The role of interleukin-20 in liver disease: Functions, mechanisms and clinical applications.

Liver disease is a severe public health concern worldwide. There is a close relationship between the liver and cytokines, and liver inflammation from a variety of causes leads to the release and activation of cytokines. The functions of cytokines are complex and variable, and are closely related to their cellular origin, target molecules and mode of action. Interleukin (IL)-20 has been studied as a pro-inflammatory cytokine that is expressed and regulated in some diseases. Furthermore, accumulating evidences has shown that IL-20 is highly expressed in clinical samples from patients with liver disease, promoting the production of pro-inflammatory molecules involved in liver disease progression, and antagonists of IL-20 can effectively inhibit liver injury and produce protective effects. This review highlights the potential of targeting IL-20 in liver diseases, elucidates the potential mechanisms of IL-20 inducing liver injury, and suggests multiple viable strategies to mitigate the pro-inflammatory response to IL-20. Genomic CRISPR/Cas9-based screens may be a feasible way to further explore the signaling pathways and regulation of IL-20 in liver diseases. Nanovector systems targeting IL-20 offer new possibilities for the treatment and prevention of liver diseases.

Novel molecular classification and prognosis of papillary renal cell carcinoma based on a large-scale CRISPR-Cas9 screening and machine learning.

Papillary renal cell carcinoma (PRCC) is a highly heterogeneous cancer, and PRCC patients with advanced/metastatic subgroup showed obviously shorter survival compared to other kinds of renal cell carcinomas. However, the molecular mechanism and prognostic predictors of PRCC remain unclear and are worth deep studying. The aim of this study is to identify novel molecular classification and construct a reliable prognostic model for PRCC. The expression data were retrieved from TCGA, GEO, GTEx and TARGET databases. CRISPR data was obtained from Depmap database. The key genes were selected by the intersection of CRISPR-Cas9 screening genes, differentially expressed genes, and genes with prognostic capacity in PRCC. The molecular classification was identified based on the key genes. Drug sensitivity, tumor microenvironment, somatic mutation, and survival were compared among the novel classification. A prognostic model utilizing multiple machine learning algorithms based on the key genes was developed and tested by independent external validation set. Our study identified three clusters (C1, C2 and C3) in PRCC based on 41 key genes. C2 had obviously higher expression of the key genes and lower survival than C1 and C3. Significant differences in drug sensitivity, tumor microenvironment, and mutation landscape have been observed among the three clusters. By utilizing 21 combinations of 9 machine learning algorithms, 9 out of 41 genes were chosen to construct a robust prognostic signature, which exhibited good prognostic ability. SERPINH1 was identified as a critical gene for its strong prognostic ability in PRCC by univariate and multiple Cox regression analyses. Quantitative real-time PCR and Western blot demonstrated that SERPINH1 mRNA and protein were highly expressed in PRCC cells compared with normal human renal cells. This study exhibited a new molecular classification and prognostic signature for PRCC, which may provide a potential biomarker and therapy target for PRCC patients.

The role of SPI1-TYROBP-FCER1G network in oncogenesis and prognosis of osteosarcoma, and its association with immune infiltration.

Osteosarcoma is an aggressive malignant bone sarcoma worldwide. A causal gene network with specific functions underlying both the development and progression of OS was still unclear. Here we firstly identified the differentially expressed genes (DEGs) between control and OS samples, and then defined the hub genes and top clusters in the protein-protein interaction (PPI) network of these DEGs. By focusing on the hub gene TYROBP in the top 1 cluster, a conserved TYROBP co-expression network was identified. Then the effect of the network on OS overall survival was analyzed. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses and Gene Set Enrichment Analysis (GSEA) were used to explore the functions of the network. XCell platform and ssGSEA algorithm were conducted to estimate the status of immune infiltration. ChEA3 platform, GSEA enrichment analysis, and Drug Pair Seeker (DPS) were used to predict the key transcription factor and its upstream signal. We identified the downregulated SPI1-TYROBP-FCER1G network in OS, which were significantly enriched in immune-related functions. We also defined a two-gene signature (SPI1/FCER1G) that can predict poorer OS overall survival and the attenuated immune infiltration when downregulated. The SPI1-TYROBP-FCER1G network were potentially initiated by transcription factor SPI1 and would lead to the upregulated CD86, MHC-II, CCL4/CXCL10/CX3CL1 and hence increased immune infiltrations. With this study, we could better explore the mechanism of OS oncogenesis and metastasis for developing new therapies.

FTIR microspectroscopic investigation of Lactobacillus paracasei apoptosis induced by cisplatin.

Recent studies have shown that bacteria can also undergo apoptosis, which has gradually attracted researchers' attention. Cisplatin is a first-line drug to treat several cancers, but it can damage beneficial bacteria. Hence it is very important to explore the damage mechanism of cisplatin on beneficial bacteria. In this study, Lactobacillus paracasei, one kind of beneficial bacteria, was used as the model to investigate cisplatin damage. Conventional detection showed that cisplatin induced the apoptosis of Lactobacillus paracasei. Then Fourier transform infrared (FTIR) microspectroscopy was used to detect biomacromolecular changes in Lactobacillus paracasei apoptosis, and the following results were obtained: ① Second derivative IR spectra showed the changes of DNA, proteins, polysaccharides and lipids; ② Peak-area ratios suggested the changes of the protein and lipid structure and the decrease of DNA content; ③ Principal component analysis (PCA) further revealed significant changes in the DNA and protein content/structure. This study may have a new insight into the adverse reaction mechanism of cisplatin on Lactobacillus, moreover, it suggests that FTIR microspectroscopy may be a useful supplementary tool for investigating bacterial apoptosis.