MRTX1133 sensitivty across the PRISM cohort of cell lines.

Abstract Asymptomatic precursor lesions that predate invasive pancreatic ductal adenocarcinoma (PDAC) by years provide a compelling opportunity for cancer interception. One such precursor is the intraductal papillary mucinous neoplasm (IPMN). Using Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry (MALDI-MS) imaging and spatial transcriptomics, we discovered long-chain hydroxylated sulfatide species and their biosynthetic enzymes as selectively enriched in IPMN. Genetic ablation of UGT8 and Gal3st1, the key enzymes catalyzing the synthesis of the sulfatide precursor galactosylceramide (GalCer) and sulfatides, respectively, suppressed sulfatide production and triggered mitochondrial ceramide accumulation in mutant Kras;Gnas IPMN cells. These metabolic disruptions led to reduced proliferation and invasiveness, alongside increased caspase-dependent apoptosis. Pharmacologic UGT8 inhibition also caused profound impairments in mitochondrial function and morphology. Integrated lipidomic and proteomic analyses on mitochondrial fractions revealed remodeling of lipid composition and dysregulation of proteins involved in mitochondrial translation, oxidative phosphorylation, mitophagy and sphingolipid metabolism, corroborating the phenotypic changes observed in our functional studies. In vivo, UGT8 inhibition suppressed tumor growth in IPMN allograft models. Collectively, our findings identify enhanced sulfatide metabolism as an early metabolic alteration of cystic pre-cancerous lesions and demonstrate that targeting UGT8 perturbs mitochondrial homeostasis and function, revealing a potential strategy for pancreatic cancer interception. Citation Format: Riccardo Ballarò, Yihui Chen, Marta Sans, Fredrik Ivar Thege, Rongzhang Dou, Jimin Min, Michele Yip-Schneider, Jianjun Zhang, Ranran Wu, Ehsan Irajizad, Yuki Makino, Kimal Rajapakshe, Mark Hurd, Ricardo A. León-Letelier, Jody Vykoukal, Jennifer B. Dennison, Kim-Anh Do, Samir M. Hanash, Robert Wolff, Paola A. Guerrera, Michael Paul Kim, C. Max Schmidt, Anirban Maitra, Johannes Fahrmann. Targeting sulfatide metabolism as a therapeutic vulnerability in pancreatic pre-cancer lesions [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 7316.

Poor-prognosis cancers account for a disproportionate share of global cancer mortality despite major advances in prevention, early detection, and therapy for other malignancies. Launched in 2023, the G7 Cancer Initiative represents an unprecedented effort to address this challenge through coordinated scientific, clinical, and policy action. This report summarizes the outcomes of the G7 Cancer Conference held in Paris in June 2025, which focused on shifting poor-prognosis cancers from a paradigm of resignation to one of collective transformation. Discussions emphasized four interdependent pillars: precision medicine supported by multi-omic profiling and artificial intelligence; early detection and minimal residual disease monitoring using liquid biopsy and advanced imaging; innovative and adaptive clinical trial designs; and emerging therapeutic platforms, including nanomedicine, epigenetic therapies, and immune modulation. The meeting highlighted that scientific innovation alone is insufficient without harmonized infrastructures, equitable access, and international cooperation. Together, these elements form a new model of global cancer governance aimed at translating biological insight into meaningful survival gains for patients with historically lethal cancers.

746 Background: PACC is a rare subtype accounting for ~1% of all exocrine pancreatic neoplasms and remains understudied compared to conventional pancreatic ductal adenocarcinoma (PDAC). Here, we performed a comparative analysis of the genomic landscapes of PACC versus PDAC using the FoundationCORE dataset to identify potential therapeutic vulnerabilities. Methods: Comprehensive genomic profiling using hybrid capture-based next-generation sequencing (NGS) was performed on 196 PACC and 29,493 PDAC tumors to identify pathogenic genomic alterations (GAs). All patients (pts) had stage III/IV disease at the time of profiling. Genomic ancestry, microsatellite instability (MSI), tumor mutational burden (TMB), and homologous recombination deficiency signature (HRDsig) were assessed. Statistical analysis was performed using Fisher’s exact test, with false discovery rate correction applied via the Benjamini-Hochberg method for independent variables or the Benjamini–Yekutieli method for dependent variables. Results: PACC was more common in males than PDAC (67.9% vs 52.7%, p<0.0001) with similar age (median 66 yrs, IQR 58-74 vs 67 yrs, IQR 60-74) and genomic ancestry distributions. A median of 4 GAs/tumor (IQR 2.25-5.75) were identified in PACC. MSI-high status was rare in both cohorts (1.0% vs 0.5%, p=1.0). TMB was higher in PACC than PDAC, driven by greater enrichment of cases in the 10-20 mut/Mb (5.1% vs 0.7%, p<0.0001) and ≥20 mut/Mb (2.0% vs 0.5%, p=0.039) ranges. HRDsig positivity was also enriched in PACC (20.9% vs 4.6%, p<0.0001), consistent with prior reports indicating strong association with germline DNA damage repair mutations. Alterations in canonical PDAC driver genes were significantly less frequent in PACC, including KRAS (6.1% vs 93.6%, p<0.0001), TP53 (17.4% vs 78.9%, p<0.0001), CDKN2A (31.6% vs 58.6, p<0.0001), and SMAD4 (19.9% vs 29.1%; p=0.0054). MTAP loss was also less frequent in PACC (15.8% vs 23.8%; p=0.0097). Conversely, PACC was enriched for mutations in BRAF (11.2% vs 2.0, p<0.0001), BRCA2 (14.3% vs 2.9%, p<0.0001), APC (10.2% vs 1.1%, p<0.0001), CTNNB1 (12.2% vs 0.7%, p<0.0001), and GNAS (12.2% vs 3.2%, p<0.0001). Conclusions: PACC exhibits a distinct genomic profile from PDAC, characterized by fewer canonical drivers and frequent KRAS wild-type status. Enrichment for BRAF mutations highlights opportunities for MAPK- targeted therapies, while increased TMB and HRD signatures suggest potential sensitivity to immunotherapy and DNA repair-directed strategies, respectively.

One of the major conundrums of cancer research and treatment is that the metastases that lead to death in most patients do not appear to involve additional driver mutations. Previously, we reported widespread loss of heterochromatin with activation of pro-metastatic genes in the subset of cells of primary pancreatic tumors that gave rise to liver and lung metastases. Here we hypothesized that this change in chromatin could create unique vulnerabilities in distant metastases. Using a CRISPR screen of human patient-derived xenografts from metastases and primary tumors, we identified KLF5 as essential for metastatic cell proliferation but not primary tumor growth. Further, we found that KLF5 induced epigenetic modifier genes, including NCAPD2 and MTHFD1, which themselves facilitated expression of specific genes driving migration and epithelial-mesenchymal transition, including TGFBR2, VIM, EMP1, and ITGB1. Inhibition of expression of these modifier genes restored heterochromatin in the specific regions that distinguish the primary and metastatic tumors. We backed up this causal chain of evidence with rigorous additional knockdown experiments with the modifier genes, and single cell RNA and chromatin experiments, and we also replicated the main findings in a second set of paired primary and distant metastasis xenograft lines. Finally, KLF5 expression was strongly associated with patient survival and human PDAC cell plasticity in a dataset of 70 PDAC patients and KLF5 expression was increased in the majority of lung, liver and peritoneal metastases compared to the matched primary tumor, confirming its importance in PDAC metastasis and mortality. In summary, we have identified a cascade of epigenetic modulators, modifiers and mediators that maintains the widespread heterochromatin loss supporting metastatic cell proliferation in human pancreatic cancer (see Graphical Abstract).

Importance:Pancreatic ductal adenocarcinoma (PDAC) is a leading cause of cancer deaths in the US. Although early detection improves survival, the rarity of the disease has rendered population screening a difficult approach. Objective:To develop and validate a parsimonious, interpretable, and generalizable model predicting incident PDAC-termed PRIME (PDAC Risk Model for Earlier Detection)-using routinely available electronic health record (EHR) data. Design, Setting, and Participants:This cohort study used the Optum Labs Data Warehouse, a longitudinal, deidentified US EHR and claims database. Adults 40 years or older with an outpatient clinical encounter between 2016 and 2018 were included. Participants from 23 health systems (n = 4 859 833) comprised the training cohort; 31 additional systems (n = 5 619 091) served as validation. International validation was conducted in the UK Biobank (n = 498 754). Data analysis occurred July 2025 to January 2026. Exposures:Demographics, diagnosis codes, and routinely measured laboratory values were evaluated. Elastic-net regularization with 10-fold cross-validation selected the predictor set. Main Outcomes and Measures:Incident PDAC was identified by International Classification of Diseases, Ninth and Tenth Revisions (ICD-9/10) codes. Model performance was assessed using time-dependent area under the curve (AUC) and calibration metrics. Results:Overall, the study included more than 11 million adults (2.1% Asian individuals, 8.4% Black individuals, 4.3% Hispanic/Latino individuals, 82.7% White individuals, and 2.4% other race/ethnicity by EHR reporting). In the training cohort (mean [SD] age, 60.4 [11] years), 14 405 individuals were diagnosed with PDAC (incidence 55 per 100 000 person-years) over a mean (SD) of 5.4 (2.5) years; in the validation cohort, 11 693 individuals were diagnosed with PDAC (54 per 100 000 person-years) over a mean (SD) of 3.9 (2.5) years. PRIME retained 19 predictors including history of pancreatitis, gastrointestinal disorders, prior cancers, type 2 diabetes, elevated aspartate aminotransferase levels, smoking, non-type-O blood, and male sex. Discrimination was strong at the 36-month time horizon (AUC = 0.75 in both the training and validation cohorts) with good calibration. In the validation cohort, patients in the top 1% of predicted risk had substantially higher PDAC risk (HR, 7.63; 95% CI, 6.85-8.49) compared with average-risk patients. In the UK Biobank, PRIME achieved a 36-month AUC of 0.71 with good calibration. Conclusions and Relevance:In this validation cohort study, PRIME was a transparent EHR-based model that effectively stratified PDAC risk across diverse US health systems and generalized internationally. Prospective studies should evaluate for EHR-guided PDAC case-finding and integration with blood-based early-detection assays.

Abstract Mutations in KRAS are a dominant driver of pancreatic ductal adenocarcinoma (PDAC), with about 50% of patients presenting with KRAS G12D mutations. Small molecule inhibitors targeting KRAS G12D suppress PDAC; however, the contribution of the tumor microenvironment (TME) to the sustained efficacy of KRAS G12D inhibition and mechanisms of resistance to KRAS G12D suppression remain to be elucidated. Here, integrated spatial transcriptomics, single-cell RNA sequencing, and CODEX-based spatial proteomics analyses of PDAC mouse models uncover that while KRAS G12D inhibition by MRTX1133 initially increases CD11c + cells and T cell infiltration proximal to cancer cells, long-term treatment results in reversal of the immune responses leading to resistance promoted by multiprotein mediator complex associated kinase CDK8. CDK8 imparts this resistance via induction of CXCL2 chemokine secretion, inhibition of FAS expression, and remodeling of the TME to promote immune evasion. Targeting CDK8 by itself or in combination with αCTLA-4 immunotherapy overcomes resistance to KRAS G12D inhibition. We also provide evidence of CDK8 upregulation in PDX tumors resistant to inhibitors selective for RAS(ON) and RAS G12D (ON): daraxonrasib and zoldonrasib, respectively, highlighting a common KRAS vulnerability node for TME resistance.

Abstract Background Intraductal papillary mucinous neoplasms (IPMNs) are recognized as precursor lesions to pancreatic ductal adenocarcinoma (PDAC). However, the molecular programs underlying progression from low-grade dysplasia to advanced disease remain incompletely characterized. Herein, we performed an integrated plasma and tissue–proteomic analyses coupled with spatial and single-cell transcriptomics to identify biologically coherent remodeling programs reflected in circulation that distinguish IPMN by dysplasia grade and invasive disease. Methods Using the O-link proximity extension assay platform, a panel of 1,104 proteins were quantified in plasma samples collected from patients with low-grade (LG) IPMN (n=30), high-grade (HG) IPMN with or without associated PDAC (IPMN/PDAC; n=40) and PDAC without IPMN (n=8). Predictive performance of individual biomarkers were assessed; likelihood ratio testing was performed to identify protein biomarkers that were complementarity with CA19-9 for risk of malignancy of IPMN. Findings were intersected with available spatial (N= 13) and single-cell (N= 6) transcriptomic datasets of IPMN tissues as well as mass spectrometry-based proteomic profiles of an independent set of resected human IPMN tissues (N= 9). Results A total of 28, 43, and 35 circulating proteins were found to be differential in HG, IPMN/PDAC, and HG + IPMN/PDAC cases compared to LG IPMN. Among differential proteins were known PDAC-associated markers CEACAM5, CTRC, and REG3A as well as several biomarkers reflecting cytoskeletal and extracellular matrix remodeling and inflammatory processes. Focusing on cytoskeletal and ECM-related proteins and using likelihood ratio testing, an “OR” rule considering CA19-9, BGN, and ITGB1BP1 achieved overall sensitivity of 48.7% for HG + IPMN/PDAC, including 38.1% sensitivity for HG IPMN, at an overall specificity of 90%, which was improved compared to that of CA19-9 alone (overall sensitivity of 28.2%; McNemar Exact test 1-sided p-value: 0.011). Integrated proteomic and spatial transcriptomic datasets of IPMN tissues revealed coordinated alterations cytoskeletal and ECM remodeling and elevated matrix stiffness as prominent features associated with IPMN/PDAC, which paralleled concordant increases in BGN and ITGB1BP1. Cell-type of origin analyses based on spatial and single-cell data further revealed fibroblasts and myeloid cells as primary contributors to expression levels of BGN whereas ITGB1BP1 was primarily expressed in neoplastic epithelium. Conclusion Advanced IPMN dysplasia and invasive disease are characterized by coordinated tissue remodeling programs that are systemically reflected in circulating proteomic profiles. Blood-based biomarkers identified through our study, such as BGN and ITB1BP1, have potential to improve upon CA19-9 for risk stratification of IPMN to better guide clinical management.

Daraxonrasib is an orally bioavailable RAS(ON) multi-selective tri-complex inhibitor of the oncogenic mutant and wild-type variants of N, H and KRAS. We previously reported encouraging efficacy in a phase 1/2 clinical trial evaluating daraxonrasib monotherapy at clinically active dose levels in patients with previously treated, RAS mutant metastatic pancreatic adenocarcinoma (PDAC), providing the basis for confirmatory evaluation in the randomized phase 3 RASolute 302 clinical trial. Here we report mechanisms of acquired resistance to daraxonrasib monotherapy observed through targeted sequencing of over 800 genes in paired pretreatment and end of treatment circulating tumor DNA samples from 44 patients in the phase 1/2 clinical trial. Treatment-emergent genomic alterations in the RAS signaling pathway were observed in more than half (26 of 44; 59%) of these patients, including, most notably, mutant KRAS amplifications in one-third (16 of 44; 36%), as well as alterations in receptor tyrosine kinase (RTK) (4 of 44; 9%), MAPK (11 of 44; 25%) and PI3K (4 of 44; 9%) pathways. Notably, no acquired secondary KRAS mutations were observed, distinct from resistance profiles of mutant-selective KRAS G12C(OFF) inhibitors. To corroborate these clinical findings, we found, or mechanistically established, concordant mechanisms of daraxonrasib resistance in human and murine preclinical models of PDAC, including mutant KRAS and MYC amplification and RTK upregulation, with these alterations guiding various combination therapy concepts. Notably, daraxonrasib combined with agents targeting DNA damage response, RTKs or the mutant-selective RAS(ON) G12D inhibitor zoldonrasib averted resistance in preclinical models. Collectively, these results show that most daraxonrasib genomic resistance mechanisms drive reactivation of RAS pathway signaling and guide potential combination strategies in PDAC for further investigation.

Cancer evolution is a complex and dynamic process, yet most treatment strategies remain static. Infrequent tumor sampling has limited our ability to counteract the transient adaptive states that precede resistance. To address this gap, ARPA-H launched the ADAPT program, an initiative aimed at transforming cancer care by aligning therapies with real-time tumor evolution. Within this framework, the ASCEND-CRC trial aims to uncover early adaptive mechanisms and identify biomarkers to guide therapeutic decision-making in metastatic colorectal cancer (CRC). The study moves beyond single pre-treatment biomarkers by integrating multimodal profiling to longitudinally track tumor evolution and define an actionable set of dynamic biomarkers that inform treatment decisions. Together with other ADAPT initiatives, ASCEND-CRC represents a paradigm shift in precision oncology, establishing a scalable platform to intercept resistance.

Pancreatic ductal adenocarcinoma (PDAC) is a complex disease characterized by high levels of cellular heterogeneity and pronounced microenvironmental remodelling. Dynamic changes during its initiation and progression contribute to resistance to conventional therapies. Building upon key molecular catalogues established by bulk and single-cell profiling studies that have advanced our understanding of PDAC biology, recent advances in spatial biology have provided much-needed insights by elucidating regionally compartmentalized transcriptomic and proteomic programmes within the PDAC microenvironment. In parallel, emerging computational frameworks in digital pathology and artificial intelligence have advanced the field into a high-dimensional, quantitative discipline, particularly for classifying molecular and clinical features from histopathology images. Despite these advancements, integration of these two modalities remains a major challenge. Here, we summarize the convergence of molecular features identified through spatially resolved profiling in PDAC and its precursor lesions, as well as current developments in AI-powered pathology in cancer research. We further propose a multi-modal integration framework that maps molecular states onto morphological and architectural phenotypes, offering a roadmap for spatially informed patient stratification beyond descriptive tissue characterization. We posit that the path forward relies on disciplined cross-scale integration of spatial, histological, and clinical data to ensure meaningful translation into clinical practice. Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal cancer, often diagnosed late and resistant to treatment. This review highlights emerging evidence from spatial profiling studies demonstrating that PDAC and its precursor lesions are not just a simple mixture of malignant and stromal cells but rather a structured ecosystem with spatially distinct immune and fibroblast niches. Digital pathology and artificial intelligence offer promising complementary approaches to extending insights gained from spatial omics to larger patient cohorts, with the potential to improve risk stratification, prognostic prediction and assessment of therapeutic response. Future research should focus on establishing ground-truth characteristics in different disease contexts in the pancreas and expanding spatially resolved datasets across diverse PDAC cohorts to enable robust development of computational frameworks and improve their clinical applications.

Tertiary lymphoid structures (TLSs) are critical regulators of antitumor immunity, yet their spatial organization, maturation, and clinical relevance remain incompletely defined across cancers. We analyzed spatial transcriptomics spanning 12 cancer types to construct a pan-cancer TLS atlas and characterized TLS spatial architecture and maturation states. TLS maturation was accompanied by coordinated remodeling of distinct niche cell populations and distance-dependent gradients in tumor programs, orthogonally supported by ultrahigh-plex single-cell spatial profiling. To enable scalable TLS profiling, we trained an artificial intelligence framework that predicts TLS maturation states directly from hematoxylin and eosin-stained images and evaluated it across TCGA and independent therapy cohorts. We further derived a maturation-aware composite score capturing intratumoral TLS state composition, which robustly stratifies patients across cancer and treatment contexts, outperforming conventional TLS metrics.

Genetic and copy number variants at resistance to adagrasib or sotorasib across the novel cohort of PDAC and GI cancer patients.

Supplemental Table 5A: Drug sensitivity metrics from MRTX1133-treated KRASG12D patient-derived organoids. Supplemental Table 5B: MRTX1133 dose response across KRASG12D mutated patient-derived organoids.