Conboy, Caitlin

Abstract Background Optimal treatment following first-line immunotherapy for advanced hepatocellular carcinoma (HCC) remains uncertain. This study evaluated futibatinib, a pan-FGFR inhibitor, combined with pembrolizumab in previously treated patients with FGF19-expressing HCC. Methods Eligible patients were ≥18 years old with advanced HCC, prior systemic therapy, Child-Pugh A-B7 liver function, ECOG 0–2, and FGF19 overexpression. Patients received futibatinib 20 mg orally daily plus pembrolizumab 200 mg intravenously every 3 weeks. The primary endpoint was progression-free survival at 6 months (PFS6). Secondary endpoints included overall survival (OS), objective response rate (ORR), quality of life, and safety. Results Between August 2021 and March 2024, 14 patients enrolled and 13 were evaluable. Median age was 72 years (range, 60–87), 53.8% were male, 92.3% had Child-Pugh A liver function, and all had received prior immunotherapy. Median progression-free survival was 15 weeks (95% CI, 9.0–NE), with a PFS6 rate of 23.1% (95% CI, 8.6–62.3%). ORR was 0% (95% CI, 0–24.7%), while stable disease was observed in 53.9% of patients. Median OS was 55.7 weeks (95% CI, 47.3–NE). Grade ≥3 adverse events occurred in 69.2% of patients, and grade ≥4 adverse events in 15.4%. One grade 5 event (acute-on-chronic kidney injury) was deemed unrelated to treatment. Common adverse events included hyperphosphatemia, fatigue, diarrhea, elevated transaminases, dry eye, nail changes, rash, and oral mucositis. Conclusions Futibatinib plus pembrolizumab demonstrated an acceptable safety profile but did not meet efficacy thresholds supporting further study in FGF19-expressing HCC. Effective post-immunotherapy treatment strategies remain an unmet need.

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.

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.