Bioinformatics analysis to identify the critical genes, microRNAs and long noncoding RNAs in melanoma

Identification of Core Genes and Pathways in Melanoma Metastasis via Bioinformatics Analysis

Metastasis is the leading cause of melanoma-related mortality. Current therapies are rarely curative for metastatic melanoma, revealing the urgent need to identify more effective preventive and therapeutic targets. This study aimed to screen the core genes and molecular mechanisms related to melanoma metastasis. A gene expression profile, GSE8401, including 31 primary melanoma and 52 metastatic melanoma clinical samples, was downloaded from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) between melanoma metastases and primary melanoma were screened using GEO2R tool. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genome (KEGG) analyses of DEGs were performed using the Database for Annotation Visualization and Integrated Discovery (DAVID). The Search Tool for the Retrieval of Interacting Genes (STRING) and Cytoscape with Molecular Complex Detection (MCODE) plug-in tools were utilized to detect the protein–protein interaction (PPI) network among DEGs. The top 10 genes with the highest degrees of the PPI network were defined as hub genes. In the results, 425 DEGs, including 60 upregulated genes and 365 downregulated genes, were identified. The upregulated genes were enriched in ECM–receptor interactions and the regulation of actin cytoskeleton, while 365 downregulated genes were enriched in amoebiasis, melanogenesis, and ECM–receptor interactions. The defined hub genes included CDK1, COL17A1, EGFR, DSG1, KRT14, FLG, CDH1, DSP, IVL, and KRT5. In addition, the mRNA and protein levels of the hub genes during melanoma metastasis were verified in the TCGA database and paired post- and premetastatic melanoma cells, respectively. Finally, KRT5-specific siRNAs were utilized to reduce the KRT5 expression in melanoma A375 cells. An MTT assay and a colony formation assay showed that KRT5 knockdown significantly promoted the proliferation of A375 cells. A Transwell assay further suggested that KRT5 knockdown significantly increased the cell migration and cell invasion of A375 cells. This bioinformatics study provided a deeper understanding of the molecular mechanisms of melanoma metastasis. The in vitro experiments showed that KRT5 played the inhibitory effects on melanoma metastasis. Therefore, KRT5 may serve important roles in melanoma metastasis.

Effects of Bacille Calmette Guerin (BCG) vaccination during COVID-19 infection

The coronavirus disease 2019 (COVID-19) is caused by the infection of highly contagious severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), also known as the novel coronavirus. In most countries, the containment of this virus spread is not controlled, which is driving the pandemic towards a more difficult phase. In this study, we investigated the impact of the Bacille Calmette Guerin (BCG) vaccination on the severity and mortality of COVID-19 by performing transcriptomic analyses of SARS-CoV-2 infected and BCG vaccinated samples in peripheral blood mononuclear cells (PBMC). A set of common differentially expressed genes (DEGs) were identified and seeded into their functional enrichment analyses via Gene Ontology (GO)-based functional terms and pre-annotated molecular pathways databases, and their Protein-Protein Interaction (PPI) network analysis. We further analysed the regulatory elements, possible comorbidities and putative drug candidates for COVID-19 patients who have not been BCG-vaccinated. Differential expression analyses of both BCG-vaccinated and COVID-19 infected samples identified 62 shared DEGs indicating their discordant expression pattern in their respected conditions compared to control. Next, PPI analysis of those DEGs revealed 10 hub genes, namely ITGB2, CXCL8, CXCL1, CCR2, IFNG, CCL4, PTGS2, ADORA3, TLR5 and CD33. Functional enrichment analyses found significantly enriched pathways/GO terms including cytokine activities, lysosome, IL-17 signalling pathway, TNF-signalling pathways. Moreover, a set of identified TFs, miRNAs and potential drug molecules were further investigated to assess their biological involvements in COVID-19 and their therapeutic possibilities. Findings showed significant genetic interactions between BCG vaccination and SARS-CoV-2 infection, suggesting an interesting prospect of the BCG vaccine in relation to the COVID-19 pandemic. We hope it may potentially trigger further research on this critical phenomenon to combat COVID-19 spread.

Construction of a Ferroptosis-Related Gene Signature for Predicting Survival and Immune Microenvironment in Melanoma Patients

Objective

In this research, we studied the genes associated with ferroptosis to develop a prognostic model and find out an association with tumor immune microenvironment in skin cutaneous melanoma (SKCM) patients.

Methods

To find SKCM-related ferroptosis genes, we used Cox regression and LASSO approach on 60 genes related to ferroptosis and SKCM-related RNA-seq. Following that, a ferroptosis-related gene signature was created. Time-dependent ROC curve and Kaplan–Meier analysis were calculated to determine its capability of prediction. Besides, several assessments were used to evaluate overall survival (OS), accompanied by the creation of a nomogram for the clinicopathologic factors and the ferroptosis-related gene signature we established. We also investigated the relationship between ferroptosis-related gene signature with three immune checkpoints and immune cell infiltration.

Results

Our prognostic model included two genes (ALOX5, CHAC1). In both TCGA and GEO cohorts, OS was lower in high-risk category. Using our gene signature, we can reliably predict OS. Additionally, our gene signature can predict immune cell infiltration and SKCM immunotherapy response.

Conclusion

Our gene signature has shown to be a reliable predictor of OS, reflect the immune microenvironment, and predict the effectiveness of immunotherapy for SKCM patients.

Functional Prediction of Long Noncoding RNAs in Cutaneous Melanoma Using a Systems Biology Approach

Cutaneous melanoma is the most aggressive type of skin cancer which its incidence has significantly increased in recent years worldwide. Thus, more investigations are required to identify the underlying mechanisms of melanoma malignant transformation and metastasis. In this context, long noncoding RNAs (lncRNAs) are a new type of noncoding transcripts that their dysregulations are associated with almost all cancers including melanoma. However, the precise functional roles of most of the significantly altered lncRNAs in melanoma have not yet been fully inspected. In this study, a comprehensive list of lncRNAs was interrogated across cutaneous melanoma samples to identify the significantly altered/dysregulated lncRNAs. To this end, lncRNAs were filtered in several steps and the selected lncRNAs projected to a bioinformatic and systems biology analysis using several publicly available databases and tools such as GEPIA and cBioPortal. According to our results, 30 lncRNAs were notably altered/dysregulated in cutaneous melanoma most of which were co-expressed with each other. Also, co-expression/alteration and differential expression analyses led to the selection of 12 out of these 30 lncRNAs as cutaneous melanoma key lncRNAs. Furthermore, functional demonstrated that these 12 lncRNAs might be involved in melanoma-relevant biological processes and pathways. In addition, the end result of our analyses demonstrated that these lncRNAs are associated with the clinicopathological features of melanoma patients. These 12 lncRNAs need to be further investigated in future studies to characterize their exact roles in melanoma development and to identify their potential for being used as drug targets and/or biomarkers for cutaneous melanoma.

MYBPC2 and MYL1 as Significant Gene Markers for Rhabdomyosarcoma

BACKGROUND

Rhabdomyosarcoma is the most common soft tissue tumor in children. Rhabdomyosarcoma commonly results in pain and bleeding caused by tumor compression and is prone to early metastasis and recurrence, which can seriously affect the therapeutic outcomes and long-term prognosis. Up to 37.7% of rhabdomyosarcomas may metastasize. Therefore, the molecular mechanisms underlying rhabdomyosarcoma must be explored to identify an effective target for its early diagnosis and specific treatment.

METHODS

A dataset of 18 rhabdomyosarcoma tissue samples and 6 healthy skeletal muscle samples was downloaded. Differentially expressed genes between rhabdomyosarcoma and healthy tissue samples were identified by GEO2R. Kyoto Encyclopedia of Genes and Genomes and gene ontology pathway enrichment analyses were performed. A protein-protein interaction network was constructed, and hub genes were identified. Expression and survival analyses of hub genes were performed. Additionally, 30 patients with rhabdomyosarcoma were recruited, and overall survival information and samples were collected. Reverse transcription quantitative real-time polymerase chain reaction assays were performed to verify the expression of MYBPC2 and MYL1 in rhabdomyosarcoma tumor tissues. The Kaplan-Meier method was used to explore overall survival based on our clinical data.

RESULTS

In total, 164 genes were up-regulated and 394 were down-regulated in rhabdomyosarcoma tumor tissues. Gene ontology analysis revealed that variations were predominantly enriched in the cell cycle, muscle contraction, muscle system processes, cytoskeleton, nucleotide binding, and cytoskeletal protein binding. The protein-protein interaction network revealed 3274 edges, and 441 nodes were constructed. Ten hub genes were identified; of these, MYBPC2 and MYL1 were significantly up-regulated in rhabdomyosarcoma. Compared with the healthy group, patients with rhabdomyosarcoma exhibiting high expression of MYBPC2 and MYL1 exhibited significantly worse overall survival.

CONCLUSIONS

We found differentially expressed genes between rhabdomyosarcoma and healthy tissue samples. MYBPC2 and MYL1 may be involved in the pathogenesis of rhabdomyosarcoma and therefore deserve further exploration.

Bioinformatic Analysis Identifies Potential Key Genes in the Pathogenesis of Melanoma

Melanoma is the deadliest skin tumor and is prone to distant metastases. The incidence of melanoma has increased rapidly in the past few decades, and current trends indicate that this growth is continuing. This study was aimed to explore the molecular mechanisms of melanoma pathogenesis and discover underlying pathways and genes associated with melanoma. We used high-throughput expression data to study differential expression profiles of related genes in melanoma. The differentially expressed genes (DEGs) of melanoma in GSE15605, GSE46517, GSE7553, and the Cancer Genome Atlas (TCGA) datasets were analyzed. Differentially expressed genes (DEGs) were identified by paired t-test. Then the DEGs were performed cluster and principal component analyses and protein–protein interaction (PPI) network construction. After that, we analyzed the differential genes through bioinformatics and got hub genes. Finally, the expression of hub genes was confirmed in the TCGA databases and collected patient tissue samples. Total 144 up-regulated DEGs and 16 down-regulated DEGs were identified. A total of 17 gene ontology analysis (GO) terms and 11 pathways were closely related to melanoma. Pathway of pathways in cancer was enriched in 8 DEGs, such as junction plakoglobin (JUP) and epidermal growth factor receptor (EGFR). In the PPI networks, 9 hub genes were obtained, such as loricrin (LOR), filaggrin (FLG), keratin 5 (KRT5), corneodesmosin (CDSN), desmoglein 1 (DSG1), desmoglein 3 (DSG3), keratin 1 (KRT1), involucrin (IVL), and EGFR. The pathway of pathways in cancer and its enriched DEGs may play important roles in the process of melanoma. The hub genes of DEGs may become promising melanoma candidate genes. Five key genes FLG, DSG1, DSG3, IVL, and EGFR were identified in the TCGA database and melanoma tissues. The results suggested that FLG, DSG1, DSG3, IVL, and EGFR might play important roles and potentially be valuable in the prognosis and treatment of melanoma. These hub genes might well have clinical significance as diagnostic markers.

Identification of Signatures of Prognosis Prediction for Melanoma Using a Hypoxia Score

Melanoma is one of the most aggressive cancers. Hypoxic microenvironment affects multiple cellular pathways and contributes to tumor progression. The purpose of the research was to investigate the association between hypoxia and melanoma, and identify the prognostic value of hypoxia-related genes. Based on the GSVA algorithm, gene expression profile collected from The Cancer Genome Atlas (TCGA) was used for calculating the hypoxia score. The Kaplan–Meier plot suggested that a high hypoxia score was correlated with the inferior survival of melanoma patients. Using differential gene expression analysis and WGCNA, a total of 337 overlapping genes associated with hypoxia were determined. Protein-protein interaction network and functional enrichment analysis were conducted, and Lasso Cox regression was performed to establish the prognostic gene signature. Lasso regression showed that seven genes displayed the best features. A novel seven-gene signature (including ABCA12, PTK6, FERMT1, GSDMC, KRT2, CSTA, and SPRR2F) was constructed for prognosis prediction. The ROC curve inferred good performance in both the TCGA cohort and validation cohorts. Therefore, our study determined the prognostic implication of the hypoxia score in melanoma and showed a novel seven-gene signature to predict prognosis, which may provide insights into the prognosis evaluation and clinical decision making.

Deep sequencing of small RNAs reveals the repertoire of miRNAs and piRNAs in Biomphalaria glabrata

BACKGROUND

Biomphalaria glabrata snails are widely distributed in schistosomiasis endemic areas like America and Caribe, displaying high susceptibility to infection by Schistosoma mansoni. After the availability of B. glabrata genome and transcriptome data, studies focusing on genetic markers and small non-coding RNAs have become more relevant. The small RNAs have been considered important through their ability to finely regulate the gene expression in several organisms, thus controlling the functions like cell growth, metabolism, and susceptibility/resistance to infection.

OBJECTIVE

The present study aims on identification and characterisation of the repertoire of small non-coding RNAs in B. glabrata (Bgl-small RNAs).

METHODS

By using small RNA sequencing, bioinformatics tools and quantitative reverse transcription polymerase chain reaction (RT-qPCR), we identified, characterised, and validated the presence of small RNAs in B. glabrata.

FINDINGS

89 mature miRNAs were identified and five of them were classified as Mollusk-specific. When compared to model organisms, sequences of B. glabrata miRNAs showed a high degree of conservation. In addition, several target genes were predicted for all the mature miRNAs identified. Furthermore, piRNAs were identified in the genome of B. glabrata for the first time. The B. glabrata piRNAs showed strong conservation of uridine as first nucleotide at 5’ end, besides adenine at 10th position. Our results showed that B. glabrata has diverse repertoire of circulating ncRNAs, several which might be involved in mollusk susceptibility to infection, due to their potential roles in the regulation of S. mansoni development.

MAIN CONCLUSIONS

Further studies are necessary in order to confirm the role of the Bgl-small RNAs in the parasite/host relationship thus opening new perspectives on interference of small RNAs in the organism development and susceptibility to infection.

MiR-4458/human antigen R (HuR) modulates PBX3 mRNA stability in melanoma tumorigenesis

Melanoma, a malignancy of the melanocyte, is characterized as the most fatal skin cancer with an increasing incidence. Of note, in spite of great attempts made for better treatment, the therapeutic outcome is barely satisfactory. Abnormal expression of microRNAs (miRNAs) acting as oncogenes or tumor suppressor genes, is frequently implicated in multiple human cancers, including melanoma. Here, we found that miRNA-4458, a reportedly tumor-suppressive miRNA in several cancers, was downregulated in melanoma cells. Besides, our findings indicated that microRNA-4458 (miR-4458) hindered cell proliferation and migration, yet induced apoptosis in melanoma. Mechanical interaction of miR-4458 and PBX3 mRNA, thereby inhibiting PBX3 expression in melanoma cells, was also presented in this work. Human antigen R (HuR) was reported to be greatly upregulated in diverse cancers and HuR-dependent stabilization of target gene contributed a lot to tumor progression. In this study, it revealed the stabilization of PBX3 mRNA by HuR, thereby boosting PBX3 expression. Lastly, we concluded that miR-4458 and HuR modulated the expression of PBX3 in a competitive manner in melanoma tumorigenesis, which might yield a novel insight into the molecular pathogenesis of melanoma.

Bioinformatics Analysis Identifies MicroRNAs and Target Genes Associated with Prognosis in Patients with Melanoma

Background

Melanoma of the skin can be associated with early metastases and poor prognosis. This study aimed to identify microRNAs (miRNAs) and target genes associated with prognosis in melanoma using bioinformatics analysis.

Material/Methods

The Gene Expression Omnibus (GEO) database identified the microarray dataset GSE20994. Differentially expressed miRNAs (DE-miRNAs) were first identified using R language software and validated by GEO2R. Potential target genes of DE-miRNAs were screened, and their targets and prognostic role were evaluated in the miRTarBase database. Pathway enrichment and functional annotation analysis for target genes were established using the DAVID database. miRNA-hub gene networks and protein-protein interaction (PPI) networks were constructed and visualized using the STRING database and Cytoscape. Kaplan-Meier survival curves were constructed using transcriptome and survival data from the UALCAN web tool.

Results

There were 132 upregulated and 134 down-regulated DE-miRNAs identified from human melanoma samples. From the top three upregulated miRNAs, there were 580 potential predicted target genes, and from the top three down-regulated miRNAs, there 543 potential predicted target genes. miR-300 was upregulated, and miR-629 was down-regulated in melanoma. Two pivotal bub genes, TP53 and GAPDH, were identified in the PPI network. Five out of ten hub genes were modulated by upregulated miR-580, and five by miR-629. Increased mRNA expression of DAPK2 was associated with increased OS, and increased mRNA expression of SKCM, TECPR2, and ZNF781 were associated with reduced OS.

Conclusions

Bioinformatics analysis identified miRNAs and target genes associated with melanoma that may represent potential prognostic and therapeutic biomarkers.

Long non-coding RNA PANDAR promotes melanoma cell invasion through regulating epithelial-mesenchymal transition

Melanoma is a malignant skin tumor and has a poor cure rate because of its high metastatic potential. Overexpression of long non-coding (lnc) RNA PANDAR has been observed in several kinds of cancer, but the function of PANDAR on melanoma is still unclear. Therefore, this study was to explore the mechanism of PANDAR on the occurrence and progression in malignant melanoma. We detected expression of PANDAR in malignant melanoma tissues and cell lines by qRT-PCR and analyzed correlation of PANDAR expression with the patients' prognosis. Furthermore, we investigated the effects of PANDAR on cell viability, migration, invasion, tumorigenesis, and epithelial-mesenchymal transition (EMT) using CCK-8, Transwell, and nude mouse subcutaneous tumor formation model assays and Western blotting analysis, respectively. From the results, we discovered that the PANDAR expression is strikingly upregulated in melanoma tissues compared with paired-adjacent non-tumorous tissues and elevated PANDAR is positively correlated with short overall survival time. The results also demonstrate that knockdown of PANDAR inhibits cell viability, migration, invasion, tumorigenesis, and EMT, whereas overexpression of PANDAR gave opposite results by promoting cell viability, migration, invasion, tumorigenesis, and EMT of melanoma cells. These new findings all illustrate that PANDAR might play a pivotal oncogenic role in the occurrence and development of melanoma, and PANDAR might promote melanoma cell invasion through regulating EMT, providing a potential diagnostic and therapeutic target for melanoma.

Integrative analysis of competing endogenous RNA network focusing on long noncoding RNA associated with progression of cutaneous melanoma

Cutaneous melanoma (CM) is the most malignant tumor of skin cancers because of its rapid development and high mortality rate. Long noncoding RNAs (lncRNAs), which play essential roles in the tumorigenesis and metastasis of CM and interplay with microRNAs (miRNAs) and mRNAs, are hopefully considered to be efficient biomarkers to detect deterioration during the progression of CM to improve the prognosis. Bioinformatics analysis was fully applied to predict the vital lncRNAs and the associated miRNAs and mRNAs, which eventually constructed the competing endogenous RNA (ceRNA) network to explain the RNA expression patterns in the progression of CM. Further statistical analysis emphasized the importance of these key genes, which were statistically significantly related to one or few clinical features from the ceRNA network. The results showed the lncRNAs MGC12926 and LINC00937 were verified to be strongly connected with the prognosis of CM patients.

The cytomegalovirus protein US31 induces inflammation through mono-macrophages in systemic lupus erythematosus by promoting NF-κB2 activation

It has been hypothesized that human cytomegalovirus (HCMV) infection, especially in monocyte and CD34 (+) myeloid cells, acts as a important regulator of immune system to promote inflammation in multiple autoimmune diseases. The aim of this study was to elucidate the HCMV gene expression profiles in the peripheral blood mononuclear cells (PBMCs) of SLE patients and demonstrate the effect and mechanism of viral gene associated with SLE in mono-macrophages functions. Using two RNA-Seq techniques in combination with RT-PCR, 11 viral genes mainly associated with latent HCMV infection were identified in the PBMCs of SLE patients. Among these viral genes, US31 with previously unknown function was highly expressed in the PBMCs of SLE patients compared to healthy controls. Analysis of function indicated that US31 expression could induce inflammation in monocyte and macrophage and stimulate macrophage differentiation toward an M1 macrophage phenotype. Screening via protein chips in combination with bioinformatic analysis and consequent detection of mono-macrophages function indicates that the direct interaction between US31 and NF-κB2 contributed the NF-kB2 activation. Consequent analysis indicated US31 directly interacted with NF-κB2, contribute to the polyubiquitination of the phosphorylated p100 and consequent activation of NF-κB2. Taken together, our data uncovered a previously unknown role of the HCMV protein US31 in inducing NF-κB-mediated mono-macrophage inflammation in the pathogenesis and development of SLE. Our findings provide a foundation for the continued investigation of novel therapeutic targets for SLE patients.