A mucus production programme promotes classical pancreatic ductal adenocarcinoma.

OBJECTIVE: The optimal therapeutic response in cancer patients is highly dependent upon the differentiation state of their tumours. Pancreatic ductal adenocarcinoma (PDA) is a lethal cancer that harbours distinct phenotypic subtypes with preferential sensitivities to standard therapies. This study aimed to investigate intratumour heterogeneity and plasticity of cancer cell states in PDA in order to reveal cell state-specific regulators. DESIGN: We analysed single-cell expression profiling of mouse PDAs, revealing intratumour heterogeneity and cell plasticity and identified pathways activated in the different cell states. We performed comparative analysis of murine and human expression states and confirmed their phenotypic diversity in specimens by immunolabeling. We assessed the function of phenotypic regulators using mouse models of PDA, organoids, cell lines and orthotopically grafted tumour models. RESULTS: Our expression analysis and immunolabeling analysis show that a mucus production programme regulated by the transcription factor SPDEF is highly active in precancerous lesions and the classical subtype of PDA - the most common differentiation state. SPDEF maintains the classical differentiation and supports PDA transformation in vivo. The SPDEF tumour-promoting function is mediated by its target genes AGR2 and ERN2/IRE1ß that regulate mucus production, and inactivation of the SPDEF programme impairs tumour growth and facilitates subtype interconversion from classical towards basal-like differentiation. CONCLUSIONS: Our findings expand our understanding of the transcriptional programmes active in precancerous lesions and PDAs of classical differentiation, determine the regulators of mucus production as specific vulnerabilities in these cell states and reveal phenotype switching as a response mechanism to inactivation of differentiation states determinants.

Genetic Ancestry Inference from Cancer-Derived Molecular Data across Genomic and Transcriptomic Platforms.

Genetic ancestry-oriented cancer research requires the ability to perform accurate and robust genetic ancestry inference from existing cancer-derived data, including whole-exome sequencing, transcriptome sequencing, and targeted gene panels, very often in the absence of matching cancer-free genomic data. Here we examined the feasibility and accuracy of computational inference of genetic ancestry relying exclusively on cancer-derived data. A data synthesis framework was developed to optimize and assess the performance of the ancestry inference for any given input cancer-derived molecular profile. In its core procedure, the ancestral background of the profiled patient is replaced with one of any number of individuals with known ancestry. The data synthesis framework is applicable to multiple profiling platforms, making it possible to assess the performance of inference specifically for a given molecular profile and separately for each continental-level ancestry; this ability extends to all ancestries, including those without statistically sufficient representation in the existing cancer data. The inference procedure was demonstrated to be accurate and robust in a wide range of sequencing depths. Testing of the approach in four representative cancer types and across three molecular profiling modalities showed that continental-level ancestry of patients can be inferred with high accuracy, as quantified by its agreement with the gold standard of deriving ancestry from matching cancer-free molecular data. This study demonstrates that vast amounts of existing cancer-derived molecular data are potentially amenable to ancestry-oriented studies of the disease without requiring matching cancer-free genomes or patient self-reported ancestry. SIGNIFICANCE: The development of a computational approach that enables accurate and robust ancestry inference from cancer-derived molecular profiles without matching cancer-free data provides a valuable methodology for genetic ancestry-oriented cancer research.

Intraductal Transplantation Models of Human Pancreatic Ductal Adenocarcinoma Reveal Progressive Transition of Molecular Subtypes.

Pancreatic ductal adenocarcinoma (PDAC) is the most lethal common malignancy, with little improvement in patient outcomes over the past decades. Recently, subtypes of pancreatic cancer with different prognoses have been elaborated; however, the inability to model these subtypes has precluded mechanistic investigation of their origins. Here, we present a xenotransplantation model of PDAC in which neoplasms originate from patient-derived organoids injected directly into murine pancreatic ducts. Our model enables distinction of the two main PDAC subtypes: intraepithelial neoplasms from this model progress in an indolent or invasive manner representing the classical or basal-like subtypes of PDAC, respectively. Parameters that influence PDAC subtype specification in this intraductal model include cell plasticity and hyperactivation of the RAS pathway. Finally, through intratumoral dissection and the direct manipulation of RAS gene dosage, we identify a suite of RAS-regulated secreted and membrane-bound proteins that may represent potential candidates for therapeutic intervention in patients with PDAC. SIGNIFICANCE: Accurate modeling of the molecular subtypes of pancreatic cancer is crucial to facilitate the generation of effective therapies. We report the development of an intraductal organoid transplantation model of pancreatic cancer that models the progressive switching of subtypes, and identify stochastic and RAS-driven mechanisms that determine subtype specification.See related commentary by Pickering and Morton, p. 1448.This article is highlighted in the In This Issue feature, p. 1426.

SOAT1 promotes mevalonate pathway dependency in pancreatic cancer.

Pancreatic ductal adenocarcinoma (PDAC) has a dismal prognosis, and new therapies are needed. Altered metabolism is a cancer vulnerability, and several metabolic pathways have been shown to promote PDAC. However, the changes in cholesterol metabolism and their role during PDAC progression remain largely unknown. Here we used organoid and mouse models to determine the drivers of altered cholesterol metabolism in PDAC and the consequences of its disruption on tumor progression. We identified sterol O-acyltransferase 1 (SOAT1) as a key player in sustaining the mevalonate pathway by converting cholesterol to inert cholesterol esters, thereby preventing the negative feedback elicited by unesterified cholesterol. Genetic targeting of Soat1 impairs cell proliferation in vitro and tumor progression in vivo and reveals a mevalonate pathway dependency in p53 mutant PDAC cells that have undergone p53 loss of heterozygosity (LOH). In contrast, pancreatic organoids lacking p53 mutation and p53 LOH are insensitive to SOAT1 loss, indicating a potential therapeutic window for inhibiting SOAT1 in PDAC.

Bioactivation of Napabucasin Triggers Reactive Oxygen Species-Mediated Cancer Cell Death.

PURPOSE: Napabucasin (2-acetylfuro-1,4-naphthoquinone or BBI-608) is a small molecule currently being clinically evaluated in various cancer types. It has mostly been recognized for its ability to inhibit STAT3 signaling. However, based on its chemical structure, we hypothesized that napabucasin is a substrate for intracellular oxidoreductases and therefore may exert its anticancer effect through redox cycling, resulting in reactive oxygen species (ROS) production and cell death. EXPERIMENTAL DESIGN: Binding of napabucasin to NAD(P)H:quinone oxidoreductase-1 (NQO1), and other oxidoreductases, was measured. Pancreatic cancer cell lines were treated with napabucasin, and cell survival, ROS generation, DNA damage, transcriptomic changes, and alterations in STAT3 activation were assayed in vitro and in vivo. Genetic knockout or pharmacologic inhibition with dicoumarol was used to evaluate the dependency on NQO1. RESULTS: Napabucasin was found to bind with high affinity to NQO1 and to a lesser degree to cytochrome P450 oxidoreductase (POR). Treatment resulted in marked induction of ROS and DNA damage with an NQO1- and ROS-dependent decrease in STAT3 phosphorylation. Differential cytotoxic effects were observed, where NQO1-expressing cells generating cytotoxic levels of ROS at low napabucasin concentrations were more sensitive. Cells with low or no baseline NQO1 expression also produced ROS in response to napabucasin, albeit to a lesser extent, through the one-electron reductase POR. CONCLUSIONS: Napabucasin is bioactivated by NQO1, and to a lesser degree by POR, resulting in futile redox cycling and ROS generation. The increased ROS levels result in DNA damage and multiple intracellular changes, one of which is a reduction in STAT3 phosphorylation.

Organoid Profiling Identifies Common Responders to Chemotherapy in Pancreatic Cancer.

Pancreatic cancer is the most lethal common solid malignancy. Systemic therapies are often ineffective, and predictive biomarkers to guide treatment are urgently needed. We generated a pancreatic cancer patient-derived organoid (PDO) library that recapitulates the mutational spectrum and transcriptional subtypes of primary pancreatic cancer. New driver oncogenes were nominated and transcriptomic analyses revealed unique clusters. PDOs exhibited heterogeneous responses to standard-of-care chemotherapeutics and investigational agents. In a case study manner, we found that PDO therapeutic profiles paralleled patient outcomes and that PDOs enabled longitudinal assessment of chemosensitivity and evaluation of synchronous metastases. We derived organoid-based gene expression signatures of chemosensitivity that predicted improved responses for many patients to chemotherapy in both the adjuvant and advanced disease settings. Finally, we nominated alternative treatment strategies for chemorefractory PDOs using targeted agent therapeutic profiling. We propose that combined molecular and therapeutic profiling of PDOs may predict clinical response and enable prospective therapeutic selection.Significance: New approaches to prioritize treatment strategies are urgently needed to improve survival and quality of life for patients with pancreatic cancer. Combined genomic, transcriptomic, and therapeutic profiling of PDOs can identify molecular and functional subtypes of pancreatic cancer, predict therapeutic responses, and facilitate precision medicine for patients with pancreatic cancer. Cancer Discov; 8(9); 1112-29. ©2018 AACR.See related commentary by Collisson, p. 1062This article is highlighted in the In This Issue feature, p. 1047.