Dataset Information

Prognostic value of eight immune gene signatures in pancreatic cancer patients.

ABSTRACT:

Background

Pancreatic cancer is one of the most common malignant tumors of the digestive tract, and it has a poor prognosis. Traditional methods are not effective to accurately assess the prognosis of patients with pancreatic cancer. Immunotherapy is a new promising approach for the treatment of pancreatic cancer; however, some patients do not respond well to immunotherapy, which may be related to tumor microenvironment regulation. In this study, we use gene expression database to mine important immune genes and establish a prognostic prediction model for pancreatic cancer patients. We hope to provide a feasible method to evaluate the prognosis of pancreatic cancer and provide valuable targets for pancreatic cancer immunotherapy.

Results

We used univariate COX proportional hazard regression analysis, the least absolute shrinkage and selection operator, and multivariate COX regression analysis to screen 8 genes related to prognosis from the 314 immune-related genes, and used them to construct a new clinical prediction model in the TCGA pancreatic cancer cohort. Subsequently, we evaluated the prognostic value of the model. The Kaplan-Meier cumulative curve showed that patients with low risk scores survived significantly longer than patients with high risk scores. The area under the ROC curve (AUC value) of the risk score was 0.755. The univariate COX analysis showed that the risk score was significantly related to overall survival (HR 1.406, 95% CI 1.237-1.598, P?ConclusionsBased on the TCGA-PAAD cohort, we identified immune-related markers with independent prognostic significance, validated, and analyzed their biological functions, to provide a feasible method for the prognosis of pancreatic cancer and provide potentially valuable targets for pancreatic cancer immunotherapy.

SUBMITTER: Wang W

PROVIDER: S-EPMC7863419 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature

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Publications

Prognostic value of eight immune gene signatures in pancreatic cancer patients.

Wang Wenting W Xu Zhijian Z Wang Ning N Yao Ruyong R Qin Tao T Lin Hao H Yue Lu L

BMC medical genomics 20210205 1

<h4>Background</h4>Pancreatic cancer is one of the most common malignant tumors of the digestive tract, and it has a poor prognosis. Traditional methods are not effective to accurately assess the prognosis of patients with pancreatic cancer. Immunotherapy is a new promising approach for the treatment of pancreatic cancer; however, some patients do not respond well to immunotherapy, which may be related to tumor microenvironment regulation. In this study, we use gene expression database to mine i ...[more]

PMID: 33546693

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Project description:Hepatocellular carcinoma (HCC) is a global health challenge with an increasing incidence worldwide. Cancer-associated fibroblasts (CAFs) function critically in HCC initiation and development. However, the prognostic significance of CAF-related gene signatures in HCC remains unknown. Therefore, the specific functions of CAF-related genes in HCC were investigated to help develop potential therapeutic strategies. In this study, CAF-related genes were screened from three CAF-related gene sets. HCC data from the Gene Expression Omnibus (GEO) database was applied to verify the screened CAF-related genes. Cluster analysis was used to identify clusters based on the expression pattern of CAF-related genes and two identified clusters were found to have a significant difference in overall survival (OS) and progression free intervals (PFI). The prognosis of HCC patients was predicted using the prognostic risk score model developed based on HCC data from The Cancer Genome Atlas (TCGA) databases. High-risk group patients had a worse OS than those in low-risk group in TCGA. These results were validated in International Cancer Genome Consortium (ICGC) database. Moreover, combining the clinicopathological characteristics related to prognosis with the model, a nomogram was built for a more accurate prediction of OS of HCC patients. In addition, analyses of immune infiltration characteristics of tumor microenvironment (TME), chemosensitivity, and immunotherapy response were conducted to further evaluate the prognostic value of CAF-related genes. Patients with low-risk scores were found to have higher chemosensitivity to cisplatin, doxorubicin, and sorafenib. Individuals with high-risk scores were found with a higher expression of most immune checkpoints which indicated patients with high-risk scores may benefit more from treatment with immune checkpoint inhibitors. Furthermore, a correlation between immune infiltration characteristics of TME and patients with different risk levels was found. These findings provide a possibility for the further development of personalized treatments in HCC.

Dataset Information

Prognostic value of eight immune gene signatures in pancreatic cancer patients.

Background

Results

Publications

Prognostic value of eight immune gene signatures in pancreatic cancer patients.

Similar Datasets

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