Citations

Abstract Background: Understanding the spatiotemporal dynamics of the tumor microenvironment (TME) during treatment is crucial for improving outcomes in pancreatic ductal adenocarcinoma (PDAC). This study presents a pre-planned spatiotemporal analysis from a phase II trial evaluating neoadjuvant mFOLFIRINOX in resectable PDAC, aimed at elucidating treatment resistance mechanisms and identifying predictive biomarkers. Methods: This multi-institutional, single-arm phase II trial enrolled treatment-naïve patients with histologically confirmed resectable PDAC (NCT05066802) who underwent six cycles of neoadjuvant mFOLFIRINOX followed by surgery. The primary endpoint was the R0 resection rate. Matched pre-treatment tumor biopsies and post-treatment surgical specimens were analyzed from selected responders (R) and non-responders (NR) using high-resolution spatial transcriptomics (10X Genomics Visium). This approach enabled comprehensive mapping of TME evolution and treatment-induced changes. Results: Between May 2020 and February 2022, 27 patients were enrolled. Of these, 24 patients underwent surgery after neoadjuvant treatment (resection rate: 88.9%), and 23 achieved R0 resection (85.2%), meeting the primary endpoint. However, 20 resected patients (83.3%) recurred. Spatiotemporal analysis was performed on matched samples from four R and four NR. In pre-treatment samples from NR group, clusters dominated by fibroblasts (enriched for ECM, EMT, and CAF phenotypes) and B cell subtypes were distinct compared to R group, which exhibited elevated antibody responses and robust T cell and macrophage activity. NR samples showed increased IgM expression but lacked corresponding Fc receptors, suggesting limited immune effector function. Post-treatment NR surgical specimens displayed elevated expression of MUC5AC and CEACAM6 in malignant ductal cells, alongside genes promoting tumor growth. Neoadjuvant mFOLFIRINOX increased fibroblast, while reducing immune cell components. NR tumors formed distinct "resistance niches" after chemotherapy, marked by ECM production, CAF activation, and RTK signaling. Conversely, R tumors showed enhanced epithelial organization with increased type-I hemidesmosome complexes facilitating epithelial adhesion to the basement membrane. Conclusion: Three months of neoadjuvant mFOLFIRINOX was feasible and tolerable for resectable PDAC but associated with high recurrence rate, emphasizing the need for better patient selection. Spatiotemporal analysis revealed critical differences in TME dynamics according to treatment response, including the emergence of resistance niches and distinct pre-treatment spatial signatures. These findings support the integration of spatial biology into future pancreatic cancer trials to improve stratification and therapy. Citation Format: Choong-kun Lee, Changjin Hong, Ho Kyoung Hwang, Min Hwan Kim, Jean Rene Clemenceau, Seock-Jin Chung, Isabel Barnfather, Sumanth Reddy Nakkireddy, Jeong Hwan Park, Ji-Youn Sung, Minji Kim, Yooho Choi, Inyeop Jang, Sunho Park, Sung Hyun Kim, Chang Moo Kang, Hye Jin Choi, Tae Hyun Hwang. Spatiotemporal evolution of the tumor microenvironment predicts treatment response in phase II trial of neoadjuvant chemotherapy for resectable pancreatic cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 771.

Background: Pancreatic ductal adenocarcinoma (PDAC) is characterized by a dense, collagen-rich stroma that impedes drug delivery. We investigated how iRGD-mediated nanoparticle delivery modifies collagen architecture using humanized mouse models. Computational analysis of Picro-Sirius Red-stained whole-slide images (WSIs) using curvelet transform-based fiber extraction method (CT-FIRE) was performed to quantitatively examine changes in collagen features, thereby understanding treatment-induced alterations in the tumor microenvironment (TME). Methods: Humanized PDAC mice were prepared with either the human PANC-1 cell line or 0779 primary human PDAC cells and treated with or without iRGD monotherapy for two months (n=12). Primary tumors were sectioned and stained with Picro-Sirius Red to visualize collagen structures. WSIs of Picro-Sirius Red-stained tissues were analyzed with CT-FIRE to extract six morphological features of collagen, including average fiber length, waviness, and density to capture structural changes. WSIs were divided into 256×256 pixel tiles with consistent sampling through bootstrapping, followed by permutation testing for statistical validation (1,000 permutations, p<0.01). Results: Computational analysis revealed significant iRGD-induced collagen remodeling with quantifiable changes in key structural and morphological features. Permutation testing showed that, compared to controls, average fiber length decreased by 3.27% (p<0.01), waviness reduced by 3.25% (p<0.01), and density diminished by 36.3% (p<0.01), compared to controls. The structural changes were more notable in 0779-derived tumors compared to PANC-1, with reductions in average fiber length (1.03%, p<0.01), waviness (8.78%, p<0.01), and collagen density (24.27%, p<0.01), demonstrating cell-line dependent stromal remodeling. Conclusions: Our findings suggest that long-term iRGD therapy alters collagen morphology in PDAC. Further investigation is warranted to understand how these alterations contribute to enhanced penetration of drugs and immune cells observed in iRGD-treated PDAC tumors. The observed cell-line dependent variations in stromal remodeling suggest tumor heterogeneity influences treatment response, highlighting the potential for personalized therapeutic approaches in stromal-rich tumors like PDAC. Citation Format: Yoon Ho Choi, Minji Kim, Hotaka Kawai, Yukihito Kuroda, Norio Miyamura, Seock-Jin Chung, Kazuki N. Sugahara, Tae Hyun Hwang. Altered collagen morphology in pancreatic cancer treated with the iRGD tumor-penetrating peptide [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 2698.

Abstract Background: Pancreatic ductal adenocarcinoma (PDAC) exhibits a complex, immunosuppressive tumor immune microenvironment (TIME), necessitating molecular-level understanding to identify therapeutic targets. We investigated how iRGD peptide therapy remodels the immunosuppressive TIME to an immune-favorable state using single-cell spatial molecular analysis. Methods: Single-cell level in situ molecular imaging was performed using Xenium analyzer with 5K gene panel on tumor samples from humanized PDAC mice (n=7) treated with iRGD monotherapy (n=3) or control (n=4), enabling comprehensive spatial molecular characterization of the TIME. Results: iRGD therapy significantly transformed the immunosuppressive TIME to an immune-favorable state through T-cell composition remodeling. We observed increased populations of CD4+ memory T cells, CD4+ helper T cells, and cytokine-secreting effector T cells, indicating enhanced immune memory and effector functions. Concurrent decreases in regulatory T cells and activated CD4+ T cells reflected reduced immune suppression. Additionally, decreased TGF-β signaling in the iRGD cohort suggested TGF-β antagonism as a mechanism for overcoming immunosuppression. Conclusions: iRGD therapy effectively converted the immunosuppressive PDAC microenvironment to an immune-favorable state by enhancing beneficial T cell populations and reducing immunosuppression through TGF-β pathway modulation. These findings support previous work by Kuroda et al. and provide mechanistic rationale for the ongoing iRGD-based immunotherapy clinical trial (iLSTA:ACTRN12623000223639).Acknowledgments: We thank DeepL for the English language editing. Citation Format: Minji Kim, Yoon Ho Choi, Hotaka Kawai, Yukihito Kuroda, Norio Miyamura, Kazuki N. Sugahara, Tae Hyun Hwang. iRGD peptide therapy transforms immunosuppressive microenvironment to immune-favorable state in pancreatic ductal adenocarcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 2701.

Ewing sarcoma and osteosarcoma constitute 36% of all primary bone cancers. However, these 2 subtypes represent the most commonly diagnosed bone cancer types in the pediatric and adolescent population. Although still largely unknown, certain genetic mutations, rearrangements, and/or predisposition syndromes likely play a role in the pathogenesis of bone cancer. Osteosarcoma may also develop as a direct result of the long-term side effects of radiation therapy. With the implementation of a multimodality approach to treatment, including multiagent neoadjuvant and adjuvant chemotherapy regimens, targeted therapy options, surgery, and radiation, individuals with Ewing sarcoma and osteosarcoma are showing higher cure rates and improved overall survival. The NCCN Guidelines for Bone Cancer provide a consensus and evidence-based framework for the workup, management, and surveillance of local and recurrent/metastatic disease.

Ophthalmic immune-related adverse events (Eye-irAEs) from immune checkpoint inhibitors can cause visual morbidity. The absence of standardized definitions for Eye-irAEs not only impedes the development of evidence-based treatments but also progress in translational research. The objective of this study was to develop consensus guidance for an approach to Eye-irAEs. Four ophthalmic physicians (uveitis specialists and neuro-ophthalmologists) drafted Eye-irAE consensus guidance and definitions, which were reviewed by the multidisciplinary Eye-irAE definition panel. The panel was divided into Group A (Neuro-ophthalmology/Orbital Disease) and Group B (Uveitis/Ocular Surface Disease). A modified Delphi consensus process was used, with two rounds of anonymous ratings by panelists and two meetings to discuss areas of controversy. For each disorder, five diagnostic components were evaluated: symptoms, examination findings, laboratory studies/imaging findings, diagnostic criteria, and treatment. Panelists rated content for usability, appropriateness and accuracy on 9-point scales in electronic surveys and provided free-text comments. Aggregated survey responses were incorporated into revised definitions. Consensus was based on numeric ratings using the RAND Corporation/ University of California Los Angeles Health Services Utilization Study (RAND/UCLA) Appropriateness Method with prespecified definitions. 29 panelists from 25 academic medical centers voted on 114 rating scales (66 neuro-ophthalmic/orbital disease components, 48 uveitis/ocular surface disease components); of these, 86.3% (57/66) in Group A and 89.6% (43/48) in Group B reached first-round consensus. After revisions, all items except 6.1% (4/66) in Group A and 1.6% (1/60) in Group B received second-round consensus. Consensus definitions were achieved for 10/11 neuro-ophthalmic/orbital disorders: optic neuritis, inflammatory optic disc edema, arteritic ischemic optic neuropathy, optic perineuritis, orbital inflammation, thyroid eye disease-like orbital inflammation, cavernous sinus syndrome, oculomotor mononeuritis, trochlear mononeuritis, and abducens mononeuritis. Consensus definitions were achieved for 9/10 uveitis/ocular surface disorders: anterior uveitis, intermediate uveitis, posterior uveitis, panuveitis, Vogt-Koyanagi-Harada-like syndrome, sarcoidosis-like syndrome, acute macular neuroretinopathy, dry eye disease, and scleritis. These disease definitions establish a standardized classification for Eye-irAE, highlighting differences between irAEs and other inflammatory disorders. Importantly, diagnostic certainty does not always align directly with the need to treat as an Eye-irAE. Given the consensus from this representative panel group, it is anticipated the definitions will be used broadly across clinical and research settings.

ABSTRACTBackground and ObjectiveThe diagnosis of interstitial lung diseases (ILDs) often relies on the integration of various clinical, radiological, and histopathological data. Achieving high diagnostic accuracy in ILDs, particularly for distinguishing usual interstitial pneumonia (UIP), is challenging and requires a multidisciplinary approach. Therefore, this study aimed to develop a multimodal artificial intelligence (AI) algorithm that combines computed tomography (CT) and histopathological images to improve the accuracy and consistency of UIP diagnosis.MethodsA dataset of CT and pathological images from 324 patients with ILD between 2009 and 2021 was collected. The CT component of the model was trained to identify 28 different radiological features. The pathological counterpart was developed in our previous study. A total of 114 samples were selected and used for testing the multimodal AI model. The performance of the multimodal AI was assessed through comparisons with expert pathologists and general pathologists.ResultsThe developed multimodal AI demonstrated a substantial improvement in distinguishing UIP from non‐UIP, achieving an AUC of 0.92. When applied by general pathologists, the diagnostic agreement rate improved significantly, with a post‐model κ score of 0.737 compared to 0.273 pre‐model integration. Additionally, the diagnostic consensus rate with expert pulmonary pathologists increased from κ scores of 0.278–0.53 to 0.474–0.602 post‐model integration. The model also increased diagnostic confidence among general pathologists.ConclusionCombining CT and histopathological images, the multimodal AI algorithm enhances pathologists' diagnostic accuracy, consistency, and confidence in identifying UIP, even in cases where specialised expertise is limited. image

ABSTRACT Disruptions in the metabolism of cholesterol and other lipids are strongly implicated in the pathogenesis of neurological disease. The CNS is highly enriched in cholesterol, which is primarily synthesized de novo . Cholesterol synthesis is also rate limiting for myelin regeneration. Given that knockout of the thrombin receptor (Protease Activated Receptor 1 (PAR1)) accelerates myelin regeneration, here we sought to determine the potential regulatory actions of PAR1 in CNS cholesterol and lipid metabolism in the intact adult CNS and during myelin regeneration. We present quantitative PCR and RNAseq evidence from murine spinal cords at the peak of myelination and in adulthood showing PAR1 knockout is associated with increased gene expression for cholesterol biosynthesis (Hmgcs1, Hmgcr, Sqle, and Dhcr7), lipid transport (ApoE, Abca1, and Ldlr), and intracellular processing (Lcat, Npc1, and Npc2) at one or more time points examined. An upregulation of genes involved in the synthesis of other lipids enriched in the myelin membrane, specifically Fa2h, Ugt8a, and Gal3st1, was also observed in PAR1 knockouts. Transcription factors essential for lipid and cholesterol production (Srebf1 and Srebf2) were also increased in PAR1 knockout spinal cords at the postnatal day 21 peak of myelination and at day 45. GC–MS and LC–MS quantification of lipids demonstrated coordinate increases in the abundance of select cholesterol and lipid species in the spinal cords of PAR1 knockout mice, including enrichment of esterified cholesterol, together with sphingomyelins and sphingolipids. Co‐localization of the SREBP1 and SREBP2 transcription factors, as well as HMGCS1, a rate‐limiting enzyme in cholesterol biosynthesis, to glia during remyelination post‐lysolecithin or cuprizone‐mediated demyelination showed a prominent regulatory role for PAR1 in Olig2+ oligodendrocytes. PAR1 knockouts also demonstrated elevated levels of SREBP2 in more mature GST3+ oligodendrocytes and SREBP1 in GFAP+ astrocytes during remyelination post‐lysolecithin. These findings demonstrate novel roles for PAR1 as a regulator of CNS cholesterol and lipid metabolism and its potential as a therapeutic target to increase cholesterol availability to improve myelin regeneration. image

The 2024 Annual Congress of the International Liver Transplantation Society (ILTS) was from May 1–4 in Houston, Texas, USA, under the theme “Liver Disease and Transplantation: Breaking Barriers and Exploring New Frontiers.” In addition to a robust scientific program, the congress also hosted a hands-on cadaveric robotic liver surgery course, a machine perfusion workshop, and a transesophageal echocardiography course. In this report, the ILTS Vanguard and Basic Sciences Committees present a summary of the congress proceedings.

366 Background: While improved survival has been previously demonstrated, the impact of immunotherapy on HRQoL in ESCC has not been well examined. Traditional PRO-based analyses in oncology trials, such as time to deterioration (TTD) and mixed models for repeated measures (MMRMs), are limited by discounting recurrent PRO events. Thus, we applied a 3-component joint model (JM) framework to define more clinically interpretable associations between patient-reported symptoms, treatment effects, and OS among subgroups of patients with ESCC from RATIONALE-306, which met its primary endpoint, with PD-L1 expression of ≥1%, ≥5%, and ≥10%. Methods: The final analytic sample included 226 patients in the tislelizumab + chemotherapy arm (T+C), 242 in the placebo + chemotherapy arm (P+C) for PD-L1 ≥1%, 113 in the T+C arm and 103 in the P+C arm for PD-L1 ≥5%, and 168 in the T+C arm and 178 in the P+C arm for PD-L1 ≥10%.From EORTC QLQ-C30 and OES18, 7 keysymptom domains were modeled (GHS, physical functioning, fatigue, dysphagia, pain, reflux, dietary restrictions). PRO data were collected at baseline and at every treatment cycle (up to 6 cycles), then every other cycle, and at safety follow-up, and change from baseline (CFBL) was analyzed. The joint model comprised three components: 1) linear mixed model predicting CFBL symptom scores; 2) Cox proportional hazard model (CPH) for time to OS; and 3) frailty (random effects for recurrent deterioration events [RDEs]) CPH model for time to PRO-based RDEs. Osoba (1998) 10-point threshold was used to define RDEs. Results: Adjusted completion rates were >90% in the ITT population for both arms. Significant T+C treatment effects wereobserved for physical functioning in PD-L1 ≥5% ( P =0.0476), and pain in PD-L1 ≥1% ( P =0.0028) and PD-L1 ≥5% ( P =0.0149) subgroups, but not in PD-L1 ≥10%. For other 5 symptoms (ie, GHS, fatigue, reflux, dysphagia, dietary restrictions), there were no statistically significant differences between treatment arms. However, T+C was associated with significant reductions in the risk of death across all 7 key symptoms and PD-L1 subgroups. As one example, with respect to interaction between pain and OS, T+C was associated with a 22% (HR, 0.78 [95% CI, 0.652-0.931]), 33% (HR, 0.67 [95% CI, 0.515-0.860]), and 47% (HR, 0.50 [95% CI, 0.344-0.720]) reduction in the risk of death in PD-L1 ≥1%, ≥5%, and ≥10%, respectively compared with P+C. Conclusions: In this analysis, the addition of tislelizumab to chemotherapy was associated with significantly less deterioration in multiple PRO symptoms including physical functioning and pain, alongside a lower risk of death, after adjusting for recurring deterioration events using a frailty model across multiple PD-L1 expression subgroups.

Abstract Electroconvulsive therapy (ECT) is an effective treatment for severe depression, especially in treatment-resistant cases. However, its potential cognitive side effects necessitate careful dosing to balance therapeutic benefits and cognitive stability. Recent advances in electric field (E-field) modeling offer promising avenues to optimize ECT dosing. This review synthesizes current knowledge on E-field modeling in ECT and explores its clinical applications. It examines the variability in E-field strengths and distributions induced by ECT and their impact on clinical outcomes. Additionally, the relationship between E-field strengths, neuroplasticity, and therapeutic efficacy is discussed. Translational studies of E-field-informed ECT are highlighted, emphasizing individualized optimal amplitude dosing and potential clinical applications. This review provides useful insights into how E-field modeling can improve the effectiveness of ECT while minimizing adverse effects, helping guide future research and clinical practice.