Pancreatic cancer survival analysis defines a signature that predicts outcome

被引:58
作者
Raman, Pichai [1 ,2 ,3 ]
Maddipati, Ravikanth [4 ]
Lim, Kian Huat [2 ,5 ]
Tozeren, Aydin [1 ]
机构
[1] Drexel Univ, Sch Biomed Engn Sci & Hlth Syst, Philadelphia, PA 19104 USA
[2] Childrens Hosp Philadelphia, Dept Biomed & Hlth Informat, Philadelphia, PA 19104 USA
[3] Childrens Hosp Philadelphia, Ctr Data Driven Discovery Biomed, Philadelphia, PA 19104 USA
[4] Univ Penn, Dept Med, Perelman Sch Med, Div Gastroenterol, Philadelphia, PA 19104 USA
[5] Stoke Therapeut Inc, Bedford, MA USA
来源
PLOS ONE | 2018年 / 13卷 / 08期
关键词
DUCTAL ADENOCARCINOMA; VASCULAR INVASION; LUNG-CANCER; TUMOR; EXPRESSION; GENE; ADRENOMEDULLIN; RESISTANCE; PROGNOSIS; SUBTYPES;
D O I
10.1371/journal.pone.0201751
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
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.
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页数:18
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