The signature composed of immune-related long noncoding ribonucleic acids (irlncRNAs) with no requirement of specific expression level seems to be valuable in predicting the survival of patients with hepatocellular carcinoma (HCC). Here, we retrieved raw transcriptome data from The Cancer Genome Atlas (TCGA), identified irlncRNAs by co-expression analysis, and recognized differently expressed irlncRNA (DEirlncRNA) pairs using univariate analysis. In addition, we modified Lasso penalized regression. Then, we compared the areas under curve, counted the Akaike information criterion (AIC) values of 5-year receiver operating characteristic curve, and identified the cut-off point to set up an optimal model for distinguishing the high-or low-disease-risk groups among patients with HCC. We then reevaluated them from the viewpoints of survival, clinic-pathological characteristics, tumor-infiltrating immune cells, chemotherapeutics efficacy, and immunosuppressed biomarkers. 36 DEirlncRNA pairs were identified, 12 of which were included in a Cox regression model. After regrouping the patients by the cut-off point, we could more effectively differentiate between them based on unfavorable survival outcome, aggressive clinic-pathological characteristics, specific tumor immune infiltration status, low chemotherapeutics sensitivity, and highly expressed immunosuppressed biomarkers. The signature established by paring irlncRNA regardless of expression levels showed a promising clinical prediction value.
Salinity is an important abiotic stressor that negatively affects plant growth. In this study, we investigated the physiological and molecular mechanisms underlying moderate and high salt tolerance in diploid (2×) and tetraploid (4×) Robinia pseudoacacia L. Our results showed greater H2O2 accumulation and higher levels of important antioxidative enzymes and non-enzymatic antioxidants in 4× plants compared with 2× plants under salt stress. In addition, 4× leaves maintained a relatively intact structure compared to 2× leaves under a corresponding condition. NaCl treatment didn’t significantly affect the photosynthetic rate, stomatal conductance or leaf intercellular CO2 concentrations in 4× leaves. Moreover, proteins from control and salt treated 2× and 4× leaf chloroplast samples were extracted and separated by two-dimensional gel electrophoresis. A total of 61 spots in 2× (24) and 4× (27) leaves exhibited reproducible and significant changes under salt stress. In addition, 10 proteins overlapped between 2× and 4× plants under salt stress. These identified proteins were grouped into the following 7 functional categories: photosynthetic Calvin-Benson Cycle (26), photosynthetic electron transfer (7), regulation/defense (5), chaperone (3), energy and metabolism (12), redox homeostasis (1) and unknown function (8). This study provides important information of use in the improvement of salt tolerance in plants.
The cyclic GMP-AMP synthase-stimulator of interferon genes (cGAS-STING) pathway induces innate immunity by activating the production of inflammatory cytokines and type I interferons. Recently, studies revealed that self-DNA from by-products of chromosome instability and tumors could activate the cGAS-STING pathway, and subsequently promote or inhibit tumor development. However, the prognostic value and correlations with immune infiltrates of the cGAS-STING pathway in hepatocellular carcinoma (HCC) have not been clarified. In this study, we used the Molecular Signatures Database, Oncomine, UALCAN, Human Protein Atlas, Kaplan–Meier plotter, LinkedOmics, and Tumor Immune Estimation Resource databases. Overexpression of XRCC5, IRF3, TRIM21, STAT6, DDX41, TBK1, XRCC6, TREX1, PRKDC, and TMEM173 was markedly correlated with clinical stages and pathological grades in HCC. Moreover, higher mRNA expression of XRCC5, XRCC6, and PRKDC was significantly related with shorter overall survival. However, higher mRNA expression of IFI16, STAT6, NLRC3, and TMEM173 was associated with favorable overall survival. Our results suggested that the kinase targets of the cGAS-STING pathway included the SRC family of tyrosine kinases (LCK and LYN), phosphoinositide 3-kinase-related protein kinase (PIKK) family kinases (ATM and ATR), and mitogen-activated protein kinase 1 (MAPK1). Furthermore, we identified significant correlations among the expression of cGAS-STING pathway and infiltration of B cells, CD4+T cells, CD8+ T cells, macrophages, neutrophils, and dendritic cells in HCC. The expression of the cGAS-STING pathway also exhibited strong relationships with diverse immune marker sets in HCC. These findings suggest that cGAS-STING pathway members may be used as prognostic biomarkers and immunotherapeutic targets HCC patients.
Microbial syntrophic metabolism has been well accepted as the heart of how methanogenic and other anaerobic microbial communities function. In this work, we applied a single-cell RT-qPCR approach to reveal gene-expression heterogeneity in a model syntrophic system of Desulfovibrio vulgaris and Methanosarcina barkeri, as compared with the D. vulgaris monoculture. Using the optimized primers and single-cell analytical protocol, we quantitatively determine gene-expression levels of 6 selected target genes in each of the 120 single cells of D. vulgaris isolated from its monoculture and dual-culture with M. barkeri. The results demonstrated very significant cell-to-cell gene-expression heterogeneity for the selected D. vulgaris genes in both the monoculture and the syntrophic dual-culture. Interestingly, no obvious increase in gene-expression heterogeneity for the selected genes was observed for the syntrophic dual-culture when compared with its monoculture, although the community structure and cell-cell interactions have become more complicated in the syntrophic dual-culture. In addition, the single-cell RT-qPCR analysis also provided further evidence that the gene cluster (DVU0148-DVU0150) may be involved syntrophic metabolism between D. vulgaris and M. barkeri. Finally, the study validated that single-cell RT-qPCR analysis could be a valuable tool in deciphering gene functions and metabolism in mixed-cultured microbial communities.
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