Abstract B72: Pancreatic cancer cell drives stroma composition
Notice bibliographique
Résumé
Abstract 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: Rémy 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, Aurélie 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, Aurélien de Reyniès, 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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».