Secondary analysis of existing microarray data reveals potential gene drivers of cutaneous squamous cell carcinoma

Aberrant AHRR, ADAMTS2 and FAM184 DNA Methylation: Candidate Biomarkers in the Oral Rinse of Heavy Smokers

OBJECTIVE

To identify DNA methylation patterns of heavy smokers in oral rinse samples.

METHODS

Genome-wide DNA methylation data was imported from Gene Expression Omnibus GSE70977 using the GEOquery package. Two independent sets were analyzed: (a) 71 epigenomes of cancer-free subjects (heavy smokers n = 37 vs. non-smokers n = 31); for concordance assessment (b) 139 oral-cancer patients' epigenomes (heavy smokers n = 92 vs. non-smokers n = 47). Differential DNA methylation for CpG positions and at the regional level was determined using Limma and DMRcate Bioconductor packages. The linear model included sex, age, and alcohol consumption. The statistical threshold was set to p < 0.05. Functional gene prioritization analysis was performed for gene-targeted analysis.

RESULTS

In individuals without cancer and heavy smokers, the FAM184B gene was found with two CpG positions differentially hypermethylated (p = 0.012 after FDR adjustment), in a region of 48 bp with an absolute methylation difference >10% between groups (p = 1.76 × 10^-8). In the analysis corresponding to oral-cancer patients, we found AHRR differentially hypomethylated cancer patients, but also in subjects without oral cancer in the targeted analyses. Remarkably, ADAMTS2 was found differentially hypermethylated in heavy smokers without a diagnosis of cancer in two consecutive probes cg05575921 (p = 3.13 × 10^-7) and cg10208897 (p = 1.36 × 10^-5).

CONCLUSIONS

Differentially methylated AHRR, ADAMTS2, and FAM184B genes are biomarker candidates in oral rinse samples.

Design and Computational Analysis of an MMP9 Inhibitor in Hypoxia-Induced Glioblastoma Multiforme

The main therapeutic difficulties in treating hypoxia-induced glioblastoma multiforme (GBM) are toxicity of current treatments and the resistance brought on by the microenvironment. More effective therapeutic alternatives are urgently needed to reduce tumor lethality. Hence, we screened plant-based natural product panels intending to identify novel drugs without elevating drug resistance. We explored GEO for the hypoxia GBM model and compared hypoxic genes to non-neoplastic brain cells. A total of 2429 differentially expressed genes expressed exclusively in hypoxia were identified. The functional enrichment analysis demonstrated genes associated with GBM, further PPI network was constructed, and biological pathways associated with them were explored. Seven webtools, including GEPIA2.0, TIMER2.0, TCGA-GBM, and GlioVis, were used to validate 32 hub genes discovered using Cytoscape tool in GBM patient samples. Four GBM-specific hypoxic hub genes, LYN, MMP9, PSMB9, and TIMP1, were connected to the tumor microenvironment using TIMER analysis. 11 promising hits demonstrated positive drug-likeness with nontoxic characteristics and successfully crossed blood-brain barrier and ADMET analyses. Top-ranking hits have stable intermolecular interactions with the MMP9 protein according to molecular docking, MD simulation, MM-PBSA, PCA, and DCCM analyses. Herein, we have reported flavonoids, 7,4'-dihydroxyflavan, (3R)-3-(4-hydroxybenzyl)-6-hydroxy-8-methoxy-3,4-dihydro-2H-1-benzopyran, and 4'-hydroxy-7-methoxyflavan, to inhibit MMP9, a novel hypoxia gene signature that could serve as a promising predictor in various clinical applications, including GBM diagnosis, prognosis, and targeted therapy.

A Study on the Expression of Messenger RNAs and Long Noncoding RNA in Keloid Fibroblasts Based on Gene Expression Omnibus Microarray Data Mining

OBJECTIVE

The purpose of this study was to find the coding RNA [messenger RNA (mRNA)] and long noncoding RNA (lncRNA) expressed in keloid through the analysis of Gene Expression Omnibus microarray chip of keloid fibroblasts.

MATERIALS AND METHODS

Gene Expression Omnibus database GSE7890 database was downloaded with selection of keloids and normal scar group data. The data were analyzed by R language combined with online database. The log2FC>1, P value <0.01 was chosen as screening criteria, and the differentially expressed mRNAs were screened for GO and KEGG function analysis.

RESULTS

One hundred fifty-five mRNA expression in the keloid group was significantly different from that in the normal group, including 31 groups with upregulated mRNA expression and 124 groups with down-regulated mRNA expression. Meanwhile, 8 lncRNAs were changed in the keloid group, including 3 upregulated (Rp11-420a23.1, Rp11-522b15.3, and Rp11-706j10.1) and 5 down-regulated (LINC00511, LINC00327, Hoxb-as3, Rp11-385n17.1, and Rp3-428l16.2). Quantitative polymerase chain reaction analysis of DElncRNAs in keloid fibroblasts showed that the expression of all DElncRNAs except for RP11-385N17.1 was increased in the keloid group compared with the control group. Moreover, the differences in LINC00511 and RP11-706J10.1 were statistically significant.

CONCLUSION

The noncoding RNA information of Gene Expression Omnibus chip data can be deeply mined through bioinformatics, and the potential epigenomic mechanism affecting keloid formation can be found from the existing database.

Dampened Inflammatory Signalling and Myeloid-Derived Suppressor-Like Cell Accumulation Reduces Circulating Monocytic HLA-DR Density and May Associate With Malignancy Risk in Long-Term Renal Transplant Recipients

Background

Malignancy is a major cause of morbidity and mortality in transplant recipients. Identification of those at highest risk could facilitate pre-emptive intervention such as reduction of immunosuppression. Reduced circulating monocytic HLA-DR density is a marker of immune depression in the general population and associates with poorer outcome in critical illness. It has recently been used as a safety marker in adoptive cell therapy trials in renal transplantation. Despite its potential as a marker of dampened immune responses, factors that impact upon monocytic HLA-DR density and the long-term clinical sequelae of this have not been assessed in transplant recipients.

Methods

A cohort study of stable long-term renal transplant recipients was undertaken. Serial circulating monocytic HLA-DR density and other leucocyte populations were quantified by flow cytometry. Gene expression of monocytes was performed using the Nanostring nCounter platform, and 13-plex cytokine bead array used to quantify serum concentrations. The primary outcome was malignancy development during one-year follow-up. Risk of malignancy was calculated by univariate and multivariate proportionate hazards modelling with and without adjustment for competing risks.

Results

Monocytic HLA-DR density was stable in long-term renal transplant recipients (n=135) and similar to non-immunosuppressed controls (n=29), though was suppressed in recipients receiving prednisolone. Decreased mHLA-DRd was associated with accumulation of CD14+CD11b+CD33+HLA-DRlo monocytic myeloid-derived suppressor-like cells. Pathway analysis revealed downregulation of pathways relating to cytokine and chemokine signalling in monocytes with low HLA-DR density; however serum concentrations of major cytokines did not differ between these groups. There was an independent increase in malignancy risk during follow-up with decreased HLA-DR density.

Conclusions

Dampened chemokine and cytokine signalling drives a stable reduction in monocytic HLA-DR density in long-term transplant recipients and associates with subsequent malignancy risk. This may function as a novel marker of excess immunosuppression. Further study is needed to understand the mechanism behind this association.

Competing Endogenous RNA Network in Non-Keloid-Prone Individuals During Wound Healing

ABSTRACT

To study the interaction between differentially expressed long non-coding RNAs (lncRNAs), microRNAs, and messenger RNAs during wound healing in normal individuals. The GSE113621 dataset was downloaded from gene expression matrix, specimens regarding non-keloid-prone individuals were selected, including items before and 6 weeks after injury. A Pearson correlation coefficient of > 0.95 was selected as the index to screen targeting relationships among different RNAs. Cytoscape was used to construct a network diagram. The expression of 2547 lncRNAs was changed during the wound healing process-1479 were upregulated and 1068 were downregulated. After analyzing competitive endogenous RNA network, 4 upregulated (MEG8, MEG3, MIR181A1HG, MIR4435-2HG) lncRNAs were found expressed during wound healing. MEG8/MEG3 may regulate fibroblast proliferation, differentiation, and apoptosis through hsa-miR-296-3p/miR-6763-5p. In-depth mining of gene expression matrix data indicated that lncRNAs and a competitive endogenous RNA regulatory network participate in the wound healing process, possibly providing novel intervention targets and treatment options for delayed wound healing.

Seven key hub genes identified by gene co-expression network in cutaneous squamous cell carcinoma

Background

Cutaneous squamous cell carcinoma (cSCC) often follows actinic keratosis (AK) and is the second most common skin cancer worldwide. To reduce metastasis risk, it is important to diagnose and treat cSCC early. This study aimed to identify hub genes associated with cSCC and AK.

Methods

This study used three datasets GSE45216, GSE98774, and GSE108008. We combined samples from the GSE45216 and GSE98774 datasets into the new dataset GSE45216–98774. We applied a weighted gene co-expression network analysis (WGCNA) to investigate key modules and hub genes associated with cSCC and AK. We considered the hub genes found in both the GSE45216–98774 and GSE108008 datasets as validated hub genes. We tested whether the expression of hub genes could predict patient survival outcomes in other cancers using TCGA pan-cancer data.

Results

We identified modules most relevant to cSCC and AK. Additionally, we identified and validated seven hub genes of cSCC: GATM, ARHGEF26, PTHLH, MMP1, POU2F3, MMP10 and GATA3. We did not find validated hub genes for AK. Each hub gene was significantly associated with the survival of various cancer types. Only GATA3 was significantly associated with melanoma survival.

Conclusions

We applied WGCNA to find seven hub genes that play important roles in cSCC tumorigenesis. These results provide new insights that help explain the pathogenesis of cSCC. These hub genes may become biomarkers or therapeutic targets for accurate diagnosis and treatment of cSCC in the future.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08604-y.

3-Deoxysappanchalcone Inhibits Skin Cancer Proliferation by Regulating T-Lymphokine-Activated Killer Cell-Originated Protein Kinase in vitro and in vivo

Background

Skin cancer is one of the most commonly diagnosed cancers worldwide. The 5-year survival rate of the most aggressive late-stage skin cancer ranges between 20 and 30%. Thus, the discovery and investigation of novel target therapeutic agents that can effectively treat skin cancer is of the utmost importance. The T-lymphokine-activated killer cell-originated protein kinase (TOPK), which belongs to the serine-threonine kinase class of the mitogen-activated protein kinase kinase (MAPKK) family, is highly expressed and activated in skin cancer. The present study investigates the role of 3-deoxysappanchalcone (3-DSC), a plant-derived functional TOPK inhibitor, in suppressing skin cancer cell growth.

Purpose

In the context of skin cancer prevention and therapy, we clarify the effect and mechanism of 3-DSC on different types of skin cancer and solar-simulated light (SSL)-induced skin hyperplasia.

Methods

In an in vitro study, western blotting and in vitro kinase assays were utilized to determine the protein expression of TOPK and its activity, respectively. Pull-down assay with 3-DSC and TOPK (wild-type and T42A/N172 mutation) was performed to confirm the direct interaction between T42A/N172 amino acid sites of TOPK and 3-DSC. Cell proliferation and anchorage-independent cell growth assays were utilized to determine the effect of 3-DSC on cell growth. In an in vivo study, the thickness of skin and tumor size were measured in the acute SSL-induced inflammation mouse model or SK-MEL-2 cell-derived xenografts mouse model treated with 3-DSC. Immunohistochemistry analysis of tumors isolated from SK-MEL-2 cell-derived xenografts was performed to determine whether cell-based results observed upon 3-DSC treatment could be recapitulated in vivo.

Results

3-DSC is able to inhibit cell proliferation in skin cancer cells in an anchorage-dependent and anchorage-independent manner by regulation of TOPK and its related signaling pathway in vitro. We also found that application of 3-DSC reduced acute SSL-induced murine skin hyperplasia. Additionally, we observed that 3-DSC decreased SK-MEL-2 cell-derived xenograft tumor growth through attenuating phosphorylation of TOPK and its downstream effectors including ERK, RSK, and c-Jun.

Conclusions

Our results suggest that 3-DSC may function in a chemopreventive and chemotherapeutic capacity by protecting against UV-induced skin hyperplasia and inhibiting tumor cell growth by attenuating TOPK signaling, respectively.

Transcriptome analysis of the procession from chronic pancreatitis to pancreatic cancer and metastatic pancreatic cancer

Exploring the underlying mechanisms of cancer development is useful for cancer treatment. In this paper, we analyzed the transcriptome profiles from the human normal pancreas, pancreatitis, pancreatic cancer and metastatic pancreatic cancer to study the intricate associations among pancreatic cancer progression. We clustered the transcriptome data, and analyzed the differential expressed genes. WGCNA was applied to construct co-expression networks and detect important modules. Importantly we selected the module in a different way. As the pancreatic disease deteriorates, the number of differentially expressed genes increases. The gene networks of T cells and interferon are upregulated in stages. In conclusion, the network-based study provides gradually activated gene networks in the disease progression of pancreatitis, pancreatic cancer, and metastatic pancreatic cancer. It may contribute to the rational design of anti-cancer drugs.

Integrated Analysis of Key Pathways and Drug Targets Associated With Vogt-Koyanagi-Harada Disease

Background

Vogt-Koyanagi-Harada (VKH) disease is a complex disease associated with multiple molecular immunological mechanisms. As the underlying mechanism for VKH disease is unclear, we hope to utilize an integrated analysis of key pathways and drug targets to develop novel therapeutic strategies.

Methods

Candidate genes and proteins involved in VKH disease were identified through text-mining in the PubMed database. The GO and KEGG pathway analyses were used to examine the biological functions of the involved pathways associated with this disease. Molecule-related drugs were predicted through Drug-Gene Interaction Database (DGIdb) analysis.

Results

A total of 48 genes and 54 proteins were associated with VKH disease. Forty-two significantly altered pathways were identified through pathway analysis and were mainly related to immune and inflammatory responses. The top five of significantly altered pathways were termed as “inflammatory bowel disease,” “cytokine-cytokine receptor interaction,” “allograft rejection,” “antigen processing,” and “presentation and Herpes simplex infection” in the KEGG database. IFN-γ and IL-6 were identified as the key genes through network analysis. The DGIdb analysis predicted 48 medicines as possible drugs for VKH disease, among which Interferon Alfa-2B was co-associated both with IFN-γ and IL-6.

Conclusions

In this study, systematic analyses were utilized to detect key pathways and drug targets in VKH disease via bioinformatics analysis. IFN-γ and IL-6 were identified as the key mediators and possible drug targets in VKH disease. Interferon Alfa-2B was predicted to be a potentially effective drug for VKH disease treatment by targeting IFN-γ and IL-6, which warrants further experimental and clinical investigations.

Secondary data mining of GEO database for long non-coding RNA and Competing endogenous RNA network in keloid-prone individuals

This study aimed to identify long non-coding RNAs (lncRNAs), microRNAs (miRNAs), and messenger RNAs (mRNAs) differentially expressed (DE) during keloid formation, predict DElncRNA-DEmiRNA-DEmRNA interactions, and construct a competing endogenous RNA (ceRNA) network through secondary data mining of keloid-related sequencing and microarray data in the open-source Gene Expression Omnibus (GEO) database. The GSE113621 dataset was downloaded from the GEO database, |log₂FC|>1 and p<0.05 were set as screening criteria, genes expressed only in keloid-prone individuals were selected as research objects, and DEmRNAs, DElncRNAs, and DEmiRNAs before injury and 6 weeks after injury were screened. A Pearson correlation coefficient (PCC) of > 0.95 was selected as the index to predict the targeting relationships among lncRNAs, miRNAs, and mRNAs; and a network diagram was constructed using Cytoscape. The expression of 2356 lncRNAs was changed in the keloid-prone group—1306 were upregulated and 1050 were downregulated. Six lncRNAs, namely, 2 upregulated (DLEU2 and AP000317.2) and 4 downregulated (ADIRF-AS1, AC006333.2, AL137127.1 and LINC01725) lncRNAs, were expressed only in the keloid-prone group and were used to construct a ceRNA network. DLEU2 may regulate fibroblast proliferation, differentiation, and apoptosis through hsa-miR-30a-5p/hsa-miR-30b-5p. In-depth mining of GEO data indicated that lncRNAs and a ceRNA regulatory network participate in the wound healing process in keloid-prone individuals, possibly providing novel intervention targets and treatment options for keloid scars.

OmicsARules: a R package for integration of multi-omics datasets via association rules mining

BACKGROUND

The improvements of high throughput technologies have produced large amounts of multi-omics experiments datasets. Initial analysis of these data has revealed many concurrent gene alterations within single dataset or/and among multiple omics datasets. Although powerful bioinformatics pipelines have been developed to store, manipulate and analyze these data, few explicitly find and assess the recurrent co-occurring aberrations across multiple regulation levels.

RESULTS

Here, we introduced a novel R-package (called OmicsARules) to identify the concerted changes among genes under association rules mining framework. OmicsARules embedded a new rule-interestingness measure, Lamda3, to evaluate the associated pattern and prioritize the most biologically meaningful gene associations. As demonstrated with DNA methlylation and RNA-seq datasets from breast invasive carcinoma (BRCA), esophageal carcinoma (ESCA) and lung adenocarcinoma (LUAD), Lamda3 achieved better biological significance over other rule-ranking measures. Furthermore, OmicsARules can illustrate the mechanistic connections between methlylation and transcription, based on combined omics dataset. OmicsARules is available as a free and open-source R package.

CONCLUSIONS

OmicsARules searches for concurrent patterns among frequently altered genes, thus provides a new dimension for exploring single or multiple omics data across sequencing platforms.