Meta-Analysis of 1,200 Transcriptomic Profiles Identifies a Prognostic Model for Pancreatic Ductal Adenocarcinoma.
Journal
JCO clinical cancer informatics
ISSN: 2473-4276
Titre abrégé: JCO Clin Cancer Inform
Pays: United States
ID NLM: 101708809
Informations de publication
Date de publication:
05 2019
05 2019
Historique:
entrez:
10
5
2019
pubmed:
10
5
2019
medline:
17
6
2020
Statut:
ppublish
Résumé
With a dismal 8% median 5-year overall survival, pancreatic ductal adenocarcinoma (PDAC) is a highly lethal malignancy. Only 10% to 20% of patients are eligible for surgery, and more than 50% of these patients will die within 1 year of surgery. Building a molecular predictor of early death would enable the selection of patients with PDAC who are at high risk. We developed the Pancreatic Cancer Overall Survival Predictor (PCOSP), a prognostic model built from a unique set of 89 PDAC tumors in which gene expression was profiled using both microarray and sequencing platforms. We used a meta-analysis framework that was based on the binary gene pair method to create gene expression barcodes that were robust to biases arising from heterogeneous profiling platforms and batch effects. Leveraging the largest compendium of PDAC transcriptomic data sets to date, we show that PCOSP is a robust single-sample predictor of early death-1 year or less-after surgery in a subset of 823 samples with available transcriptomics and survival data. The PCOSP model was strongly and significantly prognostic, with a meta-estimate of the area under the receiver operating curve of 0.70 ( PCOSP could improve treatment decisions by identifying patients who will not benefit from standard surgery/chemotherapy but who may benefit from a more aggressive treatment approach or enrollment in a clinical trial.
Identifiants
pubmed: 31070984
doi: 10.1200/CCI.18.00102
doi:
Substances chimiques
Biomarkers, Tumor
0
Types de publication
Journal Article
Meta-Analysis
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM