Influence of Heparanase and VEGF-C mRNA Expressions in Lung Cancer

Yang, Yanling; Maimaitiyiming, Xiaokaiti; Jin, Chengyu; Ahan, Nuerlan; Guo, Rui; Peng, Chuanliang

doi:10.1007/s12262-015-1291-y

Cited by 3 publications

(2 citation statements)

References 10 publications

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“…These observations mean that the unstable expression of these genes can cause different oncological outcomes. VEGF-C has been widely reported in lung cancer and is involved in lung cancer tumourigenesis and associated with lymphatic metastasis; it can be used as a biomarker for evaluating recurrence and prognosis in non-small cell lung cancer [29]. ANGPTL4 (Tumour cell-derived human angiopoietin-like protein 4) can damage vascular endothelial cell junctions, increase pulmonary capillary permeability, and promote the process of tumour cells protruding through the vascular endothelium.…”

Section: Discussionmentioning

confidence: 99%

IRGS: an immune-related gene classifier for lung adenocarcinoma prognosis

Shi

Dong

et al. 2020

J Transl Med

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Background: Tumour cells interfere with normal immune functions by affecting the expression of some immunerelated genes, which play roles in the prognosis of cancer patients. In recent years, immunotherapy for tumours has been widely studied, but a practical prognostic model based on immune-related genes in lung adenocarcinoma comparable to existing model has not been established and reported. Methods: We first obtained publicly accessible lung adenocarcinoma RNA expression data from The Cancer Genome Atlas (TCGA) for differential gene expression analysis and then filtered immune-related genes based on the ImmPort database. By using the lasso algorithm and multivariate Cox Proportional-Hazards (CoxPH) regression analysis, we identified candidate genes for model development and validation. The robustness of the model was further examined by comparing the model with three established gene models. Results: Gene expression data from a total of 524 lung adenocarcinoma patients from TCGA were used for model development. We identified four biomarkers (MAP3K8, CCL20, VEGFC, and ANGPTL4) that could predict overall survival in lung adenocarcinoma (HR = 1.98, 95% CI 1.48 to 2.64, P = 4.19e−06) and this model could be used as a classifier for the evaluation of low-risk and high-risk groups. This model was validated with independent microarray data and was highly comparable with previously reported gene expression signatures for lung adenocarcinoma prognosis. Conclusions: In this study, we identified a practical and robust four-gene prognostic model based on an immune gene dataset with cross-platform compatibility. This model has potential value in improving TNM staging for survival predictions in patients with lung adenocarcinoma. Impact: The study provides a method of immune relevant gene prognosis model and the identification of immune gene classifier for the prediction of lung adenocarcinoma prognosis with RNA sequencing and microarray compatibility.

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Section: Discussionmentioning

confidence: 99%

IRGS: an immune-related gene classifier for lung adenocarcinoma prognosis

Shi

Dong

et al. 2020

J Transl Med

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“…However, VEGF-C protein expression does not appear to significantly relate to LUAD patient survival. Yang et al found that VEGF-C mRNA expression correlated with survival of the patients with lung cancer [ 7 ]. The biological functions of VEGF-C may be analyzed as a potential prognosis factor in LUAD.…”

Section: Introductionmentioning

confidence: 99%

Uses of Vascular Endothelial Growth Factor C as a Lung Adenocarcinoma Prognostic Biomarker

Chen

Pan

et al. 2023

World J Oncol

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Background: Lung adenocarcinoma (LUAD) is the most common type of lung cancer and a leading cause of death worldwide. Vascular endothelial growth factor C (VEGF-C) has been identified as a prognosis prediction marker for LUAD. However, VEGF-C protein expression does not appear to significantly relate to LUAD patient survival in several studies. Methods:We carried out a bioinformatic analysis to review the effect of VEGF-C mRNA expression on LUAD patient outcomes. GEPIA, UALCAN, TCGAportal, OncoLnc, LCE, GeneMANIA, Metascape, ImmuCellAI, and GSCA online databases were utilized. The expression levels of VEGF-C mRNA between normal tissue and LUAD tissue, overall survival (OS) analysis, function analysis, tumor microenvironment and drug sensitivity were conducted in the current study. Results:We found that the expression level of VEGF-C mRNA was significantly lower in LUAD than normal tissue. Low expression of VEGF-C mRNA was also associated with better OS. VEGF-C expression was correlated with both NF1 and TP53 mutation status. No relationship was observed between VEGF-C and Tr1 or CD4 T-cell infiltrate scores. Additionally, VEGF-C was associated with epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor resistance. The sensitivity of 5-fluorouracil was positively correlated with VEGF-C, and the sensitivity of TGX221 was negatively correlated with VEGF-C. The activity of BI-2536 and BRD-A94377914 was positively correlated with VEGF-C. Conclusion:Novel LUAD prognostic biomarkers such as VEGF-C mRNA may aid diagnosis and treatment, and may help identify optimal LUAD populations for therapeutic treatments.

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Elevated heparanase expression is associated with poor prognosis in breast cancer: a study based on systematic review and TCGA data

et al. 2017

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Heparanase promotes tumorigenesis, angiogenesis, and metastasis. Here, we conducted a study based on systematic review and the Cancer Genome Atlas (TCGA) data that examined heparanase expression in clinical samples to determine its prognostic value. According to the meta-analysis and TCGA data, we found that heparanase expression was up-regulated in most breast cancer specimens, and elevated heparanase expression was associated with increased lymph node metastasis, larger tumor size, higher histological grade, and poor survival. These results suggest that targeting heparanase might improve treatments for breast cancer patients.

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Influence of Heparanase and VEGF-C mRNA Expressions in Lung Cancer

Cited by 3 publications

References 10 publications

IRGS: an immune-related gene classifier for lung adenocarcinoma prognosis

IRGS: an immune-related gene classifier for lung adenocarcinoma prognosis

Uses of Vascular Endothelial Growth Factor C as a Lung Adenocarcinoma Prognostic Biomarker

Elevated heparanase expression is associated with poor prognosis in breast cancer: a study based on systematic review and TCGA data

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