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Pancreatic cancer survival analysis defines a signature that predicts outcome.
- Source :
-
PloS one [PLoS One] 2018 Aug 09; Vol. 13 (8), pp. e0201751. Date of Electronic Publication: 2018 Aug 09 (Print Publication: 2018). - Publication Year :
- 2018
-
Abstract
- Pancreatic ductal adenocarcinoma (PDAC) is the third leading cause of cancer death in the US. Despite multiple large-scale genetic sequencing studies, identification of predictors of patient survival remains challenging. We performed a comprehensive assessment and integrative analysis of large-scale gene expression datasets, across multiple platforms, to enable discovery of a prognostic gene signature for patient survival in pancreatic cancer. PDAC RNA-Sequencing data from The Cancer Genome Atlas was stratified into Survival+ (>2-year survival) and Survival-(<1-year survival) cohorts (n = 47). Comparisons of RNA expression profiles between survival groups and normal pancreatic tissue expression data from the Gene Expression Omnibus generated an initial PDAC specific prognostic differential expression gene list. The candidate prognostic gene list was then trained on the Australian pancreatic cancer dataset from the ICGC database (n = 103), using iterative sampling based algorithms, to derive a gene signature predictive of patient survival. The gene signature was validated in 2 independent patient cohorts and against existing PDAC subtype classifications. We identified 707 candidate prognostic genes exhibiting differential expression in tumor versus normal tissue. A substantial fraction of these genes was also found to be differentially methylated between survival groups. From the candidate gene list, a 5-gene signature (ADM, ASPM, DCBLD2, E2F7, and KRT6A) was identified. Our signature demonstrated significant power to predict patient survival in two distinct patient cohorts and was independent of AJCC TNM staging. Cross-validation of our gene signature reported a better ROC AUC (≥ 0.8) when compared to existing PDAC survival signatures. Furthermore, validation of our signature through immunohistochemical analysis of patient tumor tissue and existing gene expression subtyping data in PDAC, demonstrated a correlation to the presence of vascular invasion and the aggressive squamous tumor subtype. Assessment of these genes in patient biopsies could help further inform risk-stratification and treatment decisions in pancreatic cancer.<br />Competing Interests: The authors have declared that no competing interests exist. While K.H.L is currently employed by Stoke Therapeutics, his contributions occurred entirely during his time at Drexel University. This does not alter the authors' adherence to PLOS ONE policies on sharing data and materials.
- Subjects :
- Aged
Algorithms
Biomarkers, Tumor genetics
Biomarkers, Tumor metabolism
Carcinoma, Pancreatic Ductal genetics
Carcinoma, Pancreatic Ductal pathology
Cohort Studies
DNA Methylation
Female
Gene Expression Regulation, Neoplastic
Humans
Immunohistochemistry
Male
Microarray Analysis
Middle Aged
Models, Biological
Pancreas pathology
Pancreatic Neoplasms genetics
Pancreatic Neoplasms pathology
Prognosis
Sequence Analysis, RNA
Survival Analysis
Carcinoma, Pancreatic Ductal metabolism
Carcinoma, Pancreatic Ductal mortality
Pancreas metabolism
Pancreatic Neoplasms metabolism
Pancreatic Neoplasms mortality
Subjects
Details
- Language :
- English
- ISSN :
- 1932-6203
- Volume :
- 13
- Issue :
- 8
- Database :
- MEDLINE
- Journal :
- PloS one
- Publication Type :
- Academic Journal
- Accession number :
- 30092011
- Full Text :
- https://doi.org/10.1371/journal.pone.0201751