Identification of key genes and evaluation of clinical outcomes in lung squamous cell carcinoma using integrated bioinformatics analysis

CEP55: an immune-related predictive and prognostic molecular biomarker for multiple cancers

BACKGROUND

Centrosomal protein 55 (CEP55) plays a significant role in specific cancers. However, comprehensive research on CEP55 is lacking in pan-cancer.

METHODS

In-house and multi-center samples (n = 15,823) were used to analyze CEP55 in 33 cancers. The variance of CEP55 expression levels among tumor and control groups was evaluated by the Wilcoxon rank-sum test and standardized mean difference (SMD). The clinical value of CEP55 in cancers was assessed using receiver operating characteristic (ROC) curves, Cox regression analysis, and Kaplan-Meier curves. The correlations between CEP55 expression and the immune microenvironment were explored using Spearman's correlation coefficient.

RESULTS

The data of clustered regularly interspaced short palindromic repeats confirmed that CEP55 was essential for the survival of cancer cells in multiple cancer types. Elevated CEP55 mRNA expression was observed in 20 cancers, including glioblastoma multiforme (p < 0.05). CEP55 mRNA expression made it feasible to distinguish 21 cancer types between cancer specimens and their control samples (AUC = 0.97), indicating the potential of CEP55 for predicting cancer status. Overexpression of CEP55 was correlated with the prognosis of cancer individuals for 18 cancer types, exhibiting its prognostic value. CEP55 expression was relevant to tumor mutation burden, microsatellite instability, neoantigen counts, and the immune microenvironment in various cancers (p < 0.05). The expression level and clinical relevance of CEP55 in cancers were verified in lung squamous cell carcinoma using in-house and multi-center samples (SMD = 4.07; AUC > 0.95; p < 0.05).

CONCLUSION

CEP55 may be an immune-related predictive and prognostic marker for multiple cancers, including lung squamous cell carcinoma.

A novel prognostic related lncRNA signature associated with amino acid metabolism in glioma

Background

Glioma is one of the deadliest malignant brain tumors in adults, which is highly invasive and has a poor prognosis, and long non-coding RNAs (lncRNAs) have key roles in the progression of glioma. Amino acid metabolism reprogramming is an emerging hallmark in cancer. However, the diverse amino acid metabolism programs and prognostic value remain unclear during glioma progression. Thus, we aim to find potential amino-related prognostic glioma hub genes, elaborate and verify their functions, and explore further their impact on glioma.

Methods

Glioblastoma (GBM) and low-grade glioma (LGG) patients' data were downloaded from TCGA and CCGA datasets. LncRNAs associated with amino acid metabolism were discriminated against via correlation analysis. LASSO analysis and Cox regression analysis were conducted to identify lncRNAs related to prognosis. GSVA and GSEA were performed to predict the potential biological functions of lncRNA. Somatic mutation data and CNV data were further built to demonstrate genomic alterations and the correlation between risk scores. Human glioma cell lines U251 and U87-MG were used for further validation in vitro experiments.

Results

There were eight amino-related lncRNAs in total with a high prognostic value that were identified via Cox regression and LASSO regression analyses. The high risk-score group presented a significantly poorer prognosis compared with the low risk-score group, with more clinicopathological features and characteristic genomic aberrations. Our results provided new insights into biological functions in the above signature lncRNAs, which participate in the amino acid metabolism of glioma. LINC01561 is one of the eight identified lncRNAs, which was adopted for further verification. In in vitro experiments, siRNA-mediated LINC01561 silencing suppresses glioma cells' viability, migration, and proliferation.

Conclusion

Novel amino-related lncRNAs associated with the survival of glioma patients were identified, and a lncRNA signature can predict glioma prognosis and therapy response, which possibly has vital roles in glioma. Meanwhile, it emphasized the importance of amino acid metabolism in glioma, particularly in providing deeper research at the molecular level.

Integrating Expression Data-Based Deep Neural Network Models with Biological Networks to Identify Regulatory Modules for Lung Adenocarcinoma

Simple Summary

The growing evidence suggested that competing endogenous RNAs (ceRNAs) have significant associations with tumor occurrence and progression, yet the regulatory mechanism of them in lung adenocarcinoma remains unclear. Identification of the regulatory modules for lung adenocarcinoma is a critical and fundamental step towards understanding the regulatory mechanisms during carcinogenesis. Deep neural network (DNN) models have become a powerful tool to intelligently recognize the sophisticated relationships of ceRNAs appropriately. In this paper, multiple deep neural network models were constructed using the expression data to identify regulatory modules for lung adenocarcinoma in biological networks. Three identified regulatory modules association with lung adenocarcinoma were validated from three aspects, i.e., literature review, functional enrichment analysis, and an independent dataset. The regulatory relationships between RNAs were validated in various datasets, including CPTAC, TCGA and an expression profile from the GEO database. Our study will contribute to improving the understanding of regulatory mechanisms in the carcinogenesis of lung adenocarcinoma and provide schemes for identifying novel regulatory modules of other cancers.

Abstract

Lung adenocarcinoma is the most common type of primary lung cancer, but the regulatory mechanisms during carcinogenesis remain unclear. The identification of regulatory modules for lung adenocarcinoma has become one of the hotspots of bioinformatics. In this paper, multiple deep neural network (DNN) models were constructed using the expression data to identify regulatory modules for lung adenocarcinoma in biological networks. First, the mRNAs, lncRNAs and miRNAs with significant differences in the expression levels between tumor and non-tumor tissues were obtained. MRNA DNN models were established and optimized to mine candidate mRNAs that significantly contributed to the DNN models and were in the center of an interaction network. Another DNN model was then constructed and potential ceRNAs were screened out based on the contribution of each RNA to the model. Finally, three modules comprised of miRNAs and their regulated mRNAs and lncRNAs with the same regulation direction were identified as regulatory modules that regulated the initiation of lung adenocarcinoma through ceRNAs relationships. They were validated by literature and functional enrichment analysis. The effectiveness of these regulatory modules was evaluated in an independent lung adenocarcinoma dataset. Regulatory modules for lung adenocarcinoma identified in this study provided a reference for regulatory mechanisms during carcinogenesis.

Identification of Potential Prognostic Biomarkers Associated with Monocyte Infiltration in Lung Squamous Cell Carcinoma

The five-year survival rate of lung squamous cell carcinoma is significantly lower than that of other cancer types. It is therefore urgent to discover novel prognosis biomarkers and therapeutic targets and understand their correction with infiltrating immune cells to improve the prognosis of patients with lung squamous cell carcinoma. In this study, we employed robust rank aggregation algorithms to overcome the shortcomings of small sizes and potential bias in each Gene Expression Omnibus dataset of lung squamous cell carcinoma and identified 513 robust differentially expressed genes including 220 upregulated and 293 downregulated genes from six microarray datasets. Functional enrichment analysis showed that these robust differentially expressed genes were obviously involved in the extracellular matrix and structure organization, epidermis development, cell adhesion molecule binding, p53 signaling pathway, and interleukin-17 signaling pathway to affect the progress of lung squamous cell carcinoma. We further identified six hub genes from 513 robust differentially expressed genes by protein-protein interaction network and 10 topological analyses. Moreover, the results of immune cell infiltration analysis from six integrated Gene Expression Omnibus datasets and our sequencing transcriptome data demonstrated that the abundance of monocytes was significantly lower in lung squamous cell carcinoma compared to controls. Immune correlation analysis and survival analysis of hub genes suggested that three hub genes, collagen alpha-1(VII) chain, mesothelin, and chordin-like protein 1, significantly correlated with tumor-infiltrating monocytes as well as may be potential prognostic biomarkers and therapy targets in lung squamous cell carcinoma. The investigation of the correlation of hub gene markers and infiltrating monocytes can also improve to well understand the molecular mechanisms of lung squamous cell carcinoma development.

CCNB1, Negatively Regulated by miR-559, Promotes the Proliferation, Migration, and Invasion of Ovarian Carcinoma Cells

Cyclin B1 (CCNB1) is regarded as an oncogene in multiple tumors. This work aims to investigate the expression, function, and related mechanisms of CCNB1 in ovarian carcinoma (OC). Three microarray datasets (GSE14407, GSE18520, and GSE54388) were obtained from the Gene Expression Omnibus (GEO) database and screened for differentially expressed genes (DEGs) of OC tissues and normal ovarian tissues. CCNB1 expression in OC tissues and paracancerous tissues was detected by immunohistochemistry. Kaplan-Meier plotter database was utilized to analyze the correlation between CCNB1 expression and the prognosis of OC patients. After the loss-of-function and gain-of-function cell models were established, cell counting kit-8 (CCK-8), bromo-deoxyuridine (BrdU), and transwell experiments were employed to examine the proliferation, migration, and invasion of OC cells, respectively. The targeting relationship between miR-559 and CCNB1 was verified using the dual-luciferase reporter gene experiment. The expressions of CCNB1 mRNA and miR-559 were detected by quantitative reverse transcription-polymerase chain reaction (qRT-PCR). Western blot was used to quantify the protein expression of CCNB1. In addition, xenograft nude mouse models were established to examine the effects of CCNB1 on lung metastasis in vivo. CCNB1 expression was markedly increased in OC tissues and cell lines. The overall survival, progression-free survival, and post-progression survival of OC patients with high CCNB1 expression were significantly shorter. OC cell proliferation, migration, and invasion were enhanced by CCNB1 overexpression while CCNB1 knockdown led to opposite effects. MiR-559 expression was remarkably reduced in OC tissues and cell lines, and miR-559 markedly suppressed the malignant characteristics of OC cells. Besides, miR-559 directly targeted the 3' UTR of CCNB1 mRNA and reduced CCNB1 expression at both the mRNA and protein levels. Overexpression of CCNB1 accelerated lung metastasis of OC cells in vivo. CCNB1, of which expression is modulated by miR-559, facilitates proliferation, migration, and invasion of OC cells, therefore, working as a potential therapeutic target of OC. This work provides new insights into the clinical diagnosis and treatment of OC.

Upregulated LINC01667 Expression Is Correlated With Poor Prognosis in Hepatocellular Carcinoma

The development of hepatocellular carcinoma (HCC) is a complex pathological process. Long intergenic non–protein-coding RNA 1667 (LINC01667, also known as MGC38584) plays an oncogenic role in several human cancers; however, its functional role in HCC tumorigenesis remains unknown. Here, we first evaluated the gene expression levels of LINC01667 in HCC using data from The Cancer Genome Atlas and Gene Expression Profiling Interactive Analysis (GEPIA) databases. We then elucidated the association between LINC01667 gene expression levels and the survival rates of patients with HCC. We detected the effect of LINC01667 on the malignant phenotypes (cell proliferation, migration, invasion and apoptosis etc.) and the MAPK and PI3K/AKT/mTOR signaling pathways of HepG2, SMMC-7721 and HUH7 cells. We also analyzed the sensitivity of HepG2, SMMC-7721 and HUH7 with different expression levels of LINC01667 to anti-HCC drugs in vitro. Based on data from the aforementioned databases and our experiments in vitro, we found that LINC01667 was overexpressed in HCC, and that patients with high LINC01667 levels had a remarkably poor overall survival rate. In addition, inhibition of LINC01667 expression suppressed the proliferation, migration and invasion of HepG2 and SMMC-7721 cells and promoted their apoptosis in vitro. In contrast, overexpression of LINC01667 promoted the proliferation, migration and invasion of HUH7 cells and suppressed their apoptosis in vitro. ChIRP-seq (chromatin isolation by RNA purification) showed that LINC01667 bound to MEG3, and downregulated the expression of MEG3. In addition, western blotting showed that LINC01667 could activate the NF-κB pathway to promote cancer progression. In conclusion, we report that LINC01667 is an important oncogene in HCC and may be used as a potential diagnostic and prognostic biomarker of HCC.

Integrative RNA-Seq and H3 Trimethylation ChIP-Seq Analysis of Human Lung Cancer Cells Isolated by Laser-Microdissection

Simple Summary

Tissue heterogeneity is one of the major problems in cancer genomics. Thus, we developed and conducted an RNA-Seq and ChIP-Seq integrative analysis of clinical lung tissue samples with the isolation of specific cell populations using laser-microdissection microscopy (LMD). The transcriptomic profile was successfully captured and somatically altered regions marked by histone H3 lysine 4 trimethylation (H3K4me3) were identified in lung cancer. We also observed the differential expressions of cancer-related genes near the altered proximal H3K4me3 regions, while altered distal H3K4me3 regions were overlapped with enhancer activity annotations of cancer regulatory genes. Additionally, proximal tumor-gained promoters were associated with the core components of polycomb repressive complex 2. Our study demonstrates the practical workflow of using LMD on clinical samples for integrative analyses, which improves the overall understanding of genetic and epigenetic dysregulation of malignancy.

Abstract

Our previous integrative study in gastric cancer discovered cryptic promoter activation events that drive the expression of important developmental genes. However, it was unclear if such cancer-associated epigenetic changes occurred in cancer cells or other cell types in bulk tissue samples. An integrative analysis consisting of RNA-Seq and H3K4me3 ChIP-Seq was used. This workflow was applied to a set of matched normal lung tissues and non-small cell lung cancer (NSCLC) tissues, for which the stroma and tumor cell parts could be isolated by laser-microdissection microscopy (LMD). RNA-Seq analysis showed subtype-specific differential expressed genes and enriched pathways in NSCLC. ChIP-Seq analysis results suggested that the proximal altered H3K4me3 regions were located at differentially expressed genes involved in cancer-related pathways, while altered distal H3K4me3 regions were annotated with enhancer activity of cancer regulatory genes. Interestingly, integration with ENCODE data revealed that proximal tumor-gained promoters were associated with EZH2 and SUZ12 occupancies, which are the core components of polycomb repressive complex 2 (PRC2). This study used LMD on clinical samples for an integrative analysis to overcome the tissue heterogeneity problem in cancer research. The results also contribute to the overall understanding of genetic and epigenetic dysregulation of lung malignancy.

Four hub genes regulate tumor infiltration by immune cells, antitumor immunity in the tumor microenvironment, and survival outcomes in lung squamous cell carcinoma patients

In this study, we performed bioinformatics analyses to identify hub genes that regulate tumor infiltration by immune cells and antitumor immunity in the lung squamous cell carcinoma (LUSC). We identified 1738 robust and stable differentially expressed genes (DEGs) in the LUSC tissues based on robust rank aggregation (RRA) analysis of RNA-sequencing data from 5 GEO-LUSC datasets. We then classified TCGA-LUSC patients based on ssGSEA and ESTIMATE analyses of LUSC tissues into high, medium and low immunity subgroups showing significant differences in tumor purity. Weighted gene co-expression network analysis of the robust DEGs revealed five immunity-related modules, including the brown module with 762 DEGs and 30 hub genes showing the highest correlation with the immunity-related LUSC patient subgroups and their clinicopathological characteristics. We selected four hub genes, LAPTM5, C1QC, CSF1R and SLCO2B1, for validation of the immunity status and prognosis of LUSC patients. High expression of these four genes correlated with increased infiltration of immune cell types, upregulation of the immunosuppressive TOX pathway genes, CD8⁺ T cell exhaustion, and shorter overall survival of LUSC patients. These findings demonstrate that four hub genes regulate tumor infiltration of immune cells, anti-tumor immunity, and survival outcomes in LUSC patients.

DNA Methylation in Ovarian Cancer Susceptibility

Epigenetic alterations are somatically acquired over the lifetime and during neoplastic transformation but may also be inherited as widespread 'constitutional' alterations in normal tissues that can cause cancer predisposition. Epithelial ovarian cancer (EOC) has an established genetic susceptibility and mounting epidemiological evidence demonstrates that DNA methylation (DNAm) intermediates as well as independently contributes to risk. Targeted studies of known EOC susceptibility genes (CSGs) indicate rare, constitutional BRCA1 promoter methylation increases familial and sporadic EOC risk. Blood-based epigenome-wide association studies (EWAS) for EOC have detected a total of 2846 differentially methylated probes (DMPs) with 71 genes replicated across studies despite significant heterogeneity. While EWAS detect both symptomatic and etiologic DMPs, adjustments and analytic techniques may enrich risk associations, as evidenced by the detection of dysregulated methylation of BNC2-a known CSG identified by genome-wide associations studies (GWAS). Integrative genetic-epigenetic approaches have mapped methylation quantitative trait loci (meQTL) to EOC risk, revealing DNAm variations that are associated with nine GWAS loci and, further, one novel risk locus. Increasing efforts to mapping epigenome variation across populations and cell types will be key to decoding both the genomic and epigenomic causal pathways to EOC.

Comprehensive transcriptomic analysis identifies novel regulators of lung adenocarcinoma

Lung adenocarcinoma (LA) is a subtype of lung cancer that accounts for about 40% of all lung cancers. Analysis of molecular mechanisms controlling this cancer can help scientists to detect, control and treat LA. Here, a microarray dataset (GSE118370) containing six normal lung (NL) and six LA samples was screened using GEO2R to find differentially expressed genes (DEGs). Then, DAVID, KEGG and ChEA were used to analyze DEGs-related gene ontology, pathways and transcription factors (TFs), respectively. The Protein-protein interaction network for DEGs and TFs was constructed by STRING and Cytoscape. To find microRNAs and metabolites associated with DEGs, miRTarBase and HMDB were used, respectively. It was found that 350 genes were upregulated and 608 genes were downregulated in LA. The upregulated genes or LA-related gens were enriched in biological process and pathways such as extracellular matrix disassembly and p53 signaling pathway, whereas the downregulated genes or NL-related genes were enriched in cell adhesion and cell-surface receptor signaling pathway. ESR1, KIF18B, BIRC5, CHEK1, CCNB1 and AURKA were determined as hub genes for LA. FOXA1 and TFAP2A had the highest number of connectivity in LA-related TFs. hsa-miR-192-5p and hsa-miR-215-5p could target the highest number of LA-related genes. Metabolite analysis showed that Estrone and NADPH were among the top ten metabolites associated with LA-related genes. Taken together, LA-related genes, especially the hub genes, TFs, and metabolites might be used as novel markers for LA, as well as for diagnosis and guiding therapeutic strategies of LA.

Fibroblast‑derived exosomal microRNA‑369 potentiates migration and invasion of lung squamous cell carcinoma cells via NF1‑mediated MAPK signaling pathway

Cancer-associated fibroblasts (CAFs) exhibit tumor-stimulating properties and are associated with poor survival in several types of cancer, making them potential therapeutic targets. The present study aimed to determine whether CAFs were associated with cell migration and invasion in lung squamous cell carcinoma (LUSC), as well as their association with microRNA-369 (miR-369) in these processes. Firstly, the changes of the malignant biological behavior were observed by treating the LUSC cells with the CAFs-derived extracellular vesicles (CAFs-EVs). Subsequently, the differentially expressed miRNAs in the cells treated with CAFs-EVs were analyzed by microarray analysis. Following inhibition of miR-369 expression in CAFs-EVs, LUSC cells were co-cultured, and the malignant biological behavior of the cells was re-examined. Then, through bioinformatics analysis and verification, the mRNA targets of miR-369 and the corresponding downstream signaling pathway were screened out. Finally, the effects of CAFs-EVs on the growth and metastasis of LUSC were demonstrated by in vivo tumor formation and metastasis experiments. It was identified that miR-369 was expressed at a relatively high level in the CAFs-EVs. Neurofibromin-1 (NF1) was hypothesized as a direct target of miR-369 in LUSC. Also, the overexpression of miR-369 activated the mitogen-activated protein kinase signaling pathway by interacting with NF1, consequently potentiating LUSC cell growth. The present study provided novel insights into the action of miR-369 in CAFs-EVs in controlling LUSC cell migration, invasion and tumorigenesis, and identified miR-369 in CAFs-EVs as an important prognostic marker and therapeutic target.

Molecular Signature of Subtypes of Non-Small-Cell Lung Cancer by Large-Scale Transcriptional Profiling: Identification of Key Modules and Genes by Weighted Gene Co-Expression Network Analysis (WGCNA)

Non-small-cell lung cancer (NSCLC) represents a heterogeneous group of malignancies consisting essentially of adenocarcinoma (ADC) and squamous cell carcinoma (SCC). Although the diagnosis and treatment of ADC and SCC have been greatly improved in recent decades, there is still an urgent need to identify accurate transcriptome profile associated with the histological subtypes of NSCLC. The present study aims to identify the key dysregulated pathways and genes involved in the development of lung ADC and SCC and to relate them with the clinical traits. The transcriptional changes between tumour and normal lung tissues were investigated by RNA-seq. Gene ontology (GO), canonical pathways analysis with the prediction of upstream regulators, and weighted gene co-expression network analysis (WGCNA) to identify co-expressed modules and hub genes were used to explore the biological functions of the identified dysregulated genes. It was indicated that specific gene signatures differed significantly between ADC and SCC related to the distinct pathways. Of identified modules, four and two modules were the most related to clinical features in ADC and SCC, respectively. CTLA4, MZB1, NIP7, and BUB1B in ADC, as well as GNG11 and CCNB2 in SCC, are novel top hub genes in modules associated with tumour size, SUVmax, and recurrence-free survival. Our research provides a more effective understanding of the importance of biological pathways and the relationships between major genes in NSCLC in the perspective of searching for new molecular targets.