Development of a Transcription Factor-Based Prognostic Model for Predicting the Immune Status and Outcome in Pancreatic Adenocarcinoma

Author:

Zhang Xianbin123ORCID,Li Li1ORCID,Liu Peng1ORCID,Tian Yu14ORCID,Gong Peng13ORCID

Affiliation:

1. Department of General Surgery & Institute of Precision Diagnosis and Treatment of Gastrointestinal Tumors, Shenzhen University General Hospital & Shenzhen University Clinical Medical Academy, Xueyuan Road 1098, 518055 Shenzhen, China

2. Guangdong Provincial Key Laboratory for Biomedical Measurements and Ultrasound Imaging, School of Biomedical Engineering, Shenzhen University Health Science Center, Xueyuan Road 1066, 518060 Shenzhen, China

3. Carson International Cancer Center & Guangdong Provincial Key Laboratory of Regional Immunity and Diseases, Shenzhen University Health Science Center, Xueyuan Road 1066, 518060 Shenzhen, China

4. Department of Epidemiology, Dalian Medical University, Lvshun Road 9, 116044 Dalian, China

Abstract

Pancreatic adenocarcinoma (PAAD) is the most common primary malignancy of the pancreas. Growing studies indicate that transcription factors (TFs) are abnormally expressed in PAAD. We, therefore, aimed to evaluate the effect of TFs in PAAD and develop a TF-based prognostic signature for the patients. The expression of the TFs and the clinical characteristics were obtained from TCGA datasets. The levels of the TFs were evaluated in PAAD tissues or nontumor tissues. Kyoto Encyclopedia of Genes and Genomes (KEGG) was used to determine the potential function of the dysregulated TFs. To create a prognostic signature, we used univariate and multivariate Cox regression. In addition, the relationship between risk score and tumor microenvironment was analyzed. In this study, we observed 19 increased and 10 decreased TFs in PAAD tissues. KEGG assays indicated that dysregulated TFs were involved in transcriptional misregulation in cancer. Multivariate Cox analysis identified two prognostic factors, Zinc finger protein 488 and BCL11A; and we developed a risk score model by these two factors. The Kaplan-Meier estimator suggested that patients with high risk exhibited a shorter overall survival than those with low risk. The receiver operating characteristic curve proved that the accuracy of this prognostic signature was 0.686 in predicting the 5-year survival. In addition, we observed that the high score was distinctly related to advanced tumor stage and immune infiltrates. Taken together, we developed a novel TF-related model which could be applied as a potential prognostic tool for PAAD and may guide the choice of immunotherapies.

Funder

Shenzhen Science and Technology Innovation Commission

Publisher

Hindawi Limited

Subject

Immunology,General Medicine,Immunology and Allergy

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