Abstract
Background: Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive tumors with an extremely low 5-year survival rate. Accumulating evidence has unveiled that inflammatory response promotes tumor progression, enhances angiogenesis, and causes local immunosuppression. Herein, we aim to develop an inflammatory related prognostic signature, and found it could be used to predict gemcitabine response in PDAC. Methods: PDAC cohorts with mRNA expression profiles and clinical information were systematically collected from the four public databases. An inflammatory response related genes (IRRGs) prognostic signature was constructed by LASSO regression analysis. Kaplan–Meier survival analysis, receiver operating characteristic analysis, principal component analysis, and univariate and multivariate Cox analyses were carried out to evaluate effectiveness, and reliability of the signature. The correlation between gemcitabine response and risk score was evaluated in the TCGA-PAAD cohort. The GDSC database, pRRophetic algorithm, and connectivity map analysis were used to predict gemcitabine sensitivity and identify potential drugs for the treatment of PDAC. Finally, we analyzed differences in frequencies of gene mutations, infiltration of immune cells, as well as biological functions between different subgroups divided by the prognostic signature. Results: We established a seven IRRGs (ADM, DCBLD2, EREG, ITGA5, MIF, TREM1, and BTG2) signature which divided the PDAC patients into low- and high-risk groups. Prognostic value of the signature was validated in 11 PDAC cohorts consisting of 1337 PDAC patients from 6 countries. A nomogram that integrated the IRRGs signature and clinicopathologic factors of PDAC patients was constructed. The risk score showed positive correlation with gemcitabine resistance. Two drugs (BMS-536924 and dasatinib) might have potential therapeutic implications in high-risk PDAC patients. We found that the high-risk group had higher frequencies of KRAS, TP53, and CDKN2A mutations, increased infiltration of macrophages M0, neutrophils, and macrophages M2 cells, as well as upregulated hypoxia and glycolysis pathways, while the low-risk group had increased infiltration of CD8+ T, naïve B, and plasma and macrophages M1 cells. Conclusion: We constructed and validated an IRRGs signature that could be used to predict the prognosis and gemcitabine response of patients with PDAC, as well as two drugs (BMS-536924 and dasatinib) may contribute to PDAC treatment.
Highlights
Pancreatic cancer is a devastating digestive system malignant tumor characterized by limited treatment success and dismal prognosis
ADM, DCBLD2, EREG, ITGA5, MIF, MMP14, and TREM1 were associated with poor prognosis and significantly increased in tumor, while BTG2 was related to favorable prognosis and decreased in tumor (Figures 2B–E)
Our study found that high-risk Pancreatic ductal adenocarcinoma (PDAC) patients had significantly low response rate to gemcitabine than low-risk patients, indicating that our signature may be used for predicting gemcitabine response of PDAC patients
Summary
Pancreatic cancer is a devastating digestive system malignant tumor characterized by limited treatment success and dismal prognosis. It accounts for 466,003 deaths in 185 countries in 2020 and is the seventh leading cause of death from cancer in both genders (Sung et al, 2021). The prognostic prediction of PDAC mainly depends on tumor stage classified by the TNM staging system. This system is limited by the lack of consideration of the tumor biological heterogeneity at the molecular level. Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive tumors with an extremely low 5-year survival rate. We aim to develop an inflammatory related prognostic signature, and found it could be used to predict gemcitabine response in PDAC
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