Comprehensive analysis of genes, pathways, and TFs in nonsmoking Taiwan females with lung cancer

Sophorae tonkinensis radix et rhizome-induced pulmonary toxicity: A study on the toxic mechanism and material basis based on integrated omics and bioinformatics analyses

The root and rhizome of Sophora tonkinensis Gagnep. (ST) are widely used for the treatment of tonsillitis, sore throats, and heat-evil-induced diseases in traditional Chinese medicine. However, the clinical application of ST is relatively limited due to its toxicity. The mechanism and material basis of ST-induced pulmonary toxicity are still unclear. In the present research, integrated omics and bioinformatics analyses were used to investigate the toxic mechanism and material basis of ST in lung tissue. Proteomics and metabonomics were integrated to analyze the differentially expressed proteins and metabolites. Joint pathway analysis was used to analyze the significantly dysregulated pathways. PubChem and the Comparative Toxicogenomics Database were applied for the screen of toxic targets and compounds. Integrated omics revealed that 323 proteins and 50 metabolites were differentially expressed after treating with ST, out of which 19 proteins and 1 metabolite were significantly enriched in seven pathways. Bioinformatics showed that 15 compounds may indirectly affect the expression of 9 toxic targets of ST. Multiple toxic targets of ST-induced pulmonary injury were found in the study, whose dysregulation may trigger pulmonary cancer, dyspnea, and oxidative stress. Multiple compounds may be the toxic material basis in response to these effects.

Identification of core genes and clinical outcomes in tumors originated from endoderm (gastric cancer and lung carcinoma) via bioinformatics analysis

ABSTRACT

During last decade, bioinformatics analysis has provided an effective way to study the relationship between various genes and biological processes. In this study, we aimed to identify potential core candidate genes and underlying mechanisms of progression of lung and gastric carcinomas which both originated from endoderm. The expression profiles, GSE54129 (gastric carcinoma) and GSE27262 (lung carcinoma), were collected from GEO database. One hundred eleven patients with gastric carcinoma and 21 health people were included in this research. Meanwhile, there were 25 lung carcinoma patients. Then, 75 differentially expressed genes were selected via GEO2R online tool and Venn software, including 31 up-regulated genes and 44 down-regulated genes. Next, we used Database for Annotation, Visualization, and Integrated Discovery and Metascpe software to analyze Kyoto Encyclopedia of Gene and Genome pathway and gene ontology. Furthermore, Cytoscape software and MCODE App were performed to construct complex of these differentially expressed genes . Twenty core genes were identified, which mainly enriched in extracellular matrix-receptor interaction, focal adhesion, and PI3K-Akt pathway (P < .01). Finally, the significant difference of gene expression between cancer tissues and normal tissues in both lung and gastric carcinomas was examined by Gene Expression Profiling Interactive Analysis database. Twelve candidate genes with positive statistical significance (P < .01), COMP CTHRC1 COL1A1 SPP1 COL11A1 COL10A1 CXCL13 CLDN3 CLDN1 matrix metalloproteinases 7 ADAM12 PLAU, were picked out to further analysis. The Kaplan-Meier plotter website was applied to examine relationship among these genes and clinical outcomes. We found 4 genes (ADAM12, SPP1, COL1A1, COL11A1) were significantly associated with poor prognosis in both lung and gastric carcinoma patients (P  < .05). In conclusion, these candidate genes may be potential therapeutic targets for cancer treatment.

Identification of candidate genes and prognostic value analysis in patients with PDL1-positive and PDL1-negative lung adenocarcinoma

Background

Increasing bodies of evidence reveal that targeting a programmed cell death protein 1 (PD-1) monoclonal antibody is a promising immunotherapy for lung adenocarcinoma. Although PD receptor ligand 1 (PDL1) expression is widely recognized as the most powerful predictive biomarker for anti-PD-1 therapy, its regulatory mechanisms in lung adenocarcinoma remain unclear. Therefore, we conducted this study to explore differentially expressed genes (DEGs) and elucidate the regulatory mechanism of PDL1 in lung adenocarcinoma.

Methods

The GSE99995 data set was obtained from the Gene Expression Omnibus (GEO) database. Patients with and without PDL1 expression were divided into PDL1-positive and PDL1-negative groups, respectively. DEGs were screened using R. The Gene Ontology (GO) database and Kyoto Encyclopedia of Genes and Genomes (KEGG) were analyzed using the Database for Annotation, Visualization and Integrated Discovery. Protein–protein interaction (PPI) networks of DEGs was visualized using Cytoscape, and the MNC algorithm was applied to screen hub genes. A survival analysis involving Gene Expression Profiling Interactive Analysis was used to verify the GEO results. Mutation characteristics of the hub genes were further analyzed in a combined study of five datasets in The Cancer Genome Atlas (TCGA) database.

Results

In total, 869 DEGs were identified, 387 in the PDL1-positive group and 482 in the PDL1-negative group. GO and KEGG analysis results of the PDL1-positive group mainly exhibited enrichment of biological processes and pathways related to cell adhesion and the peroxisome proliferators-activated receptors (PPAR) signaling pathway, whereas biological process and pathways associated with cell division and repair were mainly enriched in the PDL1-negative group. The top 10 hub genes were screened during the PPI network analysis. Notably, survival analysis revealed BRCA1, mainly involved in cell cycle and DNA damage responses, to be a novel prognostic indicator in lung adenocarcinoma. Moreover, the prognosis of patients with different forms of lung adenocarcinoma was associated with differences in mutations and pathways in potential hub genes.

Conclusions

PDL1-positive lung adenocarcinoma and PDL1-negative lung adenocarcinoma might be different subtypes of lung adenocarcinoma. The hub genes might play an important role in PDL1 regulatory pathways. Further studies on hub genes are warranted to reveal new mechanisms underlying the regulation of PDL1 expression. These results are crucial for understanding and applying precision immunotherapy for lung adenocarcinoma.

The Functional Effects of Key Driver KRAS Mutations on Gene Expression in Lung Cancer

Lung cancer is a common malignant cancer. Kirsten rat sarcoma oncogene (KRAS) mutations have been considered as a key driver for lung cancers. KRAS p.G12C mutations were most predominant in NSCLC which was comprised about 11–16% of lung adenocarcinomas (p.G12C accounts for 45–50% of mutant KRAS). But it is still not clear how the KRAS mutation triggers lung cancers. To study the molecular mechanisms of KRAS mutation in lung cancer. We analyzed the gene expression profiles of 156 KRAS mutation samples and other negative samples with two stage feature selection approach: (1) minimal Redundancy Maximal Relevance (mRMR) and (2) Incremental Feature Selection (IFS). At last, 41 predictive genes for KRAS mutation were identified and a KRAS mutation predictor was constructed. Its leave one out cross validation MCC was 0.879. Our results were helpful for understanding the roles of KRAS mutation in lung cancer.

Bioinformatics analysis reveals 6 key biomarkers associated with non-small-cell lung cancer

Objective

Non-small-cell lung cancer (NSCLC) accounts for >85% of lung cancers, and its incidence is increasing. We explored expression differences between NSCLC and normal cells and predicted potential target sites for detection and diagnosis of NSCLC.

Methods

Three microarray datasets from the Gene Expression Omnibus database were analyzed using GEO2R. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis were conducted. Then, the String database, Cytoscape, and MCODE plug-in were used to construct a protein–protein interaction (PPI) network and screen hub genes. Overall and disease-free survival of hub genes were analyzed using Kaplan-Meier curves, and the relationship between expression patterns of target genes and tumor grades were analyzed and validated. Gene set enrichment analysis and receiver operating characteristic curves were used to verify enrichment pathways and diagnostic performance of hub genes.

Results

In total, 293 differentially expressed genes were identified and mainly enriched in cell cycle, ECM–receptor interaction, and malaria. In the PPI network, 36 hub genes were identified, of which 6 were found to play significant roles in carcinogenesis of NSCLC: CDC20, ECT2, KIF20A, MKI67, TPX2, and TYMS.

Conclusion

The identified target genes can be used as biomarkers for the detection and diagnosis of NSCLC.

Identification of differentially expressed genes and enriched pathways in lung cancer using bioinformatics analysis

Lung cancer is the leading cause of cancer‑associated mortality worldwide. The aim of the present study was to identify the differentially expressed genes (DEGs) and enriched pathways in lung cancer by bioinformatics analysis, and to provide potential targets for diagnosis and treatment. Valid microarray data of 31 pairs of lung cancer tissues and matched normal samples (GSE19804) were obtained from the Gene Expression Omnibus database. Significance analysis of the gene expression profile was used to identify DEGs between cancer tissues and normal tissues, and a total of 1,970 DEGs, which were significantly enriched in biological processes, were screened. Through the Gene Ontology function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, 77 KEGG pathways associated with lung cancer were identified, among which the Toll‑like receptor pathway was observed to be important. Protein‑protein interaction network analysis extracted 1,770 nodes and 10,667 edges, and identified 10 genes with key roles in lung cancer with highest degrees, hub centrality and betweenness. Additionally, the module analysis of protein‑protein interactions revealed that 'chemokine signaling pathway', 'cell cycle' and 'pathways in cancer' had a close association with lung cancer. In conclusion, the identified DEGs, particularly the hub genes, strengthen the understanding of the development and progression of lung cancer, and certain genes (including advanced glycosylation end‑product specific receptor and epidermal growth factor receptor) may be used as candidate target molecules to diagnose, monitor and treat lung cancer.

Inhibition of microRNA‑939 suppresses the development of human non‑small cell lung cancer via the upregulation of tissue inhibitor of metalloproteinases 2

Numerous microRNAs (miRNA/miRs) have been reported to be associated with the initiation and progression of non‑small cell lung cancer (NSCLC). The aim of the present study was to examine the expression and biological role of miR‑939 in human NSCLC, in vitro. Reverse transcription‑quantitative polymerase chain reaction analysis was used to evaluate the expression of miR‑939 in NSCLC tissues. Cell Counting Kit‑8, 5‑ethynyl‑29‑deoxyuridine and Transwell assays were also used to determine the effects of miR‑939 on tumor cell proliferation and invasion in two human NSCLC cell lines (H1299 and SPCA1). Furthermore, tissue inhibitor of metalloproteinases 2 (TIMP2) was confirmed to be a target of miR‑939 by luciferase reporter assay, western blotting and bioinformatics analysis. Following downregulation of miR‑939 expression, cell proliferative and invasive abilities were significantly suppressed. Collectively, these findings indicated that the knockdown of miR‑939 may inhibit cell proliferation and invasion by regulating the expression of TIMP2 in NSCLC cells. Thus, miR‑939 may be a potential target in the treatment of NSCLC, although this requires further investigation.

Downregulation of HOXA3 in lung adenocarcinoma and its relevant molecular mechanism analysed by RT-qPCR, TCGA and in silico analysis

Recent studies have indicated that homeobox A3 (HOXA3) functions as a carcinogen in colon cancer and the methylation level of HOXA3 is significantly increased in lung adenocarcinoma (LUAD) tissues. However, at least to the best of our knowledge, few studies to date have been performed on HOXA3 in non-small cell lung cancer (NSCLC). Therefore, further studies on HOXA3 expression in NSCLC and the potential regulatory mechanisms are urgently required. In this study, HOXA3 expression in 55 tissues of cases of NSCLC and corresponding non-lung cancer tissues was detected by reverse transcription-quantitative PCR (RT-qPCR). In addition, the clinical significance of HOXA3 expression in NSCLC was evaluated using the Cancer Genome Atlas (TCGA) database. Bioinformatics analysis was then performed to elucidate the potential molecular mechanisms of action of HOXA3. Furthermore, the potential target microRNAs (miRNAs or miRs) of HOXA3 were predicted using miRWalk2.0. Based on Gene Expression Omnibus (GEO) and TGCA databases, standardized mean difference (SMD) and sROC methods were used for meta-analyses of the expression of potential target miRNAs of HOXA3 in NSCLC to evaluate their association with HOXA3. The results revealed that the HOXA3 expression levels in NSCLC, LUAD and lung squamous cell carcinoma (LUSC) were 0.1130±0.1398, 0.1295±0.16890 and 0.0906±0.0846, respectively. These values were all decreased compared with the normal tissues (0.1877±0.1975, 0.2337±0.2405 and 0.1249±0.0873, respectively, P<0.05). The TCGA database also revealed the low expression trend of HOXA3. The downregulation of HOXA3 may play an important role in the progression and the poor prognosis of LUAD. The TCGA database also suggested that HOXA3 in LUAD and LUSC tissues exhibited certain mutational levels. In addition, the methylation levels in the NSCLC, LUAD and LUSC tissues significantly increased [NSCLC: fold change (FC), 1.3226; P<0.001; LUAD: FC, 1.2712; P<0.001; and LUSC: FC, 1.3786; P<0.001]. According to the analyses using the Kyoto Encyclopedia of Genes and Genomes (KEGG), we found that the co-expression HOXA3 genes were mainly associated with the focal adhesion signalling pathway and the ECM-receptor interaction signalling pathway. Furthermore, the predicted miRNA, miR-372-3p, exhibited a high expression in both the NSCLC and LUAD tissues (P<0.05). On the whole, the findings of this study indicate that low HOXA3 expression may play a certain role in LUAD; however, its association with LUSC still requires further investigation. HOXA3 function may be achieved through different pathways or target miRNAs. However, the specific underlying mechanisms need to be confirmed through various functional studies.

Network analysis of DEGs and verification experiments reveal the notable roles of PTTG1 and MMP9 in lung cancer

Lung cancer, a malignant tumor, is the most frequently fatal cancer, with poor survival rates in the advanced stages. In order to improve the understanding of this disease, and to improve the outcomes of patients, additional studies are required. In the present study, differentially expressed genes (DEGs) in patients with lung cancer compared with controls were identified. To understand how these DEGs act together to account for the initiation of lung cancer, a protein interaction network and a transcriptional regulatory network were constructed to explore the clusters and pathways in lung cancer, and the results indicated that PTTG1 and MMP9 served major roles in the development of lung cancer in the regulatory system. Consistent with this, mRNA and protein expression levels of PTTG1 and MMP9 were significantly upregulated in lung cancer tissues compared with normal lung tissues. The overexpression of PTTG1 or MMP9 was induced in the human bronchial epithelial BEAS-2B cell line, indicating that increased PTTG1 or MMP9 alone may not only facilitate cell migration, proliferation and induce colony formation, but also suppress cell apoptosis. In summary, PTTG1 and MMP9 were identified as potential targets for therapeutic intervention through gene therapy in lung cancer.