reviewer, a re-evaluation was conducted for all the references of the reviewer. The biomarkers were categorized according to their type and the biological milieu from which they were measured. The study characteristics related to the design, methods, results, and their interpretation were assessed, as well as reproducible research practices and transparency indicators. Results A total of 7372 publications were screened and 804 studies met the inclusion criteria. A total of 1143 biomarkers were assessed among the included studies from blood ( n =821, 71.8%), intragraft ( n =169, 14.8%), or urine ( n =81, 7.1%) compartments. The number of studies significantly increased, with a median, yearly number of 31.5 studies (interquartile range [IQR], 23.8–35.5) between 2005 and 2012 and 57.5 (IQR, 53.3–59.8) between 2013 and 2022 ( P < 0.001). A total of 655 studies (81.5%) were retrospective, while 595 (74.0%) used data from a single center. The median number of patients included was 232 (IQR, 96–629) with a median follow-up post-transplant of 4.8 years (IQR, 3.0–6.2). Only 4.7% of studies were externally validated. A total of 346 studies (43.0%) did not adjust their biomarker for key prognostic factors, while only 3.1% of studies adjusted the biomarker for standard-of-care patient monitoring factors. Data sharing, code sharing, and registration occurred in 8.8%, 1.1%, and 4.6% of studies, respectively. A total of 158 studies (20.0%) emphasized the clinical relevance of the biomarker, despite the reported nonsignificant association of the biomarker with the outcome measure. A total of 288 studies assessed rejection as an outcome. We showed that these rejection studies shared the same characteristics as other studies. Conclusions Biomarker studies in kidney transplantation lack validation, rigorous design and methodology, accurate interpretation, and transparency. Higher standards are needed in biomarker research to prove the clinical utility and support clinical use.

Background: Axicabtagene ciloleucel (axi-cel), an autologous chimeric antigen receptor (CAR) T-cell therapy, achieved an overall response rate (ORR) of 94% and a complete response (CR) rate of 79% in patients with relapsed or refractory (r/r) follicular lymphoma (FL) after two or more prior lines of therapy in the ZUMA-5 trial ( Jacobson et al. Lancet Oncol. 2022). Since its FDA approval in March 2021, there has been little evidence on comparative effectiveness (CE) studies of axi-cel vs standard-of-care (SoC), except ones using ZUMA-5 and historical SCHOLAR-5 data (eg, Ghione et al. Blood. 2022). This study was aimed to address this evidence gap in CE of axi-cel vs SoC used to treat r/r FL in real-world settings. Methods: The two data sources in this study were patients who received commercial axi-cel between March 2021 and May 2023 from the CIBMTR and patients who received historical SoC (eg, chemotherapy, anti-CD20 mAb + chemotherapy, immunomodulatory imide drugs) between July 2014 and December 2020 from SCHOLAR-5, which served as an external control of ZUMA-5 trial. The index date was defined as the initiation date of either the infusion for axi-cel patients or the last eligible systemic therapy for SoC patients. Patients were included if they were age ≥ 18, had documented r/r FL with histological grade 1, 2 or 3a, and received at least 2 prior lines of therapy at the index. Patients were excluded if they had transformed diffused large B-cell lymphoma, central nervous system involvement, prior receipt of CAR T or other non-CAR T cellular therapies or allogeneic stem cell transplant, or no post-index information on outcomes. Four effectiveness outcomes were ORR, CR rate, progression-free survival (PFS), and overall survival (OS). Imbalance in observed prognostic risk factors between the two was adjusted via a propensity score analysis using the standard mortality ratio weighting (SMRW). The primary analyses included weighted univariable analysis and multivariable logistic (ORR and CR rate) or Cox (PFS and OS) regressions that were adjusted for the covariates after the SMRW. A sub-analysis of patients age ≥ 65 was conducted using the same methods as the primary analyses. Results: The unweighted study cohort included 376 patients, in which 256 (68%) received axi-cel . Thepatients who received axi-cel were more likely to be younger (median age 61 for axi-cel vs 67 for SoC), have grade 3a FL (37% vs 12%), received 3 or more prior lines of therapy (83% vs 58%), or remained refractory to the last prior therapy (79% vs 73%) vs those who received SoC. The imbalance in the observed prognostic risk factors was mitigated via the SMRW. The weighted univariable analysis, in which the sample size by treatment reflected the SMRW, is shown in Table 1. In patients of all ages, ORR was 92% in axi-cel vs 67% in SoC, and CR rate was 84% vs 37%. Because of varying follow-up lengths by treatment (median 7 months for axi-cel and 37 months for SoC), survival outcomes were reported at month 6, at which time PFS rate was 88% in axi-cel vs 64% in SoC and OS rate was 97% vs 85%. The corresponding proportions for patients age ≥ 65 were similar to those reported for patients of all ages. In the weighted multivariable regressions, axi-cel was associated with statistically significantly better outcomes by all 4 effectiveness measures vs SoC (Table 1). Specifically, in patients of all ages, the odds ratios for axi-cel were 4.93 (95% CI, 2.35−10.34) for ORR and 16.72 (95% CI, 7.03−39.73) for CR rate, and the hazard ratios for axi-cel were 0.41 (95% CI, 0.22−0.77) for PFS and 0.15 (95% CI, 0.06−0.34) for OS. Similar to the patients of all ages in the primary analyses, patients age ≥ 65 in the sub-analysis also demonstrated improved outcomes associated with axi-cel (Figure 1). Conclusions: This study showed that patients with r/r FL after two or more prior lines of therapy treated with axi-cel experienced better outcomes compared with patients treated with SoC, and that older patients also benefited significantly from axi-cel. These findings suggest that axi-cel addresses an important unmet medical need in patients with r/r FL. Future research should include longer follow-up data on outcomes of axi-cel and CE of axi-cel vs other contemporary SoC therapies.

Abstract Background Mendelian randomization (MR) studies are susceptible to metadata errors (e.g. incorrect specification of the effect allele column) and other analytical issues that can introduce substantial bias into analyses. We developed a quality control (QC) pipeline for the Fatty Acids in Cancer Mendelian Randomization Collaboration (FAMRC) that can be used to identify and correct for such errors. Methods We collated summary association statistics from fatty acid and cancer genome-wide association studies (GWAS) and subjected the collated data to a comprehensive QC pipeline. We identified metadata errors through comparison of study-specific statistics to external reference data sets (the National Human Genome Research Institute-European Bioinformatics Institute GWAS catalogue and 1000 genome super populations) and other analytical issues through comparison of reported to expected genetic effect sizes. Comparisons were based on three sets of genetic variants: (i) GWAS hits for fatty acids, (ii) GWAS hits for cancer and (iii) a 1000 genomes reference set. Results We collated summary data from 6 fatty acid and 54 cancer GWAS. Metadata errors and analytical issues with the potential to introduce substantial bias were identified in seven studies (11.6%). After resolving metadata errors and analytical issues, we created a data set of 219 842 genetic associations with 90 cancer types, generated in analyses of 566 665 cancer cases and 1 622 374 controls. Conclusions In this large MR collaboration, 11.6% of included studies were affected by a substantial metadata error or analytical issue. By increasing the integrity of collated summary data prior to their analysis, our protocol can be used to increase the reliability of downstream MR analyses. Our pipeline is available to other researchers via the CheckSumStats package (https://github.com/MRCIEU/CheckSumStats).

Background and Aims: A better understanding of the underlying mechanism of acetaminophen (APAP)‐induced liver injury (AILI) remains an important endeavor to develop therapeutic approaches. Eosinophils have been detected in liver biopsies of patients with APAP overdose. We recently demonstrated a profound protective role of eosinophils against AILI; however, the molecular mechanism had not been elucidated. Approach and Results: In agreement with our previous data from experiments using genetic deletion of eosinophils, we found that depletion of eosinophils in wild‐type (WT) mice by an anti‐IL‐15 antibody resulted in exacerbated AILI. Moreover, adoptive transfer of eosinophils significantly reduced liver injury and mortality rate in WT mice. Mechanistic studies using eosinophil‐specific IL‐4/IL‐13 knockout mice demonstrated that these cytokines, through inhibiting interferon‐γ, mediated the hepatoprotective function of eosinophils. Reverse phase protein array analyses and in vitro experiments using various inhibitors demonstrated that IL‐33 stimulation of eosinophils activated p38 mitogen‐activated protein kinase (MAPK), and in turn, cyclooxygenases (COX), which triggered NF‐κB–mediated IL‐4/IL‐13 production. In vivo adoptive transfer experiments showed that in contrast to naive eosinophils, those pretreated with COX inhibitors failed to attenuate AILI. Conclusions: The current study revealed that eosinophil‐derived IL‐4/IL‐13 accounted for the hepatoprotective effect of eosinophils during AILI. The data demonstrated that the p38 MAPK/COX/NF‐κB signaling cascade played a critical role in inducing IL‐4/IL‐13 production by eosinophils in response to IL‐33.

AbstractBackgroundEpidemiological studies have demonstrated a positive association between chronic lymphocytic leukaemia (CLL) and non-melanoma skin cancer (NMSC). We hypothesized that shared genetic risk factors between CLL and NMSC could contribute to the association observed between these diseases.MethodsWe examined the association between (i) established NMSC susceptibility loci and CLL risk in a meta-analysis including 3100 CLL cases and 7667 controls and (ii) established CLL loci and NMSC risk in a study of 4242 basal cell carcinoma (BCC) cases, 825 squamous cell carcinoma (SCC) cases and 12802 controls. Polygenic risk scores (PRS) for CLL, BCC and SCC were constructed using established loci. Logistic regression was used to estimate odds ratios (ORs) and 95% confidence intervals (CIs).ResultsHigher CLL-PRS was associated with increased BCC risk (OR4th-quartile-vs-1st-quartile = 1.13, 95% CI: 1.02–1.24, Ptrend = 0.009), even after removing the shared 6p25.3 locus. No association was observed with BCC-PRS and CLL risk (Ptrend = 0.68). These findings support a contributory role for CLL in BCC risk, but not for BCC in CLL risk. Increased CLL risk was observed with higher SCC-PRS (OR4th-quartile-vs-1st-quartile = 1.22, 95% CI: 1.08–1.38, Ptrend = 1.36 × 10–5), which was driven by shared genetic susceptibility at the 6p25.3 locus.ConclusionThese findings highlight the role of pleiotropy regarding the pathogenesis of CLL and NMSC and shows that a single pleiotropic locus, 6p25.3, drives the observed association between genetic susceptibility to SCC and increased CLL risk. The study also provides evidence that genetic susceptibility for CLL increases BCC risk.

This study investigated the role of insulin-like growth factor-1/insulin-like growth factor-1 receptor (IGF-1/IGF-1R) in the genesis and progression of diabetic kidney disease (DKD) in a streptozotocin (STZ)-induced mouse diabetes model. We showed elevated IGF-1 expression in the DKD kidneys after 16 wk of diabetic onset. Intraperitoneal administration of IGF-1R inhibitor (glycogen synthase kinase-3β, GSK4529) from week 8 to week 16 postdiabetes induction ameliorated urinary albumin excretion and kidney histological changes due to diabetes, including amelioration of glomerulomegaly, inflammatory infiltration, and tubulointerstitial fibrosis. The GSK4529 treatment also attenuated alterations in renal tubular expression of E-cad and matrix protein fibronectin. Moreover, renal fibrosis in DKD (without treatment) was associated with Snail1 overexpression that was effectively prevented by IGF-1R inhibition. Further experiments in cultured renal epithelial cells (NRK) showed that IGF-1 silencing reproduced in vivo effects of IGF-1R inhibition with markedly attenuated Snail1 expression and near normalization of the Ecad1 and fibronectin expression pattern. Further Snail1 silencing prevented high-glucose-induced changes without affecting IGF-1 expression, consistent with Snail1 acting downstream to IGF-1. The antifibrotic effects were also shown with benazepril or insulin treatment but to a much lesser degree. In summary, in STZ-induced diabetic mice, activation of IGF-1 in diabetic kidneys induces fibrogenesis through Snail1 upregulation. The diabetes-related histological and functional changes, as well as fibrogenesis, can be attenuated by IGF-1/IGF-1R inhibition.

Inflammation plays a central role in pancreatic cancer etiology and can be modulated by diet. We aimed to examine the association between the inflammatory potential of diet, assessed with the Dietary Inflammatory Index (DII®), and pancreatic cancer risk in the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial prospective cohort. Our study included 101,449 participants aged 52–78 years at baseline who completed both baseline questionnaire and a diet history questionnaire. Energy‐adjusted DII (E‐DII) scores were computed based on food and supplement intake. Cox proportional hazards models and time dependent Cox models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) with participants in the lowest E‐DII quintile (most anti‐inflammatory scores) as referent. After a median 8.5 years of follow‐up, 328 pancreatic cancer cases were identified. E‐DII scores were not associated with pancreatic cancer risk in the multivariable model (HRQ5vsQ1 = 0.94; 95% CI = 0.66–1.35; p‐trend = 0.43). Time significantly modified the association (p‐interaction = 0.01). During follow up <4 years, there was suggestive evidence of an inverse association between E‐DII and pancreatic cancer (HRQ5vsQ1 = 0.60; 95% CI = 0.35–1.02; p‐trend = 0.20) while there was a significant positive trend in the follow up ≥4 years (HRQ5vsQ1 = 1.31; 95% CI = 0.83–2.08; p‐trend = 0.03). Similar results were observed for E‐DII from food only. Our study does not support an association between inflammatory potential of diet and pancreatic cancer risk; however, heterogeneous results were obtained with different follow‐up times. These divergent associations may result from the influences of undetected disease in the short‐term.