Correlation analysis of lipid metabolism genes with the immune microenvironment in gastric cancer and the construction of a novel gene signature

Background Lipid metabolism reprogramming plays an important role in cell growth, proliferation, angiogenesis and invasion of cancer. However, the prognostic value of lipid metabolism during gastric cancer (GC) progression and the relationship with the immune microenvironment are still unclear. The aim of this study was to clarify the correlation between lipid metabolism genes and GC immunity. Method We obtained 350 patients from The Cancer Genome Atlas (TCGA) and 355 patients from Gene Expression Omnibus (GEO) databases. Lipid metabolism-related gene datasets were obtained from the Reactome and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. Molecular subtypes were obtained by Consensus clustering, and subtype immune status was analyzed using ESTIMATE, TIMER and microenvironmental cell population counter (MCP Counter) algorithm for immune analysis. Functional analyses included the application of Gene Set Enrichment Analysis (GSEA), KEGG, gene ontology (GO), and Protein–Protein Interaction Networks (PPI) to evaluate the molecular mechanisms of different subtypes. Weighted gene co-expression network analysis (WGCNA) was used to identify genes associated with immunity. The LASSO algorithm and multivariate Cox regression analysis were used to construct prognostic risk models. Result Based on the lipid metabolism genes found in GC, patients with GC can be divided into two subgroups with significantly different survival. The subgroup with a better prognosis presented higher immune scores and immune infiltrating cell abundance. 1170 immune-related genes were screened by WGCNA, and further screening by PPI network analysis revealed that PTPRC, CD4, ITGB2 and LCP2 were closely associated with immune cells. Combined with the TIDE score results, it was found that the population with high expression of the above genes might be more sensitive to immunotherapy (AU)

Correlation analysis of lipid metabolism genes with the immune microenvironment in gastric cancer and the construction of a novel gene signature.

BACKGROUND: Lipid metabolism reprogramming plays an important role in cell growth, proliferation, angiogenesis and invasion of cancer. However, the prognostic value of lipid metabolism during gastric cancer (GC) progression and the relationship with the immune microenvironment are still unclear. The aim of this study was to clarify the correlation between lipid metabolism genes and GC immunity. METHOD: We obtained 350 patients from The Cancer Genome Atlas (TCGA) and 355 patients from Gene Expression Omnibus (GEO) databases. Lipid metabolism-related gene datasets were obtained from the Reactome and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. Molecular subtypes were obtained by Consensus clustering, and subtype immune status was analyzed using ESTIMATE, TIMER and microenvironmental cell population counter (MCP Counter) algorithm for immune analysis. Functional analyses included the application of Gene Set Enrichment Analysis (GSEA), KEGG, gene ontology (GO), and Protein-Protein Interaction Networks (PPI) to evaluate the molecular mechanisms of different subtypes. Weighted gene co-expression network analysis (WGCNA) was used to identify genes associated with immunity. The LASSO algorithm and multivariate Cox regression analysis were used to construct prognostic risk models. RESULT: Based on the lipid metabolism genes found in GC, patients with GC can be divided into two subgroups with significantly different survival. The subgroup with a better prognosis presented higher immune scores and immune infiltrating cell abundance. 1170 immune-related genes were screened by WGCNA, and further screening by PPI network analysis revealed that PTPRC, CD4, ITGB2 and LCP2 were closely associated with immune cells. Combined with the TIDE score results, it was found that the population with high expression of the above genes might be more sensitive to immunotherapy. In addition, a survival prediction model for GC was developed based on five survival-related lipid metabolism genes, PIAS4, PLA2R1, PRKACA, SLCO1A2 and STARD4. The ROC analysis over time showed that the risk prediction score model had good stability. CONCLUSION: Lipid metabolism gene expression is correlated with the immune microenvironment in GC patients and can accurately predict their prognosis. Studies on lipid metabolism and GC immunity can help to screen the population for immunotherapy benefits.

Significant enhancement of power conversion efficiency for dye sensitized solar cell using 1D/3D network nanostructures as photoanodes.

The single-crystalline TiO2 nanorod arrays with rutile phase have attracted much attention in the dye sensitized solar cells (DSSCs) applications because of their superior chemical stability, better electron transport properties, higher refractive index and low production cost. However, it suffers from a low surface area as compared with TiO2 nanoparticle films. In order to enlarge the surface area of TiO2 nanorod arrays, the 1D nanorods/3D nanotubes sample was synthesized using a facile two-step hydrothermal process involving hydrothermal growth 1D/3D nanorods and followed by post-etching treatment. In such bi-layer structure, the oriented TiO2 nanorods layer could provide direct pathway for fast electron transportation, and the 3D nanotubes layer offers a higher surface area for dye loading, therefore, the 1D nanorods/3D nanotubes photoanode exhibited faster electron transport and higher surface area than either 1D or 3D nanostructures alone, and an highest efficiency of 7.68% was achieved for the DSSCs based on 1D nanorods/3D nanotubes photoanode with further TiCl4 treatment.

[The application of artificial dermis and recombinant bFGF afer immersion bath in residual burn wound].

OBJECTIVE: To observe the effect of application of a new type of artificial biological dressing and recombinant bull fibroblast growth factor( rb-FGF2) after immersion bath in the treatment of residual infected burn wounds at late postburn stage. METHODS: Fifty-six patients with residual wounds at late postburn stage were enrolled in the study, and they were randomly divided into A( n = 28, experimental) and B (n = 28, control) groups. After treatment with immersion bath, the wounds in group A were treated with semi-exposure method. The wound were covered with suitable shape of biological dressings in suitable shape and rb-FGF2 spray twice a day after an immersion bath, and the dressing was changed every other day or every 2 days. To compare the treatment effect, the wounds in group B were only treated with a dressing of monolayer gauze wetted with povidone iodine. The clinical results, the bacteriological state findings, and the corresponding safety indices were determined 10 days after treatment. RESULTS: The wound healing rate, efficacy and the bacterial clearance rate in A group were 64. 3% ,89. 3% ,92. 3% , respectively, and they were obviously higher than those in B group (32. 1% , 67. 9% , 72. 0% , respectively, P < 0. 01 ). No adverse side-effects were observed in either group. CONCLUSION: Application of artificial dermis and bFGF after immersion bath is safe and effective for the elimination of residual wounds at late postburn stage, and it is also beneficial to control wound infection and promote the wound healing.