Abstract

Lung adenocarcinoma (LUAD) is one of the most malignant tumors with high morbidity and mortality worldwide due to the lack of reliable methods for early diagnosis and effective treatment. It’s imperative to study the mechanism of its development and explore new biomarkers for early detection of LUAD. In this study, the Gene Expression Omnibus (GEO) dataset GSE43458 and The Cancer Genome Atlas (TCGA) were used to explore the differential co-expressed genes between LUAD and normal samples. Three hundred sixity-six co-expressed genes were identified by differential gene expression analysis and Weighted Gene Co-expression Network Analysis (WGCNA) method. Those genes were mainly enriched in ameboidal-type cell migration (biological process), collagen-containing extracellular matrix (cell component), and extracellular matrix structure constituent (molecular function). The protein-protein network (PPI) was constructed and 10 hub genes were identified, including IL6, VWF, CDH5, PECAM1, EDN1, BDNF, CAV1, SPP1, TEK, and SELE. The expression level of hub genes was validated in the GEPIA database, compared with normal tissues, VWF is lowly expressed and SPP1 is upregulated in LUAD tissues. The survival analysis showed increased expression of SPP1 indicated unfavorable prognosis whereas high expression of VWF suggested favorable prognosis in LUAD (p < 0.05). Based on the immune infiltration analysis, the relationship between SPP1 and VWF expression and macrophage, neutrophil, and dendritic cell infiltration was weak in LUAD. Quantitative real-time PCR (qRT-PCR) and western blotting were used to validate the expression of VWF and SPP1 in normal human bronchial epithelial (HBE) cell and three LUAD cell lines, H1299, H1975, and A549. Immunohistochemistry (IHC) was further performed to detect the expression of VWF in 10 cases LUAD samples and matched normal tissues. In summary, the data suggest that VWF is a potential novel biomarker for prognosis of LUAD.

Highlights

  • Lung cancer is the leading cause of cancer death around the world [1]

  • The gene co-expression network was constructed from TCGALUAD and GSE43458 dataset using the Weighted Gene Co-expression Network Analysis (WGCNA) package

  • The genes in the The Cancer Genome Atlas (TCGA) blue module were mainly enriched in positive regulation of transcription from RNA polymerase II promoter, calcium ion binding, and integral component of membrane

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Summary

Introduction

Lung cancer is the leading cause of cancer death around the world [1]. Lung adenocarcinoma (LUAD) is the common histological type of lung cancer, and LUAD comprising 40% of all lung cancer cases is the most common type of lung cancer. Despite advances in early diagnosis and treatment methods, the 5-year overall survival rate of LUAD patients remains low [2]. It’s imperative to discover new biomarkers for early diagnosis and treatment to improve the prognosis of patients with lung cancer. A study combining The Cancer Genome Atlas (TCGA) dataset and the Gene Expression Omnibus (GEO) dataset identified CX3CL1 overexpression as a positive prognostic factor in patients with LUAD [3]. By detecting the interested module of clinical trait and co-expressed module of related genes, WGCNA can help us to mine the key genes in cancer [7, 8] and predict the function of target genes, which identifies potential biomarker genes or therapeutic target [9, 10]

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