Citations

Abstract Background: Despite efficacy in metastatic clear cell renal cell carcinoma (ccRCC), immunotherapy currently has no role in the neoadjuvant setting. Suppressive tumor-associated macrophages (TAMs) are known to mediate resistance to immune checkpoint blockade (ICB) in ccRCC. In preclinical studies, IL-1β blockade reprograms TAMs toward an anti-tumor phenotype and promotes T cell activation, creating a tumor microenvironment (TME) more sensitive to ICB. To test this in patients, we conducted a correlative-rich neoadjuvant trial of IL-1β + PD-1 inhibition in localized ccRCC. Methods: SPARC-1 is a single-center, phase 1b study assessing the safety and feasibility of neoadjuvant canakinumab (αIL-1β) and spartalizumab (αPD-1) in patients with localized ccRCC (T1b-T4NanyM0 or TanyN1M0). All patients received 2 doses of canakinumab (300mg IV, Q4w) and spartalizumab (400mg IV, Q4w), 6 weeks (±7 days) prior to nephrectomy. The primary endpoint was safety and feasibility. Key secondary and exploratory endpoints included 12-month metastasis-free survival rate, pathologic response rate, and quantification of immune cell infiltration. To characterize immunologic reprogramming, fresh tumor specimens were collected at nephrectomy for single-cell RNA sequencing (scRNAseq) and multiparametric flow cytometry. Tissue from a treatment naïve cohort was collected for comparative analysis (n=16). Results: From August 15th, 2018, to January 30th, 2025, 14 patients were enrolled. There were no severe treatment-related adverse events (Grade ≥ 3) attributed to canakinumab or spartalizumab. At a median follow-up of 12.0 months (range, 6.3-12.0 months), the 12-month metastasis-free survival was 100%. Based on the ASSURE nomogram, the mean predicted 12-month recurrence risk was 16.7% (range, 4.7-46.5%). ScRNAseq revealed that treatment with αIL-1β + αPD-1 increased the frequency of TREM2+APOE+ TAMs (p=0.035), a population typically associated with immune suppression. However, these TAMs exhibited a phenotypic shift toward a less immunosuppressive state, with reduced IL-1β expression and increased CXCL9:SPP1 ratio, consistent with anti-tumor TAM polarization. Immune profiling revealed an increased CD8/CD4 T cell ratio (p=0.042) with modest enrichment of activated CD8+ T cells after treatment, supporting a more pro-inflammatory TME. Conclusions: The neoadjuvant combination of canakinumab (αIL-1β) and spartalizumab (αPD-1) is well-tolerated, feasible, and demonstrated promising clinical activity with no progression of disease observed in a localized ccRCC population at high risk of recurrence. Correlative analyses demonstrated that combined IL-1β and PD-1 blockade reprograms immunosuppressive TAMs, providing evidence that dual IL-1β and PD-1 inhibition can overcome myeloid-driven resistance in ccRCC. Clinical Trial Information: NCT04028245 Citation Format: Patrick J. McCann, Aleksandar Obradovic, Casey R. Ager, David H. Aggen, Catherine S. Spina, Chelsea L. Rahiman, Kaitlyn R. Campbell, Caroline Laplaca, Peyton C. Johnston, Amanda Kim, Katherine Gomez, Kriti Bagri Manjrekar, Mark N. Stein, Charles G. Drake, Karie Runcie, Matthew Dallos. Neoadjuvant IL-1β and PD-1 inhibition in localized clear-cell renal cell carcinoma: Clinical and correlative analyses of the phase 1b SPARC-1 trial [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(8_Suppl):Abstract nr CT017.

The phase III AUGMENT trial (ClinicalTrials.gov identifier: NCT01938001 ) demonstrated improved efficacy for lenalidomide plus rituximab (R 2 ) versus rituximab with placebo (R-placebo) in patients with relapsed or refractory (R/R) indolent non-Hodgkin lymphoma (iNHL). Here, we present the long-term follow-up results and prespecified subgroup analyses of patients with follicular lymphoma (FL), including those 70 years and older. Patients with R/R grade 1 to 3a iNHL were randomly assigned 1:1 to receive R 2 or R-placebo. In this long-term follow-up report, progression-free survival (PFS) was assessed per the investigator. Secondary end points included overall survival (OS) and safety. Of the 358 randomly assigned patients (intent-to-treat [ITT] population), 295 had FL (≥70 years, n = 66). At long-term follow-up (median, 65.9 months), in the ITT iNHL population, PFS (hazard ratio [HR], 0.50 [95% CI, 0.38 to 0.66]) and OS (HR, 0.59 [95% CI, 0.37 to 0.95]) were improved with R 2 versus R-placebo. Safety findings were consistent with the primary analysis. Improved long-term efficacy with R 2 versus R-placebo and manageable safety with R 2 were observed in patients with FL, including those 70 years and older. With a follow-up of >5 years, data from the AUGMENT trial continue to support the use of R 2 as a standard of care for patients with R/R iNHL.

ABSTRACT Background Street Medicine, where healthcare is provided in non‐traditional settings, provides care to people experiencing homelessness (PEH). Street medicine has been shown to improve patients' health and decrease Emergency Department visits, making it a cost effective way to provide medical care to PEH. Methods This paper is based on the SAEM25 didactic session as conducted in Philadelphia, where a panel of providers who are directly involved in street medicine clinics shared their experiences and perspectives on the various designs in practice. These topics included key logistical challenges and solutions, barriers to care and trust building, strategies for fostering sustainable partnerships with community organizations, and options for medical student or resident involvement. Results The design and unique approach of four different universities across the country was compared and contrasted by a panel of experts, all with experiences working directly with PEH. There are similarly identified barriers to providing care to PEH including location and transportation, financial and food insecurity, and trust between the community and the healthcare system. Conclusion There are multiple options that exist to provide a framework to create a clinic to support populations of PEH.

Abstract Context Patients with mild autonomous cortisol secretion (MACS) have higher rates of vertebral fractures compared to patients with non-functioning adrenal nodules, yet bone density is not always reduced. Objective To characterize the effect of MACS on bone density, metabolism, and microstructure as measured by high-resolution peripheral quantitative computed tomography (HR-pQCT). Design Cross-sectional study, 2019-2022 Setting Tertiary referral center Participants Seventy-five patients with MACS and 75 age-, sex-, and gonadal status–matched referent subjects. Measurements Bone turnover markers, dual-energy x-ray absorptiometry (DXA) scan, and HR-pQCT. Outcomes Areal and volumetric bone mineral density (aBMD, vBMD), trabecular bone score (TBS), microstructural parameters including trabecular bone volume to total volume (BV/TV) ratio. Results While no differences in aBMD were observed at any skeletal site, patients with MACS had decreased TBS (1.389 vs 1.475, P < .001) and lower osteocalcin concentration (17.1 vs 19.5 ng/mL, P = .030) than referent subjects. On HR-pQCT at the tibia, patients with MACS had reduced trabecular BV/TV (0.220 vs 0.233, P = .015) compared to referent subjects. On multivariable analysis, MACS was associated with lower TBS (odds ratio [OR] per SD decrease 2.87 [1.65-5.00]), lower trabecular BV/TV at the radius (OR per SD decrease 2.58 [1.33-5.00]), and lower trabecular BV/TV at the tibia (OR per SD decrease 4.06 [2.10-7.86]). Conclusion Patients with MACS have microstructural deterioration that may not be evident on routine DXA aBMD testing.

BACKGROUND: The metabolic mechanisms underlying right ventricular (RV) dysfunction are poorly understood, particularly outside of group 1 pulmonary hypertension (PH). We aimed to identify metabolites and pathways associated with RV systolic function and explored whether associations differed by pulmonary vascular resistance, PH group 1 status, and sex. METHODS: We analyzed data from the multicenter PVDOMICS (Pulmonary Vascular Disease Phenomics) cohort. RV systolic function metrics included fractional area change (echo), global longitudinal strain (echo), and ejection fraction (cardiac magnetic resonance). We used linear regression adjusted for age, sex, body mass index, and PH group to assess associations between metabolites and RV function. Pathway enrichment analyses were used to identify pathways significantly associated with RV function. Interaction terms were assessed to determine whether metabolite associations were modified by pulmonary vascular resistance, group 1 PH status, or sex. Least absolute shrinkage and selection operator regression was used to develop metabolite-based scores for RV function, and prognostic performance was assessed. RESULTS: There were 979 participants with plasma metabolomics and RV function data. Linear regression identified 170 metabolites that were significantly associated with all 3 RV metrics. Androgenic steroid, gamma-glutamyl amino acid, polyamine, vitamin A, fatty acid, and sterol pathways are most strongly associated with RV systolic function. Two metabolites interacted with group 1 PH status, and 6 interacted with pulmonary vascular resistance. Four androgenic steroids are associated more strongly with RV systolic function in women compared with men. Metabolite-based scores were prognostically equivalent to RV systolic function metrics and less accurate than REVEAL Lite 2 scores. CONCLUSIONS: We provide a blueprint of metabolites and metabolic pathways associated with RV systolic function across the spectrum of PH. Novel links to vitamin A and glutathione metabolites were observed. We detected few metabolites that associated with RV systolic function differentially by group 1 PH status or degree of pulmonary vascular resistance elevation. Androgenic steroids may associate more strongly with RV systolic function in women compared with men.

OBJECTIVE This study investigated the relationship between diabetes and the incidence of postoperative dysphagia following cervical spine surgery (CSS). METHODS A prospectively collected multi-institutional quality registry was retrospectively reviewed. Patients who underwent CSS were categorized on the basis of diabetes status, and correlations with preoperative and postoperative Eating Assessment Tool-10 (EAT-10) dysphagia questionnaire scores were assessed. Mixed-effects logistic regressions were performed to examine the impact of preoperative diabetes on postoperative dysphagia. RESULTS Of the 2001 patients who met the inclusion criteria, 400 (20%) had diabetes. Baseline dysphagia rates were not significantly different between groups (18% vs 14%, p = 0.08). Patients with diabetes had a significantly higher incidence of dysphagia at 1 month (66% vs 54%, p = 0.002), 3 months (39% vs 26%, p < 0.001), and 12 months (33% vs 24%, p = 0.004) after surgery compared to patients without diabetes. Including baseline dysphagia as a fixed effect, multivariable analysis indicated that diabetes was a significant predictor of postoperative dysphagia at 1 month (OR 1.46, p = 0.041) and 3 months (OR 1.63, p = 0.001) but not at 12 months (OR 1.21, p = 0.3). In patients with no baseline dysphagia, those with diabetes (329 of 400 [82.3%]) had a significantly higher incidence of new dysphagia than nondiabetics at 1 month (62% vs 50%, p = 0.003), 3 months (34% vs 21%, p < 0.001), and 12 months (27% vs 18%, p = 0.001). The mean change in EAT-10 scores between baseline and 12 months was significantly worse in patients with preoperative diabetes (2.440 ± 5.013 vs 1.688 ± 4.139, p = 0.025). Multivariable analysis indicated that diabetes was a significant predictor of new postoperative dysphagia at 1 month (OR 1.49, p = 0.040) and 3 months (OR 1.81, p < 0.001) but not at 12 months (OR 1.31, p = 0.2). CONCLUSIONS Diabetes is a significant risk factor for experiencing postoperative dysphagia following CSS. Diabetes correlated with higher incidence of dysphagia at all postoperative time points and was a strong independent predictor of postoperative dysphagia at 1 and 3 months.

ABSTRACT Background Quality of life and symptom burden of patients with myelofibrosis are well recognized and compounded in those with anemia; however, the effects of transfusion burden or anemia severity on quality of life have not been comprehensively characterized. This post hoc descriptive analysis explored the association between transfusion status or hemoglobin improvement and patient‐reported outcomes (PROs). Methods The analysis used pooled populations across treatment arms from 3 clinical trials (SIMPLIFY‐1, SIMPLIFY‐2, MOMENTUM); sample sizes for each PRO measure were dependent on the trials in which they were administered. Results At both baseline and week 24, transfusion independence was associated with umerically greater mean SF ‐36v2 and EORTC QLQ ‐ C30 scores than transfusion dependence; in the subgroup that was transfusion dependent at baseline, those who achieved transfusion independence at week 24 had greater PRO improvements than those who remained reliant on transfusions. Regardless of transfusion status, patients who achieved a hemoglobin improvement ≥ 1, ≥ 1.5, or ≥ 2 g/ dL from baseline also had clinically meaningful improvements in quality of life (assessed via mean EQ ‐ 5D ‐ 5L or SF ‐36v2 scores) and symptoms (assessed via PGIC or MPN ‐ SAF / MFSAF Total Symptom Score) at week 24 compared with those who did not. Conclusions Collectively, these results provide preliminary insights into the associations of transfusion status and anemia severity with quality of life in myelofibrosis; as current PRO measures do not directly evaluate the relationship between symptoms such as fatigue and anemia, development of new measures to more comprehensively capture the patient experience for those with anemia in myelofibrosis may be warranted. Trial Registration NCT01969838, NCT02101268, NCT04173494

Abstract The Bridging the Gaps (BTG) in Leukemia, Lymphoma and Multiple Myeloma Consensus Conference 2025 brought together a multidisciplinary group of oncology experts to address the complexities of lymphoma management, focusing on mantle cell lymphoma (MCL), chronic lymphocytic leukemia (CLL), and diffuse large B‐cell lymphoma (DLBCL). This article presents consensus recommendations developed through a modified Delphi process, which emphasize the need for tailored therapeutic strategies in light of recent advancements in treatment options. Key recommendations include the screening for high‐risk features in MCL, use of the BOVen regimen (zanubrutinib, obinutuzumab, and venetoclax) for TP53 ‐aberrant cases, and integration of chimeric antigen receptor T‐cell therapy for patients with mantle cell lymphoma that is refractory to covalent Bruton tyrosine kinase inhibitors. For CLL, recommendations include consideration of time‐limited therapies for younger patients and a “watch and wait” strategy for asymptomatic patients despite the improved activity and safety of current treatment regimens. For DLBCL, this article highlights the challenges in treatment sequencing and the role of circulating tumor DNA and minimal residual disease testing in monitoring disease progression. Overall, the conference describes the importance of ongoing research to refine management strategies and improve patient outcomes in lymphoma care, addressing the gaps in clinical practice where high‐level evidence is lacking.

US is a valuable tool for assessing ovarian and adnexal lesions but is an operator-dependent modality, and it is crucial to optimize US technique to enhance O-RADS accuracy for reliable characterization and malignancy risk assessment.

Abstract To enhance the prediction of traumatic brain injury (mTBI) outcomes, we propose a deep learning approach that integrates brain computed tomography (CT) scans with corresponding synthetic T1-weighted magnetic resonance imaging (T1-MRI). Our method significantly outperforms the prediction using CT scans alone. TRACK-TBI Pilot dataset, which includes imaging and clinical outcome data from patients with TBI, is studied. The hypothesis is brain CT and T1-MRI complement each other and together will improve TBI prognosis compared to using either CT or T1-MRI alone. Since CT and T1-MRI may not be available for the same individual, we employed a specialized version of a generative adversarial network (GAN), known as fixed-point GAN (FP-GAN). FP-GAN was trained using unpaired CT and T1-MRI scans to generate synthetic T1-MRIs from real CT scans. This process produced pseudo-paired CT-MRI data, which was then used to train a deep learning classifier for outcome prediction. The classifier consists of dual parallel 3D ResNet-18 models, each independently processing T1-MRI and CT scans. We used Glasgow Outcome Scale-Extended (GOSE) scores at 3 months post-TBI as the measure of patient outcomes. To avoid data leakage, the subjects used in FP-GAN and ResNet-18 model have no overlap. We further divided the paired data, allocating 69 samples for 5-fold cross-validation and 17 samples for testing. Prognostic performance was evaluated using the area under the receiver operating characteristic curve (AUC), F1-score (the harmonic mean of precision and recall), sensitivity (true positive rate) and specificity (true negative rate). For binary classification, we defined good recovery as GOSE ≥ 7 (positive) and poor recovery (negative) as 3 ≤ GOSE ≤ 6. Accordingly, our training set consists of 24 subjects with poor recovery and 45 subjects with good recovery, while the testing set includes 5 subjects with poor recovery and 12 subjects with good recovery. A DeLong test on AUC confirms that the improvement from incorporating synthetic T1-MRI (AUC = 0.76 ± 0.10) is statistically significant (P &lt; 0.05) compared to using CT alone (AUC = 0.68 ± 0.13). The significant improvement from using the combination of real CT and synthetic T1-MRI in sensitivity (SEN = 0.95 ± 0.07) and overall performance metrics, such as F1-score (F1 = 0.84 ± 0.03), suggests that the proposed approach provides a robust and effective prognostic approach compared to using CT alone (SEN = 0.83 ± 0.18 and F1 = 0.76 ± 0.07). This pilot research demonstrates the potential of a deep learning-based harmonization model to bridge the gap between CT and T1-MRI in TBI assessment. By integrating synthetic T1-MRI with CT, prediction performance is substantially enhanced.