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.

Mixed acinar neuroendocrine carcinoma of the pancreas (MANEC-P) is an extremely rare malignancy with a poor prognosis. However, epidemiological estimates of MANEC-P remain unknown. This study aimed to estimate and compare the incidence, prevalence, and cancer-specific survival (CSS) of MANEC-P in the United States (US). Patients with MANEC-P were identified through the Surveillance, Epidemiology, and End Results (SEER) and National Program of Cancer Registries databases between 2000–2017. The primary outcomes included age-adjusted incidence rate, limited-duration prevalence, and CSS. A total of 630 patients were identified for the incidence analysis and 149 for the prevalence and CSS analyses. The MANEC-P incidence rate was 0.011 per 100,000 individuals, which was the lowest among pancreatic cancer histologic subtypes. The incidence rate was significantly higher in men and Black races and peaked at 75–79 years of age. The incidence rate was the lowest in the midwestern region (0.009) and the highest in the northeastern US (0.013). The 17-year prevalence was 0.00005%, indicating that 189 patients were alive in the United States at the beginning of 2018. The median CSS of MANEC-P was estimated to be 41 (23, 69) months. In conclusion, MANEC-P is very rare, and its incidence rate has been steady in the US over the last two decades. MANEC-P has a poor prognosis and is the 5th leading cause of pancreatic cancer-related death in the US.

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 pYAP^Y357 can be modulated through protein tyrosine 1B phosphatase activity, and reducing pYAP^Y357 through enhanced phosphatase levels can sensitize CCA to chemotherapy.