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.

Inferring and modeling inheritance of differentially methylated changes across multiple generations.

High-throughput methylation sequencing enables genome-wide detection of differentially methylated sites (DMS) or regions (DMR). Increasing evidence suggests that treatment-induced DMS can be transmitted across generations, but the analysis of induced methylation changes across multiple generations is complicated by the lack of sound statistical methods to evaluate significance levels. Due to software design, DMS detection was usually made on each generation separately, thus disregarding stochastic effects expected when a large number of DMS is detected in each generation. Here, we present a novel method based on Monte Carlo sampling, methylInheritance, to evaluate that the number of conserved DMS between several generations is associated to an effect inherited from a treatment and not randomness. Moreover, we developed an inheritance simulation package, methInheritSim, to demonstrate the performance of the methylInheritance method and to evaluate the power of different experimental designs. Finally, we applied methylInheritance to a DNA methylation dataset obtained from early-life persistent organic pollutants (POPs) exposed Sprague-Dawley female rats and their descendants through a paternal transmission. The results show that metylInheritance can efficiently identify treatment-induced inherited methylation changes. Specifically, we identified two intergenerationally conserved DMS at transcription start site (TSS); one of those persisted transgenerationally. Three transgenerationally conserved DMR were found at intra or integenic regions.

metagene Profiles Analyses Reveal Regulatory Element's Factor-Specific Recruitment Patterns.

ChIP-Sequencing (ChIP-Seq) provides a vast amount of information regarding the localization of proteins across the genome. The aggregation of ChIP-Seq enrichment signal in a metagene plot is an approach commonly used to summarize data complexity and to obtain a high level visual representation of the general occupancy pattern of a protein. Here we present the R package metagene, the graphical interface Imetagene and the companion package similaRpeak. Together, they provide a framework to integrate, summarize and compare the ChIP-Seq enrichment signal from complex experimental designs. Those packages identify and quantify similarities or dissimilarities in patterns between large numbers of ChIP-Seq profiles. We used metagene to investigate the differential occupancy of regulatory factors at noncoding regulatory regions (promoters and enhancers) in relation to transcriptional activity in GM12878 B-lymphocytes. The relationships between occupancy patterns and transcriptional activity suggest two different mechanisms of action for transcriptional control: i) a "gradient effect" where the regulatory factor occupancy levels follow transcription and ii) a "threshold effect" where the regulatory factor occupancy levels max out prior to reaching maximal transcription. metagene, Imetagene and similaRpeak are implemented in R under the Artistic license 2.0 and are available on Bioconductor.

Using informative Multinomial-Dirichlet prior in a t-mixture with reversible jump estimation of nucleosome positions for genome-wide profiling.

Genome-wide mapping of nucleosomes has revealed a great deal about the relationships between chromatin structure and control of gene expression. Recent next generation CHIP-chip and CHIP-Seq technologies have accelerated our understanding of basic principles of chromatin organization. These technologies have taught us that nucleosomes play a crucial role in gene regulation by allowing physical access to transcription factors. Recent methods and experimental advancements allow the determination of nucleosome positions for a given genome area. However, most of these methods estimate the number of nucleosomes either by an EM algorithm using a BIC criterion or an effective heuristic strategy. Here, we introduce a Bayesian method for identifying nucleosome positions. The proposed model is based on a Multinomial-Dirichlet classification and a hierarchical mixture distributions. The number and the positions of nucleosomes are estimated using a reversible jump Markov chain Monte Carlo simulation technique. We compare the performance of our method on simulated data and MNase-Seq data from Saccharomyces cerevisiae against PING and NOrMAL methods.

Analysis of ZNF350/ZBRK1 promoter variants and breast cancer susceptibility in non-BRCA1/2 French Canadian breast cancer families.

ZNF350/ZBRK1 is a transcription factor, which associates with BRCA1 to co-repress GADD45A to regulate DNA damage repair, and the expression of ZNF350 is altered in different human carcinomas. In a previous study, we identified ZNF350 genomic variants potentially involved in breast cancer susceptibility in high-risk non-BRCA1/2 breast cancer individuals, which pointed toward a potential association for variants in the 5'-UTR and promoter regions. Therefore, direct sequencing was undertaken and identified 12 promoter variants, whereas haplotype analyses put in evidence four common haplotypes with a frequency>2%. However, based on their frequency observed in breast cancer and unrelated healthy individuals, these are not statistically associated with breast cancer risk. Luciferase promoter assays in two breast cancer cell lines identified two haplotypes (H11 and H12) stimulating significantly the expression of ZNF350 transcript compared with the common haplotype H8. The high expression of the H11 allele was associated with the variant c.-874A. Using MatInspector and Transcription Element Search softwares, in silico analyses predicted that the variant c.-874A created a binding site for the factors c-Myc and myogenin. This study represents the first characterization step of the ZNF350 promoter. Additional studies in larger cohorts and other populations will be needed to further evaluate whether common and/or rare ZNF350 promoter variants and haplotypes could be associated with a modest risk of breast cancer.

Analysis of germline gene copy number variants of patients with sporadic pancreatic adenocarcinoma reveals specific variations.

OBJECTIVES: The rapid fatality of pancreatic cancer is, in large part, the result of diagnosis at an advanced stage in the majority of patients. Identification of individuals at risk of developing pancreatic adenocarcinoma would be useful to improve the prognosis of this disease. There is presently no biological or genetic indicator allowing the detection of patients at risk. Our main goal was to identify copy number variants (CNVs) common to all patients with sporadic pancreatic cancer. METHODS: We analyzed gene CNVs in leukocyte DNA from 31 patients with sporadic pancreatic adenocarcinoma and from 93 matched controls. Genotyping was performed with the use of the GeneChip Human Mapping 500K Array Set (Affymetrix). RESULTS: We identified 431 single nucleotide polymorphism (SNP) probes with abnormal hybridization signal present in the DNA of all 31 patients. Of these SNP probes, 284 corresponded to 3 or more copies and 147 corresponded to 1 or 0 copies. Several cancer-associated genes were amplified in all patients. Conversely, several genes supposed to oppose cancer development were present as single copy. CONCLUSIONS: These data suggest that a set of 431 CNVs could be associated with the disease. This set could be useful for early diagnosis.

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.

Specific transcriptional response of four blockers of estrogen receptors on estradiol-modulated genes in the mouse mammary gland.

Novel agents for the endocrine therapy of breast cancer are needed, especially in order to take advantage of the multiple consecutive responses observed in metastatic progressing breast cancer following previous hormone therapy, thus delaying the use of cytotoxic chemotherapy with its frequent poor tolerance and serious side effects. Acolbifene (ACOL) is a novel and unique antiestrogen which represents a unique opportunity to achieve the most potent and specific blockade of estrogen action in the mammary gland and uterus while exerting estrogen-like beneficial effects in other tissues, especially the bones. To better understand the specificity of action of ACOL, we have used Affymetrix GeneChips containing 45,000 probe sets to analyze 34,000 genes to determine the specificity of this compound compared to the pure antiestrogen fulvestrant, as well as to the mixed antagonists/agonists tamoxifen and raloxifene to block the effect of estradiol (E(2)) and to induce effects of their own on the genomic profile in the mouse mammary gland. The genes modulated by E(2) were those identified in two separate experiments and validated by quantitative real-time PCR (qPCR). Three hours after the single subcutaneous injection of E(2) (0.05 µg), the simultaneous administration of ACOL, fulvestrant, tamoxifen, and raloxifene blocked by 98, 61, 43, and 92 % the number of E(2)-upregulated genes, respectively. On the other hand, 70, 10, 25, and 55 % of the genes down-regulated by E(2) were blocked by the same compounds. Of the 128 genes modulated by E(2), 49 are associated with tumorigenesis while 22 are known to be associated with breast cancer. When used alone, ACOL modulated the smallest number of genes also influenced by E(2), namely 4 %, thus possibly explaining potential utilities of this compound in breast cancer prevention and therapy.

Gene interactions in depression: pathways out of darkness.

Mood disorders, including major depressive disorder and bipolar disorder, are influenced by both genetic and environmental factors. Hypotheses about the neurobiology of mood disorders have been postulated and putatively associated genes identified. Recently, the immune-related gene encoding purinergic receptor P2X, ligand-gated ion channel, 7 (P2RX7) has been genetically associated with major depressive disorder and bipolar disorder. New candidate genes and emerging gene networks and pathways involved in the aetiology of mood disorders point to a major role for neuronal survival and the adaptive immune systems.

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.

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.

Fine temporal analysis of DHT transcriptional modulation of the ATM/Gadd45g signaling pathways in the mouse uterus.

In rodents, the uterus of a mature female undergoes changes during the uterine cycle, under the control of steroid hormones. 5alpha-Dihydrotestosterone (DHT) is recognized to play an important role in the regulation of androgen action in normal endometrium. Using microarray technology, a screening analysis of genes responding to DHT in the uterus of ovariectomized mice, has allowed us to highlight multiple genes of the ATM/Gadd45g pathway that are modulated following exposure to DHT. Two phases of regulation were identified. In the early phase, the expression of genes involved in the G2/M arrest is rapidly increased, followed by the repression of genes of the G1/S checkpoint, and by the induction of transcriptional regulators. Later, i.e. from 12 to 24 hr, genes involved in G2/M transition, cytoarchitectural and lipid-related genes are stimulated by DHT while immunity-related genes appear to be differentially regulated by the hormone. These results show that a physiological dose of DHT induces the transcription of genes promoting the cell cycle progression in mice. Profile determination of temporal uterine gene expression at the transcriptional level enables us to suggest that the DHT modulation of genes involved in ATM/Gadd45g signaling in an ATM- or p53-independent manner, could play an important role in the cyclical changes of uterine cells in the mouse uterus.

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.

Cross-Species Single-Cell Analysis of Pancreatic Ductal Adenocarcinoma Reveals Antigen-Presenting Cancer-Associated Fibroblasts.

Cancer-associated fibroblasts (CAF) are major players in the progression and drug resistance of pancreatic ductal adenocarcinoma (PDAC). CAFs constitute a diverse cell population consisting of several recently described subtypes, although the extent of CAF heterogeneity has remained undefined. Here we use single-cell RNA sequencing to thoroughly characterize the neoplastic and tumor microenvironment content of human and mouse PDAC tumors. We corroborate the presence of myofibroblastic CAFs and inflammatory CAFs and define their unique gene signatures in vivo. Moreover, we describe a new population of CAFs that express MHC class II and CD74, but do not express classic costimulatory molecules. We term this cell population "antigen-presenting CAFs" and find that they activate CD4+ T cells in an antigen-specific fashion in a model system, confirming their putative immune-modulatory capacity. Our cross-species analysis paves the way for investigating distinct functions of CAF subtypes in PDAC immunity and progression. SIGNIFICANCE: Appreciating the full spectrum of fibroblast heterogeneity in pancreatic ductal adenocarcinoma is crucial to developing therapies that specifically target tumor-promoting CAFs. This work identifies MHC class II-expressing CAFs with a capacity to present antigens to CD4+ T cells, and potentially to modulate the immune response in pancreatic tumors.See related commentary by Belle and DeNardo, p. 1001.This article is highlighted in the In This Issue feature, p. 983.

Genetic variants and haplotype analyses of the ZBRK1/ZNF350 gene in high-risk non BRCA1/2 French Canadian breast and ovarian cancer families.

Our current understanding of breast cancer susceptibility involves mutations in the 2 major genes BRCA1 and BRCA2, found in about 25% of high-risk families, as well as few other low penetrance genes such as ATM and CHEK2. Approximately two-thirds of the multiple cases families remain to be explained by mutations in still unknown genes. In a candidate gene approach to identify new genes potentially involved in breast cancer susceptibility, we analyzed genomic variants in the ZBRK1 gene, a co-repressor implicated in BRCA1-mediated repression of GADD45. Direct sequencing of ZBRK1 entire coding region in affected breast cancer individuals from 97 high-risk French Canadian breast/ovarian cancer families and 94 healthy controls led to the identification of 18 genomic variants. Haplotype analyses, using PHASE, COCAPHASE and HaploStats programs, put in evidence 3 specific haplotypes which could potentially modulate breast cancer risk, and among which 2 that are associated with a potential protective effect (p = 0.01135 and p = 0.00268), while another haplotype is over-represented in the case group (p = 0.00143). Further analyses of these haplotypes indicated that a strong component of the observed difference between both groups emerge from the first 5 variants (out of 12 used for haplotype determination). The present study also permitted to determine a set of tagging SNPs that could be useful for subsequent analyses in large scale association studies. Additional studies in large cohorts and other populations will however be needed to further evaluate if common and/or rare ZBRK1 sequence variants and haplotypes could be associated with a modest/intermediate breast cancer risk.

A type 2 diabetes disease module with a high collective influence for Cdk2 and PTPLAD1 is localized in endosomes.

Despite the identification of many susceptibility genes our knowledge of the underlying mechanisms responsible for complex disease remains limited. Here, we identified a type 2 diabetes disease module in endosomes, and validate it for functional relevance on selected nodes. Using hepatic Golgi/endosomes fractions, we established a proteome of insulin receptor-containing endosomes that allowed the study of physical protein interaction networks on a type 2 diabetes background. The resulting collated network is formed by 313 nodes and 1147 edges with a topology organized around a few major hubs with Cdk2 displaying the highest collective influence. Overall, 88% of the nodes are associated with the type 2 diabetes genetic risk, including 101 new candidates. The Type 2 diabetes module is enriched with cytoskeleton and luminal acidification-dependent processes that are shared with secretion-related mechanisms. We identified new signaling pathways driven by Cdk2 and PTPLAD1 whose expression affects the association of the insulin receptor with TUBA, TUBB, the actin component ACTB and the endosomal sorting markers Rab5c and Rab11a. Therefore, the interactome of internalized insulin receptors reveals the presence of a type 2 diabetes disease module enriched in new layers of feedback loops required for insulin signaling, clearance and islet biology.

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.

Temporal analysis of E2 transcriptional induction of PTP and MKP and downregulation of IGF-I pathway key components in the mouse uterus.

17beta-Estradiol (E2) is well known to be associated with uterine cancer, endometriosis, and leiomyomas. Although insulin-like growth factor I (IGF-I) has been identified as a mediator of the uterotrophic effect of E2 in several studies, this mechanism is still not well understood. In the present study, identification of the genes modulated by a physiological dose of E2, in the uterus, has been done in ovariectomized mice using Affymetrix microarrays. The E2-induced genomic profile shows that multiple genes belonging to the IGF-I pathway are affected after exposure to E2. Two phases of regulation could be identified. First, from 0 to 6 h, the expression of genes involved in the cell cycle, growth factors, protein tyrosine phosphatases, and MAPK phosphatases is quickly upregulated by E2, while IGF-I receptor and several genes of the MAPK and phosphatidylinositol 3-kinase pathways are downregulated. Later, i.e., from 6 to 24 h, transporters and peptidases/proteases are stimulated, whereas defense-related genes are differentially regulated by E2. Finally, cytoarchitectural genes are modulated later. The present data show that a physiological dose of E2 induces, within 24 h, a series of transcriptional events that promote the uterotrophic effect. Among these, the E2-mediated activation of the IGF-I pathway seems to play a pivotal role in the uterotrophic effect. Furthermore, the protein tyrosine phosphatases and MAPK phosphatases are likely to modulate the estrogenic uterotrophic action by targeting, at different steps, the IGF-I pathway.