Identification of Three lncRNAs as Potential Predictive Biomarkers of Lung Adenocarcinoma

lncRNA Biomarkers of Glioblastoma Multiforme

Long noncoding RNAs (lncRNAs) are RNA molecules of 200 nucleotides or more in length that are not translated into proteins. Their expression is tissue-specific, with the vast majority involved in the regulation of cellular processes and functions. Many human diseases, including cancer, have been shown to be associated with deregulated lncRNAs, rendering them potential therapeutic targets and biomarkers for differential diagnosis. The expression of lncRNAs in the nervous system varies in different cell types, implicated in mechanisms of neurons and glia, with effects on the development and functioning of the brain. Reports have also shown a link between changes in lncRNA molecules and the etiopathogenesis of brain neoplasia, including glioblastoma multiforme (GBM). GBM is an aggressive variant of brain cancer with an unfavourable prognosis and a median survival of 14-16 months. It is considered a brain-specific disease with the highly invasive malignant cells spreading throughout the neural tissue, impeding the complete resection, and leading to post-surgery recurrences, which are the prime cause of mortality. The early diagnosis of GBM could improve the treatment and extend survival, with the lncRNA profiling of biological fluids promising the detection of neoplastic changes at their initial stages and more effective therapeutic interventions. This review presents a systematic overview of GBM-associated deregulation of lncRNAs with a focus on lncRNA fingerprints in patients' blood.

First Transcriptome Analysis of Hepatoblastoma in Brazil: Unraveling the Pivotal Role of Noncoding RNAs and Metabolic Pathways

Hepatoblastoma stands as the most prevalent liver cancer in the pediatric population. Characterized by a low mutational burden, chromosomal and epigenetic alterations are key drivers of its tumorigenesis. Transcriptome analysis is a powerful tool for unraveling the molecular intricacies of hepatoblastoma, shedding light on the effects of genetic and epigenetic changes on gene expression. In this study conducted in Brazilian patients, an in-depth whole transcriptome analysis was performed on 14 primary hepatoblastomas, compared to control liver tissues. The analysis unveiled 1,492 differentially expressed genes (1,031 upregulated and 461 downregulated), including 920 protein-coding genes (62%). Upregulated biological processes were linked to cell differentiation, signaling, morphogenesis, and development, involving known hepatoblastoma-associated genes (DLK1, MEG3, HDAC2, TET1, HMGA2, DKK1, DKK4), alongside with novel findings (GYNG4, CDH3, and TNFRSF19). Downregulated processes predominantly centered around oxidation and metabolism, affecting amines, nicotinamides, and lipids, featuring novel discoveries like the repression of SYT7, TTC36, THRSP, CCND1, GCK and CAMK2B. Two genes, which displayed a concordant pattern of DNA methylation alteration in their promoter regions and dysregulation in the transcriptome, were further validated by RT-qPCR: the upregulated TNFRSF19, a key gene in the embryonic development, and the repressed THRSP, connected to lipid metabolism. Furthermore, based on protein-protein interaction analysis, we identified genes holding central positions in the network, such as HDAC2, CCND1, GCK, and CAMK2B, among others, that emerged as prime candidates warranting functional validation in future studies. Notably, a significant dysregulation of non-coding RNAs (ncRNAs), predominantly upregulated transcripts, was observed, with 42% of the top 50 highly expressed genes being ncRNAs. An integrative miRNA-mRNA analysis revealed crucial biological processes associated with metabolism, oxidation reactions of lipids and carbohydrates, and methylation-dependent chromatin silencing. In particular, four upregulated miRNAs (miR-186, miR-214, miR-377, and miR-494) played a pivotal role in the network, potentially targeting multiple protein-coding transcripts, including CCND1 and CAMK2B. In summary, our transcriptome analysis highlighted disrupted embryonic development as well as metabolic pathways, particularly those involving lipids, emphasizing the emerging role of ncRNAs as epigenetic regulators in hepatoblastomas. These findings provide insights into the complexity of the hepatoblastoma transcriptome and identify potential targets for future therapeutic interventions.

RACGAP1 promotes lung cancer cell proliferation through the PI3K/AKT signaling pathway

We aimed to investigate the expression and clinic significance of Rac GTPase Activating Protein 1 (RACGAP1) in human lung adenocarcinoma (LUAD). Online database analysis revealed a significant increase in RACGAP1 mRNA expression among 26 types of tumor tissues, including LUAD tissues. Online database and tissue microarray analyses indicated that RACGAP1 expression was significantly upregulated in LUAD tissues. Genetic variation analysis identified four different genetic variations of RACGAPs in LUAD. Moreover, online database analysis showed that RACGAP1 upregulation was correlated with shorter survival in patients with LUAD. After silencing RACGAP1 expression in A549 cells using siRNA and assessing its protein levels via Western blotting, we found that RACGAP1 knockdown inhibited cell growth and induced apoptosis determined using the Cell Counting Kit-8 assay, colony formation assay, and flow cytometry. Mechanistically, western blot analysis indicated that Bax expression increased, whereas Bcl-2 expression decreased. Moreover, RACGAP1 knockdown attenuated PI3K/AKT pathway activation in lung cancer cells. Taken together, our findings showed that RACGAP1 was overexpressed in LUAD tissues and played an important role in lung cancer by increasing cell growth through the PI3K/AKT signaling pathway. This study suggests recommends evaluating RACGAP1 in clinical settings as a novel biomarker and potential therapeutic target for lung cancer.

A review on the role of ADAMTS9-AS2 in different disorders

Recent decade has seen a tremendous progress in identification of the role of different long non-coding RNAs (lncRNAs) in human pathologies. ADAMTS9-AS2 is an example of lncRNAs with different roles in human disorders. It is mostly acknowledged as a tumor suppressor lncRNA in different types of cancers. However, it has been reported to be up-regulated in tongue squamous cell carcinoma, salivary adenoid cystic carcinoma and glioblastoma. Moreover, ADAMTS9-AS2 is possibly involved in the pathoetiology of pulpitis, acute ischemic stroke, type 2 diabetes and its complications. This lncRNA sponges miR-196b-5p, miR-223-3p, miR-130a-5p, miR-600, miR-223-3p, miR-27a-3p, miR-32, miR-143-3p, miR-143-3p and miR-182-5p in order to regulate downstream mRNAs. This review aims at summarization of the role of ADAMTS9-AS2 in different disorders with a particular focus on its diagnostic and prognostic values.

A circadian rhythm-related biomarker for predicting prognosis and immunotherapy efficacy in lung adenocarcinoma

Lung adenocarcinoma (LUAD) remains a major reason of cancer-associated mortality globally, and there exists a lack of indicators for survival in LUAD patients. Therefore, it is clinically required to obtain a novel prognostically indicator for guiding clinical management. In this study, we established a circadian rhythm (CR) related signature by a combinative investigation of multiple datasets. The newly-established signature showed an acceptable ability to predict survival and could serve as an independent indicator for prognosis. Moreover, the newly-established signature was critically associated with tumor malignancy, including proliferation, invasion, EMT and metastasis. The newly-established signature was predictive of response to immune checkpoint blockade. Collectively, we established a CR-related gene signature that could forecast survival, tumor malignancy and therapeutic response; our findings could help guiding clinical management.

Extracellular vesicle-mediated transfer of lncRNA CLDN10-AS1 aggravates low-density lipoprotein-induced vascular endothelial injury

Oxidized low-density lipoprotein (ox-LDL) stimulation impairs the oxidation-reduction equilibrium in vascular endothelial cells (VECs) and contributes to atherosclerosis (AS). This study probed the mechanisms of extracellular vesicle (EV)-mediated transfer of lncRNA CLDN10 antisense RNA 1 (CLDN10-AS1) in ox-LDL-induced VEC injury. Initially, VEC injury models were established by treating human umbilical vein endothelial cells (HUVECs) with ox-LDL. EVs were isolated from HUVECs (HUVECs-EVs) and identified. CLDN10-AS1, microRNA (miR)-186, and Yin Yang 1 (YY1) expressions in ox-LDL-treated HUVECs and EVs derived from these cells (ox-EVs) were measured. HUVECs were incubated with EVs, after which the cell viability, apoptosis, and concentrations of proinflammatory cytokines and oxidative stress markers were measured. We discovered that CLDN10-AS1 and YY1 were upregulated in ox-LDL-treated HUVECs, whereas miR-186 was downregulated. ox-EVs treatment elevated CLDN10-AS1 expression in HUVECs and ox-EVs overexpressing CLDN10-AS1 promoted VEC injury. Besides, CLDN10-AS1 is competitively bound to miR-186 and promoted YY1 expression. Rescue experiments revealed that miR-186 overexpression or YY1 suppression partially reversed the roles of ox-EVs overexpressing CLDN10-AS1 in ox-LDL-induced VEC injury. Lastly, clinical serum samples were collected for verification. Overall, CLDN10-AS1 carried by HUVECs-EVs into HUVECs competitively bound to miR-186 to elevate YY1 expression, thereby aggravating ox-LDL-induced VEC injury.

Upregulation of long noncoding RNA linc02544 and its association with overall survival rate and the influence on cell proliferation and migration in lung squamous cell carcinoma

BACKGROUND

Long noncoding RNAs (lncRNAs) exert crucial biological functions by regulating miRNAs, which are implicated in cancer progression and tumorigenesis. A previous study has indicated that lncRNA linc02544 expression is upregulated in lung adenocarcinoma, whereas, the role of linc02544 in LUSC is elusive.

METHODS

The differential linc02544 expression in LUSC tissues and adjacent non-tumor tissues were evaluated with RT-qPCR. Kaplan-Meier curve was conducted to evaluate the clinical prognostic significance of linc02544. Then cellular experiments were performed to assess the influence of linc02544 in LUSC proliferation, invasion, and migration, and a western blot assay was used to measure the metastasis-related protein levels. The downstream miRNAs were verified using the LncBase Experimental v.2 database and dual-luciferase reporter assay.

RESULTS

Linc02544 was overexpressed in LUSC tissues from positive lymph node metastasis-positive and TNM high-stage patients. Low linc02544 expression was associated with a longer survival rate. Downregulation of linc02544 by si-linc02544 restrained cell growth capacities, migration, and invasion abilities. Expression of MMP-2, MMP-9, and vimentin was decreased while E-cadherin was increased in si-linc02544 cells compared with that in untreated cells. Mechanistically, we identified that linc02544 acted as a sponge of miR-138-5p, which expression had a negative correlation. E2F3 was a potential target of miR-138-5p, CONCLUSIONS: Notably, high linc02544 expression was associated with severe clinical parameters and was a putative prognostic predictor for patients with LUSC. Downregulation of linc02544 may weaken the LUSC cell proliferation, migration, and invasion by regulating miR-138-5p/E2F3, which maybe serve as a biomarker for the prognosis and target treatment of LUSC.

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.

Identification of key genes and biological pathways in Chinese lung cancer population using bioinformatics analysis

BACKGROUND

Identification of accurate prognostic biomarkers is still particularly urgent for improving the poor survival of lung cancer patients. In this study, we aimed to identity the potential biomarkers in Chinese lung cancer population via bioinformatics analysis.

METHODS

In this study, the differentially expressed genes (DEGs) in lung cancer were identified using six datasets from Gene Expression Omnibus (GEO) database. Subsequently, enrichment analysis was conducted to evaluate the underlying molecular mechanisms involved in progression of lung cancer. Protein-protein interaction (PPI) and CytoHubba analysis were performed to determine the hub genes. The GEPIA, Human Protein Atlas (HPA), Kaplan-Meier plotter, and TIMER databases were used to explore the hub genes. The receiver operating characteristic (ROC) analysis was performed to evaluate the diagnostic value of hub genes. Reverse transcription quantitative PCR (qRT-PCR) was used to validate the expression levels of hub genes in 10 pairs of lung cancer paired tissues.

RESULTS

A total of 499 overlapping DEGs (160 upregulated and 339 downregulated genes) were identified in the microarray datasets. DEGs were mainly associated with pathways in cancer, focal adhesion, and protein digestion and absorption. There were nine hub genes (CDKN3, MKI67, CEP55, SPAG5, AURKA, TOP2A, UBE2C, CHEK1 and BIRC5) identified by PPI and module analysis. In GEPIA database, the expression levels of these genes in lung cancer tissues were significantly upregulated compared with normal lung tissues. The results of prognostic analysis showed that relatively higher expression of hub genes was associated with poor prognosis of lung cancer. In HPA database, most hub genes were highly expressed in lung cancer tissues. The hub genes have good diagnostic efficiency in lung cancer and normal tissues. The expression of any hub gene was associated with the infiltration of at least two immune cells. qRT-PCR confirmed that the expression level of CDKN3, MKI67, CEP55, SPAG5, AURKA, TOP2A were highly expressed in lung cancer tissues.

CONCLUSIONS

The hub genes and functional pathways identified in this study may contribute to understand the molecular mechanisms of lung cancer. Our findings may provide new therapeutic targets for lung cancer patients.

Identification of Differentially Expressed and Prognostic lncRNAs for the Construction of ceRNA Networks in Lung Adenocarcinoma

Background

Long noncoding RNAs (lncRNAs) could function as competitive endogenous RNAs (ceRNAs) to competitively adsorb microRNAs (miRNAs), thereby regulating the expression of their target protein-coding mRNAs. In this study, we aim to identify more effective diagnostic and prognostic markers for lung adenocarcinoma (LUAD).

Methods

We obtained differentially expressed lncRNAs (DElncRNAs), miRNAs (DEmiRNAs), and mRNAs (DEmRNAs) for LUAD by using The Cancer Genomes Atlas (TCGA) portal. Weighted gene coexpression network analysis (WGCNA) was performed to unveil core gene modules associated with LUAD. The Cox proportional hazards model was performed to determine the prognostic significance of DElncRNAs. The diagnostic and prognostic significance of DElncRNAs was further verified based on the receiver operating characteristic curve (ROC). Cytoscape was used to construct the ceRNA networks comprising the lncRNAs-miRNAs-mRNAs axis based on the correlation obtained from the miRcode, miRDB, and TargetScan.

Results

Compared with normal lung tissues, 2355 DElncRNAs, 820 DEmiRNAs, and 17289 DEmRNAs were identified in LUAD tissues. We generated 8 WGCNA core modules in the lncRNAs coexpression network, 5 modules in the miRNAs, and 12 modules in the mRNAs coexpression network, respectively. One lncRNA module (blue) consisting of 441 lncRNAs, two miRNA modules (blue and turquoise) containing 563 miRNAs, and one mRNA module (turquoise), which consisted of 15162 mRNAs, were mostly significantly related to LUAD status. Furthermore, 67 DEmRNAs were found to be tumor-associated as well as the target genes of the DElncRNAs-DEmiRNAs axis. Survival analyses showed that 6 lncRNAs (LINC01447, WWC2-AS2, OGFRP1, LINC00942, LINC01168, and AC005863.1) were significantly correlated with the prognosis of LUAD patients. Ultimately, the potential ceRNA networks including 6 DElncRNAs, 4 DEmiRNAs, and 22 DEmRNAs were constructed.

Conclusion

Our study indicated that 6 DElncRNAs had the possibilities as diagnostic and prognostic biomarkers for LUAD. The lncRNA-mediated ceRNA networks might provide novel insights into the molecular mechanisms of LUAD progression.

LncRNA ADAMTS9-AS2 is a Prognostic Biomarker and Correlated with Immune Infiltrates in Lung Adenocarcinoma

Background

The role of long noncoding RNA (LncRNA) ADAMTS9 antisense RNA 2 (ADAMTS9-AS2) is unclear in lung adenocarcinoma (LUAD). The aim of this study was to explore the relationship between ADAMTS9-AS2 and LUAD, based on The Cancer Genome Atlas (TCGA) database and bioinformatics analysis.

Methods

Various statistical methods, Kaplan–Meier method, Cox regression analysis, GSEA, and immune infiltration analysis were used to evaluate the relationship between clinical features and ADAMTS9-AS2 expression, prognostic factors, and the significant involvement of ADAMTS9-AS2 in function.

Results

In LUAD patients, low expression of ADAMTS9-AS2 was associated with N stage (P=0.011), gender (P=0.002), number of packs smoked (P=0.024) and smoker (P<0.001). Low ADAMTS9-AS2 expression predicted a poorer overall survival (OS) (HR: 0.68; 95% CI: 0.51–0.91; P=0.01). And ADAMTS9-AS2 expression (HR: 0.626; 95% CI: 0.397–0.986; P=0.043) was independently correlated with OS in LUAD patients. Unwinding of DNA, extrinsic pathway, polo-like kinase-mediated events, cori cycle, MCM pathway, proteasome pathway, lagging strand synthesis and PCNA-dependent long patch base excision repair were differentially enriched in ADAMTS9-AS2 high expression phenotype. ADAMTS9-AS2 expression was correlated with certain immune infiltrating cells.

Conclusion

In LUAD patients, ADAMTS9-AS2 expression was significantly associated with poor survival and immune infiltration. ADAMTS9-AS2 may be a promising biomarker of prognosis and response to immunotherapy for LUAD.

Differential expression of long non-coding RNAs as diagnostic markers for lung cancer and other malignant tumors

Due to advances in chip and sequencing technology, several types and numbers of long non-coding RNAs (lncRNAs) have been identified. LncRNAs are defined as non-protein-coding RNA molecules longer than 200 nucleotides, and are now thought as a new frontier in the study of human malignant diseases including NSCLC. Diagnosis of numerous malignant tumors has been closely linked to the differential expression of certain lncRNAs. LncRNAs are involved in gene expression regulation at multiple levels of epigenetics, transcriptional regulation, and post-transcriptional regulation. Mutations, deletions, or abnormal expression levels lead to physiological abnormalities, disease occurrence and are closely associated with human tumor diseases. LncRNAs play a crucial role in cancerous processes as either oncogenes or tumor suppressor genes. The expression of lncRNAs can regulate tumor cell in the proliferation, migration, apoptosis, cycle, invasion, and metastasis. As such, lncRNAs are potential diagnostic and treatment targets for cancer. And that, tumor biomarkers need to be detectable in easily accessible body samples, should be characterized by high specificity and sufficient sensitivity. Herein, it is significant clinical importance to screen and supplement new biomarkers for early diagnosis of lung cancer. This study aimed at systematically describing lncRNAs from five aspects based on recent studies: concepts, classification, structure, molecular mechanism, signal pathway, as well as review lncRNA implications in malignant tumor.

Carboxypeptidase E mRNA: Overexpression predicts recurrence and death in lung adenocarcinoma cancer patients

BACKGROUND

Effective biomarkers for prediction of recurrence of lung adenocarcinoma cancer (LADC) patients are needed to determine treatment strategies post-surgery to improve outcome.

OBJECTIVE

This study evaluates the efficacy of carboxypeptidase E (CPE) mRNA including its splice isoforms, CPE-ΔN, as a biomarker for predicting recurrence in adenocarcinoma patients.

METHODS

RNA was extracted from resected tumors from 86 patients with different stages of non-small cell LADC. cDNA was synthesized and qRT-PCR carried out to determine the copy numbers of CPE/CPE-ΔN mRNA. Patients were followed for 7 years post-tumor resection to determine recurrence and death.

RESULTS

ROC curve analysis showed the overall AUC for CPE/CPE-ΔN copy number was 0.563 in predicting recurrence and 0.563 in predicting death. Kaplan-Meier survival analysis showed statistical difference (p= 0.018), indicating that patients with high CPE/CPE-ΔN copy numbers had a shorter time of disease-free survival and also shorter time to death (p= 0.035). Subgroup analyses showed that association of disease-free survival time with CPE/CPE-ΔN copy number was stronger among stage I and II LADC patients (p= 0.047).

CONCLUSIONS

CPE/CPE-ΔN mRNA is a potentially useful biomarker for predicting recurrence and death in LADC patients, especially in identifying patients at high risk of recurrence at early stages I and II.

Bioinformatics Analysis and Functional Verification of ADAMTS9-AS1/AS2 in Lung Adenocarcinoma

Long non-coding RNAs (lncRNAs), as competitive endogenous RNAs (ceRNAs), play a critical role in biological processes of cancer. However, the roles of specific lncRNAs in ceRNA network of lung adenocarcinoma (LUAD) remains largely unclear. Herein, we identified the roles of lncRNA ADAMTS9-AS1/AS2 (ADAMTS-AS1/AS2) in lung adenocarcinoma by bioinformatics analyses and functional verification. First, differentially expressed genes ADAMTS9-AS1, ADAMTS9-AS2 and ADAMTS9 were screened out from GSE130779. Then the expression correlation of these three genes was analyzed. The results showed that ADAMTS9-AS1, ADAMTS9-AS2 and ADAMTS9 were down-regulated in LUAD, and were positively correlated with each other. After that, miRcode was used to find miR-150 which binds to ADAMTS9-AS1/ADAMTS9-AS2/ADAMTS9. Next, co-expression analysis and functional enrichment analyses were performed to further analyze differentially expressed genes. The results showed that the differentially expressed genes were mainly enriched in Beta3 integrin cell surface interactions and epithelial-to-mesenchymal transition. Finally, the cell functions of ADAMTS9-AS1 and ADAMTS9-AS2 in A549 and NCI-H1299 cell lines were verified. In vitro cell studies confirmed that ADAMTS9-AS1 and ADAMTS9-AS2 play an inhibitory role in LUAD cells.

A Novel Five-Gene Signature for Prognosis Prediction in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) has been a global health issue and attracted wide attention due to its high incidence and poor outcomes. In this study, our purpose was to explore an effective prognostic marker for HCC. Five cohort profile datasets from GEO (GSE25097, GSE36376, GSE62232, GSE76427 and GSE101685) were integrated with TCGA-LIHC and GTEx dataset to identify differentially expressed genes (DEGs) between normal and cancer tissues in HCC patients, then 5 upregulated differentially expressed genes and 32 downregulated DEGs were identified as common DEGs in total. Next, we systematically explored the relationship between the expression of 37 common DEGs in tumor tissues and overall survival (OS) rate of HCC patients in TCGA and constructed a novel prognostic model composed of five genes (AURKA, PZP, RACGAP1, ACOT12 and LCAT). Furthermore, the predicted performance of the five-gene signature was verified in ICGC and another independent clinical samples cohort, and the results demonstrated that the signature performed well in predicting the OS rate of patients with HCC. What is more, the signature was an independent hazard factor for HCC patients when considering other clinical factors in the three cohorts. Finally, we found the signature was significantly associated with HCC immune microenvironment. In conclusion, the prognostic five-gene signature identified in our present study could efficiently classify patients with HCC into subgroups with low and high risk of longer overall survival time and help clinicians make decisions for individualized treatment.

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.

LncRNA-LINC01089 inhibits lung adenocarcinoma cell proliferation and promotes apoptosis via sponging miR-543

LINC01089, a newly discovered long non-coding RNA (lncRNA), has been reported to inhibit the progression of various types of cancers. This study aimed to characterize LINC01089 in the pathogenesis of lung adenocarcinoma (LUAD). LINC01089 expression in LUAD tissues or/and cells and its association with the overall survival of LUAD patients was analyzed in The Cancer Genome Atlas (TCGA)-LUAD database, by qRT-PCR or by Kaplan-Meier's curve. Databases of StarBase, LncBase, and DEmiRNA were used to predict and confirm the interaction between LINC01089 and potential LINC01089-targeted microRNAs (miRNAs). The expressions of these miRNAs in LUAD tissues or/and cells were determined by qRT-PCR, and dual-luciferase reporter assay was performed to validate lncRNA-miRNA interaction. The expressions of B-cell lymphoma 2 (Bcl-2), Bcl-2-associated X protein (Bax) and Cleaved caspase-3 in LUAD cells were analyzed by Western blot. LINC01089 improved overall survival of LUAD patients and was low-expressed in LUAD. Upregulating LINC01089 expression reduced LUAD cell viability, inhibited colony formation, enhanced apoptosis, accompanied by downregulated Bcl-2 and miR-543 and upregulated Bax and Cleaved caspase-3. MiR-543 was determined as a target gene of LINC01089, and was high-expressed in LUAD tissues. Upregulating miR-543 expression induced the opposite effects to LINC01089 upregulation on these cellular biological behaviors and the expressions of Bcl-2, Bax and Cleaved caspase-3. Moreover, the effects of miR-543 upregulation and LINC01089 upregulation were mutually counteracted by each other. LINC01089 inhibited lung adenocarcinoma cell proliferation and promoted apoptosis via sponging miR-543.

LncRNA MIR155HG functions as a ceRNA for inhibition of lung adenocarcinoma growth and prediction of prognosis

Introduction

Long non-coding RNAs (lncRNAs) functioning as competing endogenous RNAs (ceRNAs) play critical roles in tumour progression. However, prognosis-related ceRNA networks in lung adenocarcinoma (LUAD) have not been well characterised.

Material and methods

LUAD datasets were downloaded from the TCGA database, and the patients were divided into metastasis and non-metastasis groups. The differential expression of lncRNAs (DELs), miRNAs (DEMs), and mRNAs (DEGs) was analysed using the Limma package. Next, interactions between miRNA, lncRNA, and mRNA were predicted by miRcode, miRTar-Base, miRDB, and TargetScan. The ceRNA network was constructed based on these interactions using Cytoscape software. DEG enrichment analysis was performed by GO and KEGG. After the prognosis analysis, we further screened molecules and constructed the prognosis-related ceRNA network. Moreover, the interactions between lncRNA, miRNA, and mRNA were validated by biological experiments.

Results

854 DELs, 150 DEMs, and 2211 DEGs between metastasis and non-metastasis LUAD patients were identified. Functional enrichment analysis suggested that DEGs were closely related to key biological processes involved in LUAD progression. The prognosis-related ceRNA network included 1 miRNA, 2 lncRNAs, and 4 mRNAs. In this network, MIR155HG and ADAMTS9-AS2 can function as ceRNAs of miR-212 to regulate EPM2AIP1, LAX1, PRICKLE2, and CD226. Moreover, our study confirmed that MIR155HG inhibited the proliferation, migration, and invasion of LUAD cells by sponging miR-212-3p to regulate CD226.

Conclusions

This ceRNA network contributes to understanding the pathogenesis of LUAD. Furthermore, the molecules in the network are valuable predictive factors for LUAD prognosis as well as potential therapeutic biomarkers.