No abstract

Hepatocellular carcinoma (HCC) is one of the most common cancers in the world. The landscape of HCC’s molecular alteration signature has been explored over the last few decades. Even so, more comprehensive research is still needed to improve understanding of tumorigenesis and progression of HCC, as well as to identify potential biomarkers for the malignancy. In this research, a comprehensive bioinformatics analysis was conducted based on the publicly available databases from both the Cancer Genome Atlas (TCGA) program and the gene expression omnibus (GEO) database. R/Bioconductor was used to analyze differentially expressed genes (DEGs) between HCC tumor and normal control (NC) samples, and then a protein-protein interaction (PPI) network of DEGs was established through the STRING platform. Finally, the application of specific candidate genes as diagnostic or prognostic biomarkers of HCC was explored and evaluated by ROC and survival analysis. A total of 310 DEGs were detected in the HCC tumor samples. Thirty-six hub DEGs in the PPI network and 10 candidates of the 36 genes showed significant alterations in tumor expression, including CDKN3, TOP2A, UBE2C, CDC20, PBK, ASPM, KIF20A, NCAPG, CCNB2, CYP3A4. The 10-gene signature had relatively significant effects when distinguishing tumors from normal samples (sensitivity >70%, specificity >70%, AUC >0.8, p <  0.001). Eight candidate genes were negatively correlated with the overall survival rate of the patients ( p <  0.05) and were all up-regulated in HCC tumor samples. The age and gender factors had no significant impact on the overall survival rate of HCC patients ( p >  0.05), and the TNM stage status factor had a significant negative prognosis correlation ( p <  0.05). This research provides evidence for a better understanding of tumorigenesis and progression of HCC and helps to explore candidate targets for disease diagnosis and treatment.

The specific and efficient delivery of small interfering RNA (siRNA) into cancer cells in vivo remains a major obstacle. In this study, we investigated whether ultrasound-targeted microbubble destruction (UTMD) combined with dual targeting of HSP72 and HSC70 in prostate cancer cell lines improve the specific and efficient cell uptake of siRNA, inhibit HSP90 function and induce extensive tumor-specific apoptosis. VCaP cells were transfected with siRNA oligonucleotides. Cell viability assays were used to evaluate the safety of UTMD. The expression of HSP70, HSP90, caspase-8, caspase-3, PARP-1 and cleaved caspase-3 were determined by quantitative PCR and western blotting. Apoptosis and transfection efficiency were detected by flow cytometry. We found that HSP72, HSC70 and HSP90 expression was absent or weak in normal prostate epithelial cells (RWPE-1), and became uniformly and strongly expressed in prostate cancer cells (VCaP). VCaP and RWPE-1 cells expressed very low levels of caspase-8, caspase-3, PARP-1 and cleaved caspase-3. UTMD combined with dual targeting of HSP72 and HSC70 siRNA impoved the efficiency of transfection, cell uptake of siRNA, downregulated HSP70 and HSP90 expression in VCaP cells on the mRNA and protein levels, and upregulated major apoptotic markers (PARP-1, caspase-8, caspase-3 and cleaved caspase-3), thus, inducing extensive tumor-specific apoptosis. The Cell Counting Kit-8 assay showed decreased cellular viability in the HSP72/HSC70-siRNA silenced group. These results suggest that the combination of UTMD with dual targeting of HSP72 and HSC70 may improve the specific and efficient cell uptake of siRNA, inhibit HSP90 function and induce extensive tumor-specific apoptosis, indicating a novel, potential means for targeting therapeutic strategy to prostate cancer cells.

In plants, chloride channels (CLC) are involved in a series of specific functions, such as regulation of nutrient transport and stress tolerance. Members of the wheat Triticum aestivum L. CLC (TaCLC) gene family have been proposed to encode anion channels/transporters that may be related to nitrogen transportation. To better understand their roles, TaCLC family was screened and 23 TaCLC gene sequences were identified using a Hidden Markov Model in conjunction with wheat genome database. Gene structure, chromosome location, conserved motif, and expression pattern of the resulting family members were then analyzed. Phylogenetic analysis showed that the TaCLC family can be divided into two subclasses (I and II) and seven clusters (-a, -c1, -c2, -e, -f1, -f2, and -g2). Using a wheat RNA-seq database, the expression pattern of TaCLC family members was determined to be an inducible expression type. In addition, seven genes from seven different clusters were selected for quantitative real-time PCR (qRT-PCR) analysis under low nitrogen stress or salt stress conditions, respectively. The results indicated that the gene expression levels of this family were up-regulated under low nitrogen stress and salt stress, except the genes of TaCLC-c2 cluster which were from subfamily -c. The yeast complementary experiments illustrated that TaCLC-a-6AS-1, TaCLC-c1-3AS, and TaCLC-e-3AL all had anion transport functions for NO3− or Cl−, and compensated the hypersensitivity of yeast GEF1 mutant strain YJR040w (Δgef1) in restoring anion-sensitive phenotype. This study establishes a theoretical foundation for further functional characterization of TaCLC genes and provides an initial reference for better understanding nitrate nitrogen transportation in wheat.

The spread of microorganisms in the air, especially pathogenic microorganisms, seriously affects people’s normal life. Therefore, the analysis and detection of airborne microorganisms is of great importance in environmental detection, disease prevention and biosafety. As an emerging technology with the advantages of integration, miniaturization and high efficiency, microfluidic chips are widely used in the detection of microorganisms in the environment, bringing development vitality to the detection of airborne microorganisms, and they have become a research highlight in the prevention and control of infectious diseases. Microfluidic chips can be used for the detection and analysis of bacteria, viruses and fungi in the air, mainly for the detection of Escherichia coli, Staphylococcus aureus, H1N1 virus, SARS-CoV-2 virus, Aspergillus niger, etc. The high sensitivity has great potential in practical detection. Here, we summarize the advances in the collection and detection of airborne microorganisms by microfluidic chips. The challenges and trends for the detection of airborne microorganisms by microfluidic chips was also discussed. These will support the role of microfluidic chips in the prevention and control of air pollution and major outbreaks.