A robust 6-mRNA signature for prognosis prediction of pancreatic ductal adenocarcinoma

Abstract

Pancreatic ductal adenocarcinoma (PDAC) is one of the most fatal malignancies worldwide. PDAC prognostic and diagnostic biomarkers are still being explored. The aim of this study is to establish a robust molecular signature that can improve the ability to predict PDAC prognosis. 155 overlapping differentially expressed genes between tumor and non-tumor tissues from three Gene Expression Omnibus (GEO) datasets were explored. A least absolute shrinkage and selection operator method (LASSO) Cox regression model was employed for selecting prognostic genes. We developed a 6-mRNA signature that can distinguish high PDAC risk patients from low risk patients with significant differences in overall survival (OS). We further validated this signature prognostic value in three independent cohorts (GEO batch, P < 0.0001; ICGC, P = 0.0036; Fudan, P = 0.029). Furthermore, we found that our signature remained significant in patients with different histologic grade, TNM stage, locations of tumor entity, age and gender. Multivariate cox regression analysis showed that 6-mRNA signature can be an independent prognostic marker in each of the cohorts. Receiver operating characteristic curve (ROC) analysis also showed that our signature possessed a better predictive role of PDAC prognosis. Moreover, the gene set enrichment analysis (GSEA) analysis showed that several tumorigenesis and metastasis related pathways were indeed associated with higher scores of risk. In conclusion, identifying the 6-mRNA signature could provide a valuable classification method to evaluate clinical prognosis and facilitate personalized treatment for PDAC patients. New therapeutic targets may be developed upon the functional analysis of the classifier genes and their related pathways.

Construction of a 6-gene prognostic signature to assess prognosis of patients with pancreatic cancer

“…Establishing gene scoring models contribute to quantify the prognostic evaluation criteria and increasing studies have performed successful precedents in this regard. [ 12 , 15 , 16 ] Our current study established a six-gene prognosis predictive model in patients with PaCa and validated the prognostic value of this model in total PaCa patients and several subgroups, confirming that the six-gene prognosis model could exactly predict the OS of patients with PaCa.…”

Development and validation of a metastasis-related Gene Signature for predicting the Overall Survival in patients with Pancreatic Ductal Adenocarcinoma

“…By utilizing public databases, such as TCGA and GEO, multiple prediction models based on gene expression have been established that can reliably predict prognosis of PDAC patients following surgical resection and reflect the biological behavior of the disease [5,6]. Recently, Zhou C et al established a robust six-gene signature to predict the OS of PDAC through comprehensive mining of OS-related DEGs [7]. Rigorous validations revealed that the proposed gene signature was able to distinguish high-risk and low-risk patients with significantly different OS.…”

Development and validation of a cancer stem cell-related signature for prognostic prediction in pancreatic ductal adenocarcinoma

“…In recent years, progress in next-generation sequencing technologies has allowed researchers to establish several prognostic signatures for PDAC [ 17 – 22 ]. All of these models have robust predictive ability, but they are not accurate enough, as most of them are derived from the single TCGA-PAAD dataset.…”