Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2021 May 7:2021:6663990.
doi: 10.1155/2021/6663990. eCollection 2021.

Abnormal Expression and Prognostic Significance of Bone Morphogenetic Proteins and Their Receptors in Lung Adenocarcinoma

Zhixiao Xu  1 , Chengshui Chen  1   2
Affiliations

Abnormal Expression and Prognostic Significance of Bone Morphogenetic Proteins and Their Receptors in Lung Adenocarcinoma

Zhixiao Xu et al. Biomed Res Int. .

Abstract

Background: Lung adenocarcinoma (LUAD) is one of the most life-threatening malignancies. The crucial role of bone morphogenetic protein (BMP)/BMP receptors reveals the significance of exploring BMP protein-related prognostic predictors in LUAD.

Methods: The mRNA expression of BMPs/BMP receptors was investigated in LUAD and normal lung tissues. Gene Ontology and the Kyoto Encyclopedia of Genes and Genomes pathway analyses were performed, and the prognostic values were assessed by Kaplan-Meier Plotter. Univariate and multivariate Cox regression analyses were executed to ascertain the correlation between overall survival (OS) and the mRNA expression of BMPs/BMP receptors. The receiver operating characteristic (ROC) curves were implemented to evaluate the predictive power of the prognostic model. Then, the prognostic model was validated in the GEO cohort. Furthermore, a nomogram comprising the prognostic model was established.

Results: The mRNA expression of BMP2/5/6/R2, ACVRL1, and TGFBR2/3 was lower in LUAD tissues than in normal lung tissues. High expression of BMP2/4/5/R1A/R2, ACVR1/2A/L1, and TGFBR1/3 was associated with better OS, while BMP7 and ACVR1C/2B were associated with poorer OS. Three genes (BMP5, BMP7, and ACVR2A) were screened by univariate and multivariate Cox regression analyses to develop the prognostic model in TCGA. Significantly better survival was observed in LUAD patients with a low-risk score than those with a high-risk score. The ROC curves confirmed the good performance of the prognostic model, then, the prognostic model was validated in the GSE31210 dataset. A nomogram was constructed (AUCs>0.7). And hub genes were further evaluated, including gene set enrichment analysis and immune cell infiltration.

Conclusions: BMP5, BMP7, and ACVR2A are potential therapeutic targets in LUAD. The three-gene prognostic model and the nomogram are reliable tools for predicting the OS of LUAD patients.

PubMed Disclaimer

Conflict of interest statement

The authors declare no potential conflicts of interest.

Figures

Figure 1
Figure 1
Changes in BMPs/BMP receptors expression according to various clinical characteristics. Differentially expressed BMPs/BMP receptors according to age (a), sex (b), race (c), smoke (d), EGFR mutation (e), gross pathology (f), stage (g), tumor size (h), lymph node metastasis (i), and distant metastasis (j). BMP: bone morphogenetic protein. Note: ns: P > 0.05; ∗: P ≤ 0.05; ∗∗: P ≤ 0.01; ∗∗∗: P ≤ 0.001; ∗∗∗∗: P ≤ 0.0001.
Figure 2
Figure 2
The functional annotation of BMPs/BMP receptors. (a) The Gene Ontology analysis according to the biological process, cellular component, and molecular function. (b) The Kyoto Encyclopedia of Genes and Genomes analysis of BMPs/BMP receptors. BMP: bone morphogenetic protein.
Figure 3
Figure 3
K-M and time-dependent ROC curves for the prognostic model in the TCGA-LUAD cohort (a) and the GEO-LUAD cohort (b). The K-M survival curves showed the overall survival based on the relatively high- and low-risk patients classified by the optimal cut-off value. The time-dependent ROC curve analyses of survival prediction by the prognostic model. LUAD: lung adenocarcinoma; ROC: receiver operating characteristic.
Figure 4
Figure 4
The nomogram to anticipate prognostic probabilities in LUAD. (a) Univariate and multivariate association of the three-gene prognostic model and clinical characteristics with overall survival. Red represented statistical significance, and blue represented no statistical significance. (b) Nomogram predicting 1-, 3-, and 5-year OS for LUAD patients. The nomogram was applied by adding up the points identified on the point scale of each variable. The total points projected on the bottom scales indicate the probability of 1-, 3-, and 5-year OS. (c) The calibration curve for predicting 1-, 3-, and 5-y OS of LUAD patients. (d) The DCA curves could intuitively evaluate the clinical benefit of the nomogram and the scope of application of the nomogram to obtain clinical benefits. (e) Time-dependent ROC curve analysis evaluated the accuracy of the nomograms. LUAD: lung adenocarcinoma; OS: overall survival; DCA: decision curve analysis.
Figure 5
Figure 5
Gene set enrichment analysis (GSEA) of BMP5 (a), BMP7 (b), and ACVR2A (c) showing the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. BMP: bone morphogenetic protein; ACVR2A: activin receptor A type IIA.
Figure 6
Figure 6
Association of BMP5 (a), BMP7 (b), and ACVR2A (c) expression with immune cell infiltration in LUAD. BMP: bone morphogenetic protein; ACVR2A: activin receptor A type IIA; LUAD: lung adenocarcinoma.
See this image and copyright information in PMC

References

    1. Bray F., Ferlay J., Soerjomataram I., Siegel R. L., Torre L. A., Jemal A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA: a Cancer Journal for Clinicians. 2018;68(6):394–424. doi: 10.3322/caac.21492. - DOI - PubMed
    1. Barlesi F., Mazieres J., Merlio J. P., et al. Routine molecular profiling of patients with advanced non-small-cell lung cancer: results of a 1-year nationwide programme of the French Cooperative Thoracic Intergroup (IFCT) Lancet (London, England) 2016;387(10026, article 10026):1415–1426. doi: 10.1016/S0140-6736(16)00004-0. - DOI - PubMed
    1. Travis W. D., Brambilla E., Nicholson A. G., et al. The 2015 World Health Organization classification of lung tumors: impact of genetic, clinical and radiologic advances since the 2004 classification. Journal of thoracic oncology. 2015;10(9):1243–1260. doi: 10.1097/JTO.0000000000000630. - DOI - PubMed
    1. Yang C. Y., Yang J. C., Yang P. C. Precision management of advanced non-small cell lung cancer. Annual Review of Medicine. 2020;71(1):117–136. doi: 10.1146/annurev-med-051718-013524. - DOI - PubMed
    1. Tsao A. S., Scagliotti G. V., Bunn P. A., Jr., et al. Scientific advances in lung cancer 2015. Journal of Thoracic Oncology. 2016;11(5):613–638. doi: 10.1016/j.jtho.2016.03.012. - DOI - PubMed

MeSH terms

LinkOut - more resources