Key microRNAs and hub genes associated with poor prognosis in lung adenocarcinoma

Taxifolin Inhibits the Growth of Non-Small-Cell Lung Cancer via Downregulating Genes Displaying Novel and Robust Associations with Immune Evasion Factors

Using an LL2 cell-based syngeneic mouse LC model, taxifolin suppressed allografts along with the appearance of 578 differentially expressed genes (DEGs). These DEGs were associated with enhancement of processes related to the extracellular matrix and lymphocyte chemotaxis as well as the reduction in pathways relevant to cell proliferation. From these DEGs, we formulated 12-gene (TxflSig) and 7-gene (TxflSig1) panels; both predicted response to ICB (immune checkpoint blockade) therapy more effectively in non-small-cell lung cancer (NSCLC) than numerous well-established ICB biomarkers, including PD-L1. In both panels, the mouse counterparts of ITGAL, ITGAX, and TMEM119 genes were downregulated by taxifolin. They were strongly associated with immune suppression in LC, evidenced by their robust correlations with the major immunosuppressive cell types (MDSC, Treg, and macrophage) and multiple immune checkpoints in NSCLC and across multiple human cancer types. ITGAL, ITGAX, and IIT (ITGAL-ITGAX-TMEM119) effectively predicted NSCLC's response to ICB therapy; IIT stratified the mortality risk of NSCLC. The stromal expressions of ITGAL and ITGAX, together with tumor expression of TMEM119 in NSCLC, were demonstrated. Collectively, we report multiple novel ICB biomarkers-TxflSig, TxflSig1, IIT, ITGAL, and ITGAX-and taxifolin-derived attenuation of immunosuppressive activities in NSCLC, suggesting the inclusion of taxifolin in ICB therapies for NSCLC.

Vascular endothelial-derived Von Willebrand factor inhibits lung cancer progression through the αvβ3/ERK1/2 axis

Lung cancer remains a common malignant tumor causing death due to the rapid industrialization and serious pollution of the environment. The Von Willebrand Factor (vWF) protein is an endothelial marker and is widely used to diagnose cancer and other inflammations, however its exact mechanism of action remains largely unexplored. In particular, how it plays two opposing roles in tumor development is not clear. Our study aimed to the impact of endothelial-derived vWF on tumor development by co-culturing human umbilical vein endothelial cells (HUVECs) with lung cancer cells (95D and A549). A knockdown of endothelial-derived vWF assisted lung cancer cell in proliferation, migration and inhibited apoptosis in vitro, while overexpression of endothelial-derived vWF inhibited the proliferation, migration and induced apoptosis of lung cancer cells. The results of further experiments indicated that the vWF secreted by endothelial cells could affect lung cancer cell migration and apoptosis via its binding to integrin αvβ3 on the surface of lung cancer cells. Furthermore, a novel finding was the fact that endothelial-derived vWF inhibited lung cancer cell apoptosis by phosphorylating ERK1/2. At the same time, we established experimental lung metastasis model and xenograft model in normal mice and vWF^-/- mice, and found that knockout of vWF in mice significantly promoted lung cancer growth and metastasis. In conclusion, our research found that endothelial-derived vWF could directly combine to αvβ3 on the exterior of A549 and 95D, thereby mediating lung cancer proliferation, migration and apoptosis and inhibiting the development of lung cancer.

LINC02126 is a potential diagnostic, prognostic and immunotherapeutic target for lung adenocarcinoma

Background

Adenocarcinoma has long been an independent histological class of lung cancer, which leads to high morbidity and mortality. We aimed to investigate the contribution of LINC02126 in lung adenocarcinoma.

Methods

RNA sequencing data and clinical information were downloaded. Diagnostic efficiency and survival analysis of LINC02126 were performed, followed by functional analysis of genes co-expressed with LINC02126 and differentially expressed genes (DEGs) in different LINC02126 expression groups. Tumor immune microenvironment (TIME) cell infiltration and correlation analysis of tumor mutation burden were performed in different LINC02126 expression groups.

Results

In lung adenocarcinoma, the expression level of LINC02126 was significantly decreased. Significant expression differences of LINC02126 were found in some clinical variables, including T staging, M staging, sex, stage, and EGFR mutation. LINC02126 had potential diagnostic and prognostic value for patients. In the low LINC02126 expression group, the infiltration degree of most immune cells was significantly lower than that in the high LINC02126 expression group. Tumor mutation burden level and frequency of somatic mutation in patients with low LINC02126 expression group were significantly higher than in patients with high LINC02126 expression group.

Conclusions

LINC02126 could be considered as a diagnostic, prognostic and immunotherapeutic target for lung adenocarcinoma.

Epigenetic Alterations of DNA Methylation and miRNA Contribution to Lung Adenocarcinoma

This study focused on the epigenetic alterations of DNA methylation and miRNAs for lung adenocarcinoma (LUAD) diagnosis and treatment using bioinformatics analyses. DNA methylation data and mRNA and miRNA expression microarray data were obtained from The Cancer Genome Atlas (TCGA) database. The differentially methylated genes (DMGs), differentially expressed genes (DEGs), and differentially expressed miRNAs were analyzed by using the limma package. The DAVID database performed GO and KEGG pathway enrichment analyses. Using STRING and Cytoscape, we constructed the protein-protein interaction (PPI) network and achieved visualization. The online analysis tool CMap was used to identify potential small-molecule drugs for LUAD. In LUAD, 607 high miRNA-targeting downregulated genes and 925 low miRNA-targeting upregulated genes, as well as 284 hypermethylated low-expression genes and 315 hypomethylated high-expression genes, were obtained. They were mainly enriched in terms of pathways in cancer, neuroactive ligand-receptor interaction, cAMP signaling pathway, and cytosolic DNA-sensing pathway. In addition, 40 upregulated and 84 downregulated genes were regulated by both aberrant alternations of DNA methylation and miRNAs. Five small-molecule drugs were identified as a potential treatment for LUAD, and five hub genes (SLC2A1, PAX6, LEP, KLF4, and FGF10) were found in PPI, and two of them (SLC2A1 and KLF4) may be related to the prognosis of LUAD. In summary, our study identified a series of differentially expressed genes associated with epigenetic alterations of DNA methylation and miRNA in LUAD. Five small-molecule drugs and five hub genes may be promising drugs and targets for LUAD treatment.

The Inflamm-Aging Model Identifies Key Risk Factors in Atherosclerosis

Background: Atherosclerosis, one of the main threats to human life and health, is driven by abnormal inflammation (i.e., chronic inflammation or oxidative stress) during accelerated aging. Many studies have shown that inflamm-aging exerts a significant impact on the occurrence of atherosclerosis, particularly by inducing an immune homeostasis imbalance. However, the potential mechanism by which inflamm-aging induces atherosclerosis needs to be studied more thoroughly, and there is currently a lack of powerful prediction models.

Methods: First, an improved inflamm-aging prediction model was constructed by integrating aging, inflammation, and disease markers with the help of machine learning methods; then, inflamm-aging scores were calculated. In addition, the causal relationship between aging and disease was identified using Mendelian randomization. A series of risk factors were also identified by causal analysis, sensitivity analysis, and network analysis.

Results: Our results revealed an accelerated inflamm-aging pattern in atherosclerosis and suggested a causal relationship between inflamm-aging and atherosclerosis. Mechanisms involving inflammation, nutritional balance, vascular homeostasis, and oxidative stress were found to be driving factors of atherosclerosis in the context of inflamm-aging.

Conclusion: In summary, we developed a model integrating crucial risk factors in inflamm-aging and atherosclerosis. Our computation pipeline could be used to explore potential mechanisms of related diseases.

CircRNA6783 Inhibits Cell Proliferation and Promotes Apoptosis in Lung Adenocarcinoma

Purpose

Circular RNA (circRNA) serves an important role in tumour genesis and development. But, little is known about its role in lung adenocarcinoma (LA). This study aimed to investigate circRNA6783 expression in peripheral whole blood (PWB) of LA and controls and explore its effect on proliferation and apoptosis in human lung adenocarcinoma cells (LAC).

Patients and Methods

The levels of circRNA6783 in LA cell lines and peripheral whole blood (PWB) of 40 patients and 30 controls were detected by real-time quantitative reverse transcription-polymerase chain reaction (RT-PCR). In order to explore the effect of circRNA6783 on LA behavior, we overexpressed circRNA6783 in NCI-H1975 cells. The impact on the proliferation of tumor cells was then examined by Cell Counting Kit 8 (CCK8) assay, and the effects on apoptosis in the cell line were detected using flow cytometry.

Results

The expression levels of circRNA6783 were significantly higher in LA cell lines and PWB (P < 0.05). The diagnostic value of the area under the receiver operating characteristic curve (AUC) was 0.830, with a sensitivity of 60% and specificity of 96.7%. In addition, functional experiments showed that overexpression of circRNA6783 restrained cell proliferation, significantly increased spontaneous apoptosis.

Conclusion

CircRNA6783 was upregulated in LA PWB. In vitro assessment demonstrated that circRNA6783 could act as a potential biomarker for LA diagnosis.

An 11-Gene Signature Risk-Prediction Model Based on Prognosis-Related miRNAs and Their Target Genes in Lung Adenocarcinoma

Aberrant expression of microRNAs may affect tumorigenesis and progression by regulating their target genes. This study aimed to construct a risk model for predicting the prognosis of patients with lung adenocarcinoma (LUAD) based on differentially expressed microRNA-regulated target genes. The miRNA sequencing data, RNA sequencing data, and patients’ LUAD clinical data were downloaded from the The Cancer Genome Atlas (TCGA) database. Differentially expressed miRNAs and genes were screened out by combining differential analysis with LASSO regression analysis to further screen out miRNAs associated with patients’ prognosis, and target gene prediction was performed for these miRNAs using a target gene database. Overlapping gene screening was performed for target genes and differentially expressed genes. LASSO regression analysis and survival analysis were then used to identify key genes. Risk score equations for prognostic models were established using multifactorial COX regression analysis to construct survival prognostic models, and the accuracy of the models was evaluated using subject working characteristic curves. The groups were divided into high- and low-risk groups according to the median risk score, and the correlation with the clinicopathological characteristics of the patients was observed. A total of 123 up-regulated miRNAs and 22 down-regulated miRNAs were obtained in this study. Five prognosis-related miRNAs were screened using LASSO regression analysis and Kaplan-Meier method validation, and their target genes were screened with the overlap of differentially expressed genes before multifactorial COX analysis finally resulted in an 11-gene risk model for predicting patient prognosis. The area under the ROC curve proved that the model has high accuracy. The 11-gene risk-prediction model constructed in this study may be an effective predictor of prognosis.

Construction of an immune-related lncRNA signature as a novel prognosis biomarker for LUAD

The tumor immune microenvironment of lung cancer is associated with prognosis and immunotherapy efficacy. Long noncoding RNAs are identified as prognostic biomarkers associated with immune functions. We constructed a signature comprising differentially expressed immune-related lncRNAs to predict the prognosis of patients with lung adenocarcinoma. We established the immune-related lncRNA signature by pairing immune-related lncRNAs regardless of expression level and lung adenocarcinoma patients were divided into high- and low-risk groups. The prognosis of patients in the two groups was significantly different; The immune-related lncRNA signature could serve as an independent lung adenocarcinoma prognostic indicator. The signature correlated negatively with B cell, CD4+ T cell, M2 macrophage, neutrophil, and monocyte immune infiltration. Patients with low risk scores had a higher abundance of immune cells and stromal cells around the tumor. Gene set enrichment analysis showed that samples from low-risk group were more active in the IgA production in intestinal immune network and the T and B cell receptor signaling pathway. High-risk groups had significant involvement of the cell cycle, DNA replication, adherens junction, actin cytoskeleton regulation, pathways in cancer, and TGF-β signaling pathways. High risk scores correlated significantly negatively with high CTLA-4 and HAVCR2 expression and higher median inhibitory concentration of common anti-tumor chemotherapeutics (e.g., cisplatin, paclitaxel, gemcitabine) and targeted therapy (e.g., erlotinib and gefitinib). We identified a reliable immune-related lncRNA lung adenocarcinoma prognosis model, and the immune-related lncRNA signature showed promising clinical prediction value.

Construction of a prognostic signature of autophagy-related lncRNAs in non-small-cell lung cancer

Background

Autophagy inhibits tumorigenesis by limiting inflammation. LncRNAs regulate gene expression at various levels as RNAs; thus, both autophagy and lncRNAs are closely related to the occurrence and development of tumours.

Methods

A total of 232 autophagy-related genes were used to construct a coexpression network to extract autophagy-related lncRNAs. A prognostic signature was constructed by multivariate regression analysis. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis was applied to analyse enrichment in cancer-related pathways. Immune infiltration analysis was used to analyse the relationship between the prognostic signature and the tumour microenvironment.

Results

Nine autophagy-related lncRNAs were used to construct a prognostic model for non-small-cell lung cancer. The median risk score was used to discriminate the high- and low-risk groups, and the low-risk group was found to have better survival. Because KEGG pathway analysis showed that the prognostic signature was enriched in some immune pathways, further analysis of immune infiltration was conducted, and it was found that the prognostic signature did play a unique role in the immune microenvironment. Additionally, the prognostic signature was associated with clinical factors.

Conclusion

We constructed a prognostic model of autophagy-related lncRNAs that can predict the prognosis of non-small-cell lung cancer.