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Cellular and molecular heterogeneity in the liver has been increasingly recognized to drive liver fibrosis progression, but the particular events that occur initially in response to liver injury and trigger immune cell recruitment remain unclear. Here, we identify epigenetically aberrant liver sinusoidal endothelial cells (LSECs) as key players in this process. Mechanistically, the epigenetic readers like bromodomain-containing protein 4–dependent (BRD4-dependent) super enhancers (SEs) activate proinflammatory genes, including promyelocytic leukemia (PML). The PML protein, in turn, binds BRD4 and amplifies proinflammatory angiocrine signaling through phase separation–dependent SE activation via PML/BRD4 condensate formation. In mouse models, LSEC-specific depletion of the PML/BRD4 complex mitigates liver inflammation and fibrosis. Single-cell RNA-seq reveals that epigenetically aberrant LSECs exhibit a reprogrammed proinflammatory angiocrine landscape in mouse fibrotic livers. TIMP1 + LSECs promote the recruitment of CD63 + monocyte–derived macrophages (MoMFs) during liver fibrosis progression. Thereby, PML/BRD4 in LSECs governs inflammatory immune cell recruitment in liver fibrosis. Pharmacological BRD4 inhibition or epigenetic PML-SE repression alleviates liver inflammation and fibrosis. In conclusion, PML/BRD4-mediated SE activation via phase separation drives proinflammatory angiocrine signaling in LSECs, initiating the inflammatory cascade and subsequent immune cell recruitment during liver fibrosis.

Abstract Background Relapsed medulloblastoma remains a significant therapeutic challenge as it is near universally fatal. The tumor microenvironment of medulloblastoma plays a critical role in tumor progression, influencing tumor growth, immune evasion, and therapeutic resistance. We hypothesized that defining tumor-immune interactions in diagnostic and relapsed medulloblastoma may uncover mechanisms of immune evasion and identify novel therapeutic targets. Methods We analyzed paired primary and recurrent RNA-sequencing data from 140 medulloblastoma patients to profile immune cell composition and validate spatial relationships within the TME. To identify key tumor-immune interactions, we developed a novel algorithm to detect receptor-ligand pairs using single-cell RNA-sequencing data. These interactions were validated across RNA and proteomic datasets. Their functional significance was empirically demonstrated in newly developed immunocompetent models of recurrent medulloblastoma that closely recapitulate the human disease. Results We observed a shift toward a heightened immunosuppressive TME at relapse. Using our algorithm, we identified biologically significant receptor-ligand interactions, most notably MIF-CD74, constitutively expressed at RNA and protein levels across medulloblastoma subgroups, at diagnosis and relapse. Disrupting MIF-CD74 interactions led to significant alterations in the tumor microenvironment, highlighting its functional significance. Conclusions Our multifaceted approach identified key tumor-immune interactions in medulloblastoma. Among these, MIF-CD74 was validated as a targetable interaction, demonstrating the utility of our integrative approach for identifying novel therapeutic targets across multiple tumor types.

Abstract Background: For LS-DLBCL, clinical trials (FLYER, LYSA/GOELAMS 02-03, LYSA LNH09-1B, S1001) have shown that 4 cycles of rituximab, cyclophosphamide, doxorubicin, vincristine and prednisone (RCHOP4) without radiation (RT) leads to durable remissions in >90% of cases. However, only patients (pts) with non-bulky disease and/or international prognostic index (IPI) of 0 and complete metabolic response (CMR) on interim positron emission tomography (PET) scan, if performed, were eligible for RCHOP4 alone in these studies. Outcomes in trial-ineligible LS-DLBCL and the appropriate real-world candidates for RCHOP4 are still undefined. Methods: We conducted a multicenter retrospective study of adult pts with stage I/II DLBCL of any tumor bulk, IPI and with or without B-symptoms diagnosed after 2011 and treated with RCHOP4 +/- 2 cycles R from 21 U.S. centers. Pts with PMBCL, PTLD or receiving non-standard dose RCHOP for cycle (C) 1 or planned consolidative RT were excluded. The primary endpoint was PFS from C1 by Kaplan-Meier method, not counting indolent lymphoma relapse. Event free survival (EFS) was time to next therapy without progression (including unplanned RT for non-CR), progression or death. A competing risks analysis of non-relapse mortality (NRM) vs. DLBCL progression was performed. Results: The characteristics of the 428 pts were: median age 60 (18-88), 60% male, 11% Hispanic and 4% non-Hispanic Black, 62% stage I, 15% elevated LDH, 3% ECOG PS>1, 5% tumor bulk >7cm, 9% had B-symptoms and median Charlson Comorbidity Index (CCI) was 4 (2-12). IPI was 0, 1 and 2-3 in 42%, 46% and 12% and stage-modified IPI (smIPI) was 0, 1, 2 and 3-4 in 25%, 48%, 21% and 6% of pts. 66% had nodal (59% head/neck, 11% pelvic, 9% multiple above diaphragm, 7% abdominal) and 46% extranodal sites (37% head/neck, 20% gastric/intestinal, 9% spleen, 8% skin/soft tissue); 6% had transformed/concurrent FL/MZL or grade 3B FL, 33% (138/408) were non-GCB cell of origin (COO), 25% (90/357) double expressor (DEL) and 0.5% (2/379) double-hit. 13% had completely resected disease, 97% staging PET and 47% bone marrow biopsy. Median diagnosis to treatment interval was 30 days (IQR 20-43), 6% had dose reductions after C1, 77% had an interim PET (iPET) after C2 (33%) or C3 (67%), 15% received 2 additional cycles R and 4% CNS prophylaxis. CMR rates by iPET were 83% after C2 and 94% after C3, and 95% by end-of-treatment PET. iPET PMR was more likely if smIPI>2 or bulky disease. Median follow-up time was 2.7 years. There were 32 progression events: 14 occurred at the primary site and 17 at distant sites (1 unknown), and 12 occurred after 2 years. Another 11 pts received unplanned RT after RCHOP4 for non-CR. There were 24 deaths, 12 without prior progression. Cause of death was DLBCL in 7 and non-DLBCL in 17 cases (6 infection, 2 ILD, 2 heart failure, 2 second cancer, 1 seizure, 4 unknown). EFS, PFS and OS rates were 88%, 90% and 96% at 3 years. By univariable Cox regression, Black race, elevated LDH, smIPI>2, DEL, increasing CCI, multiple subdiaphragmatic nodal sites and iPET PMR were associated with worse PFS. Non-significant variables of note included COO, extranodal sites, complete resection, missing bone marrow biopsy, missing iPET and additional cycles R. By multivariable analysis (including age>60, stage, ECOG PS>1, elevated LDH, bulky disease, CCI, B-symptoms and DEL), ECOG PS>1 (HR 3.95 p=0.050), CCI (HR 1.29 p=0.003) and DEL (HR 2.02 p=0.069) were associated with worse PFS. Cumulative incidence of DLBCL progression and NRM were 8% and 2% at 3 years. Competing risk analysis by univariable models found that age>60, ECOG PS>1, smIPI>2, elevated LDH, CCI and bulky disease were associated with NRM, while DEL and B-symptoms were associated with DLBCL progression.Conclusion: Presented is the largest retrospective cohort of LS-DLBCL treated uniformly with RCHOP4 to date. Despite modest follow-up time and lack of an “intention-to-treat“ population, this study shows that abbreviated RCHOP4 leads to excellent outcomes in the real-world, albeit with continuous risk of late relapse. smIPI risk factors were associated with worse PFS, though this may in part be driven by risk of non-lymphoma death. As pts with advanced age, poor performance status or comorbidities may benefit from reduced treatment exposure, RCHOP4 should still be considered for these and other “trial-ineligible” pts, particularly if other high-risk features (iPET PMR, DEL or B-symptoms) are absent.

Abstract Diffuse large B-cell lymphoma (DLBCL) poses a challenge in hematology given its varied symptoms, and the complex interplay between disease and treatment effects on health-related quality of life (HRQoL). The phase 3 POLARIX study demonstrated superior progression-free survival and a similar safety profile with polatuzumab vedotin plus rituximab, cyclophosphamide, doxorubicin, and prednisone (Pola-R-CHP) vs R-CHOP (rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone) in patients with previously untreated DLBCL. Here, we evaluate HRQoL through patient-reported outcome (PRO) instruments to fully characterize the patient experience in the POLARIX study. Changes from baseline in HRQoL, lymphoma symptoms, and gastrointestinal (GI) symptoms were assessed, as well as incidence and severity of common symptoms by PROs vs clinician-reported adverse events (AEs). Baseline characteristics of PRO-evaluable patients (N = 874) were consistent. Comparison between PROs and clinician-reported AEs revealed a notable discordance; patients generally reported a higher incidence of symptoms than clinicians, emphasizing the need for patient-centric tools to accurately capture the patient experience. Both treatments exhibited rapid and sustained improvements in HRQoL and lymphoma symptoms, with the most substantial improvements seen in global health status/QoL, lymphoma symptoms, fatigue, role, emotional, and social functioning. GI symptoms (diarrhea, constipation, nausea, and vomiting) were generally similar between treatment arms and returned to baseline levels after treatment completion. These HRQoL data underscore the complementarity of PROs, as an adjunct to clinician-reported AEs, in evaluating the efficacy and tolerability of new treatments, including Pola-R-CHP, which may represent a new benchmark for patient-reported HRQoL in previously untreated DLBCL. This trial was registered at www.clinicaltrials.gov as NCT03274492.

Abstract The prevalence of steatotic liver disease (SLD) is rising globally, presenting a significant public health challenge. While non-contrast computed tomography (CT) scans hold promise for the opportunistic detection of SLD, their full potential has not been systematically explored. Clinical indicators, such as serum data, are crucial for monitoring the progression of SLD. We introduce a novel Multimodal AI for Opportunistic Steatotic Liver Disease Screening (MAOSS), which integrates demographic data, serum tests, conventional CT biomarkers, and deep learning-derived CT image features to enhance model performance and explainability. MAOSS employs an innovative learning strategy, trained on a large-scale dataset (n = 1,783) encompassing both histopathologically-confirmed SLD and radiologically-reported steatosis cases. The model underwent extensive retrospective validation using steatosis grades derived from both histology and MRI-PDFF across internal and external datasets (n = 913), as well as real-world patient data (n = 18,504). It accurately detected mild to severe steatosis (≥ S1) with AUCs ranging from 0.903 to 0.929. Notably, MAOSS significantly improved the overall AUC for radiologists (n = 11) from 0.709 to 0.798 (p < 0.001). Furthermore, MAOSS was applied to optimize the standard clinical pathway for a simulated primary risk screening of SLD patients (n = 1,192), resulting in the identification of 31% more patients at risk of steatohepatitis and liver fibrosis progression, highlighting its potential to enhance SLD detection and management.