Identification of Cigarette Smoking-Related Novel Biomarkers in Lung Adenocarcinoma

Identification of prognostic biomarkers of smoking-related lung cancer

Background

The early diagnosis and effective prognostic treatment measures for lung cancer are still limited, leading to a 5-year survival rate of less than 15% for these patients. Smoking is one of the causes of lung cancer, but it is not the initial carcinogenic factor. It is not clear what specific mechanism cigarette induces lung cancer, and there is a lack of research on the relationship between related genes and the prognosis of patients with smoking lung cancer. The objective of this study was to provide new theoretical evidence and potential therapeutic targets for the mechanisms of smoking-related lung cancer formation.

Methods

The gene expression profile data from the GSE12428 dataset which includes 63 lung cancer and normal tissue pairs were downloaded from the Gene Expression Omnibus (GEO) database, and data from smokers with lung cancer [both lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC)] from The Cancer Genome Atlas (TCGA) database were analyzed. The differential genes in smokers with lung cancer were screened using the linear model for microarray data via R software. The differential gene enrichment analysis was performed using the online analysis software Database for Annotation, Visualization and Integrated Discovery (DAVID). The expression levels of differential genes and their correlation with patient tumor clinical stage were analyzed using gene expression profiling interactive analysis (GEPIA). The overall survival rate was analyzed using Kaplan-Meier curves.

Results

In the GSE12428 dataset, 225 upregulated genes and 565 downregulated genes were identified in cancer tissues; based on smoking status, 1 upregulated gene and 4 downregulated genes were identified. Among smokers who also had lung cancer, 4 genes were downregulated, namely CSH1, BPIFA1, SLPI, and SCGB3A1. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis revealed that these genes were mainly associated with biological functions such as antibacterial response, humoral immune response, and response to external stimuli. Among them, BPIFA1, SLPI, and SCGB3A1 expression was decreased in lung cancer tissues, with SCGB3A1 showing significant differences. Additionally, high expression of SCGB3A1 was associated with favorable prognosis in patients with lung cancer.

Conclusions

Three genes BPIFA1, SLPI and SCGB3A1, were identified as being associated with smokers with lung cancer, with SCGB3A1 showing a close correlation with patient prognosis. These findings provide potential new targets for the treatment of lung cancer. Certainly, this study needs to more investigate the mechanism of these genes regulation.

MYH7 in cardiomyopathy and skeletal muscle myopathy

Myosin heavy chain gene 7 (MYH7), a sarcomeric gene encoding the myosin heavy chain (myosin-7), has attracted considerable interest as a result of its fundamental functions in cardiac and skeletal muscle contraction and numerous nucleotide variations of MYH7 are closely related to cardiomyopathy and skeletal muscle myopathy. These disorders display significantly inter- and intra-familial variability, sometimes developing complex phenotypes, including both cardiomyopathy and skeletal myopathy. Here, we review the current understanding on MYH7 with the aim to better clarify how mutations in MYH7 affect the structure and physiologic function of sarcomere, thus resulting in cardiomyopathy and skeletal muscle myopathy. Importantly, the latest advances on diagnosis, research models in vivo and in vitro and therapy for precise clinical application have made great progress and have epoch-making significance. All the great advance is discussed here.

Comprehensive analysis to identify GNG7 as a prognostic biomarker in lung adenocarcinoma correlating with immune infiltrates

Background: G Protein Subunit Gamma 7 (GNG7), an important regulator of cell proliferation and cell apoptosis, has been reported to be downregulated in a variety of tumors including lung adenocarcinoma (LUAD). However, the correlation between low expression of GNG7 and prognosis of LUAD as well as the immune infiltrates of LUAD remains unclear.

Methods: The samples were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). R software was performed for statistical analysis. GNG7 expression and its prognostic value in LUAD were assessed through statistically analyzing the data from different databases. A nomogram was constructed to predict the impact of GNG7 on prognosis. Gene set enrichment analysis (GSEA) and single-sample gene set enrichment analyses GSEA (ssGSEA) were employed to determine the potential signal pathways and evaluated the immune cell infiltration regulated by GNG7. The prognostic significance of GNG7 expression associated with immune cell infiltration was investigated using the Tumor Immune Estimation Resource 2.0 (TIMER2.0) and the Kaplan-Meier plotter database. The UALCAN, cBio Cancer Genomics Portal (cBioPortal) and MethSurv database were used to analyze the correlation between the methylation of GNG7 and its mRNA expression as well as prognostic significance.

Results: GNG7 was demonstrated to be down-regulated in LUAD and its low expression was associated with poor prognosis. A clinical reliable prognostic-predictive model was constructed. Pathway enrichment showed that GNG7 was highly related to the B cell receptor signaling pathway. Further analysis showed that GNG7 was positively associated with B cell infiltration and low levels of B cell infiltration tended to associate with worse prognosis in patients with low GNG7 expression. Moreover, methylation analysis suggested hypermethylation may contribute to the low expression of GNG7 in LUAD.

Conclusion: Decreased expression of GNG7 at least partly caused by hypermethylation of the GNG7 promoter is closely associated with poor prognosis and tumor immune cell infiltration (especially B cells) in LUAD. These results suggest that GNG7 may be a promising prognostic biomarker and a potential immunotherapeutic target for LUAD, which provides new insights into immunotherapy for LUAD.