Identification of genes associated with cancer progression and prognosis in lung adenocarcinoma: Analyses based on microarray from Oncomine and The Cancer Genome Atlas databases

Study of the mechanism by which Xiaoyan decoction combined with E7449 regulates tumorigenesis in lung adenocarcinoma

TNKS is a new target for the treatment of lung adenocarcinoma, the synergistic effects of the TCM compound Xiaoyan decoction and the TNKS inhibitor E7449 in the intervention on TNKS were investigated, and the possible underlying mechanisms involved were clarified. Immunohistochemistry was used to analyse TNKS expression in tumour tissues. The impact of targeting TNKS on cell growth, invasion, apoptosis, key genes and signalling pathways was investigated in tumour cells by Western blotting, rescue experiments, colony formation assays, flow cytometry and label-free experiments. Tumour xenografts with A549 cells were then transplanted for in vivo study. We found that TNKS high expression was closely related to the advanced tumour stage and tumour size in lung adenocarcinom. After TNKS was knocked down in vitro, the growth, proliferation, migration and invasion were markedly reduced in A549 and H1975 cells. We subsequently applied the Xiaoyan decoction and TNKS inhibitors to intervene in lung adenocarcinoma. Xiaoyan decoction and E7449 suppressed TNKS expression and inhibited adenocarcinoma cell proliferation, migration, invasion and apoptosis in vitro. Proteomic analysis revealed that E7449 treatment may be most closely associated with the classic Wnt/β-catenin pathway, whereas Xiaoyan decoction treatment may be related to the WNT/PLAN pathway. Xenograft studies confirmed that E7449 or Xiaoyan decoction inhibited lung tumour growth in vivo and attenuated the Wnt signalling pathway in adenocarcinoma. These findings suggest that TNKS is a novel therapeutic target. TCM preparations and small molecule inhibitors are expected to constitute an effective combination strategy.

An integrative analysis of GEO data to identify possible therapeutic biomarkers of prostate cancer and targeting potential protein through Zea mays phytochemicals by virtual screening approaches

Prostate cancer (PC) is a prevalent type of cancer among men. Delaying the treatment of patients with upgraded or upstaged cancer may lead to unmanageable circumstances. The aim of this study is to contribute to the finding of biomarkers that are specific to PC and identify drug candidates derived from plants. The information about cancer is critical for clinicians to make decisions about patient treatment in the era of precision medicine. Advances in genomics technology have opened up new possibilities for identifying genes that are associated with cancer, including PC. This study identifies novel differentially expressed genes for PC. The seven PC microarray datasets were selected from the National Center for Biotechnology Information (NCBI)/Gene Expression Omnibus (GEO). The differentially expressed genes (DEGs) were found based on a fold change of |logFC| ≥ 1 and an adjusted p-value of <0.05. The DEGs were further studied using several bioinformatics tools, including STRING, CytoHubba, SRplot, Coremine Medical database, FunRich and GeneMANIA, cBioPortal. The six new potential biomarkers, GAGE2A, GAGE12G, GAGE2E, GAGE13, GAGE12F and CSAG1 were identified. These biomarkers are associated with biological processes (BPs) such as cell division, and gene expression regulation, so these genes may have a crucial role in PC progression and may serve as potential biomarkers for PC. A total of 497 phytochemicals from corn plants have been screened against the target protein and found LTS0176591 as the best lead molecule with docking score of -6.31 kcal/mol. Further, molecular mechanics-generalized born surface area (MM-GBSA), molecular dynamics simulation, principal component analysis (PCA), free energy landscape (FEL) and molecular mechanics-Poisson-Boltzmann surface area (MM-PBSA) were carried out to validate the findings.Communicated by Ramaswamy H. Sarma.

A novel artificial intelligence approach to detect the breast cancer using KNNet technique with EPM gene profiling

Women's most frequent type of cancer is breast cancer, second only to lung cancer. This paper summarizes changes in genomics and epigenetics and incremental biological activities. A tumour develops through a series of phases involving a separate abnormal gene. Even though many diseases cause DNA mutations, most treatments are designed to relieve symptoms rather than change the DNA. Clustering short palindromic repeats (CRISPR) or Cas9 is the primary approach for discovering and confirming tumorigenic genomic targets. A Kohonen neural network with an expression programming model was developed for gene selection. The main problem in genetic selection is reducing the number of features chosen while maintaining accuracy. This purpose is accomplished systematically. In the end, the approach method performed better than the existing quantum squirrel-inspired algorithm and the recurrent neural network oppositional call search algorithm for genetic selection. The KNNet-EPM model used an expression programming approach to identify gene biomarkers for breast cancer. This method was achieved with RAE of 42%, sensitivity of 93%, f1 score of 88%, accuracy of 98%, kappa score of 83%, specificity of 92% and MAE of 30%.

Robust Bayesian variable selection for gene-environment interactions

Gene-environment (G× E) interactions have important implications to elucidate the etiology of complex diseases beyond the main genetic and environmental effects. Outliers and data contamination in disease phenotypes of G× E studies have been commonly encountered, leading to the development of a broad spectrum of robust regularization methods. Nevertheless, within the Bayesian framework, the issue has not been taken care of in existing studies. We develop a fully Bayesian robust variable selection method for G× E interaction studies. The proposed Bayesian method can effectively accommodate heavy-tailed errors and outliers in the response variable while conducting variable selection by accounting for structural sparsity. In particular, for the robust sparse group selection, the spike-and-slab priors have been imposed on both individual and group levels to identify important main and interaction effects robustly. An efficient Gibbs sampler has been developed to facilitate fast computation. Extensive simulation studies, analysis of diabetes data with single-nucleotide polymorphism measurements from the Nurses' Health Study, and The Cancer Genome Atlas melanoma data with gene expression measurements demonstrate the superior performance of the proposed method over multiple competing alternatives.

Pyrimidinergic receptor P2Y6 expression is elevated in lung adenocarcinoma and is associated with poor prognosis

BACKGROUD

Previous in vitro studies have indicated that pyrimidinergic receptor P2Y6 (P2RY6, P2Y6 receptor) may function as a cancer-promoting factor in lung adenocarcinoma (LUAD). However, the prognostic significance of P2RY6 expression in LUAD has not been investigated.

OBJECTIVE

This study aimed to assess the impact of P2RY6 expression on the survival of patients with LUAD.

METHODS

First, we assessed P2RY6 mRNA and protein expression in LUAD and non-cancerous lung tissues using the online bioinformatics analysis tool GEPIA, fresh LUAD tissues, and LUAD tissue microarrays (TMAs). Second, we investigated the correlation between P2RY6 expression and clinicopathological parameters of LUAD patients based on data from The Cancer Genome Atlas (TCGA) database and TMAs. Finally, we analyzed the prognostic significance of P2RY6 expression in LUAD using the online survival analysis tool Kaplan-Meier Plotter and data from TMAs.

RESULTS

We demonstrated that P2RY6 mRNA and protein expression levels in LUAD tissues were significantly higher than those in non-cancerous lung tissues. The expression of P2RY6 in LUAD was positively correlated with poor differentiation, more lymph node metastasis, and more advanced clinical stage. Higher P2RY6 expression level was correlated with shorter survival of the LUAD patients. Univariate and multivariate Cox regression analyses indicated that higher P2RY6 tumor expression was an independent unfavorable prognostic factor for LUAD patients.

CONCLUSIONS

P2RY6 expression was elevated in LUAD and correlated with poor prognosis.

The Association of Aberrant Expression of FGF1 and mTOR-S6K1 in Colorectal Cancer

Colorectal cancer (CRC) is one of the most frequent malignant neoplasms worldwide, and the effect of treatments is limited. Fibroblast growth factor 1 (FGF1) has been involved in a wide variety of several malignant diseases and takes part in the tumorigenesis of CRC. However, the function and mechanism of FGF1 in CRC remains elusive. In this study, the results indicated that FGF1 is elevated in CRC tissues and linked with poor prognosis (P < 0.001). In subgroup analysis of FGF1 in CRC, regardless of any clinic-factors except gender, high level FGF1 expression was associated with markedly shorter survival (P < 0.05). In addition, the expression of p-S6K1 and FGF1 was not associated in normal tissue (P = 0.781), but their expression was closely related in tumor tissue (P = 0.010). The oncogenic role of FGF1 was determined using in vitro and in vivo functional assays. FGF1 depletion inhibited the proliferation and migration of CRC cells in vitro and vivo. FGF1 was also significantly correlated with mTOR-S6K1 pathway on the gene and protein levels (P < 0.05). In conclusion, FGF1 acts as a tumor activator in CRC, and against FGF1 may provide a new visual field on treating CRC, especially for mTORC1-targeted resistant patients.

Collagen type 1 alpha 1 chain is a novel predictive biomarker of poor progression-free survival and chemoresistance in metastatic lung cancer

Background: Collagen type 1 alpha 1 chain (COL1A1) is an extracellular matrix protein comprising two alpha 1 chains and one alpha 2 chain. Our previous study identified that COL1A1 is the key gene during the development and progression of lung adenocarcinoma by multi-omics analysis. However, the clinical significance of COL1A1 expression in lung cancer samples remains largely unknown. Here, we aimed to evaluate the level of COL1A1 in lung cancer samples and correlate its level with the clinical outcome.

Methods:COL1A1 gene expression in lung cancer samples was analyzed using the Oncomine database (www.oncomine.org). A total of 308 lung cancer samples (208 formalin-fixed paraffin-embedded tissues and 100 blood samples) were assessed for protein expression of COL1A1. Immunohistochemistry staining and enzyme-linked immunosorbent assay were used to detect COL1A1 expression in tissues and serum, respectively.

Results: We identified an elevation of COL1A1 in mRNA level and gene amplification in lung cancer tissues compared with normal lung tissues. High COL1A1 expression was observed in lung cancer tissues and serum (P < 0.05), it was significantly correlated with the peripheral type tumor, the larger diameter of the tumor, the occurrence of lymph node metastases and distant metastases, a higher TNM stage, and smoking (P < 0.05). High COL1A1 expression was associated with poor progression-free survival (PFS) and chemoresistance in lung cancer patients (P < 0.05). Multivariable Cox-regression analysis showed that COL1A1 expression was an independent prognostic factor (P < 0.05). Furthermore, the area under the receiver operating characteristic (AUC) curve was 0.909 for the combined COL1A1 and carcinoembryonic antigen (CEA) measurement.

Conclusion: Our findings revealed that COL1A1 could be used as a novel diagnostic, prognostic, and chemoresistance biomarker of human lung cancer, and these results provide a potential therapeutic strategy for lung cancer patients.

SHP2 inhibition enhances the anticancer effect of Osimertinib in EGFR T790M mutant lung adenocarcinoma by blocking CXCL8 loop mediated stemness

BACKGROUND

Additional epidermal growth factor receptor (EGFR) mutations confer the drug resistance to generations of EGFR targeted tyrosine kinase inhibitor (EGFR-TKI), posing a major challenge to developing effective treatment of lung adenocarcinoma (LUAD). The strategy of combining EGFR-TKI with other synergistic or sensitizing therapeutic agents are considered a promising approach in the era of precision medicine. Moreover, the role and mechanism of SHP2, which is involved in cell proliferation, cytokine production, stemness maintenance and drug resistance, has not been carefully explored in lung adenocarcinoma (LUAD).

METHODS

To evaluate the impact of SHP2 on the efficacy of EGFR T790M mutant LUAD cells to Osimertinib, SHP2 inhibition was tested in Osimertinib treated LUAD cells. Cell proliferation and stemness were tested in SHP2 modified LUAD cells. RNA sequencing was performed to explore the mechanism of SHP2 promoted stemness.

RESULTS

This study demonstrated that high SHP2 expression level correlates with poor outcome of LUAD patients, and SHP2 expression is enriched in Osimertinib resistant LUAD cells. SHP2 inhibition suppressed the cell proliferation and damaged the stemness of EGFR T790M mutant LUAD. SHP2 facilitates the secretion of CXCL8 cytokine from the EGFR T790M mutant LUAD cells, through a CXCL8-CXCR1/2 positive feedback loop that promotes stemness and tumorigenesis. Our results further show that SHP2 mediates CXCL8-CXCR1/2 feedback loop through ERK-AKT-NFκB and GSK3β-β-Catenin signaling in EGFR T790M mutant LUAD cells.

CONCLUSIONS

Our data revealed that SHP2 inhibition enhances the anti-cancer effect of Osimertinib in EGFR T790M mutant LUAD by blocking CXCL8-CXCR1/2 loop mediated stemness, which may help provide an alternative therapeutic option to enhance the clinical efficacy of osimertinib in EGFR T790M mutant LUAD patients.

Diagnostic and Prognostic Significance of Keap1 mRNA Expression for Lung Cancer Based on Microarray and Clinical Information from Oncomine Database

We performed a bioinformatics analysis with validation by multiple databases, aiming to evaluate the diagnostic and prognostic value of Kelch-like ECH-associated protein 1 (Keap1) mRNA for lung cancer, and to explore possible mechanisms. Diagnostic performance of Keap1 mRNA was determined by receiver operating characteristic (ROC) curve analysis. Prognostic implication of Keap1 mRNA was estimated by Kaplan-Meier survival analysis. Co-expressed genes with both Keap1 and Nfe2L2 were identified by LinkedOmics. Mechanisms of Keap1-Nfe2L2-co-expressed genes underlying the pathogenesis of lung cancer were explored by function enrichment and pathway analysis. The ROC curve analysis determined a good diagnostic performance of Keap1 mRNA for lung squamous cell carcinoma (LUSC), with an area under the ROC curve (AUC) of 0.833, sensitivity of 72.7%, and specificity of 90.6% (P<0.001). Multivariate Cox regression recognized high Keap1 mRNA to be an independent risk factor of mortality for overall lung cancer [hazard ratio (HR): 11.034, P=0.044], but an independent antagonistic factor for lung adenocarcinoma (LUAD) (HR: 0.404, P<0.001). Validation by UALCAN and GEPIA supported Oncomine findings regarding the diagnostic value of Keap1 mRNA for LUSC, but denied its prognostic value. After screening, we identified 17 co-expressed genes with both Keap1 and Nfe2L2 for LUAD, and 22 for LUSC, mainly enriched in signaling pathway of oxidative stress-induced gene expression via Nrf2. In conclusion, Keap1 mRNA has a good diagnostic performance, but controversial prognostic efficacy for LUSC. The pathogenesis of lung cancer is associated with Keap1-Nfe2L2-co-expressed genes by signaling pathway of oxidative stress-induced gene expression via Nrf2.

Identification of Key Genes With Differential Correlations in Lung Adenocarcinoma

Background

With the advent of large-scale molecular profiling, an increasing number of oncogenic drivers contributing to precise medicine and reshaping classification of lung adenocarcinoma (LUAD) have been identified. However, only a minority of patients archived improved outcome under current standard therapies because of the dynamic mutational spectrum, which required expanding susceptible gene libraries. Accumulating evidence has witnessed that understanding gene regulatory networks as well as their changing processes was helpful in identifying core genes which acted as master regulators during carcinogenesis. The present study aimed at identifying key genes with differential correlations between normal and tumor status.

Methods

Weighted gene co-expression network analysis (WGCNA) was employed to build a gene interaction network using the expression profile of LUAD from The Cancer Genome Atlas (TCGA). R package DiffCorr was implemented for the identification of differential correlations between tumor and adjacent normal tissues. STRING and Cytoscape were used for the construction and visualization of biological networks.

Results

A total of 176 modules were detected in the network, among which yellow and medium orchid modules showed the most significant associations with LUAD. Then genes in these two modules were further chosen to evaluate their differential correlations. Finally, dozens of novel genes with opposite correlations including ATP13A4-AS1, HIGD1B, DAP3, and ISG20L2 were identified. Further biological and survival analyses highlighted their potential values in the diagnosis and treatment of LUAD. Moreover, real-time qPCR confirmed the expression patterns of ATP13A4-AS1, HIGD1B, DAP3, and ISG20L2 in LUAD tissues and cell lines.

Conclusion

Our study provided new insights into the gene regulatory mechanisms during transition from normal to tumor, pioneering a network-based algorithm in the application of tumor etiology.

Identifying of biomarkers associated with gastric cancer based on 11 topological analysis methods of CytoHubba

Gastric cancer (GC) is one of the most common types of malignancy. Its potential molecular mechanism has not been clarified. In this study, we aimed to explore potential biomarkers and prognosis-related hub genes associated with GC. The gene chip dataset GSE79973 was downloaded from the GEO datasets and limma package was used to identify the differentially expressed genes (DEGs). A total of 1269 up-regulated and 330 down-regulated genes were identified. The protein-protein interactions (PPI) network of DEGs was constructed by STRING V11 database, and 11 hub genes were selected through intersection of 11 topological analysis methods of CytoHubba in Cytoscape plug-in. All the 11 selected hub genes were found in the module with the highest score from PPI network of all DEGs by the molecular complex detection (MCODE) clustering algorithm. In order to explore the role of the 11 hub genes, we performed GO function and KEGG pathway analysis for them and found that the genes were enriched in a variety of functions and pathways among which cellular senescence, cell cycle, viral carcinogenesis and p53 signaling pathway were the most associated with GC. Kaplan-Meier analysis revealed that 10 out of the 11 hub genes were related to the overall survival of GC patients. Further, seven of the 11 selected hub genes were verified significantly correlated with GC by uni- or multivariable Cox model and LASSO regression analysis including C3, CDK1, FN1, CCNB1, CDC20, BUB1B and MAD2L1. C3, CDK1, FN1, CCNB1, CDC20, BUB1B and MAD2L1 may serve as potential prognostic biomarkers and therapeutic targets for GC.

LncRNA CBR3-AS1 potentiates Wnt/β-catenin signaling to regulate lung adenocarcinoma cells proliferation, migration and invasion

Background

Long non-coding RNAs (lncRNAs) are pervasively transcribed in genome and emerging as a new player in tumorigenesis due to their functions in transcriptional, posttranscriptional and epigenetic mechanisms of gene regulation. As the most frequent malignancy and the foremost source of cancer mortality, lung cancer is a heterogeneous disorder. The most common type of lung cancer is Non-small cell lung cancer (NSCLC), occupying 85% of the total cases, and the main subtypes of NSCLC include lung adenocarcinoma (LAD), large cell carcinoma (LCC), and lung squamous cell carcinoma (LSCC). Recently, numerous lncRNAs have been reported to be strongly linked to NSCLC. In the present study, we found that a new lncRNA CBR3-AS1 is highly expressed in lung cancer. In addition, we also examined the expression of lncRNA CBR3-AS1 in 60 of LADs, 40 of LCCs and 40 of LSCCs patient samples, finding that CBR3-AS1 was specificity highly expressed in LAD cancer tissues. Mechanically, we discovered that CBR3-AS1 could regulate the proliferation, migration and invasion of LAD cells through targeting Wnt/β-catenin signaling.

Methods

Real-time PCR, RNA-pulldown, RIP, western blotting, lentivirus transfection, luciferase reporter assays, cell proliferation assays, colony formation assays, wound healing scratch assays and transwell assays were employed to examine the relationship between lncRNA CBR3-AS1 and its regulation of Wnt/β-catenin signaling in LAD cells.

Results

LncRNA CBR3-AS1 is highly-expressed in LAD and cell lines. LncRNA CBR3-AS1 shows physical association with β-catenin. CBR3-AS1 could facilitate Wnt/β-catenin signaling activation thought promoting nuclear localization of β-catenin. CBR3-AS1 promotes LAD cell proliferation, migration and invasion by targeting Wnt/β-catenin signaling.

Conclusion

It can be found that a new functional lncRNA CBR3-AS1 could promote nuclear localization of β-catenin so as to facilitate Wnt/β-catenin signaling activation and regulate the proliferation, migration and invasion of LAD cells.

Linc00426 accelerates lung adenocarcinoma progression by regulating miR-455-5p as a molecular sponge

Increasing lines of evidence indicate the role of long non-coding RNAs (LncRNAs) in gene regulation and tumor development. Hence, it is important to elucidate the mechanisms of LncRNAs underlying the proliferation, metastasis, and invasion of lung adenocarcinoma (LUAD). We employed microarrays to screen LncRNAs in LUAD tissues with and without lymph node metastasis and revealed their effects on LUAD. Among them, Linc00426 was selected for further exploration in its expression, the biological significance, and the underlying molecular mechanisms. Linc00426 exhibits ectopic expression in LUAD tissues and cells. The ectopic expression has been clinically linked to tumor size, lymphatic metastasis, and tumor differentiation of patients with LUAD. The deregulation of Linc00426 contributes to a notable impairment in proliferation, invasion, metastasis, and epithelial–mesenchymal transition (EMT) in vitro and in vivo. Mechanistically, the deregulation of Linc00426 could reduce cytoskeleton rearrangement and matrix metalloproteinase expression. Meanwhile, decreasing the level of Linc00426 or increasing miR-455-5p could down-regulate the level of UBE2V1. Thus, Linc00426 may act as a competing endogenous RNA (ceRNA) to abate miR-455-5p-dependent UBE2V1 reduction. We conclude that Linc00426 accelerates LUAD progression by acting as a molecular sponge to regulate miR-455-5p, and may be a potential novel tumor marker for LUAD.

High Serine-arginine Protein Kinase 1 Expression with PTEN Loss Defines Aggressive Phenotype of Prostate Cancer Associated with Lethal Outcome and Decreased Overall Survival

Background

Serine-arginine protein kinase 1 (SRPK1) has been implicated in prostate cancer (PCa) progression. However, its prognostic value and association with ERG and PTEN expression, two of the most common genetic alterations, have not been explored fully.

Objective

We assessed the prognostic value of SRPK1 in association with ERG and PTEN in a cohort of patients managed nonsurgically by androgen deprivation therapy (ADT) for advanced disease.

Design, setting, and participants

The study cohort consisted of men diagnosed with PCa by transurethral resection of the prostate (TURP; n = 480). The patients were divided into three main groups: incidental (patients with Gleason score [GS] ≤7 with no prior ADT), advanced (patients with GS ≥8 with no prior ADT), and castrate-resistant PCa (patients with prior ADT).

Outcome measurements and statistical analysis

A total of 480 TURP samples were assessed by immunohistochemistry for SRPK1, ERG, and PTEN, and results were correlated with Gleason grade group (GG), overall survival (OS), and PCa-specific mortality (PCSM).

Results and limitations

High SRPK1 expression was noted in 105/455 (23%) available patient cores. Expression of SRPK1 was associated with Gleason grade grouping (p < 0.0001) with high expression detected in 22/74 (33%) with GG 5. High SRPK1 was not associated with ERG positivity (p = 0.18) but was significantly associated with PTEN intensity (p = 0.001). High SRPK1 was associated with OS (hazard ratio [HR] 1.99; confidence interval [CI]: 1.57–2.54, p < 0.0001) and PCSM (HR 1.64; CI: 1.19–2.26, p < 0.002). Adjusting for Gleason score, patients with high SRPK1 and negative PTEN had the worst clinical outcome for both OS and PCSM compared with other patients (p < 0.0001, HR: 3.02; CI: 1.87–4.88 and HR: 6.40, CI: 3.19–12.85, respectively).

Conclusions

High SRPK1 is associated with worse OS and PCSM. Moreover, patients with high SRPK1 expression and loss of PTEN had the worst clinical outcome for OS and cancer-specific mortality. Combined status of SRPK1 and PTEN may provide added value in stratifying patients into various prognostic groups.

Patient summary

The expression of serine-arginine protein kinase 1 (SRPK1) combined with PTEN has a significant prognostic role in prostate cancer patients. Patients with high SRPK1 expression and negative PTEN had the worst clinical outcome for overall survival and cancer-specific mortality.

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.

Low Levels of SPARC are Associated with Tumor Progression and Poor Prognosis in Human Endometrial Carcinoma

Background

SPARC (secreted protein acidic and rich in cysteine), also known as osteonectin, BM-40, and 43 K protein, is a matricellular protein associated with various tumor progressions. The aim of this research was to investigate the prognostic value of SPARC in endometrial carcinoma (EC) and its function in cancer cell invasion and metastasis.

Methods

From both mRNA and protein levels, SPARC expression in normal endometrial tissue and EC tissue, normal endometrial cells and 4 EC cell lines (KLE, HEC-1A, HEC-1B, Ishikawa) were evaluated by immunohistochemistry (IHC) or immunocytochemistry (ICC), quantitative real-time PCR (qRT-PCR) and Western blotting. RNA interference mediated by lentivirus was performed to get the stable SPARC down-expressing cells. The functional analysis techniques in vitro and in vivo were used to detect the effects of SPARC knockdown on EC cell proliferation, apoptosis, invasion and metastasis.

Results

The expressions of SPARC in EC tissues and cells were much lower than those in normal endometrial cells and tissues; meanwhile, its low expression was closely related to the malignant clinicopathological characteristics of EC. SPARC knockdown could inhibit apoptosis, promote the process of EMT and improve the proliferation and invasion capacities of EC cells in vitro and in vivo.

Conclusion

The low expression of SPARC was detected in EC tissues and cells, which was positively correlated with the poor prognosis of EC patients. SPARC acted as a tumor suppressor gene that hindered EC progression, which proposed a new therapeutic strategy for EC treatment.

Stemness Related Genes Revealed by Network Analysis Associated With Tumor Immune Microenvironment and the Clinical Outcome in Lung Adenocarcinoma

Lung adenocarcinoma (LUAD) is one of the leading fatal malignancy with high morbidity and mortality worldwide. However, due to its complicated mechanism and lack of effective clinical therapeutics, early diagnosis and prognosis are still unsatisfactory. Most of the previous studies focused on cancer stem cells (CSCs), the relationship between cancer stemness (stem-like characteristics) and anti-tumor immunity has not been clearly revealed. Therefore, this study aimed to comprehensively analyze the role of cancer stemness and tumor microenvironment (TME) in LUAD using weighted gene co-expression network analysis (WGCNA). We constructed a gene co-expression network, identified key modules, and hub genes, and further explored the relationship between hub gene expression and cancer immunological characteristics through a variety of algorithms, including Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data (ESTIMATE) and Gene Set Enrichment Analysis (GSEA). The hub genes were renamed stemness related genes (SRGs), whose functions were examined at the transcription and protein levels through survival analysis with additional samples, Oncomine database, immunohistochemistry, single cell RNA sequencing (scRNA-seq) and single-sample Gene Set Enrichment Analysis (ssGSEA). Subsequently, Tumor Immune Dysfunction and Exclusion (TIDE) and Connectivity Map (CMap) were implemented for treatment and prognosis analyses. As a result, 15 co-expressed SRGs (CCNA2, CCNB1, CDC20, CDCA5, CDCA8, FEN1, KIF2C, KPNA2, MCM6, NUSAP1, RACGAP1, RRM2, SPAG5, TOP2A, and TPX2) were identified. The overexpression of which was discovered to be associated with reduced immune infiltration in LUAD. It was discovered that there was a general negative correlation between cancer stemness and immunity. The expression of SRGs could probably affect our tumor occurrence, progression, the efficacy of chemotherapy and immunotherapy, and clinical outcomes. In conclusion, the 15 SRGs reported in our study may be used as potential candidate biomarkers for prognostic indicators and therapeutic targets after further validation.

SMAD-6, -7 and -9 are potential molecular biomarkers for the prognosis in human lung cancer

SMADs, a family of proteins that function as signal transducers and transcriptional regulators to regulate various signaling pathways, including the transforming growth factor-β signaling pathway, are similar to the mothers against decapentaplegic family of genes and the sma gene family in Caenorhabditis elegans. SMADs generate context-dependent modulation by interacting with various sequence-specific transcription factors, such as E2F4/5, c-Fos, GATA3, YY1 and SRF, which have been found to serve a key role in lung carcinoma oncogenesis and progression. However, the prognostic values of the eight SMADs in lung cancer have not been fully understood. In the present study, the expression levels and survival data of SMADs in patients with lung carcinoma from the Oncomine, Gene Expression Profiling Interactive Analysis, Kaplan-Meier plotter and cBioPortal databases were downloaded and analyzed. It was found that the mRNA expression levels of SMAD-6, -7 and -9 were decreased in lung adenocarcinoma and squamous cell carcinoma compared with that in adjacent normal tissues, while there was no significant difference in SMADs 1-5. Survival analysis revealed that not only were low transcriptional levels of SMAD-6, -7 and -9 associated with low overall survival but they also had prognostic role for progression-free survival and post-progression survival (P<0.05) in patients with lung carcinoma. In conclusion, the present study demonstrated that SMAD-6, -7 and -9 are potential biomarkers for the prognosis of patients with lung carcinoma.

Bioinformatics Analysis of Key Genes and circRNA-miRNA-mRNA Regulatory Network in Gastric Cancer

Gastric cancer (GC) is one of the most common malignancies in the world, with morbidity and mortality ranking second among all cancers. Accumulating evidences indicate that circular RNAs (circRNAs) are closely correlated with tumorigenesis. However, the mechanisms of circRNAs still remain unclear. This study is aimed at determining hub genes and circRNAs and analyzing their potential biological functions in GC. Expression profiles of mRNAs and circRNAs were downloaded from the Gene Expression Omnibus (GEO) data sets of GC and paracancer tissues. Differentially expressed genes (DEGs) and differentially expressed circRNAs (DE-circRNAs) were identified. The target miRNAs of DE-circRNAs and the bidirectional interaction between target miRNAs and DEGs were predicted. Functional analysis was performed, and the protein-protein interaction (PPI) network and the circRNA-miRNA-mRNA network were established. A total of 456 DEGs and 2 DE-circRNAs were identified with 3 mRNA expression profiles and 2 circRNA expression profiles. GO analysis indicated that DEGs were mainly enriched in extracellular matrix and cell adhesion, and KEGG confirmed that DEGs were mainly associated with focal adhesion, the PI3K-Akt signaling pathway, extracellular matrix- (ECM)- receptor interaction, and gastric acid secretion. 15 hub DEGs (BGN, COL1A1, COL1A2, FBN1, FN1, SPARC, SPP1, TIMP1, UBE2C, CCNB1, CD44, CXCL8, COL3A1, COL5A2, and THBS1) were identified from the PPI network. Furthermore, the survival analysis indicate that GC patients with a high expression of the following 9 hub DEGs, namely, BGN, COL1A1, COL1A2, FBN1, FN1, SPARC, SPP1, TIMP1, and UBE2C, had significantly worse overall survival. The circRNA-miRNA-mRNA network was constructed based on 1 circRNA, 15 miRNAs, and 45 DEGs. In addition, the 45 DEGs included 5 hub DEGs. These results suggested that hub DEGs and circRNAs could be implicated in the pathogenesis and development of GC. Our findings provide novel evidence on the circRNA-miRNA-mRNA network and lay the foundation for future research of circRNAs in GC.

Sex-biased ceRNA networks reveal that OSCAR can promote proliferation and migration of lung adenocarcinoma in women

Lung adenocarcinoma (LUAD) is one of several malignant tumours with the highest incidence rates. Currently, there is an urgent need for effective diagnostic and therapeutic targets for LUAD in clinical practice. Numerous studies have shown that there may be differences in the development pattern of LUAD between male and female patients, leading to the need for differential treatment. At the same time, previous studies have shown that competitive endogenous (ce)RNA plays an important role in the development of LUAD, but there is no relevant research on whether there is a gender difference in the ceRNA network of LUAD. In this study, we constructed gender-independent, male-specific, and female-specific ceRNA networks using RNA sequencing results from TCGA database. Subsequently, through analysis of the core genes of the ceRNA network, we determined that the male and female ceRNA networks indeed display different features. In addition, we also found that the osteoclast-associated receptor (OSCAR) gene was a potential diagnostic target for detecting LUAD in females, and that increased expression of this gene promoted the proliferation and migration of A549 and H1975 LUAD cell lines; more specifically, A549 and H1975 are male and female LUAD cell lines, respectively. This suggests that the OSCAR gene has the potential to serve as target molecule for the diagnosis and treatment of female-specific LUADs.

Effect of AGER on the biological behavior of non‑small cell lung cancer H1299 cells

Advanced glycosylation end-product specific receptor (AGER) is a multi-ligand cell surface receptor abnormally expressed in lung cancer, and is a member of the immunoglobulin superfamily. Therefore, this study aimed to explore the effect of AGER on the biological behavior of non-small cell lung cancer (NSCLC) H1299 cell line. A microarray-based gene expression profiling analysis of the GSE27262 dataset from the Gene Expression Omnibus (GEO) database was conducted to identify differentially expressed genes, which were verified using The Cancer Genome Atlas (TCGA) database. The expression of AGER in the normal human lung BEAS-2B cell line and NSCLC H1299 cell line was examined using reverse transcription-quantitative PCR. Lentiviral interference and overexpression vectors of AGER were constructed and transfected into H1299 cells using Lipofectamine^®. AGER expression and biological properties, including cell viability, apoptosis, migration and invasion abilities, in H1299 cells were investigated using MTT, flow cytometry, wound healing and Transwell assays. AGER was expressed at a low level in NSCLC tissues and H1299 cells (P<0.05). Compared with control cells, AGER overexpression cells displayed decreased cell viability, proliferation, migration and invasion abilities, and significantly increased levels of apoptosis. Furthermore, AGER overexpression increased the expression of Bax and decreased the expression of Bcl-2 in H1299 cells (P<0.05), and AGER knockdown displayed the opposite effects on H1299 cells. Therefore, AGER overexpression decreased the proliferation, invasion and migration abilities of H1299 cells, and increased apoptosis. The present study suggested that AGER might serve as a potential molecular marker for NSCLC.

Leveraging methylation to identify the potential causal genes associated with survival in lung adenocarcinoma and lung squamous cell carcinoma

Understanding the different genetic landscape between lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) is important for understanding the underlying molecular mechanism, which may facilitate the development of effective and precise treatments. Although previous studies have identified a number of differentially expressed genes (DEGs) responsible for lung cancer, it is unknown which of these genes are causal. The present study integrated DNA methylation, RNA sequencing, clinical characteristics and survival outcomes of patients with LUAD and LUSC from The Cancer Genome Atlas. DEGs were first identified using edgeR by comparing tumor and normal tissue, and differentially methylated probes (DMPs) were assessed using ChAMP. Candidate genes for further time-to-event instrumental variable analysis were selected as the intersecting genes between DEGs and the genes including DMP CpG sites within the transcription start site (TSS1500), with DMPs in TSS1500 region being the instrumental variables. Extensive sensitivity analyses were conducted to assess the robustness of the results. The present study identified 906 DEGs for LUAD, among which 538 also had DMPs in the TSS1500 region. In addition, 1,543 DEGs were identified for LUSC, among which 1,053 also had DMPs in the TSS1500 region. Time-to-event instrumental variable analysis detected eight potential causal genes for LUAD survival, including aryl hydrocarbon receptor nuclear translocator like 2, semaphorin 3G, serum deprivation-response protein, chloride intracellular channel protein 5, LIM zinc finger domain containing 2, epithelial membrane protein 2, carbonic anhydrase 7 and LOC116437. The results also identified that phosphatidylinositol-3,4,5-trisphosphate-dependent Rac exchange factor 2 may be a potential causal gene for LUSC. Therefore, the results of the present study suggested that there was molecular heterogeneity between these two lung cancer subtypes. Such analysis framework can be extended to other cancer genomics research.

DNA methylation biomarkers for nasopharyngeal carcinoma

Background

Aberrant methylation of DNA plays an important role in the pathogenesis of nasopharyngeal carcinoma (NPC). In the current study, we aimed to integrate three cohorts profile datasets to identify abnormally methylated-differentially expressed genes and pathways associated with NPC.

Methods

Data of gene expression microarrays (GSE53819, GSE412452) and gene methylation microarrays (GSE52068) obtained from the GEO database. Aberrantly methylated differentially expressed genes (DEGs) were obtained by GEO2R. The David database was utilized to perform enrichment and functional analysis regarding selected genes. To create a protein-protein interaction (PPI), STRING and Cytoscape software were utilized. The MCODE was used for module analysis of the PPI network.

Results

In total, 181 hypomethylation-high expression genes were identified, which were enriched in the biological mechanisms involved in the differentiation of endodermal cell, mitotic nuclear division, mitotic cell cycle process, chromosome segregation and cell cycle phase transition, etc. Pathway enrichment showed ECM-receptor interaction, PI3K-Akt signaling pathway, Focal adhesion, Protein digestion and absorption and Amoebiasis, etc. The top 3 hub genes of PPI network were FANCI, POSTN, and IFIH1. Additionally, 210 hypermethylation-low expression genes were identified, and our data revealed enrichment in biological processes including axoneme assembly, micro tubular formation, assembly of axonemal dynein complex, cilium movement and cilium organization, etc. Pathway analysis indicated enrichment in B cell receptor signaling pathway, Hematopoietic cell lineage, Leukocyte transendothelial migration, Complement and coagulation cascades and Fc gamma R-mediated phagocytosis, etc. The ZMYND10, PACRG and POU2AF1 were identified as the top three hub genes of PPI network. After validation in TCGA and GEPIA database, most hub genes remained significant. Patients with high expression of POSTN found to have shorter overall survival, while in patients with high expression of ZMYND10 and POU2AF1 longer overall survival was identified.

Conclusions

The data revealed novel aberrantly methylated-differentially expressed genes and pathways in NPC by bioinformatics analysis, potentially providing novel insights for the molecular mechanisms governing NPC progression. Hub genes including FANCI, POSTN, IFIH1, ZMYND10, PACRG and POU2AF1 might serve as novel biomarkers for precision diagnosis and providing medical treatment for patient with NPC.

Biochemical Characterization of a New Oligoalginate Lyase and Its Biotechnological Application in Laminaria japonica Degradation

Oligoalginate lyases catalyze the degradation of alginate polymers and oligomers into monomers, a prerequisite for biotechnological utilizing alginate. In this study, we report the cloning, expression and biochemical characterization of a new polysaccharide lyase (PL) family 17 oligoalginate lyase, OalV17, from the marine bacterium Vibrio sp. SY01. The recombinant OalV17 showed metal ion independent and detergent resistant properties. Furthermore, OalV17 is an exo-type enzyme that yields alginate monomers as the main product and recognizes alginate disaccharides as the minimal substrate. Site-directed mutagenesis followed by kinetic analysis indicates that the residue Arg²³¹ plays a key role in substrate specificity. Furthermore, a rapid and efficient alginate monomer-producing method was developed directly from Laminaria japonica. These results suggest that OalV17 is a potential candidate for saccharification of alginate.

RNA-sequencing and microarray data mining revealing: the aberrantly expressed mRNAs were related with a poor outcome in the triple negative breast cancer patients

Background

Triple negative breast cancer (TNBC) account for about 20% of breast carcinomas and the American society of clinical oncology guidelines does not specify approaches for TNBC patients since lack of specific driver molecules and targeted drugs.

Methods

We filtered out the aberrantly expressed mRNAs on the basis of RNA-seq data deposited in the Gene Expression Omnibus database, and verified and deeply analyzed screened differentially expressed genes (DEGs) using a combined bioinformatics approach.

Results

Of 21,755 genes with 472 TNBC cases from 3 independent laboratories, 159 mRNAs were identified as DEGs. To verify our results, we assessed the expression levels of top 8 DEGs in Oncomine database. The hierarchical clustering analysis, functional and pathway enrichment analysis were carried out for all DEGs. The results reveal that N-acetyltransferase 1 (NAT1) is most obvious of expression change's gene. Protein-protein interaction (PPI) network construction of 159 DEGs selected 3 hub genes: desmoglein 3 (DSG3), family with sequence similarity 83 member D (FAM83D) and GATA binding protein 3 (GATA3). For further analysis of the potential role of NAT1 in TNBC, the co-expression profiles of NAT1 in BC were made out, and we found that there are 5 genes [GATA3, trefoil factor 3 (TFF3), forkhead box A1 (FOXA1), signal peptide, CUB domain and EGF like domain containing 2 (SCUBE2), G protein-coupled receptor 160 (GPR160)] which co-expressed with NAT1 also were DEGs that we screened out before. Co-occurrence analysis confirmed that same as DEGs, GATA3 and SCUBE2 co-expressed with NAT1, and had a tendency towards a co-occurrence with NAT1 in TNBC. The survival curves showed that NAT1, GATA3 and SCUBE2 expression are significantly related with prognosis.

Conclusions

From all above results, we speculate that NAT1, GATA3 and SCUBE2 play a vital role in TNBC.

α1,6-Fucosyltransferase (FUT8) regulates the cancer-promoting capacity of cancer-associated fibroblasts (CAFs) by modifying EGFR core fucosylation (CF) in non-small cell lung cancer (NSCLC)

Cancer-associated fibroblasts (CAFs) are the main cancer-promoting component in the tumor microenvironment (TME) of non-small cell lung cancer (NSCLC). α1,6-Fucosyltransferase (FUT8), the key enzyme catalyzing core α1,6-fucosylation (CF), plays a promoting role in multiple malignancies. In the current study, we investigated the function of FUT8 in CAFs and elucidated the mechanism through which FUT8 regulates the cancer-promoting capacity of CAFs in NSCLC. A bioinformatics analysis was performed to reveal the relationship between FUT8 and CAFs. Resected specimens from NSCLC patients were analyzed to assess the expression of FUT8 in CAFs. Primary CAFs and normal lung fibroblasts (NLFs) were extracted from NSCLC patient specimens and were co-cultured with NSCLC cell lines in a novel 3D-printed non-contact co-culture device. An In vivo CAF/NSCLC co-injection tumorigenesis assay was performed using nude mice to study the function of FUT8/CF in TME formation. The current study revealed that FUT8-mediated CF in CAFs plays a positive role in the cancer-promoting capacity of these cells. FUT8 overexpression was observed in CAFs isolated from some lung adenocarcinoma cases. Further investigation showed that FUT8/CF in CAFs promoted the formation of an invasive and malignant TME in vivo and in vitro, and the resulting NSCLC cells exhibited faster proliferation and increased invasiveness. EGFR signaling exerts a catalytic effect on the cancer-promoting capacity of CAFs and is regulated by the CF modification of the EGFR protein.

Deep gene selection method to select genes from microarray datasets for cancer classification

Background

Microarray datasets consist of complex and high-dimensional samples and genes, and generally the number of samples is much smaller than the number of genes. Due to this data imbalance, gene selection is a demanding task for microarray expression data analysis.

Results

The gene set selected by DGS has shown its superior performances in cancer classification. DGS has a high capability of reducing the number of genes in the original microarray datasets. The experimental comparisons with other representative and state-of-the-art gene selection methods also showed that DGS achieved the best performance in terms of the number of selected genes, classification accuracy, and computational cost.

Conclusions

We provide an efficient gene selection algorithm can select relevant genes which are significantly sensitive to the samples’ classes. With the few discriminative genes and less cost time by the proposed algorithm achieved much high prediction accuracy on several public microarray data, which in turn verifies the efficiency and effectiveness of the proposed gene selection method.

LIMCH1 suppress the growth of lung cancer by interacting with HUWE1 to sustain p53 stability

BACKGROUND

The aim of this study was to identify the expression of LIM and calponin-homology domains 1 (LIMCH1) in lung cancer and normal tissues, to determine the interaction between LIMCH1 and HUWE1 in regulating p53 stability.

METHODS

The expression of LIMCH1 was detected by the Oncomine and Cancer Genome Atlas databases. Expression of LIMCH1 mRNA was identified using qRT-PCR. In transfected human lung cancer cells, co-immunoprecipitation experiments were performed. The mechanism that HUWE1 sustained lung cancer malignancy was verified by western blotting. The proliferation of tranfected cells was assessed by CCK-8 assay and colony formation.

RESULTS

Bioinformatic data and e TCGA database suggested LIMCH1 mRNA levels in tumor tissues were down-regulated compared to tumor adjacent tissues. We found low expression of LIMCH1 mRNA in tumor sites and tumor cell line. Exogenous expression of LIMCH1 interacts with HUWE1 promotes expression of p53. Use of siRNA or shRNA against LIMCH1 resulted in decreased p53 protein levels. LIMCH1 deletion lead to enhance of p53 ubiquitination and protein expression of p53 and substrate p21, puma. Growth curve showed that LIMCH1 deletion significantly promoted the proliferation of A549 cells.

CONCLUSIONS

LIMCH1 was a negative regulator and indicated a new molecular mechanism for the pathogenesis of lung cancer via modulating HUWE1 and p53.

MetaGxData: Clinically Annotated Breast, Ovarian and Pancreatic Cancer Datasets and their Use in Generating a Multi-Cancer Gene Signature

A wealth of transcriptomic and clinical data on solid tumours are under-utilized due to unharmonized data storage and format. We have developed the MetaGxData package compendium, which includes manually-curated and standardized clinical, pathological, survival, and treatment metadata across breast, ovarian, and pancreatic cancer data. MetaGxData is the largest compendium of curated transcriptomic data for these cancer types to date, spanning 86 datasets and encompassing 15,249 samples. Open access to standardized metadata across cancer types promotes use of their transcriptomic and clinical data in a variety of cross-tumour analyses, including identification of common biomarkers, and assessing the validity of prognostic signatures. Here, we demonstrate that MetaGxData is a flexible framework that facilitates meta-analyses by using it to identify common prognostic genes in ovarian and breast cancer. Furthermore, we use the data compendium to create the first gene signature that is prognostic in a meta-analysis across 3 cancer types. These findings demonstrate the potential of MetaGxData to serve as an important resource in oncology research, and provide a foundation for future development of cancer-specific compendia.

Overexpression of microRNA-423-3p indicates poor prognosis and promotes cell proliferation, migration, and invasion of lung cancer

BACKGROUND

Lung cancer is one of the common malignant tumors worldwide with high incidence and mortality. MicroRNA-423-3p (miR-423-3p) acts as an oncogene in several types of cancers. The aim of this study is to reveal the clinical significance and biological function of miR-423-3p in lung cancer.

METHODS

The expression of miR-423-3p was detected in lung cancer specimens by reverse transcription-quantitative polymerase chain reaction (qRT-PCR) assay. Kaplan-Meier survival and Cox regression analyses were used to investigate the prognostic significance of miR-423-3p in lung cancer. CCK-8 and Transwell assays were used to determine the functional role of miR-423-3p in lung cancer.

RESULTS

We observed that miR-423-3p was significantly upregulated in lung cancer tissues and cell lines. Overexpression of miR-423-3p was significantly associated with lymph node metastasis, TNM stage, and poor prognosis. Multivariate Cox regression analysis results showed that miR-423-3p was an independent prognostic indicator for lung cancer patients. Results of functional analyses revealed that overexpression of miR-423-3p promoted cell proliferation, migration, and invasion in lung cancer cells.

CONCLUSIONS

These results indicated that miR-423-3p acts as an oncogene and promotes cell proliferation migration, and invasion of lung cancer. And miR-423-3p may serve as a potential prognostic biomarker and therapeutic target for the treatment of lung cancer.

Construction and comprehensive analysis of a ceRNA network to reveal potential prognostic biomarkers for hepatocellular carcinoma

Background

Long noncoding RNAs (lncRNAs) can act as microRNA (miRNA) sponges to regulate protein-coding gene expression; therefore, lncRNAs are considered a major part of the competitive endogenous RNA (ceRNA) network and have attracted growing attention. The present study explored the regulatory mechanisms and functional roles of lncRNAs as ceRNAs in hepatocellular carcinoma (HCC) and their potential impact on HCC patient prognosis.

Methods

In this study, we systematically studied the expression profiles and prognostic value of lncRNA, miRNA, and mRNA from a total of 838 HCC patients from five HCC cohorts (TCGA, GSE54236, GSE76427, GSE64041 and GSE14520). The TCGA, GSE54236 and GSE76427 HCC cohorts were utilized to establish a prognosis-related network of dysregulated ceRNAs by bioinformatics methods. The GSE64041 and GSE14520 HCC cohorts were utilized to verify the expression of candidate genes.

Results

In total, 721 lncRNAs, 73 miRNAs, and 1563 mRNAs were aberrantly expressed in HCC samples. A ceRNA network including 26 lncRNAs, four miRNAs, and six mRNAs specific to HCC was established. The survival analysis showed that four lncRNAs (MYCNOS, DLX6-AS1, LINC00221, and CRNDE) and two mRNAs (CCNB1 and SHCBP1) were prognostic biomarkers for patients with HCC in both the TCGA and GEO databases.

Conclusion

The proposed ceRNA network may help elucidate the regulatory mechanism by which lncRNAs function as ceRNAs and contribute to the pathogenesis of HCC. Importantly, the candidate lncRNAs, miRNAs, and mRNAs involved in the ceRNA network can be further evaluated as potential therapeutic targets and prognostic biomarkers for HCC.

Electronic supplementary material

The online version of this article (10.1186/s12935-019-0817-y) contains supplementary material, which is available to authorized users.

Identification of Key Genes and Circular RNAs in Human Gastric Cancer

Background

Globally, gastric cancer (GC) is the third most common source of cancer-associated mortality. The aim of this study was to identify key genes and circular RNAs (circRNAs) in GC diagnosis, prognosis, and therapy and to further explore the potential molecular mechanisms of GC.

Material/Methods

Differentially expressed genes (DEGs) and circRNAs (DE circRNAs) between GC tissues and adjacent non-tumor tissues were identified from 3 mRNA and 3 circRNA expression profiles. Functional analyses were performed, and protein–protein interaction (PPI) networks were constructed. The significant modules and key genes in the PPI networks were identified. Kaplan-Meier analysis was performed to evaluate the prognostic value of these key genes. Potential miRNA-binding sites of the DE circRNAs and target genes of these miRNAs were predicted and used to construct DE circRNA–miRNA–mRNA networks.

Results

A total of 196 upregulated and 311 downregulated genes were identified in GC. The results of functional analysis showed that these DEGs were significantly enriched in a variety of functions and pathways, including extracellular matrix-related pathways. Ten hub genes (COL1A1, COL3A1, COL1A2, COL5A2, FN1, THBS1, COL5A1, SPARC, COL18A1, and COL11A1) were identified via PPI network analysis. Kaplan-Meier analysis revealed that 7 of these were associated with a poor overall survival in GC patients. Furthermore, we identified 2 DE circRNAs, hsa_circ_0000332 and hsa_circ_0021087. To reveal the potential molecular mechanisms of circRNAs in GC, DE circRNA–microRNA–mRNA networks were constructed.

Conclusions

Key candidate genes and circRNAs were identified, and novel PPI and circRNA–microRNA–mRNA networks in GC were constructed. These may provide useful information for the exploration of potential biomarkers and targets for the diagnosis, prognosis, and therapy of GC.

Identification of genes associated with cancer progression and prognosis in lung adenocarcinoma: Analyses based on microarray from Oncomine and The Cancer Genome Atlas databases

Background

Lung adenocarcinoma (LUAD) accounts for approximately 40% of all lung cancer patients. There is an urgent need to understand the mechanisms of cancer progression in LUAD and to identify useful biomarkers to predict prognosis.

Methods

In this study, Oncomine database was used to identify potential genes contributed to cancer progression. Bioinformatics analysis including pathway enrichment and text mining was used to explain the potential roles of identified genes in LUAD. The Cancer Genome Atlas database was used to analyze the association of gene expression with survival result.

Results

Our results indicated that 80 genes were significantly dysregulated in LUAD according to four microarrays covering 356 cases of LUAD and 164 cases of normal lung tissues. Twenty genes were consistently and stably dysregulated by more than twofold. Ten of 20 genes had a relationship with overall survival or disease‐free survival in a cohort of 516 LUAD patients, and 19 genes were associated with tumor stage, gender, age, lymph node, or smoking. Low expression of AGER and high expression of CCNB1 were specifically associated with poor survival.

Conclusion

Our findings implicate AGER and CCNB1 might be potential biomarkers for diagnosis and prognosis targets for LUAD.