Steroid receptor coactivator 1 (Src-1) and Twist1 are aberrantly upregulated in a variety of tumors and play an important role in tumor progression. However, the exact role of Src-1 and Twist1 in nasopharyngeal carcinoma (NPC) is uncertain. In this study, we investigated the possible prognostic value and biological effect of Src-1 and Twist1 in NPC. Src-1 and Twist1 expression was detected in a cohort of NPC patients (n = 134) by qRT-PCR. Kaplan-Meier survival analysis was used comparing overall survival (OS) and progression-free survival (PFS). Multivariate analysis was performed using the Cox proportional hazard regression model. Biologic effect of Src-1 and Twist1 in NPC cell lines was evaluated by western blot, colony formation assay, soft agar assay, scratch wound healing assay, transwell invasion assay and tumor xenografts growth. We have found that Src-1 and Twist1 were aberrantly upregulated in human NPC tissues, and associated with advanced tumor stage, distant metastasis and unfavorable prognosis. Knockdown of Src-1 or Twist1 in human NPC cell line CNE-1 suppressed colony formation, anchorage-independent growth, cell migration, invasion and tumor xenografts growth, while enforced expression of Src-1 or Twist1 in human NPC cell line HNE-2 promotes anchorage-independent growth, cell migration and invasion. In addition, Src-1 and Twist1 could suppress E-cadherin expression and increase Vimentin expression, thus suggested that Src-1 and Twist1 enhanced the malignant behaviors of NPC cells via inducing epithelial-mesenchymal transition (EMT). Our data indicated that Src-1 and Twist1 could be possible prognostic biomarkers and potential therapy targets for patients with NPC.
Summary
Microbiome research is now moving beyond the compositional analysis of microbial taxa in a sample. Increasing evidence from large human microbiome studies suggests that functional consequences of changes in the intestinal microbiome may provide more power for studying their impact on inflammation and immune responses. Although 16S rRNA analysis is one of the most popular and a cost-effective method to profile the microbial compositions, marker-gene sequencing cannot provide direct information about the functional genes that are present in the genomes of community members. Bioinformatic tools have been developed to predict microbiome function with 16S rRNA gene data. Among them, PICRUSt2 has become one of the most popular functional profile prediction tools, which generates community-wide pathway abundances. However, no state-of-art inference tools are available to test the differences in pathway abundances between comparison groups. We have developed ggpicrust2, an R package, for analyzing functional profiles derived from 16S rRNA sequencing. This powerful tool enables researchers to conduct extensive differential abundance (DA) analyses and generate visually appealing visualizations that effectively highlight functional signals. With ggpicrust2, users can obtain publishable results and gain deeper insights into the functional composition of their microbial communities.
Availability and implementation
The package is open-source under the MIT and file license and is available at CRAN and https://github.com/cafferychen777/ggpicrust2. Its shiny web is available at https://a95dps-caffery-chen.shinyapps.io/ggpicrust2_shiny/.
Supplementary information
Supplementary data are available at Bioinformatics online.
Under the background of energy conservation and emission reduction advocated by the state, the sales volume of new energy vehicles increased rapidly and reached new highs in 2021. However, many domestic new energy vehicles still face the problems of serious homogenization and low market share. In view of this situation, we mine and capture the data of online consumers and potential consumers, analyze consumers' preferences in combination with the knowledge learned, take Shenzhen BYD Co., Ltd. as an example, analyze its competitive environment, and finally put forward feasible suggestions.
Digital inclusive finance provides digital inclusive services to the outside world by adopting high and new technologies such as computer, cloud computing and big data. Using it in the field of rural revitalization can provide a certain guiding role for resource reallocation, lead rural industries to achieve better development, and provide more reliable support for the process of achieving the goal of accurate poverty alleviation. This paper sums up several common digital inclusive finance models, and explores their specific implementation paths in rural revitalization, so as to provide reference for peers.
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