Identification of key genes and construction of microRNA-mRNA regulatory networks in non-small cell lung cancer

Downregulation of microRNA‑494 inhibits cell proliferation in lung squamous cell carcinoma via the induction of PUMA‑α‑mediated apoptosis

Increased evidence has shown that abnormal microRNA (miRNA) plays pivotal roles in numerous types of cancer. However, their expression, function and mechanism in lung squamous cell carcinoma (LSCC) remains to be fully elucidated. The aim of the present study was to investigate the suppressive role of miR-494 in LSCC progression and elucidate its regulatory mechanism. By analyzing expression profiles of miRNAs in LSCC tissues using miRNA microarray, it was revealed that miR-494 was significantly upregulated in 22 pairs of LSCC tissues. Subsequently, reverse transcription-quantitative PCR was performed to determine the expression of miR-494 and p53-upregulated-modulator-of-apoptosis-α (PUMA-α). Western blot analysis was conducted to examine protein levels. Dual-luciferase reporter assay was used to confirm the binding between miR-494 and PUMA-α. Annexin V-fluoresceine isothiocyanate/propidium iodide staining and CCK-8 assays were employed to determine cell apoptosis and cell viability, respectively. It was also revealed that miR-494 was highly expressed in LSCC cell lines compared with that in 16HBE cells. Further experiments confirmed that knockdown of miR-494 reduced cell viability and induced LSCC apoptosis. Bioinformatics analysis predicted that miR-494 could potentially target PUMA-α; also known as Bcl-2-binding component 3, a pro-apoptotic factor, and an inverse correlation between the expression of miR-494 and PUMA-α mRNA levels in LSCC tissues was found. Furthermore, PUMA-α inhibition could reverse the promoting effect of miR-494 knockdown on apoptosis in LSCC cells. Taken together, these findings demonstrated that miR-494 functions as an oncogene by targeting PUMA-α in LSCC, and miR-494 may serve as a novel therapeutic target for treating LSCC.

Integrative Analysis for Identification of Therapeutic Targets and Prognostic Signatures in Non-Small Cell Lung Cancer

Differential expressions of certain genes during tumorigenesis may serve to identify novel manageable targets in the clinic. In this work with an integrated bioinformatics approach, we analyzed public microarray datasets from Gene Expression Omnibus (GEO) to explore the key differentially expressed genes (DEGs) in non-small cell lung cancer (NSCLC). We identified a total of 984 common DEGs in 252 healthy and 254 NSCLC gene expression samples. The top 10 DEGs as a result of pathway enrichment and protein–protein interaction analysis were further investigated for their prognostic performances. Among these, we identified high expressions of CDC20, AURKA, CDK1, EZH2, and CDKN2A genes that were associated with significantly poorer overall survival in NSCLC patients. On the contrary, high mRNA expressions of CBL, FYN, LRKK2, and SOCS2 were associated with a significantly better prognosis. Furthermore, our drug target analysis for these hub genes suggests a potential use of Trichostatin A, Pracinostat, TGX-221, PHA-793887, AG-879, and IMD0354 antineoplastic agents to reverse the expression of these DEGs in NSCLC patients.

Construction of ceRNA network to identify the lncRNA and mRNA related to non-small cell lung cancer

BACKGROUND

Non-small cell lung cancer (NSCLC) harms human health, but its pathogenesis remains unclear. We wish to provide more molecular therapeutic targets for NSCLC.

METHODS

The NSCLC tissue and normal tissue samples were screened for genetic comparison in the TCGA database. The predicted lncRNA and mRNA in BEAS2B and A549 cells were detected.

RESULTS

Volcano plot displayed differentially expressed lncRNAs and mRNAs in adjacent tissues and NSCLC tissues. The survival curve showed that the lncRNA and mRNA had a significant impact on the patient's survival. The results of GO term enrichment analysis indicated that mRNA functions were enriched in cell cycle-related pathways. In the ceRNA interaction network, 13 lncRNAs and 20 miRNAs were found to have an interactive relationship. Finally, 3 significantly different lncRNAs (LINC00968, lnc-FAM92A-9 and lnc-PTGFR-1) and 6 mRNAs (CTCFL, KRT5, LY6D, TMEM, GBP6, and TMEM179) with potential therapeutic significance were screened out. And the cell experiment verified our results.

CONCLUSION

We screened out clinically significant 3 lncRNAs and 6 mRNAs involved in the ceRNA network, which were the key to our future research on the treatment of NSCLC.

Biochar produced from the co-pyrolysis of sewage sludge and waste tires for cadmium and tetracycline adsorption from water

Application of sewage sludge biochar as an adsorbent for pollutant removal has obtained special attention due to their low cost and surface functionality. In this research, sludge-tire composite biochar (STB) was successfully prepared through co-pyrolysis at 300, 500 and 700 °C, respectively. Cadmium (Cd) and tetracycline (TC) were selected as the target pollutant. The results indicated that STB has the highest surface area (49.71 m²/g), more inorganic minerals (Kaolinite) as well as relatively stable physicochemical properties with 10% tire particles (TP) at 700 °C. The adsorption results indicated that the pseudo-second-order equation and Langmuir isotherm model could better describe the adsorption of Cd²⁺ and TC by STB. The maximum adsorption capacity of Cd²⁺ and TC was 50.25 mg/g and 90.09 mg/g, respectively. The main mechanism of the adsorption process of STB for Cd mainly involves anion binding adsorption and ion exchange. The main mechanism of the adsorption process of STB for TC mainly involves complexation and cation exchange. The present study could set a scientific foundation for further research on the recycle of sewage sludge and tires.

LncRNA COL1A2-AS1 promotes skin fibroblast apoptosis by repressing p-Smad3 and promoting β-catenin expression

LncRNA COL1A2-AS1 has been demonstrated to inhibit fibroblast proliferation of hypertrophic scars. However, the function of COL1A2-AS1 in normal skin fibroblasts remains poorly studied. Here, we report that overexpression of COL1A2-AS1 promoted normal skin fibroblast apoptosis. On the basis of mRNA-seq data and gene set enrichment analysis plus Kyoto encyclopedia of genes and genomes pathway analysis, 16 upregulated and 125 downregulated mRNAs were found; TGF-β, Wnt, and MAPK pathways were potentially involved. Western blot assay confirmed that overexpression of COL1A2-AS1 repressed p-Smad3 expression and promoted β-catenin expression. Furthermore, COL1A2-AS1 overexpression combined with either TGF-β1 or siRNA against β-catenin reversed the upregulation of apoptosis in the COL1A2-AS1 overexpression group. In conclusion, our study revealed the roles of COL1A2-AS1 in normal skin fibroblast apoptosis, with COL1A2-AS1 functioning by repressing p-Smad3 expression and promoting β-catenin expression.

Screening, identification and validation of CCND1 and PECAM1/CD31 for predicting prognosis in renal cell carcinoma patients

Clear cell renal cell carcinoma (ccRCC) is one of the most common cancers worldwide. Despite intense efforts to elucidate its pathogenesis, the molecular mechanisms and genetic characteristics of this cancer remain unknown. In this study, three expression profile data sets (GSE15641, GSE16441 and GSE66270) were integrated to identify candidate genes that could elucidate functional pathways in ccRCC. Expression data from 63 ccRCC tumors and 54 normal samples were pooled and analyzed. The GSE profiles shared 379 differentially expressed genes (DEGs), including 249 upregulated genes, and 130 downregulated genes. A protein-protein interaction network (PPI) was constructed and analyzed using STRING and Cytoscape. Functional and signaling pathways of the shared DEGs with significant p values were identified. Kaplan-Meier plots of integrated expression scores were used to analyze survival outcomes. These suggested that FN1, ICAM1, CXCR4, TYROBP, EGF, CAV1, CCND1 and PECAM1/CD31 were independent prognostic factors in ccRCC. Finally, to investigate early events in renal cancer, we screened for the hub genes CCND1 and PECAM1/CD31. In summary, integrated bioinformatics analysis identified candidate DEGs and pathways in ccRCC that could improve our understanding of the causes and underlying molecular events of ccRCC. These candidate genes and pathways could be therapeutic targets for ccRCC.