Development and Validation of a Seven-Gene Signature for Predicting the Prognosis of Lung Adenocarcinoma

The Risk Correlation between N7-Methylguanosine Modification-Related lncRNAs and Survival Prognosis of Oral Squamous Cell Carcinoma Based on Comprehensive Bioinformatics Analysis

Objective. N7-methylguanosine modification-related lncRNAs (m7G-related lncRNAs) are involved in progression of many diseases. This study was aimed at revealing the risk correlation between N7-methylguanosine modification-related lncRNAs and survival prognosis of oral squamous cell carcinoma. Methods. In the present study, coexpression network analysis and univariate Cox analysis were used to obtained 31 m7G-related mRNAs and 399 m7G-related lncRNAs. And the prognostic risk score model of OSCC patients was evaluated and optimized through cross-validation. Results. Through the coexpression analysis and risk assessment analysis of m7G-related prognostic mRNAs and lncRNAs, it was found that six m7G-related prognostic lncRNAs (AC005332.6, AC010894.1, AC068831.5, AL035446.1, AL513550.1, and HHLA3) were high-risk lncRNAs. Three m7G-related prognostic lncRNAs (AC007114.1, HEIH, and LINC02541) were protective lncRNAs. Then, survival curves were drawn by comparing the survival differences between patients with high and low expression of each m7G-related prognostic lncRNA in the prognostic risk score model. Further, risk curves, scatter plots, and heat maps were drawn by comparing the survival differences between high-risk and low-risk OSCC patients in the prognostic model. Finally, forest maps and the ROC curve were generated to verify the predictive power of the prognostic risk score model. Our results will help to find early and accurate prognostic risk markers for OSCC, which could be used for early prediction and early clinical intervention of survival, prognosis, and disease risk of OSCC patients in the future.

Single-cell RNA sequencing analysis to explore immune cell heterogeneity and novel biomarkers for the prognosis of lung adenocarcinoma

Background: Single-cell RNA sequencing is necessary to understand tumor heterogeneity, and the cell type heterogeneity of lung adenocarcinoma (LUAD) has not been fully studied.

Method: We first reduced the dimensionality of the GSE149655 single-cell data. Then, we statistically analysed the subpopulations obtained by cell annotation to find the subpopulations highly enriched in tumor tissues. Monocle was used to predict the development trajectory of five subpopulations; beam was used to find the regulatory genes of five branches; qval was used to screen the key genes; and cellchart was used to analyse cell communication. Next, we used the differentially expressed genes of TCGA-LUAD to screen for overlapping genes and established a prognostic risk model through univariate and multivariate analyses. To identify the independence of the model in clinical application, univariate and multivariate Cox regression were used to analyse the relevant HR, 95% CI of HR and p value. Finally, the novel biomarker genes were verified by qPCR and immunohistochemistry.

Results: The single-cell dataset GSE149655 was subjected to quality control, filtration and dimensionality reduction. Finally, 23 subpopulations were screened, and 11-cell subgroups were annotated in 23 subpopulations. Through the statistical analysis of 11 subgroups, five important subgroups were selected, including lung epithelial cells, macrophages, neuroendocrine cells, secret cells and T cells. From the analysis of cell trajectory and cell communication, it is found that the interaction of five subpopulations is very complex and that the communication between them is dense. We believe that these five subpopulations play a very important role in the occurrence and development of LUAD. Downloading the TCGA data, we screened the marker genes of these five subpopulations, which are also the differentially expressed genes in tumorigenesis, with a total of 462 genes, and constructed 10 gene prognostic risk models based on related genes. The 10-gene signature has strong robustness and can achieve stable prediction efficiency in datasets from different platforms. Two new molecular markers related to LUAD, HLA-DRB5 and CCDC50, were verified by qPCR and immunohistochemistry. The results showed that HLA-DRB5 expression was negatively correlated with the risk of LUAD, and CCDC50 expression was positively correlated with the risk of LUAD.

Conclusion: Therefore, we identified a prognostic risk model including CCL20, CP, HLA-DRB5, RHOV, CYP4B1, BASP1, ACSL4, GNG7, CCDC50 and SPATS2 as risk biomarkers and verified their predictive value for the prognosis of LUAD, which could serve as a new therapeutic target.

HMOX1 promotes lung adenocarcinoma metastasis by affecting macrophages and mitochondrion complexes

Background

Metastasis is the leading cause of lung adenocarcinoma (LUAD) patient death. However, the mechanism of metastasis is unclear. We performed bioinformatic analyses for HMOX1 (Heme oxygenase-1), aiming to explore its role in LUAD metastasis.

Methods

Pan-cancer analysis was first used to identify the metastasis-associated role of HMOX1 in LUAD. HMOX1-related genomic alterations were then investigated. Based on functional enrichment, we systematically correlated HMOX1 with immunological characteristics and mitochondrial activities. Furthermore, weighted gene co-expression network analysis (WGCNA) was applied to construct the HMOX1-mediated metastasis regulatory network, which was then validated at the proteomic level. Finally, we conducted the survival analysis and predicted the potential drugs to target the HMOX1 network.

Results

HMOX1 expression was significantly associated with epithelial-mesenchymal transition (EMT) and lymph and distant metastasis in LUAD. High HMOX1 levels exhibited higher macrophage infiltration and lower mitochondrial complex expression. WGCNA showed a group of module genes co-regulating the traits mentioned above. Subsequently, we constructed an HMOX1-mediated macrophage-mitochondrion-EMT metastasis regulatory network in LUAD. The network had a high inner correlation at the proteomic level and efficiently predicted prognosis. Finally, we predicted 9 potential drugs targeting HMOX1-mediated metastasis in LUAD, like chloroxine and isoliquiritigenin.

Conclusions

Our analysis elaborates on the role of HMOX1 in LUAD metastasis and identified a highly prognostic HMOX1-mediated metastasis regulatory network. Novel potential drugs targeting the HMOX1 network were also proposed, which should be tested for their activity against LUAD metastasis in future studies.

Exosomal hsa_circ_0000519 modulates the NSCLC cell growth and metastasis via miR-1258/RHOV axis

This study aims to explore the function and mechanism of exosomal circ_0000519 in non-small cell lung cancer (NSCLC) development. Expression of circ_0000519, microRNA (miR)-1258, and Ras homolog gene family V (RHOV) in serum samples of NSCLC patients or cell lines were examined via quantitative reverse transcription-polymerase chain reaction and Western blotting. The function of circ_0000519 was evaluated through 5-ethynyl-2′-deoxyuridine (EdU) staining, colony formation, transwell, Western blotting, xenograft, and immunohistochemistry analyses. The binding relationship was evaluated by a dual-luciferase reporter assay and RNA pull-down assay. Results showed that circ_0000519 abundance was enhanced in the serum samples of NSCLC patients and cells. circ_0000519 knockdown suppressed the cell growth by decreasing the colony-formation ability and Cyclin D1 expression and inhibited cell metastasis via reducing migration, invasion, and levels of Vimentin and matrix metalloproteinase 9 (MMP9). circ_0000519 overexpression promoted cell growth and metastasis. circ_0000519 was carried by exosomes and knockdown of exosomal circ_0000519 suppressed the cell growth and metastasis. miR-1258 was downregulated in NSCLC cells and targeted by circ_0000519. RHOV was targeted by miR-1258 and upregulated in the NSCLC cells. miR-1258 knockdown or RHOV overexpression attenuated the influence of exosomal circ_0000519 knockdown on cell growth and metastasis. Exosomal circ_0000519 knockdown decreased xenograft tumor growth. Collectively, the knockdown of exosomal circ_0000519 repressed the cell growth and metastasis in NSCLC through the miR-1258/RHOV axis, which provided a new insight into NSCLC development and treatment.