Citations

ABSTRACT Truncating mutations in the tumor suppressor STAG2 , which encodes a component of the cohesin complex, are prevalent across diverse human cancers. Here, we report that acute reconstitution of physiological STAG2 levels in STAG2 -mutant human glioblastoma multiforme cancer cells triggers a rapid reduction in the size of chromatin loops genome-wide. Despite this global change in chromatin loop size, early transcriptional responses to STAG2 restoration are limited to a small number of genes, most of which are induced by STAG2 reconstitution. Notably, the growth-suppressor EFEMP1 (Fibulin-3), a secreted glycoprotein that functions as an extracellular matrix-associated inhibitor of glioblastoma growth and invasion, was the only gene consistently induced across all experimental models. The most robust and conserved STAG2-induced genes all reside within intense chromatin loops whose anchors and overall intensity did not appear to change in response to STAG2 reconstitution. These findings suggest that inactivating mutations of STAG2 promote neoplastic transformation by alleviating a restriction on chromatin loop size, allowing for an expanded range of chromatin interactions that disrupts the maintenance of a tumor-suppressive transcriptome.

TPS7101 Background: Patients with high-risk CLL/SLL not achieving a complete response (CR) after ≥ 12 months of BTK inhibitor (BTKi) monotherapy remain at risk for early progression due to residual disease and BTKi resistance. A BCL-2 inhibitor (BCL-2i) introduces a complementary, BCR-independent apoptotic mechanism that may deepen responses and prolong progression-free survival (PFS). Lisaftoclax, a selective oral BCL-2i with a short half-life (4-6 h), enables once-daily dosing and is approved in China as second-line CLL therapy. Lisaftoclax monotherapy has demonstrated overall response rates (ORRs) of 67% in relapsed/refractory CLL and 62.5% in BTKi-refractory disease, including del(17p)/ TP53 -mutated cases. Lisaftoclax combined with acalabrutinib achieved ORRs >97% with favorable tolerability. This study evaluates whether lisaftoclax plus BTKi (acalabrutinib, zanubrutinib, or ibrutinib) improves PFS and/or overall survival (OS) (vs continued BTKi monotherapy) in patients with CLL/SLL and residual disease after prolonged BTKi treatment. Methods: This study will enroll approximately 440 patients randomly allocated to receive lisaftoclax plus BTKi or BTKi alone. Eligible patients have CLL/SLL and, after ≥12 months of BTKi monotherapy (lines 1-3), have achieved neither CR nor progressive disease (PD). Randomization is stratified by del(17p)/ TP53 status. Key inclusion criteria include age ≥18 years, ECOG PS 0-2, and residual disease with either high-risk features (del(17p)/ TP53 mutation, unmutated IGHV , or complex karyotype [≥5 abnormalities]), or measurable residual disease with lymph nodes ≥2.5 cm in the absence of high-risk features. Exclusion criteria include prior BCL-2i therapy or Richter transformation. Patients in the investigational arm will undergo a 5-day oral lisaftoclax ramp-up to 400 mg once daily plus physician's choice of BTKi in 28-day cycles until progression or toxicity. Control patients continue their current BTKi monotherapy. Safety and disease assessments (CT/MRI) will occur regularly. The primary endpoint is PFS by independent review committee (iwCLL 2018); key secondary endpoint OS; and other secondary endpoints, PFS by investigator, ORR, duration of response, MRD negativity, and safety. Enrollment is ongoing across 126 sites in 18 countries (ClinicalTrials.gov ID: NCT06104566). Clinical trial information: NCT06104566 .

e19046 Background: While outcomes in pts with R/R FL have improved with current SOC treatments (Tx), there remains a need for safe, efficacious, and convenient Tx options. GOLCA is a potential, first-in-class, oral CELMoD designed for Tx of lymphoma, with preferential distribution to lymphoid organs and enhanced activity in lymphoma cell lines. GOLCA induces rapid and deep degradation of Ikaros and Aiolos, leading to direct cell killing and immunomodulatory activity. GOLCA + R was well tolerated and effective in heavily pretreated pts in the two-part Ph 1/2 study, CC-99282-NHL-001. Here, we provide longer f/u in pts with R/R FL from Part B of the study. Methods: Pts with R/R FL with ≥2 prior lines of Tx (≥1 if prior anti-CD20 Tx) received GOLCA orally, once daily at 0.2 mg (n=22) or 0.4 mg (n=38) ± R for up to 2 y or until progressive disease (PD)/unacceptable toxicity. Primary endpoints included safety and RP2D determination; secondary endpoints are preliminary efficacy and PK. Results: As of September 15, 2025, 60 pts were enrolled. In 0.2 and 0.4 mg groups, median prior Tx lines were 3 and 3, 32% and 32% had prior lenalidomide (LEN), 27% and 29% had prior T-cell–redirecting Tx (CAR T and/or bispecific antibody) and 32% and 32% were refractory to last regimen. Tx is ongoing in 6 (27%) and 17 (45%) pts at 0.2 and 0.4 mg, respectively; discontinuations (d/c) were mostly due to PD. Neutropenia, an on-target side effect of GOLCA, was the most common grade 3/4 Tx-emergent adverse event (TEAE) occurring in 59% and 68% of pts at 0.2 and 0.4 mg, followed by anemia (9% and 16%) and febrile neutropenia (9% and 8%). Median time to resolution of neutropenia was 8 days. Dose reductions occurred in 14% and 37% of pts at 0.2 and 0.4 mg, most commonly due to neutropenia (5% and 21%) and febrile neutropenia (5% and 5%). No d/c or deaths were from GOLCA-related TEAEs. Non-hematologic TEAEs were infrequent and mostly low grade. In efficacy-evaluable pts (GOLCA 0.2 and 0.4 mg + R, n=22 and n=36), median f/u was 14.03 months (mo), overall response rate (ORR) was 77% (complete response rate [CRR], 41%) at 0.2 mg, and 97% (CRR, 78%) at 0.4 mg. In the 0.4 mg group, responses were consistent in high-risk subsets including pts with prior LEN (ORR, 100%; CRR, 75%) and/or T-cell–redirecting Tx (ORR, 91%; CRR, 64%). GOLCA 0.4 mg + R demonstrated durable responses (median DOR, 9.17 mo; 91% of pts who achieved a CR remained in CR at cutoff). Conclusions: With longer f/u, GOLCA + R demonstrated promising efficacy with durable responses and no new safety signals. The 0.4 mg group had higher ORR and CRR than 0.2 mg, including in pts with prior LEN-based and/or T-cell–redirecting Tx, with a manageable safety profile at both doses. The results support the development of GOLCA + R as a fixed-duration, chemotherapy-free outpatient Tx in the Ph 3 GOLSEEK-4 study in 2L+ FL (NCT06911502). Clinical trial information: NCT03930953 .

e16535 Background: RMC is a rare and highly aggressive malignancy that predominantly affects young individuals with sickle hemoglobinopathies. Due to its rarity, no validated prognostic models exist to guide clinical decision-making. We aimed to develop and internally validate a prognostic model for patients with RMC using routinely available clinical and laboratory variables. Methods: We analyzed a single-institution cohort of patients with RMC. Candidate variables were identified based on biological plausibility and represented in a directed acyclic graph. Missing data were handled via multiple imputation by chained equations ( m = 50). Variables were ranked using elastic net Cox regression ( α = 0.5, λ = λ min ) with stability selection derived from 100 bootstrap resamples per imputed dataset. Predictors achieving > 60% selection frequency were retained for a nested parsimony analysis. Bootstrap internal validation ( B = 2000) estimated optimism-corrected discrimination and calibration performance, with the calibration slope applied as global shrinkage to penalize final coefficients for overfitting. Clinical utility was evaluated via decision curve analysis (DCA) at 18- and 24-month horizons. Results: Among 180 patients (median age 29; IQR 23–37), 142 deaths occurred with a median follow-up of 12.4 months. The final model included four predictors (Table). The optimism-corrected c-index was 0.667 (optimism = 0.009), and the calibration slope was 0.964, indicating minimal overfitting. Calibration plots showed excellent predicted-observed agreement at 12, 18, 24, and 36 months. DCA showed net benefit across threshold probabilities of 10%–75% at 18 months and 10%–80% at 24 months compared to default strategies. In sensitivity analysis, inclusion of TP53 mutation status improved discrimination ( c -index 0.686) and model fit ( ΔAIC −10.6). An interactive web-based risk calculator was developed to facilitate clinical implementation. Conclusions: This study presents the first internally validated prognostic model for RMC, demonstrating acceptable discrimination and excellent calibration using routinely available variables. By stratifying patients into distinct risk groups, this model may inform treatment intensity—guiding escalation to multi-agent regimens or sequential chemotherapy cycling in high-risk patients, while identifying lower-risk patients who may benefit from de-escalation strategies such as metastasis-directed therapy for oligometastatic disease or consideration of cytoreductive nephrectomy. External validation is warranted. Variable Time Ratio 95% CI p value ECOG performance status 0.64 0.53–0.77 <0.001 Distal (non-retroperitoneal) lymph node metastases 0.69 0.52–0.92 0.011 Neutrophil-to-lymphocyte ratio 0.98 0.94–1.02 0.25 Corrected calcium (mg/dL) 0.77 0.56–1.06 0.10 Sensitivity Analysis Only TP53 Mutation 0.63 0.36-1-10 0.10

e16159 Background: Pivotal trials established atezolizumab-bevacizumab and durvalumab-tremelimumab as first-line therapies for unresectable hepatocellular carcinoma (HCC). Atezolizumab plus bevacizumab demonstrated superior survival outcomes compared to sorafenib for unresectable HCC in the IMbrave150 trial in 2020, while durvalumab plus tremelimumab showed superior survival in the HIMALAYA trial in 2022. However, data on head-to-head comparison of these two combinations as first-line systemic therapy for the patient with decompensated HCC are limited. This study aims to compare survival outcomes between these two treatment regimens in decompensated HCC patients to address a critical gap in the current literature, as decompensated patients have largely been excluded from clinical trials. Methods: This retrospective study utilized electronic health records from 146 U.S. healthcare organizations within the TriNetX Network. Adults aged ≥21 years diagnosed with decompensated HCC receiving atezolizumab/bevacizumab and durvalumab/tremelimumab from 10/21/2022 to 8/20/2024 were included. The comparison group received atezolizumab/bevacizumab, and the control group received durvalumab/tremelimumab. The primary outcome was all-cause mortality. A 1:1 propensity score matching was conducted to balance baseline characteristics (age, gender, race/ethnicity, lab results including liver function tests, platelet counts, INR, gamma glutamyl transferase, alpha-fetoprotein, and underlying liver diseases). Kaplan–Meier survival analysis and Cox regression was used to estimate the mortality risk. Subgroup analysis was stratified by HCC etiology. Results: A total of 302 and 664 patients received durvalumab/tremelimumab, atezolizumab/bevacizumab, respectively. After propensity matching, 253 patients per group were included. Median OS was 283 days with durvalumab/tremelimumab and 391 days with atezolizumab/bevacizumab. The two treatment regimens showed no significant difference in survival (hazard ratio [HR]: 0.875, 95% confidence intervals [CI] 0.696–1.101, p=0.254). Subgroup analyses demonstrated no significant differences in survival between the two groups of patients in MASLD (HR: 0.698, 95% CI: 0.468–1.040), alcohol associated liver disease (HR: 0.821, 95% CI: 0.603–1.118), and chronic viral hepatitis (HR: 0.852, 95% CI: 0.596–1.219). Conclusions: There was no statistically significant difference in survival outcomes between atezolizumab plus bevacizumab and durvalumab plus tremelimumab in patients with decompensated advanced HCC. These results support current real-world practice in which both regimens may be considered viable first-line treatment options in this high-risk population with liver decompensation.

e14545 Background: Durable antitumor immunity depends on the maintenance of stem-like CD8⁺ T cells capable of sustaining long-term effector responses. Oncolytic viruses (OVs) are potent immunomodulatory agents that reshape the tumor microenvironment and augment antitumor immunity. We hypothesized that platinum-based chemotherapy alters tumor-intrinsic type I interferon (IFN-I) signaling in a manner that can be functionally restored by OV therapy, thereby promoting the generation and persistence of stem-like CD8⁺ T cells. Methods: Tumor cells treated with platinum chemotherapy were evaluated in vitro for changes in IFN-I pathway activity, OV replication, and markers of immunogenic cell death (ICD). Syngeneic mouse tumor models were used to assess antitumor efficacy and immune remodeling following combination therapy. Tumor-infiltrating lymphocytes were analyzed by single-cell RNA sequencing and multiparameter flow cytometry to define CD8⁺ T-cell states and functional programs. Guided by these preclinical findings, a clinical trial combining XELOX, PD-1 blockade, and OV therapy was initiated (ChiCTR2500107607). Results: Platinum chemotherapy significantly suppressed tumor-intrinsic IFN-I signaling, while OV therapy restored antiviral responses, enhanced viral replication, and increased ICD in vitro. In vivo, the combination strategy resulted in superior tumor control and profound remodeling of the tumor immune microenvironment. The most pronounced immunologic effect was observed within the stem-like CD8⁺ T-cell compartment. Combination therapy induced a distinct population of TCF7⁺ ISG15^high NFATC1^low AP-1^low CD8⁺ T cells, characterized by restrained activation, enhanced persistence, and reduced propensity toward terminal exhaustion. In IRF7-deficient tumors, this stem-like CD8⁺ T-cell population failed to emerge and antitumor efficacy was significantly diminished, indicating that moderate tumor-intrinsic IFN-I signaling is required for this immune state. Conclusions: Tumor-intrinsic type I interferon signaling is a critical determinant of synergy between platinum chemotherapy and oncolytic virotherapy, enabling the maintenance of durable stem-like CD8⁺ T-cell immunity. These findings establish a mechanistic rationale for combining platinum chemotherapy, oncolytic viruses, and immune checkpoint blockade and support ongoing clinical translation. Clinical trial information: ChiCTR2500107607.

Abstract Background High‐resolution MRI is essential for accurate diagnosis and treatment planning, but its clinical acquisition is often constrained by long scanning times, which increase patient discomfort and reduce scanner throughput. While super‐resolution (SR) techniques offer a post‐acquisition solution to enhance resolution, existing deep learning approaches face trade‐offs between reconstruction fidelity and computational efficiency, limiting their clinical applicability. Purpose This study aims to develop an efficient and accurate deep learning framework for MRI SR that preserves fine anatomical detail while maintaining low computational overhead, enabling practical integration into clinical workflows. Materials and Methods We propose a novel SR framework based on multi‐head selective state‐space models (MHSSM) integrated with a lightweight channel multilayer perceptron (MLP). The model employs 2D patch extraction with hybrid scanning strategies (vertical, horizontal, and diagonal) to capture long‐range dependencies while mitigating pixel forgetting. Each MambaFormer block combines MHSSM, depthwise convolutions, and gated channel mixing to balance local and global feature representation. The framework was trained and evaluated on two distinct datasets: 7T brain T1 MP2RAGE maps (142 subjects) and 1.5T prostate T2w MRI (334 subjects). Performance was compared against multiple baselines including Bicubic interpolation, GAN‐based (CycleGAN, Pix2pix, SPSR), transformer‐based (SwinIR), Mamba‐based (MambaIR), and diffusion‐based (I 2 SB, Res‐SRDiff) methods. Results The proposed model demonstrated superior performance across all evaluation metrics while maintaining exceptional computational efficiency. On the 7T brain dataset, our method achieved the highest structural similarity (SSIM: ) and peak signal‐to‐noise ratio (PSNR: dB), along with the best perceptual quality scores (LPIPS: ; GMSD: ). These results represented statistically significant improvements over all baselines (), including a 2.1% SSIM gain over SPSR and a 2.4% PSNR improvement over Res‐SRDiff. For the prostate dataset, the model similarly outperformed competing approaches, achieving SSIM of , PSNR of dB, LPIPS of , and GMSD of . Notably, our framework accomplished these results with only 0.9 million parameters and 57 GFLOPs, representing reductions of 99.8% in parameters and 97.5% in computational operations compared to Res‐SRDiff, while also substantially outperforming SwinIR and MambaIR in both accuracy and efficiency metrics. Conclusion The proposed framework provides a computationally efficient yet accurate solution for MRI SR, delivering well‐defined anatomical details and improved perceptual fidelity across anatomically distinct datasets. By significantly reducing computational demands while maintaining state‐of‐the‐art performance, the model offers strong potential for feasibility toward clinical translation and scalable integration into future imaging workflows.

9525 Background: Melanocortin-1 receptor (MC1R) is a novel target for radiopharmaceutical therapy and is highly expressed on melanoma tumor cells. VMT01 is an MC1R-targeted peptide. 203 Pb is used for patient selection via SPECT imaging. Peptide radiolabeling with 212 Pb delivers alpha-particle therapy. Here, we present data on the treatment of adult patients with MC1R-positive metastatic melanoma receiving [ 212 Pb]VMT01 either as a monotherapy or in combination with the programmed death-1 (PD-1) checkpoint inhibitor, nivolumab. Methods: This is an ongoing phase I/IIa, first-in-human, prospective, multicenter, open-label, radioactive dose-finding and dose-expansion trial. The objectives are to investigate safety, pharmacokinetics, dosimetry, and efficacy. Participants receive up to 3 treatment cycles with either [ 212 Pb]VMT01 3 mCi, 5 mCi, or 1.5 mCi monotherapy, or combination therapy with [ 212 Pb]VMT01 (1.5 mCi) + nivolumab (480 mg, Q4W) or [ 212 Pb]VMT01 (3 mCi) + nivolumab. Participants are evaluated for any DLTs for the first 6 weeks after cycle 1. Efficacy is assessed by RECIST v1.1 criteria by the investigator. Results: As of 24 December 2025, 26 participants (53.8% male; median age: 68 years [range: 27-81]) with MC1R-positive metastatic melanoma were enrolled. The median prior systemic therapies was 4. All 26 enrolled participants received ≥1 dose of [²¹²Pb]VMT01. No DLTs were reported. All SAEs (including one grade 5 SAE) were attributed to disease progression. Most TEAEs were grade 1 (19.2%) and grade 2 (34.6%). Grade 3 TEAEs occurred in 8 participants (30.8%), 5 on monotherapy and 3 on combination therapy (3 mCi + nivolumab). Of the 22 evaluable participants, 1 PR, 9 SD, and 12 PD were reported. Four participants had progression-free survival of ≥6 months. Conclusions: [ 212 Pb]VMT01 as a monotherapy and in combination with nivolumab was generally safe and well-tolerated in 26 enrolled participants, with antitumor activity observed at the 3 mCi dose level. These data may be supplemented with a more complete follow-up at the time of the meeting. Clinical trial information: NCT05655312 .

8045 Background: Surgical resection is the primary therapy for stage I-II NSCLC but not performed in a subset of patients due to comorbidities or self-election, who instead undergo radiation with or without systemic therapy (RT±ST). Little is known about the demographic, tumoral, therapeutic, and quality-of-life (QOL) characteristics of this non-surgical group. Understanding their differences from the surgical group is essential for developing precision treatment strategies and tailored survivorship guidelines. Methods: In a prospectively enrolled (1997-2016) and followed (through 2025) cohort of 20,951 primary lung cancer patients, 6,486 (31%) had stage I-II NSCLC, including 5,359 (83%) treated surgically (Surgical) and 1,113 (17%) otherwise (Non-surgical). Preexisting diseases were grouped into cancer, lung, and other comorbidities. QOL data were available for 40% of all patients. Descriptive analysis of demographics, tumor features, treatment patterns, and QOL metrics, as well as survival analysis (median years and overall survival [OS] rates) were conducted. QOL measures, on overall and 15 symptom and functional domains, were scored 0 (worst) to 10 (best), with 1-unit difference considered clinically and statistically meaningful. Results: At time of diagnosis, compared to the Surgical, the Non-surgical patients were older (median 73 v 68 years), more likely to have smoked cigarettes (91% v 83%), squamous cell and unspecified NSCLC (53% v 28%), stage IIB (19% v 12%), and preexisting lung comorbidities (71% v 58%). Non-surgical patients more frequently received RT±ST than the Surgical (70% v 21%) and had shorter median survival (2.5 v 7.8) years. Within the Non-surgical, 28% had no cancer treatment (No-Tx), 44% RT-only, 7% ST-only, and 19% both (RT+ST); their respective median diagnosis ages were 74, 76, 68, 70 years; median survival were 1.7, 2.7, 2.2, 3.2 years; 5-year OS (95%CI) at 25% (21-31), 25% (21-29), 26% (17-38), 30% (25-37); and 10-year OS at 9% (7-14), 7% (5-10), 10% (5-21), 9% (6-14), respectively. RT-only group had highest rates of comorbidities (37-84%) and the No-Tx the lowest (31-66%). Although the overall QOL scored the same for all groups, RT-only patients reported the worst scores on multiple symptoms burden, and the No-Tx reported the least pain and lung cancer symptoms but the worst on mental well-being and social activities. Conclusions: Non-surgically managed stage I-II NSCLC cases present clinically distinct patients with the shortest median survival in No-Tx group and highest 5-year survival in RT+ST. RT-only patients were oldest, had the most comorbidities, and reported the worst symptom burdens. These differences highlight the need for more in-depth analyses and studies (considering age, histology, comorbidity, QOL, etc.) to support tailored therapeutic strategies and survivorship care for patients who decline or are not suitable for surgery.

8021 Background: Lung cancer is the leading cause of cancer-related mortality worldwide, primarily due to delayed diagnosis and diagnostic variability in histopathological assessment. Advances in deep learning applied to medical imaging offer the potential to enhance early detection accuracy, reduce interobserver variability, and improve diagnostic efficiency in lung cancer. Methods: In this retrospective study, we evaluated DAVINCI using a dataset of 8,962 patients with confirmed lung malignancies. The model utilizes a specialized architecture combining convolutional neural networks (CNNs) and residual blocks to optimize feature extraction from high-resolution pathological slides. Performance was measured via detection accuracy, recall, specificity, and Area Under the Curve (AUC). Results: A total of 8,962 patients were included in the analysis. The DAVINCI model correctly identified lung cancer in 93% of cases, corresponding to 8,334 of 8,962 patients, with a 95% confidence interval (CI) of 86%–100% (7,707–8,962 patients). Model specificity was also 93% (95% CI, 86%–100%), indicating a high true-negative rate. Sensitivity (recall) was 87%, with correct detection in 7,797 patients and a 95% CI of 80%–94% (7,170–8,425 patients). The model demonstrated strong discriminatory performance, achieving an area under the curve (AUC) of 0.91 (95% CI, 0.84–0.98). In comparison, active pathologists achieved a mean diagnostic accuracy of 83%, corresponding to 7,438 of 8,962 cases, with a 95% CI of 76%–90% (6,811–8,066 cases). In terms of efficiency, DAVINCI processed whole-slide images in 16–19 seconds, substantially faster than conventional manual review, which typically requires several minutes per slide. Conclusions: DAVINCI demonstrated superior accuracy, robust discriminatory performance, and markedly faster processing compared with human review, supporting its potential role in early lung cancer detection at scale.