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pmid:36479101

The role of Angiogenesis and remodeling (AR) associated signature for predicting prognosis and clinical outcome of immunotherapy in pan-cancer.

Xiaojiao Sun · Zhuo Zhang · Zhiqi Wang · Ran Xie · Chuxiao Yi · Huiyu Liu · Xiaowei Chi · Tiancheng Li · Haitao Liu · Yi Han · Xiaocong Pang · Yimin Cui · Zhenming Liu

Frontiers in immunology · 2022 doi:10.3389/fimmu.2022.1033967

Paper

complete

Experiment

complete

Data

partial

Analysis

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Execution

absent

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Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
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title
The role of Angiogenesis and remodeling (AR) associated signature for predicting prognosis and clinical outcome of immunotherapy in pan-cancer.
doi
10.3389/fimmu.2022.1033967
pmid
36479101
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[0]
Xiaojiao Sun
[1]
Zhuo Zhang
[2]
Zhiqi Wang
[3]
Ran Xie
[4]
Chuxiao Yi
[5]
Huiyu Liu
[6]
Xiaowei Chi
[7]
Tiancheng Li
[8]
Haitao Liu
[9]
Yi Han
[10]
Xiaocong Pang
[11]
Yimin Cui
[12]
Zhenming Liu
journal
Frontiers in immunology
year
2022
abstract
Background: Angiogenesis and remodeling (AR) is necessary for the growth and metastasis of cancers. Although AR related genes involved in this process are reported, the correlation between AR and clinical outcome, immune cell infiltration, and immunotherapy is still unknown in diverse cancers. This study aimed to investigate the role of AR in the tumor immune microenvironment (TIME) in pan-cancer, and explore its values in prognostic prediction and therapeutic responses. Methods: Firstly, AR genes (including angiogenesis genes and blood vessel remodeling genes) are collected from MsigDB database. The differential expression, and prognostic value of AR genes were studied in 33 tumor types based on TCGA and GTEx data. The AR score of each sample was calculated using the "ssGSEA" function of R package "GSVA" in pan-cancer. The correlation of the AR score with TIME index, such as the amount of stromal and immune components and the immune cell infiltration, was evaluated via integrating multiple computational methods. And we also utilized IMvigor210 and GSE78220 data to explore the prediction value of the AR score on the immunotherapy response. Results: Significant differences in AR gene expression between tumors and adjacent normal tissues were found in most cancer types. The AR score varied depending on the types of tumors, and high score was related to worse survival in various tumors, such as pancreatic and stomach adenocarcinoma and so on. Moreover, the AR score was further explored to be positively correlated with proportions and pathways of immune and stromal in TIME. And the AR score was positively correlated with immunosuppressive cells, including TAMs and iTregs, while negatively with CD8+ T cells. Further analysis revealed that patients with high AR had worse therapy efficacy and survival status in bladder cancer and melanomas. Conclusions: Our systematic analysis revealed that AR is closely associated TIME, and prognosis, and clinical characteristics in multiple cancers. Targeting AR genes may activate immune microenvironment and increase the efficacy of immunotherapy.
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R package “survminer” and “survival” were used to perform the Univariate Cox regression (uniCox) and Kaplan-Meier analyses to explore the relationship of AR score with the survival of patients, including overall survival (OS), disease specific survival (DSS), disease free interval (DFI) and progression free interval (PFI).
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AR is closely associated with the tumor immune microenvironment, prognosis, and clinical characteristics in multiple cancers.
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Although AR related genes involved in this process are reported, the correlation between AR and clinical outcome, immune cell infiltration, and immunotherapy is still unknown in diverse cancers. This study aimed to investigate the role of AR in the tumor immune microenvironment (TIME) in pan-cancer, and explore its values in prognostic prediction and therapeutic responses.\nMethods: Firstly, AR genes (including angiogenesis genes and blood vessel remodeling genes) are collected from MsigDB database. The differential expression, and prognostic value of AR genes were studied in 33 tumor types based on TCGA and GTEx data. The AR score of each sample was calculated using the \"ssGSEA\" function of R package \"GSVA\" in pan-cancer. The correlation of the AR score with TIME index, such as the amount of stromal and immune components and the immune cell infiltration, was evaluated via integrating multiple computational methods. 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