Citations

Abstract Background Cholangiocarcinoma (CCA) is an aggressive hepatobiliary malignancy with marked molecular heterogeneity, limited systemic treatment options, and poor prognosis. Chemoresistance and KRAS mutations remain major therapeutic challenges. Dysregulation of the Hippo pathway, particularly YAP/TAZ hyperactivation, drives CCA progression and resistance. TEAD, the essential transcriptional partner of YAP/TAZ, represents a promising target. IAG933 is a novel oral pan-TEAD inhibitor designed to disrupt YAP/TAZ–TEAD interactions. RMC-6236, a pan-KRAS inhibitor, has also gained attention. Combining TEAD and KRAS inhibition may overcome resistance and improve efficacy in CCA. Methods We evaluated IAG933 in human (HuCCT1, RBE) and murine (SB1, FAC) CCA cell lines. Cells were treated with IAG933 alone or in combination with GemCis or RMC-6236. Cell viability assays were used to determine IC50 values and calculate combination index (CI). TEAD activity was assessed by luciferase reporter and qRT-PCR of YAP/TAZ target genes (CTGF, CYR61, NUAK2). In vivo efficacy was evaluated in syngeneic orthotopic and patient-derived xenograft (PDX) models. Results IAG933 suppressed TEAD-dependent transcription (IC50≈500 nM) and downregulated YAP/TAZ target genes. Combination with GemCis or RMC-6236 produced synergistic effects (CI < 1) in all CCA lines. In vivo, IAG933 monotherapy suppressed tumor growth similarly to GemCis. Dual TEAD and KRAS inhibition achieved marked tumor regression and significantly delayed tumor regrowth after treatment cessation in KRAS-mutant PDX models. Conclusion IAG933 effectively suppresses YAP/TAZ–TEAD signaling and inhibits CCA growth. While the combination with GemCis showed limited additional benefit due to strong single-agent efficacy, synergy with RMC-6236 produced durable antitumor effects, particularly in run-out studies, delaying regrowth in KRAS-mutant models. These findings highlight IAG933 as a promising therapeutic candidate targeting the Hippo–TEAD pathway, with potential benefit in KRAS-mutant CCA.

Abstract Background Cholangiocarcinoma (CCA) is a deadly cancer of the hepatic bile duct epithelial cells. Loss-of-function mutations of epigenetic regulator ubiquitin C-terminal hydrolase deubiquitinase BRCA1associated protein 1 (BAP1) occur in 26-32% of human CCA and are associated with worse prognosis and resistance to cytotoxic therapy. The goal of this study is to identify how BAP1 loss promotes cell death evasion through metabolic rewiring. Materials and methods Isogenic wild-type and BAP1-deficient human and murine CCA cell lines were generated with shRNA/siRNA or CRISPR/Cas9 and were used to assess ferroptosis sensitivity by treatment with ferroptosis inducers. In vitro, ferroptosis was assessed by phospholipid peroxidation (C-11BODIPY), mitochondrial phospholipid peroxidation (MitoPeDPP, MitoCLox), iron overload (MitoFerro green) and cell death (CellTiter-Glo). Phospholipidomics and proteomics were performed in isogenic cells by LC-MS/MS. Syngeneic liver orthotopic CCA murine models and patient-derived xenografts (PDX) were used for in vivo pre-clinical studies. Results Our findings indicate that BAP1 loss confers CCA ferroptosis resistance. BAP1 loss protects CCA against mitochondrial iron overload, ROS accumulation, and phospholipid peroxidation. BAP1 loss protects from mitochondrial phospholipid peroxidation and cardiolipin oxidation. Unbiased phospholipidomic profiling revealed that BAP1 loss remodels membrane phospholipid composition, enriching for ferroptosis blocking monounsaturated phospholipids (MUFA-PLs) at the expense of ferroptosis-inducing polyunsaturated (PUFA-PLs). We found that BAP1 loss upregulates TLCD1, a phosphatidylethanolamine acyltransferase that incorporates MUFAs into membrane phospholipids, thereby stabilizing membranes against peroxidation. TLCD1 knockdown in ferroptosis-resistant BAP1-deficient CCA cells, restored ferroptosis sensitivity. Notably, TLCD1 is significantly upregulated in human BAP1-mutant CCA as compared to BAP1-expressing tumors. While not a mitochondrial protein, TLCD1 localizes in the ER and by the mitochondrial outer membrane, as demonstrated by our immunofluorescence analysis in human CCA cells. From a therapeutic perspective, we developed EpCAM (adhesion molecule highly expressed in CCA cells)-aptamer coated lactosomes packaged with siRNA against glutathione peroxidase 4 (GPX4), as a proof-of-concept strategy to safely induce ferroptosis selectively in CCA in vitro and in vivo. Administration of siGPX4-lactosomes in pre-clinical syngeneic liver orthotopic CCA murine models demonstrated a favorable safety profile, achieved robust intratumoral GPX4 knockdown (>50%), exhibited optimal biodistribution, induced significant tumor lipid peroxidation, and resulted in reduced tumor burden. Lastly, ferroptosis inducer JKE-1674, combined with gemcitabine/cisplatin (Gem/Cis) significantly blocked tumor growth of Gem/Cis-resistant patient-derived xenografts. Conclusions Our findings reveal that BAP1 loss reprograms mitochondrial phospholipid metabolism thus conferring CCA resistance to ferroptosis, identifying TLCD1 as a targetable metabolic vulnerability in BAP1-mutant CCA. Additionally, our findings support ferroptosis inducing compounds as promising therapeutic approaches for CCA.

Abstract Background: Cholangiocarcinoma (CCA) is an aggressive hepatobiliary malignancy with marked molecular heterogeneity, limited systemic treatment options, and poor prognosis. Chemoresistance and KRAS mutations remain major therapeutic challenges. Dysregulation of the Hippo pathway, particularly YAP/TAZ hyperactivation, drives CCA progression and resistance. TEAD, the essential transcriptional partner of YAP/TAZ, represents a promising target. IAG933 is a novel oral pan-TEAD inhibitor designed to disrupt YAP/TAZ-TEAD interactions. RMC-6236, a pan-KRAS inhibitor, has also gained attention. Combined TEAD and KRAS inhibition may overcome resistance and improve efficacy in CCA. Methods: We evaluated IAG933 in human (HuCCT1, RBE) and murine (SB1, FAC) CCA cell lines. Cells were treated with IAG933 alone or in combination with GemCis or RMC-6236. Cell viability assays were used to determine IC50 values and calculate combination indexes (CI). TEAD activity was assessed by luciferase reporter and qRT-PCR of YAP/TAZ target genes (CTGF, CYR61, NUAK2). Transcriptomic alterations were analyzed by RNA sequencing. In vivo efficacy was evaluated in syngeneic orthotopic and patient-derived xenograft (PDX) models. Results: IAG933 suppressed TEAD-dependent transcription (IC50 ≈ 500 nM) and downregulated YAP/TAZ target genes. Combination with GemCis or RMC-6236 produced synergistic effects (CI < 1) in all CCA lines. Transcriptomic analysis revealed activation of oxidative stress response pathways, particularly SOD2 upregulation. MitoSOX staining confirmed increased mitochondrial ROS after treatment. In vivo, IAG933 monotherapy suppressed tumor growth similarly to GemCis. Dual TEAD and KRAS inhibition achieved marked tumor regression and significantly delayed tumor regrowth after treatment cessation in KRAS-mutant PDX models. Conclusion: IAG933 effectively suppresses YAP/TAZ-TEAD signaling and inhibits CCA growth. While the combination with GemCis showed limited additional benefit due to strong single-agent efficacy, synergy with RMC-6236 produced durable antitumor effects, particularly in run-out studies, delaying regrowth in KRAS-mutant models. These findings highlight IAG933 as a promising therapeutic candidate targeting the Hippo-TEAD pathway, with potential benefit in KRAS-mutant CCA. Citation Format: Hidemi Nishi,Erik Jessen,Danielle M. Carlson,Amro M. Abdelrahman,Enis H. Ozmert,J. Pedro Fincatto Safi,Brandon A. Wilbanks,Shelby K. Yee,Jack W. Sample,Nathan W. Werneburg,Rory L. Smoot. TEAD inhibition by IAG933 as a novel therapeutic strategy for cholangiocarcinoma [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 3081.

Abstract Introduction: Src Family Kinases (SFKs) have a crucial role in tumor proliferation, survival, and metastasis. NXP900 is a highly selective SFK inhibitor with a novel mechanism of action that locks SFKs in a closed, inhibited conformation, providing sustained suppression of catalytic and non-catalytic functions, which is distinct from other SFK inhibitors like dasatinib. A phase I clinical trial of NXP900 in patients with advanced solid tumors is ongoing. Our preclinical studies showed therapeutic efficacy of NXP900 in cholangiocarcinoma (CCA) through decreased YAP, RAF-MAP and PI3K-AKT signaling. Multiomic profiling (RNA-seq, proteomics, phosphoproteomics) of CCA patient-derived xenografts implicated AKT pathway activation in primary NXP900 resistance. NXP900-resistant CCA cell lines generated via prolonged sublethal dose escalation showed a strong IL13RA2-AKT signature on multiomic analysis. Thus, we hypothesized that IL13RA2-AKT signaling was a mechanism of NXP900 resistance. We aimed to define this mechanism and demonstrate that the combinatorial targeting of IL13RA2 or AKT resensitizes to NXP900 treatment. Methods: HuCCT1 or HuCCT1-Resisant (HuCCT1-R) cells were injected bilaterally into the flanks of NOD/SCID mice and were allowed to grow for 3 months prior to tumor collection and analysis. Tumor engraftment and growth between HuCCT1 and HuCCT1-R groups were compared. To delineate the mechanisms for acquired NXP900 resistance, in-vitro treatment studies were performed using siRNAs targeting IL13RA2 as well as combination treatment with capivasertib, a pan-AKT inhibitor. Results: The HuCCT1-R cell line exhibited a higher rate of tumor engraftment and formed significantly larger tumors compared to the parental HuCCT1 cell line, indicating enhanced tumorigenic potential associated with acquired resistance. Silencing of IL13RA2 in HuCCT1-R cells resulted in pronounced reduction of cell proliferation and partially restored sensitivity to NXP900 treatment. Immunoblot analysis demonstrated a corresponding reduction in phosphorylated AKT (Thr308), consistent with suppression of downstream PI3K-AKT signaling. Furthermore, combination treatment of HuCCT1-R cells with the AKT inhibitor capivasertib, and NXP900 led to a significant increase in cell death and a greater inhibition in cell proliferation compared to either agent alone, indicating enhanced responsiveness and improved therapeutic efficacy. Conclusion: These findings confirm the central role of IL13RA2 signaling and the PI3K-AKT pathway in mediating acquired resistance to NXP900, consistent with our previous multiomics analysis. Importantly, this study identifies combination strategies that may be able to overcome NXP900 resistance, supporting the development of combinatorial approaches to restore therapeutic efficacy in resistant tumors. Citation Format: Shelby K. Yee, Hendrien Kuipers, Danielle M. Carlson, Jack W. Sample, Enis Ozmert, Hidemi Nishi, Erik Jessen, Dong-Gi Mun, Aushinie M. Abeynayake, Jennifer L. Tomlinson, Amro M. Abdelrahman, Nathan W. Werneburg, Binbin Li, Mitesh J. Borad, Mark J. Truty, Sumera I. Ilyas, Gregory J. Gores, Rory L. Smoot. Resistance to the SFK inhibitor NXP900 in cholangiocarcinoma is characterized by IL13RA2-AKT signaling and can be overcome by combination therapy [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 7124.

Pancreatic ductal adenocarcinoma (PDAC) remains a highly lethal cancer with a 5-year survival rate of 13%. Despite recent molecular stratification of tumors into distinct classical and basal-like cell states, most tumors are heterogeneous and contain both subtypes. Therefore, therapeutic approaches targeting only one subtype are unlikely to be effective as standalone PDAC treatments. Here, we integrated chromatin accessibility [assay for transposase-accessible chromatin with sequencing (ATAC-seq)], genome-wide occupancy [chromatin immunoprecipitation sequencing (ChIP-seq)] for epigenetic status (H3K27ac), and H3K4me3-anchored chromatin topology (HiChIP) to uncover subtype-independent highly interactive enhancers that interact with essential genes in PDAC. Motif analysis revealed that these common enhancers were bound by KLF5 with subsequent depletion leading to decreased cell viability via induction of apoptosis. To elucidate the transcriptional and epigenetic mechanisms by which KLF5 functions in PDAC, we used rapid depletion of KLF5 with dTAG technology and profiled the effects on the open and active chromatin landscape and transcription with nascent RNA and messenger RNA sequencing over time. Enhancer inactivation via KRAB domain Zim3-dCas9 fusion protein confirmed KLF5-bound enhancers regulate target genes, including the anti-apoptotic gene BCL2L1 . Multiplex immunofluorescence confirmed costaining of KLF5 and Bcl-xL in patient samples and overexpression of Bcl-xL rescued the induction of apoptosis after KLF5 depletion. Together, this study provides insights into common mechanisms to target highly heterogeneous PDAC tumors.

ABSTRACT The limited efficacy of current therapies against cholangiocarcinoma (CCA) necessitates the development of novel treatment strategies. Src family kinases (SFKs) contribute significantly to tumor progression and resistance in CCA. Therefore, we investigated the novel, first-in-class SFK ‘OFF’ inhibitor NXP900 in diverse preclinical CCA models, including those with acquired resistance. This study evaluated the therapeutic effects of NXP900 and detailed adaptive molecular responses to SFK inhibitor therapy. We also aimed to identify biomarkers predictive of drug sensitivity using integrated multiomic profiling and develop strategies to overcome resistance. NXP900 inhibited YAP activity through direct inhibition of tyrosine phosphorylation and indirect activation of the Hippo pathway via LATS. These effects were associated with decreased tumor cell viability in CCA cell lines and several in vivo models. Notably, IDH -mutant patient-derived xenograft CCA models were particularly sensitive to NXP900. NXP900 also synergized with gemcitabine/cisplatin chemotherapy, enhancing antitumor efficacy in both in vitro and in vivo models. Multiomic analyses combining transcriptomics, global proteomics, and phosphoproteomics identified molecular features associated with primary response and acquired resistance. IL13RA-AKT signaling was upregulated in resistant models; NXP900 sensitivity could be restored with AKT or IL13RA2 inhibition. Together, these findings demonstrate the therapeutic potential of NXP900 as a novel YAP inhibitor in CCA and support further investigation in a clinical trial. Graphical Abstract

Background and Aims: Cholangiocarcinoma (CCA) is one of the most lethal cancers, characterized by molecular heterogeneity and treatment resistance. To uncover new biological signals and therapeutic opportunities, we employed multiomic characterization combined with machine learning. Approach and Results: We profiled all anatomical CCA subtypes using whole exome sequencing, mRNA sequencing, and proteome/phosphoproteome analysis. Integrative dimensional reduction revealed RNA, protein, and phosphoprotein features driving tumor heterogeneity, enabling clustering. Machine learning algorithms identified molecular features for each cluster and mapped external datasets and patient-derived xenograft (PDX) models onto these clusters. Kinase enrichment analysis highlighted targetable kinases active in each cluster. In vivo validation was performed in cluster-specific PDX models using the selective TNK1 inhibitor, TP-5801. We identified 3 molecular clusters with distinct pathway characterization: immunomodulatory (cluster 1), metabolic (cluster 2), and gene regulation/cellular fate (cluster 3). Cluster assignment was independent of anatomic subtype but correlated with overall survival following curative-intent resection. We also identified multiomic features and pathways linked to overall survival and lymph node metastases, crucial for patient treatment selection. Kinase enrichment analysis pinpointed TNK1 as a highly active kinase in the metabolic cluster. Treatment with TP-5801 significantly reduced tumor growth in a metabolic PDX model, but not in models representing the other clusters. Combining internal data with publicly available datasets, we identified the immunomodulatory cluster as most responsive to gemcitabine/cisplatin therapy, confirmed in vivo using cluster-specific PDX models. Conclusions: Integrated multiomic characterization provides translational insights by defining unique molecular subtypes associated both with therapeutic response and overall clinical outcomes. This approach identified TNK1 as a previously unrecognized therapeutic target in a defined subset of CCA tumors.

Abstract Background: The standard first line therapy for cholangiocarcinoma (CCA), gemcitabine and cisplatin +/- immunotherapy, only induces disease control in approximately 75% of patients (KEYNOTE-966 Trial). While several candidate single genes that predict gemcitabine and cisplatin resistance have been proposed, the overall molecular landscape that leads to resistance is not well understood. Predicting response based on molecular characteristics would benefit the clinical decision-making process when selecting appropriate chemotherapy regimens for CCA patients. Methods: Fifty-five Mayo Clinic CCA patients who underwent whole transcriptome RNA sequencing were included. Forty-eight patients had TempusXR sequencing and 7 patients used institutional labs. Normalized transcript-level data was converted to KEGG pathway-level data using overrepresentation ranking. Patient oncology notes were manually reviewed for response to gemcitabine plus cisplatin therapy, with or without concurrent pembrolizumab or durvalumab. Oncologists used a mixture of formal RECIST criteria and expert opinion to determine whether the response to gemcitabine and cisplatin +/- immunotherapy was progressive disease (PD), stable disease (SD), partial response (PR), or complete response (CR). The binary outcome of PD vs SD/PR/CR based on KEGG pathway overrepresentation was modelled using a Tabular Prior-data Fitted Network (TabPFN). Validation was performed using leave-one-out cross-validation. External model testing was performed on RNA sequencing data from 11 patient-derived xenografts that were treated with gemcitabine and cisplatin and underwent ultrasound measurements of tumor size. Results: There were 34 patients with SD/PR/CR and 21 patients with PD as the best response while receiving gemcitabine and cisplatin +/- immunotherapy. TabPFN cross-validation accuracy was 0.73, recall 0.94, precision 0.71, and F1 score 0.81. External validation accuracy was 0.70, with one xenograft exhibiting mixed response. In contrast, the best trained model using a 14-gene subset previously published for gemcitabine resistance prediction in pancreatic adenocarcinoma had accuracy 0.58. Conclusions: Machine learning models like TabPFN can capture relationships in high-dimensional transcriptomic information in novel ways that enhance our ability to predict chemotherapy response. Integrating machine learning to understand the complex molecular landscape of CCA will be a valuable tool for therapeutic regimen selection. Citation Format: Ellen L. Larson, Erik Jessen, Dong-Gi Mun, Amro Abdelrahman, Jennifer Tomlinson, Danielle Carlson, Hojjat Salehinejad, Caitlin Conboy, Rory Smoot. Machine learning models of RNA expression landscapes help predict overall tumor response to chemotherapy in cholangiocarcinoma [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Artificial Intelligence and Machine Learning; 2025 Jul 10-12; Montreal, QC, Canada. Philadelphia (PA): AACR; Clin Cancer Res 2025;31(13_Suppl):Abstract nr A020.

Abstract NF-κB signaling can be subdivided into canonical and noncanonical pathways, culminating in the transcriptional activity of RELA and RELB, respectively. However, the upstream signals that activate these transcription factors and their specific regulatory roles in pancreatic ductal adenocarcinoma (PDAC) remain incompletely understood. Here, we demonstrate that TNFα is the primary activator of canonical NF-κB signaling via RELA, while TWEAK engages noncanonical signaling through RELB in PDAC. Using transcriptome-wide gene expression, genome-wide occupancy profiling, and epigenome mapping, we delineate distinct temporal dynamics and regulatory activities of each pathway. Single-cell RNA-seq analysis and multiplex immunofluorescence staining in primary PDAC samples further reveal extensive and distinct interactions with components of the tumor microenvironment. Motif analysis of RELA- and RELB-bound regions uncovers a particularly strong association of RELB with AP1 elements. Notably, while RELA binds to both open and closed chromatin, RELB exclusively occupies regions with pre-existing chromatin accessibility and AP1 co-binding. Collectively, these findings underscore the distinct and complementary roles of TNFα and TWEAK in PDAC, with TNFα engaging a broader transcriptional program via RELA and TWEAK selectively targeting genes marked by accessible chromatin and epigenetic activity. This study provides critical insights into the regulatory dynamics of NF-κB signaling in PDAC, highlighting unique and complementary functions of RELA and RELB in modulating downstream gene expression. Significance TNFα and TWEAK selectively activate RELA and RELB in pancreatic cancer, revealing that RELB-driven noncanonical signaling depends on chromatin accessibility and AP-1, uncovering distinct, targetable epigenetic dependencies from canonical signaling. Graphical abstract

Background: Cholangiocarcinoma is a molecularly heterogenous cancer arising from the biliary epithelium. Individual omic techniques have identified clinically relevant, targetable subtypes but most tumors have no targetable alterations based on exome or transcriptomic evaluation. Integrated multiomics approaches incorporating transcriptomic, proteomic, and phosphoproteomic characterization provide deeper understanding and identify non-mutated, activated pathways that can be targeted. To optimize the potential clinical utility of these approaches, minimal classifier features must be defined. Methods: Approximately 60,000 RNA, protein, and phosphoprotein features were extracted from 35 cholangiocarcinomas treated at the primary US study site. 206 patients treated and profiled at an institution in China were also included. Using the Multiomics Factor Analysis clustering method, patients were sorted into 3 distinct molecular profiles. Important molecular features were selected using competing feature selection (FS) methods: Boruta, RreliefF, variable selection using random forests (RF), recursive factor elimination (RFE), median decrease accuracy in RF, and Concrete Autoencoders. Machine learning classification prediction models including Extreme Gradient Boosting, gradient-boosted trees, multinomial logit, and support vector machine (SVM) were tested on each FS. Each combination of FS and predictive model was tested with 10 replicates of 10-fold cross-validation of a randomly-selected balanced test set and an oversampled, balanced training subset. Accuracy, F1 score, AUC, precision, and recall were assessed for each FS and predictive model combination. A custom function of physical assay cost and classification accuracy was optimized to find the best assay. KEGG pathway overrepresentation analysis was used to analyze feature subsets. Results: A consistent set of 50 important RNA and protein features was identified, including previously reported prognostic factors, like SpryD4 protein expression, as well as previously unreported pathway surrogates, such as Slc2A2 or Pipox protein. Pathway overrepresentation analysis found insulin signaling and resistance and amino acid biosynthesis/metabolism pathways were overrepresented in the discriminative feature set. The gradient-boosted trees algorithm combined with the RFE FS method had the best performance, with a multiclass macro average (±sd) cross-validation accuracy 89% (±6%), F1 score 89% (±8%), AUC 0.98 (±0.02), precision 90% (±10%), recall 89% (±6%). Conclusions: Feature selection methods and predictive machine learning models work synchronously to develop accurate molecular subtype assays based on just 50 protein and RNA levels. This strategy has the potential to make molecular subtyping for cholangiocarcinoma and other molecularly complex cancers fast and widely available. Citation Format: Ellen Larson, Erik Jessen, Dong-Gi Mun, Jennifer Tomlinson, Amro Abdelrahman, Danielle Carlson, Hojjat Salehinejad, Rory Smoot. Feature selection and machine learning strategies optimize an affordable molecular assay for cholangiocarcinoma subtype [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 1107.