ArticlePloS one2014
A thirteen-gene expression signature predicts survival of patients with pancreatic cancer and identifies new genes of interest.
Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.
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Who cites it
22 citing papers in PubMed, 1 synthesis or guideline pooled it, 36 citations in OpenAlex.
- Identification of a robust functional subpathway signature for pancreatic ductal adenocarcinoma by comprehensive and integrated analyses.Cell communication and signaling : CCS · 2020Pooled it
- Connectivity mapping-based identification of pharmacological inhibitor targeting HDAC6 in aggressive pancreatic ductal adenocarcinoma.NPJ precision oncology · 2024Article
- FASN multi-omic characterization reveals metabolic heterogeneity in pancreatic and prostate adenocarcinoma.Journal of translational medicine · 2023Article
- The Development of a Gleason Score-Related Gene Signature for Predicting the Prognosis of Prostate Cancer.Journal of clinical medicine · 2022Article
- Identification and verification of CCNB1 as a potential prognostic biomarker by comprehensive analysis.Scientific reports · 2022Article
- Deeper insights into long-term survival heterogeneity of pancreatic ductal adenocarcinoma (PDAC) patients using integrative individual- and group-level transcriptome network analyses.Scientific reports · 2022Article
- An Independent Prognostic Model Based on Ten Autophagy-Related Long Noncoding RNAs in Pancreatic Cancer Patients.Genetics research · 2022Article
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- Comprehensive Analysis of Immunoinhibitors Identifies LGALS9 and TGFBR1 as Potential Prognostic Biomarkers for Pancreatic Cancer.Computational and mathematical methods in medicine · 2020Article
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- Paxillin regulated genomic networks in prostate cancer.Steroids · 2019Article
- AreCancers · 2019Article
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- MetaGxData: Clinically Annotated Breast, Ovarian and Pancreatic Cancer Datasets and their Use in Generating a Multi-Cancer Gene Signature.Scientific reports · 2019Article
- Identification of Prognostic Biomarkers by Combined mRNA and miRNA Expression Microarray Analysis in Pancreatic Cancer.Translational oncology · 2018Article
- Article
- Cell-free DNA promoter hypermethylation in plasma as a predictive marker for survival of patients with pancreatic adenocarcinoma.Oncotarget · 2017Article
- Article
- Sex-Specific Associations between Particulate Matter Exposure and Gene Expression in Independent Discovery and Validation Cohorts of Middle-Aged Men and Women.Environmental health perspectives · 2017Article
- RNA sequencing of pancreatic adenocarcinoma tumors yields novel expression patterns associated with long-term survival and reveals a role for ANGPTL4.Molecular oncology · 2016Article
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Authors and funding
9 authors at 1 institution in 1 country.
Funding
Abstract
backgroundCurrently, prognostication for pancreatic ductal adenocarcinoma (PDAC) is based upon a coarse clinical staging system. Thus, more accurate prognostic tests are needed for PDAC patients to aid treatment decisions. METHODS AND
findingsAffymetrix gene expression profiling was carried out on 15 human PDAC tumors and from the data we identified a 13-gene expression signature (risk score) that correlated with patient survival. The gene expression risk score was then independently validated using published gene expression data and survival data for an additional 101 patients with pancreatic cancer. Patients with high-risk scores had significantly higher risk of death compared to patients with low-risk scores (HR 2.27, p = 0.002). When the 13-gene score was combined with lymph node status the risk-score further discriminated the length of patient survival time (p<0.001). Patients with a high-risk score had poor survival independent of nodal status; however, nodal status increased predictability for survival in patients with a low-risk gene signature score (low-risk N1 vs. low-risk N0: HR = 2.0, p = 0.002). While AJCC stage correlated with patient survival (p = 0.03), the 13-gene score was superior at predicting survival. Of the 13 genes comprising the predictive model, four have been shown to be important in PDAC, six are unreported in PDAC but important in other cancers, and three are unreported in any cancer.
conclusionsWe identified a 13-gene expression signature that predicts survival of PDAC patients and could prove useful for making treatment decisions. This risk score should be evaluated prospectively in clinical trials for prognostication and for predicting response to chemotherapy. Investigation of new genes identified in our model may lead to novel therapeutic targets.
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