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. 2021 Apr 1;21(1):146.
doi: 10.1186/s12876-021-01734-4.

Identification of the angiogenesis related genes for predicting prognosis of patients with gastric cancer

Sheng Zheng #  1   2 , Zizhen Zhang #  1   2 , Ning Ding  1   2 , Jiawei Sun  1   2 , Yifeng Lin  1   2 , Jingyu Chen  1   2 , Jing Zhong  1   2 , Liming Shao  1 , Zhenghua Lin  1   2 , Meng Xue  3   4
Affiliations

Identification of the angiogenesis related genes for predicting prognosis of patients with gastric cancer

Sheng Zheng et al. BMC Gastroenterol. .

Abstract

Introduction: Angiogenesis is a key factor in promoting tumor growth, invasion and metastasis. In this study we aimed to investigate the prognostic value of angiogenesis-related genes (ARGs) in gastric cancer (GC).

Methods: mRNA sequencing data with clinical information of GC were downloaded from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. The differentially expressed ARGs between normal and tumor tissues were analyzed by limma package, and then prognosis‑associated genes were screened using Cox regression analysis. Nine angiogenesis genes were identified as crucially related to the overall survival (OS) of patients through least absolute shrinkage and selection operator (LASSO) regression. The prognostic model and corresponding nomograms were establish based on 9 ARGs and verified in in both TCGA and GEO GC cohorts respectively.

Results: Eighty-five differentially expressed ARGs and their enriched pathways were confirmed. Significant enrichment analysis revealed that ARGs-related signaling pathway genes were highly related to tumor angiogenesis development. Kaplan-Meier analysis revealed that patients in the high-risk group had worse OS rates compared with the low-risk group in training cohort and validation cohort. In addition, RS had a good prognostic effect on GC patients with different clinical features, especially those with advanced GC. Besides, the calibration curves verified fine concordance between the nomogram prediction model and actual observation.

Conclusions: We developed a nine gene signature related to the angiogenesis that can predict overall survival for GC. It's assumed to be a valuable prognosis model with high efficiency, providing new perspectives in targeted therapy.

Keywords: Angiogenesis; Gastric cancer; Gene; Prognostic.

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Conflict of interest statement

None of the authors has any conflict of interest to disclose.

Figures

Fig. 1
Fig. 1
Differentially expressed ARGs between GC and normal gastric tissues. a The heatmap for the 338 ARGs from TCGA-STAD cohort; b volcano plot for screened ARGs
Fig. 2
Fig. 2
Functional enrichment analysis of differentially expressed ARGs. a Significantly enriched gene ontology (GO) terms of differentially expressed ARGs based on biological processes. b Significantly enriched of differentially expressed ARGs in GO terms based on cellular components and molecular functions. c The heatmap shows the LogFC values enriched by ARGs genes in different KEGG pathways. d Significantly enriched KEGG pathways of differentially expressed ARGs by Volcano
Fig. 3
Fig. 3
PPI network and module analysis. a The PPI network of all the differentially expressed ARGs visualized by Cytoscape. b Critical module 1 in PPI network. c Critical module 2 in PPI network
Fig. 4
Fig. 4
Establishment of ARGs prognostic model related to the prognosis of GC by lasso regression model. a LASSO coefficient profiles of the 18 ARGs. b A coefficient profile plot was generated against the log (lambda) sequence. c Univariate COX regression analysis for RS of GC patients in TCGA database. d Multivariate Cox regression analysis for RS of GC cancer patients in TCGA datasets
Fig. 5
Fig. 5
Development of RS based on the 9 ARGs signature of patients with GC in TCGA and GEO. a, b The RS distribution, vital status of patients and heatmap of the 9 ARGs expression profiles between high risk group and low risk group in training or validation group. c, e Kaplan–Meier analysis of the prognostic model in TCGA or GEO datasets. d, f Time-dependent ROC analysis showing the optimal AUC of the gene signature in the two cohorts
Fig. 6
Fig. 6
Stratified analysis of the relationship between RS score and survival rate of patients with gastric cancer in TCGA cohorts. a Age > 65 years and age ≤ 65 years. b female sex and male sex. c G1-2 and G3. d Stage I&II and stage II&III. e NO stage and N1-3 stage. (f) M0 stage and M1 stage
Fig. 7
Fig. 7
Nomogram for predicting of 1-, 3- and 5-year overall survival (OS) based on the nine ARGs signature. a A nomogram based on the risk scores, clinical stage and age of GC patients. b ROC analysis of the nomogram for predicting the 1-, 3- and 5-year OS. c Calibration curves of nomogram for survival prediction at 1-, 3- and 5-year
See this image and copyright information in PMC

References

    1. Bray F, Ferlay J, Soerjomataram I, et al. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2018;68(6):394–424. - PubMed
    1. Ilson DH. Angiogenesis in gastric cancer: hitting the target? Lancet. 2014;383(9911):4–6. doi: 10.1016/S0140-6736(13)61892-9. - DOI - PubMed
    1. Sisic L, Strowitzki MJ, Blank S, et al. Postoperative follow-up programs improve survival in curatively resected gastric and junctional cancer patients: a propensity score matched analysis. Gastric Cancer. 2018;21(3):552–568. doi: 10.1007/s10120-017-0751-4. - DOI - PubMed
    1. Sisic L, Blank S, Nienhuser H, et al. The postoperative part of perioperative chemotherapy fails to provide a survival benefit in completely resected esophagogastric adenocarcinoma. Surg Oncol. 2020;33:177–188. doi: 10.1016/j.suronc.2017.06.001. - DOI - PubMed
    1. Zhao L, Jiang L, He L, et al. Identification of a novel cell cycle-related gene signature predicting survival in patients with gastric cancer. J Cell Physiol. 2019;234(5):6350–6360. doi: 10.1002/jcp.27365. - DOI - PubMed

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