Development and validation of novel inflammatory response-related gene signature to predict prostate cancer recurrence and response to immune checkpoint therapy

Author:

Luo Yong1,Liu Xiaopeng2,Lin Jingbo1,Zhong Weide13456,Chen Qingbiao1

Affiliation:

1. Department of Urology, the Second People's Hospital of Foshan, Affiliated Foshan Hospital of Southern Medical University, Foshan, China

2. Department of Science and Teaching, the Second People's Hospital of Foshan, Affiliated Foshan Hospital of Southern Medical University, Foshan, China

3. Department of Urology, Guangdong Key Laboratory of Clinical Molecular Medicine and Diagnostics, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, China

4. Urology Key Laboratory of Guangdong Province, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, China

5. Guangdong Provincial Institute of Nephrology, Nanfang Hospital, Southern Medical University, Guangzhou, China

6. State Key Laboratory of Quality Research in Chinese Medicines, Macau University of Science and Technology, Macau, China

Abstract

<abstract> <p>The aim of this study is to construct an inflammatory response-related genes (IRRGs) signature to monitor biochemical recurrence (BCR) and treatment effects in prostate cancer patients (PCa). A gene signature for inflammatory responses was constructed on the basis of the data from the Cancer Genome Atlas (TCGA) database, and validated in external datasets. It was analyzed using receiver operating characteristic curve, BCR-free survival, Cox regression, and nomogram. Distribution analysis and external model comparison were utilized. Then, enrichment analysis, tumor mutation burden, tumor immune microenvironment, and immune cell infiltration signatures were investigated. The role of the signature in immunotherapy was evaluated. The expression patterns of core genes were verified by RNA sequencing. We identified an IRRGs signature in the TCGA-PRAD cohort and verified it well in two other independent external datasets. The signature was a robust and independent prognostic index for predicting the BCR of PCa. The high-risk group of our signature predicted a shortened BCR time and an aggressive disease progression. A nomogram was constructed to predict BCR-free time in clinical practices. Neutrophils and CD8+ T cells were in higher abundance among the low-risk individuals. Immune functions varied significantly between the two groups and immune checkpoint therapy worked better for the low-risk patients. The expression of four IRRGs showed significant differences between PCa and surrounding benign tissues, and were validated in BPH-1 and DU145 cell lines by RNA sequencing. Our signature served as a reliable and promising biomarker for predicting the prognosis and evaluating the efficacy of immunotherapy, facilitating a better outcome for PCa patients.</p> </abstract>

Publisher

American Institute of Mathematical Sciences (AIMS)

Subject

Applied Mathematics,Computational Mathematics,General Agricultural and Biological Sciences,Modeling and Simulation,General Medicine

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