Microarray expression profile of long non-coding RNAs in human lung adenocarcinoma

Potentials as biomarker and therapeutic target of upregulated long non-coding RNA HLA-F antisense RNA 1 in hepatitis B virus-associated hepatocellular carcinoma

The tissue-specific characteristics have encouraged researchers to identify organ-specific lncRNAs as disease biomarkers. This study aimed to identify the clinical and functional roles of long non-coding RNA HLA-F antisense RNA 1 (HLA-F-AS1) in hepatitis B virus (HBV)-hepatocellular carcinoma (HCC). A total of 121 HBV-HCC, 81 chronic hepatitis B (CHB), and 85 normal liver tissues were evaluated in this study. Real-time quantitative PCR assay was used to evaluate the RNA expression levels. Performance in diagnosis was compared between alpha fetoprotein (AFP) and HLA-F-AS1 using Receiver Operating Characteristic (ROC) curves. Performance in post-hepatectomy prognosis with high or low HLA-F-AS1 was compared using Kaplan-Meier curves. Multi-variable analysis was used to determine the informative predictors. Downstream miRNAs for HLA-F-AS1 were predicted and miR-128-3p was confirmed by luciferase reporter assay and RNA pull-down assay. In vitro functional analysis was performed by MTS reagent for cell proliferation and transwell assay for cell migration. HLA-F-AS1 levels were significantly increased in the HBV-HCC compared to normal healthy tissue and CHB tissues. HLA-F-AS1 exhibited a well potential in making a distinction between HBV-HCC and health, as well as HBV-HCC and CHB. The survival analysis revealed that patients with high levels of HLA-F-AS1 tend to shorter overall survival times. The best prognostic performance was achieved by HLA-F-AS1 after multi-variable analysis (HR 2.290, 95% CI 1.191-4.403, p = 0.013). Functional analysis showed that HLA-F-AS1 promoted cell proliferation and migration via miR-128-3p. Up-regulation of HLA-F-AS1 could serve as a promising diagnostic and prognostic marker for HBV-HCC after surgery, maybe useful in the management of HBV-HCC patients. HLA-F-AS1 can promote the progression of HBV-HCC, may be useful in the targeting treatment of HBV-HCC patients.

Construction of a New Immune-Related Competing Endogenous RNA Network with Prognostic Value in Lung Adenocarcinoma

Tumor microenvironment has significant influence on the gene expression of tumor tissues and on the clinical outcomes in lung adenocarcinoma. Infiltrating immune and stromal cells not only perturb the tumor signal in molecular studies, but also play crucial roles in cancer biology. The competing endogenous RNAs (ceRNAs) are useful to explain the post-transcriptional layer regulated by gene translation and play an important role in the occurrence and progression of lung adenocarcinoma. Therefore, identifying novel molecular markers by constructing ceRNA associated with immune infiltration is of great significance to guide the treatment of lung adenocarcinoma in the future. According to the immune and stromal scores of lung adenocarcinoma samples in The Cancer Genome Atlas (TCGA) database calculated by the ESTIMATE algorithm, we identified differentially expressed lncRNAs, miRNAs and mRNAs associated with immune infiltration, including 60 dysregulated lncRNAs, 38 dysregulated mRNAs, and 29 dysregulated miRNAs. Based on the PPI network and Cox regression analysis, 5 mRNAs including CNR2, P2RY12, ZNF831, RSPO1, and F2 were identified to be related to immune infiltration and prognosis in lung adenocarcinoma, and their differential expression, prognosis and correlation with immune cells were verified. Next, through target binding prediction, pearson correlation analysis and expression analysis, a novel immune-related ceRNA network containing 6 lncRNAs, 4 miRNAs, and 3 mRNAs was finally constructed. The present study constructed a novel immune-associated lncRNA-miRNA-mRNA ceRNA network, which deepens our understanding on the molecular network mechanism of lung adenocarcinoma and provides potential prognostic markers and novel therapeutic targets for the patients with lung adenocarcinoma.

Divergent patterns of healthy aging across human brain regions at single-cell resolution reveal links to neurodegenerative disease

Age is a major common risk factor underlying neurodegenerative diseases, including Alzheimer's disease, Parkinson's disease, and amyotrophic lateral sclerosis. Previous studies reported that chronological age correlates with differential gene expression across different brain regions. However, prior datasets have not disambiguated whether expression associations with age are due to changes in cell numbers and/or gene expression per cell. In this study, we leveraged single nucleus RNA-sequencing (snRNAseq) to examine changes in cell proportions and transcriptomes in four different brain regions, each from 12 donors aged 20-30 years (young) or 60-85 years (old). We sampled 155,192 nuclei from two cortical regions (entorhinal cortex and middle temporal gyrus) and two subcortical regions (putamen and subventricular zone) relevant to neurodegenerative diseases or the proliferative niche. We found no changes in cellular composition of different brain regions with healthy aging. Surprisingly, we did find that each brain region has a distinct aging signature, with only minor overlap in differentially associated genes across regions. Moreover, each cell type shows distinct age-associated expression changes, including loss of protein synthesis genes in cortical inhibitory neurons, axonogenesis genes in excitatory neurons and oligodendrocyte precursor cells, enhanced gliosis markers in astrocytes and disease-associated markers in microglia, and genes critical for neuron-glia communication. Importantly, we find cell type-specific enrichments of age associations with genes nominated by Alzheimer's disease and Parkinson's disease genome-wide association studies (GWAS), such as apolipoprotein E (APOE), and leucine-rich repeat kinase 2 (LRRK2) in microglia that are independent of overall expression levels across cell types. We present this data as a new resource which highlights, first, region- and cell type-specific transcriptomic changes in healthy aging that may contribute to selective vulnerability and, second, provide context for testing GWAS-nominated disease risk genes in relevant subtypes and developing more targeted therapeutic strategies. The data is readily accessible without requirement for extensive computational support in a public website, https://brainexp-hykyffa56a-uc.a.run.app/.

lncRNA EGFEM1P Drives the Progression of Papillary Thyroid Cancer by Regulating miR-6867-5p/CHI3L1 Axis

Long noncoding RNA (lncRNA), a subgroup of noncoding RNA with > 200 nt, plays critical roles in cancer progression. Here, we aimed to explore the detailed biological function of lncRNA EGFEM1P during papillary thyroid cancer (PTC) progression. RT-qPCR and Western blot were used to analyze the expression of lncRNA EGFEM1P, miR-6867-5p, and CHI3L1. CCK8, colony formation, and Transwell migration assays were undertaken to assess PTC cell proliferation and migration. A xenograft tumor mouse model was also used to establish tumor growth in vivo. Luciferase reporter and anti-AGO2 RNA immunoprecipitation (RIP) assays were used to clarify the interplay between miR-6867-5p and lncRNA EGFEM1P or CHI3L1. We found lncRNA EGFEM1P and CHI3L1 to be highly expressed in PTC tissues and cells, while miR-6867-5p expression decreases. Functionally, lncRNA EGFEM1P silence delays PTC cell proliferation and migration, and impairs tumorigenesis in vivo. LncRNA EGFEM1P targets miR-6867-5p, and CHI3L1 is a target gene of miR-6867-5p. LncRNA EGFEM1P silence decreases the pro-proliferation and pro-migration caused by the miR-6867-5p inhibitor in PTC cells, and CHI3L1 silence abrogates the pro-tumorigenic action resulting from the miR-6867-5p inhibitor in PTC cells. Our data showed that lncRNA EGFEM1P targeting of the miR-6867-5p/CHI3L1 axis drives PTC progression, suggesting lncRNA EGFEM1P as a therapeutically target for PTC.

LncRNA-AC009948.5 promotes invasion and metastasis of lung adenocarcinoma by binding to miR-186-5p

BACKGROUND

Long non-coding RNAs (LncRNAs) has been confirmed to play a crucial role in the development and progression of various cancer types. Here we evaluated the expression profiles of LncRNAs in Lung adenocarcinoma (LUAD) tissues and identified a novel LncRNA, termed LncRNA-AC009948.5. However, the role and potential molecular mechanisms of this novel LncRNA in LUAD carcinogenesis is unknown.

METHODS

Regarding the public databases and based on integrating bioinformatics analyses, we determined whether LncRNA-AC009948.5 exerts its oncogenic functions via sponging miR-186-5p in LUAD. Furthermore, we determined whether NCAPG2 was a downstream target of miR-186-5p. Moreover, the expression level and biological function of LncRNA-AC009948.5 in LUAD were determined by qRT-PCR, cell apoptosis, Edu, transwell, wound healing and western blot assays. Besides, xenograft mice were established for validation. We explored the expression of LncRNA-AC009948.5 and its roles in the prognosis of LUAD.

RESULTS

LncRNA expression microarray data indicate that LncRNA-AC009948.5 is upregulated in LUAD samples. The present study confirmed the upregulation of LncRNA-AC009948.5 in LUAD tissues and cells. Encreased expression of LncRNA-AC009948.5 was correlated with tumor size, lymph nodes, distant metastasis and histological grade, and poor prognosis.LncRNA-AC009948.5 knockdown significantly inhibited cell proliferation, migration, and invasion in vitro, as well as tumorigenesis and metastasis in vivo. Conversely, LncRNA-AC009948.5 upregulated had opposite effects. Mechanistically, we elucidated that LncRNA-AC009948.5 could directly bind to miR-186-5p and subsequently suppress expression of the target gene of NCAPG2.

CONCLUSIONS

LncRNA-AC009948.5 promotes lung adenocarcinoma cells metastasis via the miR-186-5p/NCAPG2 axis and activation of the EMT process. Which may serve as potential targets for the treatment of LUAD in the future.

The miR-4732-5p/XPR1 axis suppresses the invasion, metastasis, and epithelial-mesenchymal transition of lung adenocarcinoma via the PI3K/Akt/GSK3β/Snail pathway

The roles of microRNAs (miRNAs) in the occurrence, metastasis, and prognosis of lung adenocarcinoma (LUAD) have been drawing extensive attention from researchers. The aim of this study is to identify the effects of miR-4732-5p on the migration, invasion, and metastasis of LUAD. In this study, we found that the expression of miR-4732-5p was decreased in LUAD based on the data derived from The Cancer Genome Atlas (TCGA) database, tissues, and cell lines. LUAD patients with a low expression of miR-4732-5p exhibited a lower survival rate. Meanwhile, miR-4732-5p could directly target xenotropic and polytropic retrovirus receptor 1 (XPR1), and elevated XPR1 was observed in LUAD mRNA microarrays, Gene Expression Omnibus (GEO), and The Human Protein Atlas (HPA) database. Overexpression of miR-4732-5p significantly inhibits the migration, invasion, and metastasis of LUAD in vitro and in vivo, which can be reversed by overexpression of XPR1. We also found that the PI3K/Akt/GSK3β/Snail pathway induced by EGF induced EMT could be inhibited by miR-4732-5p overexpression and XPR1 knockdown. The migration and invasion of LUAD could be converted by cytoskeletal rearrangements, and the polymerization of EGF induced F-actin in A549 cells could be inhibited by elevated miR-4732-5p. Our results suggest that miR-4732-5p exerts anti-tumor effects on the invasion and metastasis of LUAD by regulating XPR1 in vivo and in vitro, indicating that the miR-4732-5p/XPR1 axis may be a potential target for LUAD therapeutic intervention.

Ontologies and Knowledge Graphs in Oncology Research

The complexity of cancer research stems from leaning on several biomedical disciplines for relevant sources of data, many of which are complex in their own right. A holistic view of cancer—which is critical for precision medicine approaches—hinges on integrating a variety of heterogeneous data sources under a cohesive knowledge model, a role which biomedical ontologies can fill. This study reviews the application of ontologies and knowledge graphs in cancer research. In total, our review encompasses 141 published works, which we categorized under 14 hierarchical categories according to their usage of ontologies and knowledge graphs. We also review the most commonly used ontologies and newly developed ones. Our review highlights the growing traction of ontologies in biomedical research in general, and cancer research in particular. Ontologies enable data accessibility, interoperability and integration, support data analysis, facilitate data interpretation and data mining, and more recently, with the emergence of the knowledge graph paradigm, support the application of Artificial Intelligence methods to unlock new knowledge from a holistic view of the available large volumes of heterogeneous data.

Prognostic Value of Genomic Instability of m6A-Related lncRNAs in Lung Adenocarcinoma

Background: Genomic instability of N6-methyladenosine (m⁶A)–related long noncoding RNAs (lncRNAs) plays a pivotal role in the tumorigenesis of lung adenocarcinoma (LUAD). Our study identified a signature of genomic instability of m⁶A-associated lncRNA signature and revealed its prognostic role in LUAD.

Methods: We downloaded RNA-sequencing data and somatic mutation data for LUAD from The Cancer Genome Atlas (TCGA) and the GSE102287 dataset from the Gene Expression Omnibus (GEO) database. The “Limma” R package was used to identify a network of regulatory m⁶A-related lncRNAs. We used the Wilcoxon test method to identify genomic-instability–derived m⁶A-related lncRNAs. A competing endogenous RNA (ceRNA) network was constructed to identify the mechanism of the genomic instability of m⁶A-related lncRNAs. Univariate and multivariate Cox regression analyses were performed to construct a prognostic model for internal testing and validation of the prognostic m⁶A-related lncRNAs using the GEO dataset. Performance analysis was conducted to compare our prognostic model with the previously published lncRNA models. The CIBERSORT algorithm was used to explore the relationship of m⁶A-related lncRNAs and the immune microenvironment. Prognostic m⁶A-related lncRNAs in prognosis, the tumor microenvironment, stemness scores, and anticancer drug sensitivity were analyzed to explore the role of prognostic m⁶A-related lncRNAs in LUAD.

Results: A total of 42 genomic instability–derived m⁶A-related lncRNAs were differentially expressed between the GS (genomic stable) and GU (genomic unstable) groups of LUAD patients. Four differentially expressed lncRNAs, 17 differentially expressed microRNAs, and 75 differentially expressed mRNAs were involved in the genomic-instability–derived m⁶A-related lncRNA-mediated ceRNA network. A prediction model based on 17 prognostic m⁶A-associated lncRNAs was constructed based on three TCGA datasets (all, training, and testing) and validated in the GSE102287 dataset. Performance comparison analysis showed that our prediction model (area under the curve [AUC] = 0.746) could better predict the survival of LUAD patients than the previously published lncRNA models (AUC = 0.577, AUC = 0.681). Prognostic m⁶A-related-lncRNAs have pivotal roles in the tumor microenvironment, stemness scores, and anticancer drug sensitivity of LUAD.

Conclusion: A signature of genomic instability of m⁶A-associated lncRNAs to predict the survival of LUAD patients was validated. The prognostic, immune microenvironment and anticancer drug sensitivity analysis shed new light on the potential novel therapeutic targets in LUAD.

Gene Expression Analysis Platform (GEAP): A highly customizable, fast, versatile and ready-to-use microarray analysis platform

There are still numerous challenges to be overcome in microarray data analysis because advanced, state-of-the-art analyses are restricted to programming users. Here we present the Gene Expression Analysis Platform, a versatile, customizable, optimized, and portable software developed for microarray analysis. GEAP was developed in C# for the graphical user interface, data querying, storage, results filtering and dynamic plotting, and R for data processing, quality analysis, and differential expression. Through a new automated system that identifies microarray file formats, retrieves contents, detects file corruption, and solves dependencies, GEAP deals with datasets independently of platform. GEAP covers 32 statistical options, supports quality assessment, differential expression from single and dual-channel experiments, and gene ontology. Users can explore results by different plots and filtering options. Finally, the entire data can be saved and organized through storage features, optimized for memory and data retrieval, with faster performance than R. These features, along with other new options, are not yet present in any microarray analysis software. GEAP accomplishes data analysis in a faster, straightforward, and friendlier way than other similar software, while keeping the flexibility for sophisticated procedures. By developing optimizations, unique customizations and new features, GEAP is destined for both advanced and non-programming users.

Convolutional Neural Network Addresses the Confounding Impact of CT Reconstruction Kernels on Radiomics Studies

Achieving high feature reproducibility while preserving biological information is one of the main challenges for the generalizability of current radiomics studies. Non-clinical imaging variables, such as reconstruction kernels, have shown to significantly impact radiomics features. In this study, we retrain an open-source convolutional neural network (CNN) to harmonize computerized tomography (CT) images with various reconstruction kernels to improve feature reproducibility and radiomic model performance using epidermal growth factor receptor (EGFR) mutation prediction in lung cancer as a paradigm. In the training phase, the CNN was retrained and tested on 32 lung cancer patients’ CT images between two different groups of reconstruction kernels (smooth and sharp). In the validation phase, the retrained CNN was validated on an external cohort of 223 lung cancer patients’ CT images acquired using different CT scanners and kernels. The results showed that the retrained CNN could be successfully applied to external datasets with different CT scanner parameters, and harmonization of reconstruction kernels from sharp to smooth could significantly improve the performance of radiomics model in predicting EGFR mutation status in lung cancer. In conclusion, the CNN based method showed great potential in improving feature reproducibility and generalizability by harmonizing medical images with heterogeneous reconstruction kernels.

Construction and Integrated Analysis of Competitive Endogenous Long Non-Coding RNA Network in Thoracic Aortic Dissection

Background

Long non-coding RNAs (lncRNAs) can act as a competitive endogenous RNA (ceRNA) to regulate gene expression by sequestering the microRNA (miRNA). However, the lncRNA-miRNA-mRNA ceRNA network in thoracic aortic dissection (TAD) has been rarely documented.

Methods

Three Gene Expression Omnibus (GEO) datasets were used to detect differentially expressed mRNAs, miRNAs, and lncRNAs in TAD. Gene ontology and the Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were conducted for the differentially expressed mRNAs. A protein–protein interaction network for differentially expressed mRNAs was also constructed, and hub genes were identified. We established a ceRNA network of TAD based on the differentially expressed miRNAs, mRNAs and lncRNAs, and verified our results using an independent dataset and quantitative real-time PCR (qRT-PCR).

Results

In TAD, 267 lncRNAs, 81 miRNAs, and 346 mRNAs were identified as differentially expressed. The established ceRNA network consisted of seven lncRNA nodes, three mRNA nodes, and three miRNA nodes, and the expression of miRNAs in TAD was opposite to that of lncRNAs and mRNAs. Subsequently, an independent GEO dataset and qRT-PCR were used to validate the expression of three mRNAs. In addition, the expression differences in SLC7A5, associated miRNA and lncRNA were verified. According to gene set enrichment analysis of SLC7A5, the most significant KEGG pathway was considerably enriched in spliceosome and pentose phosphate pathway.

Conclusion

We established a novel ceRNA regulatory network in TAD, which provides valuable information for further research in the molecular mechanisms of TAD.

The relationship between LncRNAs and lung adenocarcinoma as well as their ceRNA network

BACKGROUND

More and more studies have shown that long non-coding RNA (LncRNA) as a competing endogenous RNA (ceRNA) plays an important role in lung cancer. Therefore, we analyzed the RNA expression profiles of 82 lung cancer patients which were all from Gene Expression Omnibus (GEO).

METHODS

Firstly, we used BLASTN (evalue = 1e-10) to annotate the gene sets, performed in-group correction and batched normalization of the three data sets with R. Secondly, we used the limma and sva packages to compare tumor tissues with normal tissues. Then through WGCNA, we obtained the 4 gene modules most related to the trait.

RESULTS

We intersected the genes of above 4 modules with the differential expression genes: 28 LncRNAs (up: 5, down: 23) and 265 mRNAs (up:11, down: 254). Based on these genes, we picked up 6 LncRNAs (CCDC39, FAM182A, SRGAP3-AS2, ADAMTS9-AS2, AC020907.2, SFTA1P), then set and visualized the LncRNA-miRNA-mRNA ceRNA network with 12 miRNAs related to 12 mRNAs. Finally, we performed downstream analysis of 265 mRNAs by Gene Ontology (GO) enrichment analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis and Protein-Protein Interaction (PPI) network.

CONCLUSION

After analyzing, we think this study provides a new direction for basic and clinical research related to LAD, and is expected to provide new targets for early diagnosis, prognostic evaluation and clinical treatment of lung cancer.

Long Noncoding RNA LINC01006 Facilitates Cell Proliferation, Migration, and Epithelial-Mesenchymal Transition in Lung Adenocarcinoma via Targeting the MicroRNA 129-2-3p/CTNNB1 Axis and Activating Wnt/β-Catenin Signaling Pathway

Lung adenocarcinoma (LUAD) is a common type of malignancy of lung cancers. Long intergenic noncoding RNAs (lincRNAs) have emerged as crucial regulators of various cancers, including LUAD. LINC01006 is a newly discovered long noncoding RNA (lncRNA) whose function in LUAD remains to be explored. This study is to explore the role of LINC01006 in LUAD. Quantitative real-time PCR (RT-qPCR) analysis and Western blotting were used to determine the expression levels and protein levels, respectively. Functional assays and animal experiments investigated the role of LINC01006 both in vivo and in vitro. Moreover, TOP/FOP assay was performed to detect the activation of the Wnt/β-catenin signaling pathway. The interaction between LINC01006 and microRNA 29-2-3-p (miR-29-2-3-p)/catenin beta 1 (CTNNB1) was explored by RNA binding protein immunoprecipitation (RIP), RNA pulldown, luciferase reporter assays, and rescue experiments. According to the results, LINC01006 was highly expressed in LUAD tissues and cell lines. LINC01006 knockdown significantly suppressed cell proliferative, migratory, and epithelial-mesenchymal transition (EMT) capacities and tumor development. Moreover, LINC01006 enhanced CTNNB1 via sequestering miR-129-2-3p and activated the Wnt/β-catenin pathway in LUAD. Overall, LINC01006 promotes LUAD development via activating the Wnt/β-catenin pathway, implying that LINC01006 might be a promising biomarker for LUAD treatment.

Immune-related genes and gene sets for predicting the response to anti-programmed death 1 therapy in patients with primary or metastatic non-small cell lung cancer

Although antibodies targeting the immune checkpoint protein programmed death-1 (PD-1) exert therapeutic effects in patients with primary or metastatic non-small cell lung cancer (NSCLC), the majority of patients exhibit partial or complete resistance to anti-PD1 treatment. Thus, the aim of the present study was to identify reliable biomarkers for predicting the response to anti-PD-1 therapy. The present study analyzed tumor specimens isolated from 24 patients (13 with primary and 11 with metastatic NSCLC) prior to treatment with approved PD1-targeting antibodies. The expression profile of 395 immune-related genes was examined using RNA immune-oncology panel sequencing. The results demonstrated that six immune-related differently expressed genes (DEGs), including HLA-F-AS1, NCF1, RORC, DMBT1, KLRF1 and IL-18, and five DEGs, including HLA-A, HLA-DPA1, TNFSF18, IFI6 and PTK7, may be used as single biomarkers for predicting the efficacy of anti-PD-1 treatment in patients with primary and with metastatic NSCLC, respectively. In addition, two DEG sets comprising either six (HLA-F-AS1, NCF1, RORC, DMBT1, KLRF and IL-18) or two (HLA-A and TNFSF18) DEGs as potential combination biomarkers for predicting the efficacy of anti-PD-1 therapy in patients with NSCLC. Patients with a calculated expression level of the DEG sets >6.501 (primary NSCLC) or >6.741 (metastatic NSCLC) may benefit from the anti-PD-1 therapy. Overall, these findings provided a basis for the identification of additional biomarkers for predicting the response to anti-PD-1 treatment.

Identifying an lncRNA-Related ceRNA Network to Reveal Novel Targets for a Cutaneous Squamous Cell Carcinoma

Simple Summary

The exact functions and molecular mechanism of lncRNAs, acting as competitive endogenous RNAs in a cutaneous squamous cell carcinoma, remain unexplored. The present study was conducted to identify the differentially expressed lncRNAs and mRNAs and establish the lncRNA-related competing endogenous RNA networks associated with a cutaneous squamous cell carcinoma. A competing endogenous RNA network consisting of 137 miRNA-lncRNA and 221 miRNA-mRNA pairs was constructed. As for the functional analysis of the mRNAs in the network, a FoxO signaling pathway, an autophagy and cellular senescence were the top enrichment terms based on the Kyoto Encyclopedia of Genes and Genomes analysis. We identified five core mRNAs and built a core mRNA-associated competing endogenous RNA network. Finally, one lncRNA HLA-F-AS1 and three mRNAs named AGO4, E2F1 and CCND1 in the core mRNA-associated competing endogenous RNA network were validated with the same expression patterns. The core mRNAs and their associated lncRNAs may provide potential therapeutic targets for cutaneous squamous cell carcinomas.

Abstract

A cutaneous squamous cell carcinoma (cSCC) derived from keratinocytes is the second most common cause of non-melanoma skin cancer. The accumulation of the mutational burden of genes and cellular DNA damage caused by the risk factors (e.g., exposure to ultraviolet radiation) contribute to the aberrant proliferation of keratinocytes and the formation of a cSCC. A cSCC encompasses a spectrum of diseases that range from recursor actinic keratosis (AK) and squamous cell carcinoma (SCC) in situ (SCCIS) to invasive cSCCs and further metastatic SCCs. Emerging evidence has revealed that lncRNAs are involved in the biological process of a cSCC. According to the ceRNA regulatory theory, lncRNAs act as natural miRNA sponges and interact with miRNA response elements, thereby regulating the mRNA expression of their down-stream targets. This study was designed to search for the potential lncRNAs that may become potential therapeutic targets or biomarkers of a cSCC. Considering the spirit of the study to be adequately justified, we collected microarray-based datasets of 19 cSCC tissues and 12 normal skin samples from the GEO database (GSE42677 and GSE45164). After screening the differentially expressed genes via a limma package, we identified 24 differentially expressed lncRNAs (DElncRNAs) and 3221 differentially expressed mRNAs (DEmRNAs). The miRcode, miRTarBase, miRDB and TargetScan databases were used to predict miRNAs that could interact with DElncRNAs and DEmRNAs. A total of 137 miRNA-lncRNA and 221 miRNA-mRNA pairs were retained in the ceRNA network, consisting of 31 miRNAs, 11 DElncRNAs and 155 DEmRNAs. For the functional analysis, the top enriched biological process was enhancer sequence-specific DNA binding in Gene Ontology (GO) terms. The FoxO signaling pathway, autophagy and cellular senescence were the top enrichment terms based on a Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. The combination of a STRING tool and Cytoscape software (plug-in MCODE) identified five core mRNAs and built a core mRNA-associated ceRNA network. The expression for five identified core mRNAs and their related nine lncRNAs was validated using the external dataset GSE7553. Finally, one lncRNA HLA-F-AS1 and three mRNAs named AGO4, E2F1 and CCND1 were validated with the same expression patterns. We speculate that lncRNA HLA-F-AS1 may sponge miR-17-5p or miR-20b-5p to regulate the expression of CCND1 and E2F1 in the cSCC. The present study may provide potential diagnostic and therapeutic targets for cSCC patients.

Long noncoding RNA LINC00520 accelerates lung adenocarcinoma progression via miR-1252-5p/FOXR2 pathway

It has been corroborated that long noncoding RNA (lncRNA) played fundamental function in various human malignancies development including lung adenocarcinoma (lung ADC). In our study, LINC00520 roles in lung ADC tumorigenesis were explored. We found that LINC00520 level was elevated in lung ADC tissues and cell lines. Besides, the LINC00520 expression had a negative connection with miR-1252-5p level in lung ADC tissues. Additionally, our results demonstrated the reciprocal repression influence between LINC00520 and miR-1252-5p. Moreover, luciferase reporter assays, RIP (RNA-binding protein immunoprecipitation) and pull down assays revealed that miR-1252-5p regulated LINC00520 in RISC-dependent. Furthermore, knockdown of LINC00520 inhibited lung ADC cells proliferation, migration and invasion, while co-transfection with a miR-1252-5p inhibitor inverted these influences. Additionally, the findings also demonstrated that FOXR2 was a target of miR-1252-5p; thus, LINC00520 could regulate FOXR2 level. Moreover, LINC00520 silencing suppressed the tumor growth of lung ADC in vivo. In summary, our data indicated that LINC00520 may act as a ceRNA to modulated FOXR2 level by sponging miR-1252-5p, which might bring a potential and effective biomarker to lung ADC treatment.

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.

Insulin resistance in obese adolescents affects the expression of genes associated with immune response

OBJECTIVE

The development of obesity and its metabolic complications is associated with dysregulation of various intrinsic mechanisms, which control basic metabolic processes through changes in the expression of numerous regulatory genes.

METHODS

The expression level of HLA-DRA, HLA-DRB1, HLA-G, HLA-F, and NFX1 genes as well as miR-190b was measured in the blood of obese adolescents without signs of resistance to insulin and with insulin resistance in comparison with the group of relative healthy control individuals without signs of obesity.

RESULTS

It was shown that obesity without signs of insulin resistance is associated with upregulation of the expression level of HLA-DRA and HLA-DRB1 genes, but with down-regulation of HLA-G gene expression in the blood as compared to control group of relative healthy adolescents. At the same time, no significant changes were observed in the expression level of HLA-F and NFX1 genes in the blood of this group of obese adolescents. Development of insulin resistance in obese individuals leads to significant down-regulation of HLA-DRA, HLA-DRB1, HLA-G, and HLA-F gene expressions as well as to up-regulation of NFX1 gene as well as microRNA miR-190b in the blood as compared to obese patients without signs of insulin resistance.

CONCLUSIONS

Results of this study provide evidence that obesity affects the expression of the subset of genes related to immune response in the blood and that development of insulin resistance in obese adolescents is associated with strong down-regulation of the expressions of HLA-DRA, HLA-DRB1, HLA-F, and HLA-G genes, which may be contribute to the development of obesity complications. It is possible that transcription factor NFX1 and miR-190b participate in downregulation of HLA-DRA gene expression in the blood of obese adolescents with insulin resistance.

HLA-F-AS1/miR-330-3p/PFN1 axis promotes colorectal cancer progression

OBJECTIVE

Accumulating Studies implies that long-chain non-coding RNA (lncRNA) plays a vital regulatory role in the occurrence and progression of tumors. This study aimed to explore the function and mechanism of lncRNA HLA-F antisense RNA 1 (HLA-F-AS1) in colorectal cancer (CRC).

METHODS

Expressions of HLA-F-AS1, miR-330-3p and profilin 1 (PFN1) mRNA in CRC tissues were detected by RT-PCR. MTT assay was used to detect cell proliferation, and Transwell assay was used to detect cell migration and invasion. In addition, PFN1 and apoptosis-related protein Bcl-2 associated X (Bax) and B cell lymphoma/leukmia-2 (Bcl2) were detected by western blot. Interactions between miR-330-3p and HLA-F-AS1 or the 3'UTR of PFN1 were predicted and determined by bioinformatics analysis and luciferase reporter assay.

RESULTS

Expressions of HLA-F-AS1 and PFN1 were significantly up-regulated while miR-330-3p was significantly down-regulated in CRC tissues and cell lines. Over-expressions of HLA-F-AS1 or transfection of miR-330-3p inhibitors could promote the proliferation, migration and invasion and block apoptosis of CRC cells, whereas knockdown of HLA-F-AS1 or transfection of miR-330-3p mimics led to the opposite effects. Additionally, HLA-F-AS1 could down-regulate miR-330-3p via sponging it. HLA-F-AS1 also enhanced the expressions of PFN1, which was validated as a target gene of miR-330-3p.

CONCLUSION

HLA-F-AS1 promoted CRC progression via regulating miR-330-3p/PFN1 axis.

An eight-lncRNA signature predicts survival of breast cancer patients: a comprehensive study based on weighted gene co-expression network analysis and competing endogenous RNA network

PURPOSE

To identify a lncRNA signature to predict survival of breast cancer (BRCA) patients.

METHODS

A total of 1222 BRCA case and control datasets were downloaded from the TCGA database. The weighted gene co-expression network analysis of differentially expressed mRNAs was performed to generate the modules associated with BRCA overall survival status and further construct a hub on competing endogenous RNA (ceRNA) network. LncRNA signatures for predicting survival of BRCA patients were generated using univariate survival analyses and a multivariate Cox hazard model analysis and validated and characterized for prognostic performance measured using receiver operating characteristic (ROC) curves.

RESULTS

A prognostic score model of eight lncRNAs signature was identified as Prognostic score = (0.121 × EXP_AC007731.1) + (0.108 × EXP_AL513123.1) + (0.105 × EXP_C10orf126) + (0.065 × EXP_WT1-AS) + (- 0.126 × EXP_ADAMTS9-AS1) + (- 0.130 × EXP_SRGAP3-AS2) + (0.116 × EXP_TLR8-AS1) + (0.060 × EXP_HOTAIR) with median score 1.088. Higher scores predicted higher risk. The lncRNAs signature was an independent prognostic factor associated with overall survival. The area under the ROC curves (AUC) of the signature was 0.979, 0.844, 0.99 and 0.997 by logistic regression, support vector machine, decision tree and random forest models, respectively, and the AUCs in predicting 1- to 10-year survival were between 0.656 and 0.748 in the test dataset from TCGA database.

CONCLUSIONS

The eight-lncRNA signature could serve as an independent biomarker for prediction of overall survival of BRCA. The lncRNA-miRNA-mRNA ceRNA network is a good tool to identify lncRNAs that is correlated with overall survival of BRCA.