Abstract
ObjectiveGrowing evidence has highlighted that the immune and stromal cells that infiltrate in pancreatic cancer microenvironment significantly influence tumor progression. However, reliable microenvironment-related prognostic gene signatures are yet to be established. The present study aimed to elucidate tumor microenvironment-related prognostic genes in pancreatic cancer.MethodsWe applied the ESTIMATE algorithm to categorize patients with pancreatic cancer from TCGA dataset into high and low immune/stromal score groups and determined their differentially expressed genes. Then, univariate and LASSO Cox regression was performed to identify overall survival-related differentially expressed genes (DEGs). And multivariate Cox regression analysis was used to screen independent prognostic genes and construct a risk score model. Finally, the performance of the risk score model was evaluated by Kaplan-Meier curve, time-dependent receiver operating characteristic and Harrell’s concordance index.ResultsThe overall survival analysis demonstrated that high immune/stromal score groups were closely associated with poor prognosis. The multivariate Cox regression analysis indicated that the signatures of four genes, including TRPC7, CXCL10, CUX2, and COL2A1, were independent prognostic factors. Subsequently, the risk prediction model constructed by those genes was superior to AJCC staging as evaluated by time-dependent receiver operating characteristic and Harrell’s concordance index, and both KRAS and TP53 mutations were closely associated with high risk scores. In addition, CXCL10 was predominantly expressed by tumor associated macrophages and its receptor CXCR3 was highly expressed in T cells at the single-cell level.ConclusionsThis study comprehensively investigated the tumor microenvironment and verified immune/stromal-related biomarkers for pancreatic cancer.
Highlights
Pancreatic cancer is one of the most lethal solid tumors because of the lack of early diagnosis and rapid progression that lead to poor prognosis (Kamisawa et al, 2016)
The risk prediction model constructed by those genes was superior to AJCC staging as evaluated by time-dependent receiver operating characteristic and Harrell’s concordance index, and both KRAS and TP53 mutations were closely associated with high risk scores
CXCL10 was predominantly expressed by tumor associated macrophages and its receptor CXCR3 was highly expressed in T cells at the single-cell level
Summary
Pancreatic cancer is one of the most lethal solid tumors because of the lack of early diagnosis and rapid progression that lead to poor prognosis (Kamisawa et al, 2016). It has been ranked as the third leading cause of cancer-related death in the United States with a 5-year survival rate of < 10% (Siegel et al, 2018). Activated non-tumor cells, especially pancreatic stellate cells, produce much extracellular matrix proteins to create dense interstitial pressure that causes unavailability of nutrients and drugs (Sun et al, 2018; Thomas and Radhakrishnan, 2019). It is critical to understand the molecular composition and function of TME to predict the prognosis of patients with pancreatic cancer
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