Yuna Blum

Gene expression profiling of patient-derived pancreatic cancer xenografts predicts sensitivity to the BET bromodomain inhibitor JQ1: implications for individualized medicine efforts

c‐MYC controls more than 15% of genes responsible for proliferation, differentiation, and cellular metabolism in pancreatic as well as other cancers making this transcription factor a prime target for treating patients. The transcriptome of 55 patient‐derived xenografts show that 30% of them share an exacerbated expression profile of MYC transcriptional targets (MYC‐high). This cohort is characterized by a high level of Ki67 staining, a lower differentiation state, and a shorter survival time compared to the MYC‐low subgroup. To define classifier expression signature, we selected a group of 10 MYC target transcripts which expression is increased in the MYC‐high group and six transcripts increased in the MYC‐low group. We validated the ability of these markers panel to identify MYC‐high patient‐derived xenografts from both: discovery and validation cohorts as well as primary cell cultures from the same patients. We then showed that cells from MYC‐high patients are more sensitive to JQ1 treatment compared to MYC‐low cells, in monolayer, 3D cultured spheroids and in vivo xenografted tumors, due to cell cycle arrest followed by apoptosis. Therefore, these results provide new markers and potentially novel therapeutic modalities for distinct subgroups of pancreatic tumors and may find application to the future management of these patients within the setting of individualized medicine clinics.

Pancreatic Adenocarcinoma Therapeutic Targets Revealed by Tumor-Stroma Cross-Talk Analyses in Patient-Derived Xenografts

SUMMARY Preclinical models based on patient-derived xenografts have remarkable specificity in distinguishing transformed human tumor cells from non-transformed murine stromal cells computationally. We obtained 29 pancreatic ductal adenocarcinoma (PDAC) xenografts from either resectable or non-resectable patients (surgery and endoscopic ultrasound-guided fine-needle aspirate, respectively). Extensive multiomic profiling revealed two subtypes with distinct clinical outcomes. These subtypes uncovered specific alterations in DNA methylation and transcription as well as in signaling pathways involved in tumor-stromal cross-talk. The analysis of these pathways indicates therapeutic opportunities for targeting both compartments and their interactions. In particular, we show that inhibiting NPC1L1 with Ezetimibe, a clinically available drug, might be an efficient approach for treating pancreatic cancers. These findings uncover the complex and diverse interplay between PDAC tumors and the stroma and demonstrate the pivotal role of xenografts for drug discovery and relevance to PDAC.

Distinct epigenetic landscapes underlie the pathobiology of pancreatic cancer subtypes

Recent studies have offered ample insight into genome-wide expression patterns to define pancreatic ductal adenocarcinoma (PDAC) subtypes, although there remains a lack of knowledge regarding the underlying epigenomics of PDAC. Here we perform multi-parametric integrative analyses of chromatin immunoprecipitation-sequencing (ChIP-seq) on multiple histone modifications, RNA-sequencing (RNA-seq), and DNA methylation to define epigenomic landscapes for PDAC subtypes, which can predict their relative aggressiveness and survival. Moreover, we describe the state of promoters, enhancers, super-enhancers, euchromatic, and heterochromatic regions for each subtype. Further analyses indicate that the distinct epigenomic landscapes are regulated by different membrane-to-nucleus pathways. Inactivation of a basal-specific super-enhancer associated pathway reveals the existence of plasticity between subtypes. Thus, our study provides new insight into the epigenetic landscapes associated with the heterogeneity of PDAC, thereby increasing our mechanistic understanding of this disease, as well as offering potential new markers and therapeutic targets.Pancreatic ductal adenocarcinoma (PDAC) is a complex disease and its underlying epigenomic heterogeneity is not fully understood. Here, the authors utilize patient-derived PDAC xenografts to define the epigenomic landscape of PDAC, highlighting chromatin states linked to differing disease aggressiveness and survival.

SMAP: exploiting high-throughput sequencing data of patient derived xenografts

Background Patient-derived xenograft is the model of reference in oncology fordrug response analyses. Xenografts samples have the specificity to be composedof cells from both the graft and the host species. Sequencing analysis ofxenograft samples therefore requires specific processing methods to properlyreconstruct genomic profiles of both the host and graft compartments. Results We propose a novel xenograft sequencing process pipeline termedSMAP for Simultaneous mapping. SMAP integrates the distinction of host andgraft sequencing reads to the mapping process by simultaneously aligning to bothgenome references. We show that SMAP increases accuracy of species-assignmentwhile reducing the number of discarded ambiguous reads compared to otherexisting methods. Moreover, SMAP includes a module called SMAP-fuz toimprove the detection of chimeric transcript fusion in xenograft RNAseq data. Finally, we apply SMAP on a real dataset and show the relevance of pathway andcell population analysis of the tumoral and stromal compartments. Conclusions In high-throughput sequencing analysis of xenografts, our resultsshow that: i. the use of ad hoc sequence processing methods is essential, ii. highsequence homology does not introduce a significant bias when proper methodsare used and iii. the detection of fusion transcripts can be improved using ourapproach. SMAP is available on GitHub: cit-bioinfo.github.io/SMAP.

Stratification of Pancreatic Ductal Adenocarcinomas Based on Tumor and Microenvironment Features

BACKGROUND & AIMS Genomic studies have revealed subtypes of pancreatic ductal adenocarcinoma (PDA) based on their molecular features, but different studies have reported different classification systems. It is a challenge to obtain high-quality, freshly frozen tissue for clinical analysis and determination of PDA subtypes. We aimed to redefine subtypes of PDA using a large number of formalin-fixed and paraffin-embedded PDA samples, which are more amenable to routine clinical evaluation. METHODS We collected PDA samples from 309 consecutive patients who underwent surgery from September 1996 through December 2010 at 4 academic hospitals in Europe; nontumor tissue samples were not included. Samples were formalin fixed and paraffin embedded. DNA and RNA were isolated; gene expression, targeted DNA sequencing, and immunohistochemical analyses were performed. We used independent component analysis to deconvolute normal, tumor, and microenvironment transcriptome patterns in samples. We devised classification systems from an unsupervised analysis using a consensus clustering approach of our data set after removing normal contamination components. We associated subtypes with overall survival and disease-free survival of patients using Cox proportional hazards regression with estimation of hazard ratios and 95% confidence interval. We used The Cancer Genome Consortium and International Cancer Genome Consortium PDA data sets as validation cohorts. RESULTS We validated the previously reported basal-like and classical tumor-specific subtypes of PDAs. We identified features of the PDA, including microenvironment gene expression patterns, that allowed tumors to be categorized into 5 subtypes, called pure basal like, stroma activated, desmoplastic, pure classical, and immune classical. These PDA subtypes have features of cancer cells and immune cells that could be targeted by pharmacologic agents. Tumor subtypes were associated with patient outcomes, based on analysis of our data set and the International Cancer Genome Consortium and The Cancer Genome Consortium PDA data sets. We also observed an exocrine signal associated with acinar cell contamination (from pancreatic tissue). CONCLUSIONS We identified a classification system based on gene expression analysis of formalin-fixed PDA samples. We identified 5 PDA subtypes, based on features of cancer cells and the tumor microenvironment. This system might be used to select therapies and predict patient outcomes. We found evidence that the previously reported exocrine-like (called ADEX) tumor subtype resulted from contamination with pancreatic acinar cells. ArrayExpress accession number: E-MTAB-6134.

Abstract 4396: Multiomics assessment of the cancer and stromal compartments of patient-derived pancreatic xenografts reveals clinically-relevant subtypes and novel targeted therapies

Patient-derived xenografts (PDX) are appearing as a prime approach for preclinical studies despite being insufficiently characterized as a model of the human disease and its diversity. In this work, 29 PDX were obtained from either surgery or endoscopic ultrasound-guided fine needle aspirate of pancreatic adenocarcinoma. The extensive genomic profiling of these pancreatic PDX, revealed two clinically-relevant subtypes having broad similarities with human primary tumors. These subtypes are defined by highly specific DNA methylation and transcriptomic profiles (mRNA, miRNA or lncRNA) but are not distinguishable by exonic mutations or copy number aberrations. Moreover, by specifically analyzing the stroma transcriptome, as defined by the expression of murine transcripts, we found that it is able to stratify the patients with the same efficiency than the analysis of grafted human tumor cells. This finding suggest that transformed pancreatic cells drive the composition of their own stroma. Finally, the multiomics analysis pinpoints novel therapeutic targets, one of which we demonstrate to be an efficient method for treating pancreatic cancer. Overall, we show that PDX are trustworthy pre-clinical models of pancreatic adenocarcinoma including of unresectable tumors. Their multiomics profiling allow the independent analysis of the uncontaminated cancer or stromal compartments and discloses several original therapeutics targets. Citation Format: Remy Nicolle, Yuna Blum, Laetitia Marisa, Celine Loncle, Odile Gayet, Vincent Moutardier, Olivier Turrini, Marc Giovannini, Benjamin Bian, Martin Bigonnet, Marion Rubis, Nabila Elarouci, Lucile Armenoult, Mira Ayadi, Pauline Duconseil, Mohamed Gasmi, Mehdi Ouaissi, Aurelie Maignan, Gwen Lomberk, Jean-Marie Boher, Jacques Ewald, Erwan Bories, Jonathan Garnier, Anthony Goncalves, Flora Poizat, Jean-Luc Raoul, Veronique Secq, Stephane Garcia, Philippe Grandval, Marine Barraud-Blanc, Emmanuelle Norguet, Marine Gilabert, Jean-Robert Delpero, Julie Roques, Ezequiel Calvo, Fabienne Guillaumond, Sophie Vasseur, Raul Urrutia, Aurelien de Reynies, Nelson Dusetti, Juan Iovanna. Multiomics assessment of the cancer and stromal compartments of patient-derived pancreatic xenografts reveals clinically-relevant subtypes and novel targeted therapies [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 4396. doi:10.1158/1538-7445.AM2017-4396

Abstract B72: Pancreatic cancer cell drives stroma composition

The extensive desmoplasia in pancreatic ductal adenocarcinoma (PDAC) has raised major interrogations on its role and function in the carcinogenic process. Patient-derived xenograft (PDX) offers an ideal setting to distinguish and to study the interactions between the cancerous epithelial cells and its stroma. Indeed, sequencing profiles of a mix of cancerous/Human and stroma/Mouse cells can be analyzed separately in silico by unambiguously assigning each sequence to the human or mouse genome. Using RNA sequencing, we profiled 30 pancreatic tumor PDXs and extracted the transcriptome profiles of epithelial cancerous cells as well as their corresponding stroma. On average, 70% of RNA sequencing reads were specifically attributed to a human origin, and therefore an epithelial origin, while 22% of RNA sequencing reads were mouse-specific. Using the rate of mouse sequences as a surrogate of the proportion of non-transformed cells, we observe a high variability in the infiltration level from 7% to 60%. The estimation was also consistent in whole exome sequencing (using the same sequencing process) and with the histological quantification of fibrotic tissue. By specifically analyzing the gene expression in mouse-stromal cells, we show that their transcriptomic profile is consistent with the recent description of human PDAC in situ tumors with high levels of genes of the reported activated-stroma and normal-stroma signatures. We also show that stromal cells over-express genes involved in the SLIT/ROBO axon guidance signalling pathway, in angiogenesis as well as a large number of collagens, cytokines and ligands associated with growth and developmental pathways. Recent studies identified two major subtypes of PDAC from transcriptomic analysis: a well differentiated, often referred as classical, and an undifferentiated, previously recognized as Basal, Quasi-Mesenchymal or Squamous. The stroma characterized in this work broadly reflects this heterogeneity with stromal gene expression signatures predictive of each subtype. For instance, collagens are significantly over-expressed in the stroma of squamous tumors. The concomitant analysis of transcriptomic profiles of both subtypes shows potential cross-talks between cancerous and stromal cells. Particularly in Squamous tumors, genes implicated in the axon-guidance and Wnt pathways are significantly upregulated in both, stroma and transformed cells. On the other hand, the stroma and transformed cells of Classical tumors shows an upregulation of complementary genes associated with several metabolic pathways. Taken together, our transcriptomic analysis reveals that human transformed pancreatic cells determine the composition, quantitatively and qualitatively, of stroma mouse cells in a PDX model. This model also reveals a broad variability of PDAC stromas and highlights potential cross-talks between them through known and novel pathways. Citation Format: Remy Nicolle, Yuna Blum, Laetitia Marisa, Jonathan Garnier, Benjamin Bian, Celine Loncle, Martin Bigonnet, Odile Gayet, Vincent Moutardier, Pauline Duconseil, Mohamed Gasmi, Mehdi Ouaissi, Olivier Turrini, Marc Giovannini, Aurelie Maignan, Jean-Marie Boher, Jacques Ewald, Erwan Bories, Marc Barthet, Anthony Goncalves, Flora Poizat, Jean-Luc Raoul, Veronique Secq, Stephane Garcia, Philippe Grandval, Marine Barraud-Blanc, Emmanuelle Norguet, Marine Gilabert, Jean-Robert Delpero, Ezequiel Calvo, Aurelien de Reynies, Juan Iovanna, Nelson Dusetti.{Authors}. Pancreatic cancer cell drives stroma composition. [abstract]. In: Proceedings of the AACR Special Conference on Pancreatic Cancer: Advances in Science and Clinical Care; 2016 May 12-15; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2016;76(24 Suppl):Abstract nr B72.

Abstract A48: Multi-omics characterization of PDAC subtypes using PDX reveals that epigenetic but not genetic analysis permit a clinically relevant classification

Genome-wide molecular profiles have been proven to be beneficial for the identification of clinically relevant tumor subtypes in many neoplastic diseases. While pancreatic ductal adenocarcinoma (PDAC) is the fourth leading cause of cancer-related death, very few genomic and transcriptomic studies have been conducted. This is mainly due to the difficulty to obtain a suitable cohort of PDAC tumor samples. The major obstacle is the usually high proportion of non-transformed stromal cells, which can greatly hinder the analysis of carcinogenic-specific processes. Moreover, tumor cohorts requiring resection samples can be biased by the exclusion of inoperable patients, representing 85% of all patients presenting PDAC. In this study, we generated Patient Derived Xenografts (PDX) with samples collected from 29 patients using either Endoscopic Ultrasound-Guided Fine-Needle Aspirates or, for operable patients, resections. The transcriptomic profiles, of both mRNA and miRNA, and the epigenetic landscape of early PDX passages consistently identified two tumor-specific molecular subtypes: a well differentiated group often referred to as classical, and an undifferentiated group previously recognized as Basal, Quasi-Mesenchymal or Squamous. Of all the genetic alterations determined by Copy Number analysis and exome sequencing, none were specific to any of the two subtypes, which therefore could not be discriminated solely on genetic basis. These two PDAC subtypes are characterized by distinct epigenetic and transcriptomic profiles of which the analysis revealed the deregulation of several pathways previously imputed in PDAC development and carcinogenesis in general. In particular, we showed that the Wnt pathway as well as several metabolic pathways, including cytochrome P450 genes recently implicated in drug resistance, are both epigenetically and transcriptionally deregulated. Altogether, our results provide new insights on pancreatic carcinogenesis and suggest that PDAC phenotypical heterogeneity is mainly driven by epigenetic rather than genetic events. Citation Format: Remy Nicolle, Yuna Blum, Laetitia Marisa, Jonathan Garnier, Benjamin Bian, Celine Loncle, Martin Bigonnet, Odile Gayet, Vincent Moutardier, Pauline Duconseil, Mohamed Gasmi, Mehdi Ouaissi, Olivier Turrini, Marc Giovannini, Aurelie Maignan, Jean-Marie Boher, Jacques Ewald, Erwan Bories, Marc Barthet, Anthony Goncalves, Flora Poizat, Jean-Luc Raoul, Veronique Secq, Stephane Garcia, Philippe Grandval, Marine Barraud-Blanc, Emmanuelle Norguet, Marine Gilabert, Jean-Robert Delpero, Ezequiel Calvo, Aurelien de Reynies, Nelson Dusetti, Juan Iovanna.{Authors}. Multi-omics characterization of PDAC subtypes using PDX reveals that epigenetic but not genetic analysis permit a clinically relevant classification. [abstract]. In: Proceedings of the AACR Special Conference on Pancreatic Cancer: Advances in Science and Clinical Care; 2016 May 12-15; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2016;76(24 Suppl):Abstract nr A48.