Tomlinson, Jennifer L.

Abstract Background SWI/SNF chromatin remodeling complexes are frequently mutated across human cancers, including biliary tract cancers (BTC). Within the SWI/SNF complexes, loss-of-function (LOF) mutations in ARID1A and PBRM1 are the most common and frequently co-occur alongside PI3K/AKT pathway activation. Yet, how those mutations affect the intracellular signaling landscape and transcriptomic programs is underexplored and may yield novel therapeutic opportunities. Methods Clinicodemographic parameters and mutation profiles of 250 patients with BTC were retrospectively collected through electronic medical records. Advanced overall survival (OS) was assessed in a multivariable analysis. Transcriptomic data were obtained and differentially expressed genes (DEGs) and pathways associated with SWI/SNF mutation status were analyzed. Changes in the transcriptomic landscape were compared to a murine syngeneic model of intrahepatic cholangiocarcinoma (CCA) initiated by loss of ARID1A and/or PBRM1 for cross-species validation. Results After adjusting for age, sex, and anatomical subtype, patients with SWI/SNF LOF mutations were found to have a 30% reduction in mortality risk (HR = 0.70, 95% CI: 0.50-0.98, p = 0.037). The transcriptomic cohort of 233 BTC patients included 71 (30%) with SWI/SNF LOF mutations, 21 (9%) with variants of uncertain significance, and 141 (61%) with SWI/SNF wild-type tumors. Differential gene expression and pathway analysis revealed changes in adaptive immune response, extracellular matrix, and cancer-associated proteoglycans. RNA-sequencing of murine tumors revealed the dominant effect of ARID1A loss in single and double knock-out tumors and conserved pathway alterations between mouse and human tumors. Conclusion Both murine and human primary tumors with either ARID1A alone or ARID1A/PBRM1 co-mutations exhibited altered expression of critical genes and pathways associated with proteoglycan synthesis and extracellular matrix. Ongoing research is investigating how CCA cells depend on those pathways and their canonical regulators for tumor formation and progression.

Abstract Background & Objectives Cholangiocarcinoma (CCA) is a highly aggressive malignancy arising from the bile duct epithelium. Despite advancements in diagnostic techniques, the diagnosis of cholangiocarcinoma (CCA) remains challenging. Currently, CA19-9 is the best available blood-based marker for detection of CCA, which has a sensitivity of 50-60% and a specificity of 80%. Moreover, individuals who are Lewis-antigen-negative (∼20% in some populations) have undetectable CA 19–9 levels resulting in false negative diagnoses. Therefore, there is a critical need for developing novel blood-based diagnostic approach for improving the sensitivity of diagnosis of CCA to improve clinical outcomes. Glycosylation, one of the most prevalent post-translational modifications, plays a crucial role in regulating biological functions such as cell-cell communication, protein folding and receptor signaling and is frequently dysregulated in cancer. Cell surface proteins, including glycoproteins, are overexpressed in CCA are likely to be shed into the blood and we investigated development of mass spectrometry-based methods to measure changes in glycosylation in patients with CCA. Methods Mass spectrometry data were acquired in parallel reaction monitoring mode using Orbitrap Eclipse Tribrid mass spectrometers. In addition, we tested the use of heavy glycopeptides for absolute quantitation of each glycopeptide. Mass spectrometry data were analyzed using Skyline to estimate glycopeptide abundance. Results First, we performed tandem mass tag-based quantitative proteomics and glycoproteomics of tumor tissues and serum collected from CCA patients using high-resolution mass spectrometry. From these experiments, a number of glycopeptides were found to be increased in abundance in CCA patients. We subsequently developed a targeted mass spectrometry–based assay to monitor four candidate glycopeptides derived from polymeric immunoglobulin receptor and aminopeptidase N to validate their performance in a large patient cohort from 269 patients with CCA and 100 healthy individuals. Conclusion We anticipate that this finding will lay the foundation for novel diagnostics that could benefit patients with this aggressive malignancy.

Abstract Background: Cholangiocarcinoma (CCA) is an aggressive hepatobiliary malignancy with limited treatment options. CCA exhibits a distinct desmoplastic and tolerogenic tumor immune microenvironment (TIME) characterized by elevated bile acid concentrations resulting from obstructive cholestasis and dysregulated bile acid metabolism. TGR5 is an essential component of bile acid signaling. We hypothesize that bile acids promote CCA progression by establishing an immunosuppressive TIME through TGR5 signaling, which can be therapeutically targeted using SBI-364, a novel potent small molecule TGR5 inhibitor. Methods: Single-cell RNA sequencing (scRNA-seq) of immune cells from human intrahepatic (iCCA) and perihilar (pCCA) CCA tumors were conducted. Therapeutic studies were performed using syngeneic murine models of iCCA (PMID: 38458319), a novel syngeneic model of pCCA, and patient-derived xenograft (PDX) models. In collaboration with Sanford Burnham Prebys, SBI-364, a first in-class competitive TGR5 antagonist, was assessed in vivo. Additionally, we performed co-culture experiments with bile acid +/- SBI-364-treated murine bone marrow-derived monocytic myeloid-derived suppressor cells (M-MDSCs) and CD8+ T cells to assess functional immunosuppressive effects. Results: Human scRNA-seq revealed significantly increased TGR5 (GPBAR1) expression predominantly in myeloid cell populations within the CCA TIME. SBI-364 treatment significantly reduced tumor burden in both syngeneic orthotopic iCCA models and a novel pCCA model that recapitulates the anatomic characteristics of perihilar CCA. In contrast, NOD/SCID mice bearing PDX535 (predicted sensitive) and PDX136 (predicted resistant), SBI-364 treatment did not achieve tumor reduction, suggesting that TGR5 inhibition predominantly attenuates tumor progression through modulation of bile acid-immune cell interactions. SBI-364 treated murine tumors had a significant reduction in immunosuppressive macrophages expressing interleukin-10 and M-MDSCs compared to vehicle treated tumors. Furthermore, bile acid-treated M-MDSCs exhibited enhanced suppression of CD8+ T cell proliferation and function, an effect that was abrogated by SBI-364 co-treatment. Conclusion: We demonstrate that TGR5 inhibition represents a promising therapeutic strategy across multiple immunocompetent preclinical CCA models. We demonstrate that the bile-acid TGR5 axis promotes CCA progression via immunosuppressive myeloid cells. Specifically, TGR5 signaling potentiates the immunosuppressive capacity of M-MDSCs, contributing to an immunosuppressive niche that facilitates tumor progression. These results establish TGR5 as a rational therapeutic target for overcoming immune evasion in cholangiocarcinoma. Citation Format: Enis Hikmet Ozmert, Binbin Li, Jingchun Yang, Hannah Elizabeth Stumpf, Jessica R. Willhite, Danielle Carlson, Jennifer L. Tomlinson, Jon Covel, Raghuveer Ramachandra, Steven Olson, Rory L. Smoot, Sumera Ilyas. Therapeutic targeting of TGR5 abrogates bile acid driven myeloid cell immunosuppression in 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 2896.

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.

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

Lacking effective therapeutics, cholangiocarcinoma (CCA) remains a deadly malignancy of the biliary tract. The Hippo pathway effector protein Yes-associated protein (YAP) is implicated in CCA pathogenesis and chemotherapeutic resistance; however, the oncogenic mechanisms underlying YAP regulation remain incompletely understood. An enhanced understanding of YAP and its role in CCA may uncover novel therapeutic targets and better define resistance pathways. Human CCA cells and murine syngeneic CCA models were utilized to explore the molecular relationship of YAP and protein tyrosine phosphatase 1B (PTP1B). Previous work in CCA has demonstrated that YAP interacts with multiple protein tyrosine phosphatases, including SHP2 and PTP1B. We observed that PTP1B pharmacologic inhibition was associated with increased cell proliferation and YAP target gene expression, while genetically enforced overexpression of PTP1B was associated with a decrease in YAP activation. Treatment of CCA cells in vitro and syngeneic, orthotopically implanted CCA murine tumors in vivo with standard cytotoxic chemotherapy, gemcitabine/cisplatin, had enhanced efficacy in the setting of PTP1B overexpression. These findings demonstrate that pYAPY357 can be modulated through protein tyrosine 1B phosphatase activity, and reducing pYAPY357 through enhanced phosphatase levels can sensitize CCA to chemotherapy.

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.

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.

Abstract Background: Cholangiocarcinoma (CCA) is a malignancy of the biliary epithelium with increasing incidence and poor survival. Despite the advances in targeted therapies, treatment success has been hindered by primary or acquired resistance. New therapeutic strategies are necessary to improve outcomes in this patient population. This study investigates the anti-tumor efficacy of TGR-5 inhibition in CCA using a novel small molecular inhibitor, SBI-364. Methods: Cell viability was assessed using a CellTiter-Glo assay in four unique CCA cell lines treated with SBI-364 at concentrations ranging from 1 nM to 100 µM for 48 hours. Viability was expressed as a percentage relative to untreated controls. Cell migration was assessed using a scratch wound healing assay at 0, 12, and 24 hours following SBI-364 treatment. Migration was reported as the percentage of wound closure relative to the initial scratch width. Apoptosis was assessed using the Caspase-Glo® 3/7 Assay (Promega) after 12 hours of treatment with SBI-364. Caspase activity was normalized to untreated controls and expressed as relative luminescence units. Results: SBI-364 reduced cell viability in a dose-dependent manner across all CCA cell lines with IC50 values ranging from 4.1-15.8 µM. Higher concentrations of SBI-364 induced increased cytotoxicity. In the scratch assay, untreated CCA cells achieved 100 % wound closure within 24 hours. Treatment with SBI-364 at 10 µM significantly inhibited cellular migration, with reduced wound closure compared to controls (p < 0.05). Apoptosis analysis revealed a significant increase in caspase-3/7 activity in three CCA cell lines following treatment with 10 µM SBI-364 for 12 hours (p < 0.01). Conclusion: TGR-5 inhibition using novel small molecule inhibitor SBI-364 demonstrates potent anti-tumor effects in CCA by reducing viability, inhibiting migration, and promoting apoptosis. These findings support further investigation of SBI-364 as a promising therapeutic strategy in CCA. Citation Format: Enis Ozmert, Jennifer L. Tomlinson, Danielle M. Carlson, Rory L. Smoot. Efficacy of TGR-5 inhibition in cholangiocarcinoma using the novel small molecule inhibitor SBI-364 [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 5588.