Bioinformatics analysis of mRNA and miRNA microarray to identify the key miRNA‑gene pairs in small‑cell lung cancer

Exploring effective biomarkers and potential immune related gene in small cell lung cancer

Small cell lung cancer (SCLC) is well known as a highly malignant neuroendocrine tumor. Immunotherapy combined with chemotherapy has become a standard treatment for extensive SCLC. However, since most patients quickly develop resistance and relapse, finding new therapeutic targets for SCLC is important. We obtained four microarray datasets from the Gene Expression Omnibus database and screened differentially expressed genes by two methods: batch correction and "RobustRankAggregation". After the establishment of a protein-protein interaction network through Cytoscape, seven hub genes (AURKB, BIRC5, TOP2A, TYMS, PCNA, UBE2C, and AURKA) with high expression in SCLC samples were obtained by eight CytoHubba algorithms. The Least Absolute Shrinkage and Selection Operator regression and the Wilcoxon test were used to analyze the differences in the immune cells' infiltration between normal and SCLC samples. The contents of seven kinds of immune cells were considered to differ significantly between SCLC samples and normal samples. A negative association was found between BIRC5 and monocytes in the correlation analysis between immune cells and the seven hub genes. The subsequent in vitro validation of experimental results showed that downregulating the expression of BIRC5 by siRNA can promote apoptotic activity of SCLC cells and inhibit their vitality, migration, and invasion. The use of BIRC5 inhibitor inhibited the vitality of SCLC cells and increased their apoptotic activity. BIRC5 may be a novel therapeutic target option for SCLC.

Identification of potential regulatory mechanisms and therapeutic targets for lung cancer

Lung cancer poses a significant health threat globally, especially in regions like India, with 5-year survival rates remain alarmingly low. Our study aimed to uncover key markers for effective treatment and early detection. We identified specific genes related to lung cancer using the BioXpress database and delved into their roles through DAVID enrichment analysis. By employing network theory, we explored the intricate interactions within lung cancer networks, identifying ASPM and MKI67 as crucial regulator genes. Predictions of microRNA and transcription factor interactions provided additional insights. Examining gene expression patterns using GEPIA and KM Plotter revealed the clinical relevance of these key genes. In our pursuit of targeted therapies, Drug Bank pointed to methotrexate as a potential drug for the identified key regulator genes. Confirming this, molecular docking studies through Swiss Dock showed promising binding interactions. To ensure stability, we conducted molecular dynamics simulations using the AMBER 16 suite. In summary, our study pinpoints ASPM and MKI67 as vital regulators in lung cancer networks. The identification of hub genes and functional pathways enhances our understanding of molecular processes, offering potential therapeutic targets. Importantly, methotrexate emerged as a promising drug candidate, supported by robust docking and simulation studies. These findings lay a solid foundation for further experimental validations and hold promise for advancing personalized therapeutic strategies in lung cancer.Communicated by Ramaswamy H. Sarma.

Identifying potential pathogenesis and immune infiltration in diabetic foot ulcers using bioinformatics and in vitro analyses

BACKGROUND

Diabetic foot ulcers (DFU) are among the fastest-growing diseases worldwide. Recent evidence has emphasized the critical role of microRNA (miRNA)-mRNA networks in various chronic wounds, including DFU. In this study, we aimed to clarify the miRNA-mRNA axes associated with the occurrence of DFU.

METHODS

Expression profiles of miRNAs and mRNAs were extracted from the Gene Expression Omnibus. Differentially expressed genes and differentially expressed miRNAs were identified, and miRNA-mRNA regulatory axes were constructed through integrated bioinformatics analyses. We validated the miRNA-mRNA axes using quantitative real-time PCR (qPCR) and dual-luciferase reporter assays. We conducted an immune infiltration analysis and confirmed the bioinformatics results using immunofluorescence staining. Single-sample gene set enrichment analysis (ssGSEA) was used to analyze the metabolic mechanisms.

RESULTS

miR-182-5p-CHL1/MITF and miR-338-3p-NOVA1 interactions were identified using in silico analysis. The qPCR results showed apparent dysregulation of these miRNA-mRNA axes in DFU. The dual-luciferase reporter assay confirmed that miR-182-5p targeted CHL1 and MITF, and miR-338-3p targeted NOVA1. We conducted an immune infiltration analysis and observed that key genes correlated with decreased infiltration of M1 macrophages and resting mast cells in DFU. Immunofluorescence staining verified the co-localization of CHL1 and tryptase, while MITF and CD68 showed weak positive correlations. Metabolic pathways related to these three genes were identified using ssGSEA.

CONCLUSIONS

In summary, the miR-182-5p-CHL1/MITF and miR-338-3p-NOVA1 pathway interactions and decreased infiltration of M1 macrophages and resting mast cells may provide novel clues to the pathogenesis of DFU.

TRIAL REGISTRATION

The clinical trial included in this study was registered in the Chinese Clinical Trial Registry ( ChiCTR2200066660 ) on December 13, 2022.

The uprise of RNA biology in neuroendocrine neoplasms: altered splicing and RNA species unveil translational opportunities

Neuroendocrine neoplasms (NENs) comprise a highly heterogeneous group of tumors arising from the diffuse neuroendocrine system. NENs mainly originate in gastrointestinal, pancreatic, and pulmonary tissues, and despite being rare, show rising incidence. The molecular mechanisms underlying NEN development are still poorly understood, although recent studies are unveiling their genomic, epigenomic and transcriptomic landscapes. RNA was originally considered as an intermediary between DNA and protein. Today, compelling evidence underscores the regulatory relevance of RNA processing, while new RNA molecules emerge with key functional roles in core cell processes. Indeed, correct functioning of the interrelated complementary processes comprising RNA biology, its processing, transport, and surveillance, is essential to ensure adequate cell homeostasis, and its misfunction is related to cancer at multiple levels. This review is focused on the dysregulation of RNA biology in NENs. In particular, we survey alterations in the splicing process and available information implicating the main RNA species and processes in NENs pathology, including their role as biomarkers, and their functionality and targetability. Understanding how NENs precisely (mis)behave requires a profound knowledge at every layer of their heterogeneity, to help improve NEN management. RNA biology provides a wide spectrum of previously unexplored processes and molecules that open new avenues for NEN detection, classification and treatment. The current molecular biology era is rapidly evolving to facilitate a detailed comprehension of cancer biology and is enabling the arrival of personalized, predictive and precision medicine to rare tumors like NENs.

Repression of linc01555 up-regulates angiomotin-p130 via the microRNA-122-5p/clic1 axis to impact vasculogenic mimicry-mediated chemotherapy resistance in small cell lung cancer

Long non-coding ribonucleic acid 01555 (linc01555) is a brand-new long non-coding RNA (lncRNA) that acts a carcinogenic function in various cancers. However, its role in small cell lung cancer (SCLC) is uncertain. This research was to figure out the role of linc01555 in cisplatin (DDP) resistance of SCLC cells and its possible latent mechanism. After establishment of the resistant sub-strain H446/DDP or DMS-53/DDP, detection of linc01555, microRNA (miR)-122-5p and CLICl was done in the H446/DDP or DMS-53/DDP cell line. After intervention, cell biological functions were determined, as well as tube formation ability. The detection of angiomotin (Amot)-p130 and the validation of the regulatory mechanism were performed. Furthermore, tumor xenografts were applied in nude mice to evaluate the effect of linc01555 on DDP resistance in SCLC in vivo. Linc01555 was elevated in SCLC tissues and cells, and in H446/DDP cells or DMS-53/DDP vs. its parental cells; Restraining linc01555 or elevating miR-122-5p repressed the proliferation and metastasis of H446/DDP or DMS-53/DDP cells and vasculogenic mimicry (VM) formation. CLIC1 mediated miR-122-5p to influence the occurrence and development of SCLC. Linc01555 competitively combined with miR-122-5p, which targeted CLIC1. Refrained linc01555 elevated Amot-p130 via the miR-122-5p/CLIC1 axis. Reduced linc01555 refrained tumor growth and DDP resistance in vivo.In short, linc01555 may cause changes in DDP resistance via miR-122-5p/CLIC1 in SCLC. The finding may offer drug targets for SCLC resistance.

Bioinformatic Analysis Identifies of Potential miRNA-mRNA Regulatory Networks Involved in the Pathogenesis of Lung Cancer

Objective. The purpose of the present study was to explore the biomarkers related to lung cancer based on the bioinformatics method, which might be new targets for lung cancer treatment. Methods. GSE17681 and GSE18842 were obtained from the Gene Expression Omnibus (GEO) database. The differentially expressed miRNAs (DEMs) and genes (DEGs) in lung cancer samples were screened via the GEO2R online tool. DEMs were submitted to the mirDIP website to predict target genes. Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were conducted via uploading DEGs to the DAVID database. The protein-protein interaction network (PPI) of the DEGs was analyzed by STRING’s online tool. Then, the PPI network was visualized using Cytoscape 3.8.0. Results. 46 DEMs were identified in GSE17681, and the website predicted that there were 873 target genes of these DEMs. 1029 DEGs were identified in the GSE18842 chip. GO analysis suggested that the co-DEGs participated in the canonical Wnt signaling pathway, regulation of the Wnt signaling pathway, a serine/threonine kinase signaling pathway, the Wnt signaling pathway, and cell-cell signaling by Wnt. KEGG analysis results showed the co-DEGs of GSE17681 and GSE18842 were related to the Hippo signaling pathway and adhesion molecules. In addition, six hub genes that were related to lung cancer were identified as hub genes, including mTOR, NF1, CHD7, ETS1, IL-6, and COL1A1. Conclusions. The present study identified six hub genes that were related to lung cancer, including mTOR, NF1, CHD7, ETS1, IL-6, and COL1A1, which might be a potential target for lung cancer.

Enhancer-associated regulatory network and gene signature based on transcriptome and methylation data to predict the survival of patients with lung adenocarcinoma

Accumulating evidence has proved that aberrant methylation of enhancers plays regulatory roles in gene expression for various cancers including lung adenocarcinoma (LUAD). In this study, the transcriptome and methylation data of The Cancer Genome Atlas (TCGA)-LUAD cohort were comprehensively analyzed with a five-step Enhancer Linking by Methylation/Expression Relationships (ELMER) process. Step 1: 131,371 distal (2 kb upstream from the transcription start site) probes were obtained. Step 2: 10,665 distal hypomethylated probes were identified in an unsupervised mode with the get.diff.meth function. Step 3: 699 probe-gene pairs with negative correlations were screened using the get.pair function in an unsupervised mode. Step 4: After mapping with probes, 768 motifs were obtained and 24 of them were enriched. Step 5: 127 transcription factors (TFs) with differential expressions and negative correlations with methylation levels were screened, which were corresponding to 21 motifs. After the ELMER process, a prognostic “TFs-motifs-genes” regulatory network was constructed. The Least absolute shrinkage and selection operator (LASSO) and Stepwise regression analyses were further applied to identify variables in the TCGA-LUAD cohort and an eight-gene signature was constructed for calculating the risk score. The risk score was verified in two independent validation cohorts. The area under curve values of receiver operating characteristic curves predicting 1-, 3-, and 5-years survival ranged from 0.633 to 0.764. With the increase of the risk scores, both the survival statuses and clinical traits showed a worse tendency. There were significant differences in the degrees of immune cell infiltration, TMB values, and TIDE scores between the high-risk and low-risk groups. Finally, a better-performing prognostic nomogram was integrated with the risk score and other clinical traits. In short, this multi-omics analysis demonstrated the application of ELMER in analyzing enhancer-associated regulatory network in LUAD, which provided promising strategies for epigenetic therapy and prognostic biomarkers.

Identification of HMMR as a prognostic biomarker for patients with lung adenocarcinoma via integrated bioinformatics analysis

Background

Lung adenocarcinoma (LUAD) is the most prevalent tumor in lung carcinoma cases and threatens human life seriously worldwide. Here we attempt to identify a prognostic biomarker and potential therapeutic target for LUAD patients.

Methods

Differentially expressed genes (DEGs) shared by GSE18842, GSE75037, GSE101929 and GSE19188 profiles were determined and used for protein-protein interaction analysis, enrichment analysis and clinical correlation analysis to search for the core gene, whose expression was further validated in multiple databases and LUAD cells (A549 and PC-9) by quantitative real-time PCR (qRT-PCR) and western blot analyses. Its prognostic value was estimated using the Kaplan-Meier method, meta-analysis and Cox regression analysis based on the Cancer Genome Atlas (TCGA) dataset and co-expression analysis was conducted using the Oncomine database. Gene Set Enrichment Analysis (GSEA) was performed to illuminate the potential functions of the core gene.

Results

A total of 115 shared DEGs were found, of which 24 DEGs were identified as candidate hub genes with potential functions associated with cell cycle and FOXM1 transcription factor network. Among these candidates, HMMR was identified as the core gene, which was highly expressed in LUAD as verified by multiple datasets and cell samples. Besides, high HMMR expression was found to independently predict poor survival in patients with LUAD. Co-expression analysis showed that HMMR was closely related to FOXM1 and was mainly involved in cell cycle as suggested by GSEA.

Conclusion

HMMR might be served as an independent prognostic biomarker for LUAD patients, which needs further validation in subsequent studies.

MiR-1246 regulates the PI3K/AKT signaling pathway by targeting PIK3AP1 and inhibits thyroid cancer cell proliferation and tumor growth

One of the most prevalent forms of endocrine malignancies is thyroid cancer. Herein, we explored the mechanisms whereby miR-1246 is involved in thyroid cancer. Phosphoinositide 3-kinase adapter protein 1 (PIK3AP1) was identified as a potential miR-1246 target, with the online Gene Expression Omnibus (GEO) database. The binding between miR-1246 and PIK3AP1 and the dynamic role of these two molecules in downstream PI3K/AKT signaling were evaluated. Analysis of GEO data demonstrated significant miR-1246 downregulation in thyroid cancer, and we confirmed that overexpression of miR-1246 can inhibit migratory, invasive, and proliferative activity in vitro and tumor growth in vivo. Subsequent studies indicated that miR-1246 overexpression decreased the protein level of PIK3AP1 and the phosphorylation of PI3K and AKT, which were reversed by PIK3AP1 overexpression. At the same time, overexpression of PIK3AP1 also reversed the miR-1246 mimics-induced inhibition proliferative, migratory, and invasive activity, while promoting increases in apoptotic death, confirming that miR-1246 function was negatively correlated with that of PIK3AP1. Subsequently, we found that the miR-1246 mimics-induced inhibition of PI3K/AKT phosphorylation was reversed by the PI3K/AKT activator IGF-1. miR-1246 mimics inhibited proliferative, migratory, and invasive activity while promoting increases in apoptotic death, which were reversed by IGF-1. Furthermore, miR-1246 agomir can inhibit tumor growth in vivo. We confirmed that miR-1246 affects the signaling pathway of PI3K/AKT via targeting PIK3AP1 and inhibits the development of thyroid cancer. Thus, miR-1246 is a new therapeutic target for thyroid cancer.

Integrated Analysis of the m6A-Related lncRNA Identified lncRNA ABALON/miR-139-3p/NOB1 Axis Was Involved in the Occurrence of Lung Cancer

Background

Lung cancer has the characteristics of early metastasis, high recurrence, and high mortality rate despite emerging advances in diagnostic. Early diagnosis can significantly improve the patient’s chances of cure and survival.

Purpose

This study aimed to identify and assess a prognostic lncRNA/miRNA/gene signature in patients with lung cancer.

Methods

Pearson correlation analysis, univariate Cox analysis and LASSO Cox analysis were used to construct a lung cancer prognostic risk model based on m6A-related lncRNA. The interaction between lncRNA-miRNA-gene was verified by luciferase reporter gene experiment.

Results

The Pearson correlation analysis determined that 1655 lncRNAs significantly correlated with the expression of m6A genes. A lung cancer prognostic risk model, including 14 m6A-related lncRNAs, was constructed through univariate Cox analysis and least absolute shrinkage and selection operator (LASSO) Cox analysis. ABALON was identified as the key lncRNA through cluster analysis and gene expression difference analysis.

Conclusion

It was experimentally verified that ABALON acted as a competing endogenous RNA by sponging miR-139-3p and indirectly regulated the expression of NOB1. This study provided a new biological target for the early diagnosis of lung cancer and a new direction for studying the mechanism of lung cancer.

Identification of Key Biomarkers and Pathways in Small-Cell Lung Cancer Using Biological Analysis

Background

Small-cell lung cancer (SCLC) is a major cause of carcinoma-related deaths worldwide. The aim of this study was to identify the key biomarkers and pathways in SCLC using biological analysis.

Methods

Key genes involved in the development of SCLC were identified by downloading three datasets from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were screened using the GEO2R online analyzer; for the functional annotation and pathway enrichment analysis of genes, Funrich software was used. Construction of protein-to-protein interaction (PPI) networks was accomplished using the Search Tool for the Retrieval of Interacting Genes (STRING), and network visualization and module identification were performed using Cytoscape.

Results

A total of 268 DEGs were ultimately obtained. The enriched functions and pathways of the upregulated DEGs included cell cycle, mitotic, and DNA replication, and the downregulated DEGs were enriched in epithelial-to-mesenchymal transition, serotonin degradation, and noradrenaline. Analysis of significant modules demonstrated that the upregulated genes are primarily concentrated in functions related to cell cycle and DNA replication. Kaplan-Meier analysis of hub genes revealed that they may promote the carcinogenesis and progression of SCLC. The result of ONCOMINE demonstrated that these 10 hub genes were significantly overexpressed in SCLC compared with normal samples.

Conclusion

Identification of the molecular functions and signaling pathways of participating DEGs can deepen the current understanding of the molecular mechanisms of SCLC. The knowledge gained from this work may contribute to the development of treatment options and improve the prognosis of SCLC in the future.

Exosomal miRNA-205 promotes breast cancer chemoresistance and tumorigenesis through E2F1

Breast cancer (BC) is a common malignant tumor in females. The challenge in treating BC is overcoming chemoresistance. Exosome-mediated transfer of miRNAs is a molecule-shuttle in intercellular communication. Thus, we aimed to investigate whether exosomal miRNA-205 could affect chemoresistance and tumorigenesis in recipient tumor cells and to elucidate the underlying mechanism in vivo and in vitro. Microarray and qRT-PCR assays demonstrated that miRNA-205 was upregulated in tamoxifen resistance MCF-7/TAMR-1 (M/T) cells and M/T cell-derived exosomes (M/T-Exo). The M/T-Exo was internalized by human BC cells (BCCs), causing increased expression of miRNA-205 in BCCs. Coculturing with M/T-Exo promoted tamoxifen resistance, proliferation, migration, and invasion while suppressed apoptosis in recipient BCCs, which were associated with activating the caspase pathway and phosphorylating Akt. Luciferase reporter assays showed that miRNA-205 directly targeted E2F Transcription Factor 1 (E2F1) in BCCs. Furthermore, knockdown of miRNA-205 or overexpression of E2F1 reversed the roles of M/T-Exo in BCCs. In vivo experiments showed that the intratumoral injection of M/T-Exo caused greater tamoxifen resistance and larger tumor size relative to mice treated with miRNA-205-knockdown or E2F1-overexpressing BCCs. Together, the results suggest that exosomal miRNA-205 may promote tamoxifen resistance and tumorigenesis in BC through targeting E2F1 in vivo and in vitro.

Bioinformatics analysis of mRNA and miRNA microarray to identify the key miRNA-mRNA pairs in cisplatin-resistant ovarian cancer

Background

Ovarian cancer (OC) is a gynecological malignancy with the highest mortality rate. Cisplatin (DDP) based chemotherapy is a standard strategy for ovarian cancer. Despite good response rates for initial chemotherapy, almost 80% of the patients treated with DDP based chemotherapy will experience recurrence due to drug-resistant, which will ultimately result in fatality. The aim of the present study was to examine the pathogenesis and potential molecular markers of cisplatin-resistant OC by studying the differential expression of mRNAs and miRNAs between cisplatin resistant OC cell lines and normal cell lines.

Methods

Two mRNA datasets (GSE58470 and GSE45553) and two miRNA sequence datasets (GSE58469 and GSE148251) were downloaded from the Gene expression omnibus (GEO) database. Differentially expressed genes (DEGs) and differentially expressed miRNAs (DEMs) were screened by the NetworkAnalyst. Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were conducted to analyze the biological functions of DEGs. The protein-protein interaction network was constructed using STRING and Cytoscape software to identify the molecular mechanisms of key signaling pathways and cellular activities. FunRich and MiRNATip databases were used to identify the target genes of the DEMs.

Results

A total of 380 DEGs, and 5 DEMs were identified. Protein–protein interaction (PPI) network of DEGs containing 379 nodes and 1049 edges was constructed, and 4 key modules and 24 hub genes related to cisplatin-resistant OC were screened. Two hundred ninety-nine target genes of the 5 DEMs were found out. Subsequently, one of these 299 target genes (UBB) belonging to the hub genes of GSE58470 and GSE45553 was identified by MCODE and CytoHubba,which was regulated by one miRNA (mir-454).

Conclusions

One miRNA–mRNA regulatory pairs (mir-454-UBB) was established. Taken together, our study provided evidence concerning the alteration genes involved in cisplatin-resistant OC, which will help to unravel the mechanisms underlying drug resistant.

Molecular Signature of Small Cell Lung Cancer after Treatment Failure: The MCM Complex as Therapeutic Target

Small cell lung cancer (SCLC) is a highly aggressive cancer, and patients who become refractory to first-line treatment have a poor prognosis. The development of effective treatment regimens is urgently needed. In this study, we identified a gene expression signature of SCLC after treatment failure using SCLC clinical specimens (GEO accession number: GSE162102). A total of 1,136 genes were significantly upregulated in SCLC tissues. These upregulated genes were subjected to KEGG pathway analysis, and "cell cycle", "Fanconi anemia", "alcoholism", "systemic lupus erythematosus", "oocyte meiosis", "homologous recombination", "DNA replication", and "p53 signaling" were identified as the enriched pathways among the genes. We focused on the cell cycle pathway and investigated the clinical significance of four genes associated with this pathway: minichromosome maintenance (MCM) 2, MCM4, MCM6, and MCM7. The overexpression of these MCM genes was confirmed in SCLC clinical specimens. Knockdown assays using siRNAs targeting each of these four MCM genes showed significant attenuation of cancer cell proliferation. Moreover, siRNA-mediated knockdown of each MCM gene enhanced the cisplatin sensitivity of SCLC cells. Our SCLC molecular signature based on SCLC clinical specimens after treatment failure will provide useful information to identify novel molecular targets for this disease.

Identification of potential target genes and crucial pathways in small cell lung cancer based on bioinformatic strategy and human samples

Small cell lung cancer (SCLC) is a carcinoma of the lungs with strong invasion, poor prognosis and resistant to multiple chemotherapeutic drugs. It has posed severe challenges for the effective treatment of lung cancer. Therefore, searching for genes related to the development and prognosis of SCLC and uncovering their underlying molecular mechanisms are urgent problems to be resolved. This study is aimed at exploring the potential pathogenic and prognostic crucial genes and key pathways of SCLC via bioinformatic analysis of public datasets. Firstly, 117 SCLC samples and 51 normal lung samples were collected and analyzed from three gene expression datasets. Then, 102 up-regulated and 106 down-regulated differentially expressed genes (DEGs) were observed. And then, functional annotation and pathway enrichment analyzes of DEGs was performed utilizing the FunRich. The protein-protein interaction (PPI) network of the DEGs was constructed through the STRING website, visualized by Cytoscape. Finally, the expression levels of eight hub genes were confirmed in Oncomine database and human samples from SCLC patients. It showed that CDC20, BUB1, TOP2A, RRM2, CCNA2, UBE2C, MAD2L1, and BUB1B were upregulated in SCLC tissues compared to paired adjacent non-cancerous tissues. These suggested that eight hub genes might be viewed as new biomarkers for prognosis of SCLC or to guide individualized medication for the therapy of SCLC.

Xiaoai Jiedu Recipe suppresses hepatocellular carcinogenesis through the miR-200b-3p /Notch1 axis

Purpose

Xiaoai Jiedu recipe (XJR), a formula long used by Chinese National Medical Professor Zhou Zhongying, has potent antitumor properties, but the molecular mechanism is still unclear. The aim of the study was to investigate the antitumor mechanism of XJR on hepatocellular carcinoma (HCC) by focusing on miRNA.

Methods

Three concentrations of XJR (low, middle, and high) were used to treat tumor xenograft mice models. Microarray technology was used to identify the differential expressed genes after XJR treatment, and bioinformatic tools and luciferase reporter assay to predict the potential pathways. HepG2 cells were transfected with inhibitor of miR-200b-3p to detect the effect of miR-200b-3p and Notch1 on tumor growth.

Results

XJR effectively exerted anti-HCC effect both in vitro and in vivo. MiRNA chip analysis results showed that the expression of 75 miRNAs was upregulated and 158 miRNAs was downregulated in blood from XJR-treated mice. Further validation by using real-time polymerase chain reaction (RT-PCR) assay showed that the expression of five miRNAs (miR-453, miR-200b-3p, miR-135a-1-3p, miR-1960, miR-378a-5p, and miR-466f) was consistent with the results of miRNA chip analysis. Among them, miR-200b-3p was selected as candidate for further research. Results of the MTT, migration, and wound healing assays showed that down-expression of miR-200b-3p abrogated the effect of XJR on cell growth and metastasis. Luciferase reporter assay confirmed that Notch1 was the direct target of miR-200b-3p. XJR significantly decreased Notch1 expression in HepG2 cells, whereas miR-200B-3p inhibitor abrogated the XJR-induced decrease in Notch1 expression.

Conclusion

This study indicated that XJR could effectively inhibit HCC and might exert its antitumor effect through the miR‐200b-3p/Notch1 axis. These findings provided new avenues for the use of XJR for prevention and treatment of HCC.

Common and distinct features of potentially predictive biomarkers in small cell lung carcinoma and large cell neuroendocrine carcinoma of the lung by systematic and integrated analysis

BACKGROUND

Large-cell neuroendocrine carcinoma of the lung (LCNEC) and small-cell lung carcinoma (SCLC) are neuroendocrine neoplasms. However, the underlying mechanisms of common and distinct genetic characteristics between LCNEC and SCLC are currently unclear. Herein, protein expression profiles and possible interactions with miRNAs were provided by integrated bioinformatics analysis, in order to explore core genes associated with tumorigenesis and prognosis in SCLC and LCNEC.

METHODS

GSE1037 gene expression profiles were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) in LCNEC and SCLC, as compared with normal lung tissues, were selected using the GEO2R online analyzer and Venn diagram software. Gene ontology (GO) analysis was performed using Database for Annotation, Visualization and Integrated Discovery. The biological pathway analysis was performed using the FunRich database. Subsequently, a protein-protein interaction (PPI) network of DEGs was generated using Search Tool for the Retrieval of Interacting Genes and displayed via Cytoscape software. The PPI network was analyzed by the Molecular Complex Detection app from Cytoscape, and 16 upregulated hub genes were selected. The Oncomine database was used to detect expression patterns of hub genes for validation. Furthermore, the biological pathways of these 16 hub genes were re-analyzed, and potential interactions between these genes and miRNAs were explored via FunRich.

RESULTS

A total of 384 DEGs were identified. A Venn diagram determined 88 common DEGs. The PPI network was constructed with 48 nodes and 221 protein pairs. Among them, 16 hub genes were extracted, 14 of which were upregulated in SCLC samples, as compared with normal lung specimens, and 10 were correlated with the cell cycle pathway. Furthermore, 57 target miRNAs for 8 hub genes were identified, among which 31 miRNAs were correlated with the progression of carcinoma, drug-resistance, radio-sensitivity, or autophagy in lung cancer.

CONCLUSION

This study provided effective biomarkers and novel therapeutic targets for diagnosis and prognosis of SCLC and LCNEC.