Title:A Pan-cancer Analysis Reveals the Tissue Specificity and Prognostic Impact
of Angiogenesis-associated Genes in Human Cancers
Volume: 18
Issue: 8
Author(s): Zhenshen Bao, Minzhen Liao, Wanqi Dong, Yanhao Huo, Xianbin Li*, Peng Xu*Wenbin Liu*
Affiliation:
- Institute of Computational Science and Technology, Guangzhou University, Guangzhou, 510006, Guangdong, China
- Institute of Computational Science and Technology, Guangzhou University, Guangzhou, 510006, Guangdong, China
- School of Computer Science of Information Technology, Qiannan Normal University for Nationalities, Duyun, 558000,
Guizhou, China
- Institute of Computational Science and Technology, Guangzhou University, Guangzhou, 510006, Guangdong, China
- Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangzhou, 510080, Guangdong, China
Keywords:
Angiogenesis, AAGs, systematically, poor prognosis, overall survival, personalized.
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.