A Pan-cancer Analysis Reveals the Tissue Specificity and Prognostic Impact of Angiogenesis-associated Genes in Human Cancers

Author:

Bao Zhenshen12,Liao Minzhen1,Dong Wanqi3,Huo Yanhao1,Li Xianbin1,Xu Peng12,Liu Wenbin14

Affiliation:

1. Institute of Computational Science and Technology, Guangzhou University, Guangzhou, 510006, Guangdong, China

2. School of Computer Science of Information Technology, Qiannan Normal University for Nationalities, Duyun, 558000, Guizhou, China

3. School of Education (Teachers College), Guangzhou University, Guangzhou, 510006, Guangdong, China

4. Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangzhou, 510080, Guangdong, China

Abstract

Introduction: Angiogenesis is one of the hallmarks of cancer and can impact the processes of cancer initiation, progression, and response to therapy. Background: Anti-angiogenic therapy is thus an encouraging therapeutic option to treat cancers, but the detailed angiogenic mechanisms and the association between angiogenesis and clinical outcome remain unknown in different cancers. Methods: Here, we systematically assess the impacts of 82 angiogenesis-associated genes (AAGs) in tumor tissue specificity and prognosis across 16 cancer types. Results: Results demonstrate that the expression patterns of the 82 AAGs can reflect the tumor tissue specificity, and high expressions of up-regulated AAGs are significantly associated with poor prognosis of cancer. We further define a prognostic score for predicting overall survival (OS) based on the expressions of up-regulated AAGs and confirm its reliable predictive ability. Results indicate that a low prognostic score demonstrates a superior OS and vice versa. Conclusion: The results of this study will contribute to the understanding of different tumor angiogenesis mechanisms in various tissues and cancer-personalized anti-angiogenic treatment. The code of our analysis can be accessed at https://github.com/ZhenshenBao/AAGs_analysis.git.

Funder

National Natural Science Foundation of China

Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application

Publisher

Bentham Science Publishers Ltd.

Subject

Computational Mathematics,Genetics,Molecular Biology,Biochemistry

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