Abstract B57: Early-onset pancreatic ductal adenocarcinomas are characterized by a distinct mutational landscape
Notice bibliographique
Résumé
Abstract Background: Advanced pancreatic ductal adenocarcinoma (PDAC) remains a leading cause of cancer-related mortality. There has been a rising incidence of early-onset pancreatic cancer (EOPC; ≤55 years). Reported treatment and survival outcomes in EOPC remain limited and have only been reported in the pre-FOLFIRINOX era. We characterized the genomic and transcriptomic landscapes of EOPC, while also leveraging provincial health data to investigate survival outcomes in advanced EOPC in a separate dataset. Methods: We generated a comprehensive and integrative dataset utilizing RNA-seq data and matched clinical metadata for 402 PDAC patients across 5 distinct studies and 4 sequencing centers, encompassing both resectable (ICGC, TCGA) and advanced (Personalized OncoGenomics and COMPASS) disease. 345 (85.8%) and 371 (92.3%) of samples had SNV/indel and CNV data available, respectively. Patients were stratified into EOPC (n=96), average-onset pancreatic cancer (AOPC, ≥70 years; n=121), and intermediate (>55 and <70 years; n=185) groups. Batch correction was performed on RNA-seq data using an Empirical Bayes approach and verified by principal components analysis. Mutation enrichment and differential gene expression analyses were conducted using Fisher’s exact test and Spearman correlation, respectively. All significance values were corrected for multiple comparisons using the Benjamini-Hochberg procedure. Survival analysis in a separate provincial dataset was conducted using 676 patients who received systemic therapy between January 2012-December 2015 across 6 cancer centers in British Columbia, Canada. Kaplan-Meier survival analysis was performed to compare overall survival (OS) between EOPC (n=102) vs. AOPC (n=239) vs. intermediate (n=335). Results: CDKN2A SNV/indels were identified in 22% and 26% of intermediate and AOPC patients, and in only 7% of EOPC patients (p<0.01). SNV/indels in epigenetic modifiers KMT2C/D trended towards lower frequency in EOPC (4% and 5%, respectively) compared to intermediate (13% and 13%) and AOPC (13% and 13%), although these observations did not pass multiple test correction (p=0.09, 0.20). Differential expression analysis and subsequent gene set enrichment analysis revealed EOPC-specific upregulation of genes belonging to pathways related to synaptic signal transduction. In a separate analysis of provincial data for survival outcomes, median OS revealed improved outcomes in EOPC compared to AOPC and intermediate groups (10.9, 7.5, and 8.3 months respectively, p=0.002). Conclusions: Using an extensive PDAC sequencing dataset, we highlight a novel association between CDKN2A SNV/indel frequency and EOPC. Transcriptome-based analysis identified significant associations between age of onset and expression of synaptic signal transduction pathways. Collectively, these data indicate potential age-specific differences in the mutational and developmental trajectories of PDAC and generate novel hypotheses for further study of EOPC. Citation Format: Erica S. Tsang, James T. Topham, Joanna M. Karasinska, Michael K.C. Lee, Shehara Mendis, Luka Culibrk, Robert Denroche, Gun Ho Jang, Steve E. Kalloger, Richard A. Moore, Andrew J. Mungall, Janessa Laskin, Grainne M. O'Kane, Jennifer J. Knox, Steven Gallinger, Steven J. Jones, Marco A. Marra, Jonathan M. Loree, David F. Schaeffer, Daniel J. Renouf. Early-onset pancreatic ductal adenocarcinomas are characterized by a distinct mutational landscape [abstract]. In: Proceedings of the AACR Special Conference on Pancreatic Cancer: Advances in Science and Clinical Care; 2019 Sept 6-9; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2019;79(24 Suppl):Abstract nr B57.
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 | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 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 ».