IntroductionDysbiosis of the lower airway flora is associated with lung cancer, of which the relationship between Streptococcus, especially pathogenic Streptococcus pneumoniae (S. pneumoniae), and the progression of lung cancer are unclear.MethodsBronchoalveolar lavage fluid (BALF) samples were prospectively collected from patients with pulmonary nodules during diagnostic bronchoscopy, and finally included 70 patients diagnosed with primary lung cancer and 20 patients with benign pulmonary nodules as the disease control group. The differential flora was screened by 16S ribosomal RNA (rRNA) gene amplicon sequencing. An in vitro infection model of lung adenocarcinoma (LUAD) cells exposed to S.pneumoniae was established to observe its effects on cell migration and invasion ability. Exploring the molecular mechanisms downstream of DDIT4 through its loss- and gain-of-function experiments.Results16S rRNA sequencing analysis showed that the abundance of Streptococcus in the lower airway flora of lung cancer patients was significantly increased. After exposure to S. pneumoniae, A549 and H1299 cells significantly enhanced their cell migration and invasion ability. The results of DDIT4 loss- and gain-of-function experiments in A549 cells suggest that up-regulation of DDIT4 activates the mTORC2/Akt signaling pathway, thereby enhancing the migration and invasion of A549 cells while not affecting mTORC1. Immunofluorescence (IF) and fluorescence in situ hybridization (FISH) showed that S. pneumoniae was enriched in LUAD tissues, and DDIT4 expression was significantly higher in cancer tissues than in non-cancerous tissues. The increased expression of DDIT4 was also related to the poor prognosis of patients with LUAD.DiscussionThe data provided by this study show that S. pneumoniae enriched in the lower airway of patients with lung cancer can up-regulate DDIT4 expression and subsequently activate the mTORC2/AKT signal pathway, thereby increasing the migration and invasion abilities of A549 cells. Our study provides a potential new mechanism for targeted therapy of LUAD.
IntroductionThe prognosis of bladder cancer (BLCA) and response to immune checkpoint inhibitors (ICIs) are determined by multiple factors. Existed biomarkers for predicting the effect of immunotherapy cannot accurately predict the response of BLCA patients to ICIs.MethodsTo further accurately stratify patients’ response to ICIs and identify potential novel predictive biomarkers, we used the known T cell exhaustion (TEX)-related specific pathways, including tumor necrosis factor (TNF), interleukin (IL)-2, interferon (IFN)-g, and T- cell cytotoxicpathways, combined with weighted correlation network analysis (WGCNA) to analyze the characteristics of TEX in BLCA in detail, constructed a TEX model.ResultsThis model including 28 genes can robustly predict the survival of BLCA and immunotherapeutic efficacy. This model could divide BLCA into two groups, TEXhigh and TEXlow, with significantly different prognoses, clinical features, and reactivity to ICIs. The critical characteristic genes, such as potential biomarkers Charged Multivesicular Body Protein 4C (CHMP4C), SH2 Domain Containing 2A (SH2D2A), Prickle Planar Cell Polarity Protein 3 (PRICKLE3) and Zinc Finger Protein 165 (ZNF165) were verified in BLCA clinical samples by real-time quantitative chain reaction (qPCR) and immunohistochemistry (IHC).DiscussionOur findings show that the TEX model can serve as biological markers for predicting the response to ICIs, and the involving molecules in the TEX model might provide new potential targets for immunotherapy in BLCA.
Mutations of DNA organisms are introduced by replication errors. However, SARS-CoV-2, as an RNA virus, is additionally subjected to rampant RNA editing by hosts. Both resources contributed to SARS-CoV-2 mutation and evolution, but the relative prevalence of the two origins is unknown. We performed comparative genomic analyses at intra-species (world-wide SARS-CoV-2 strains) and inter-species (SARS-CoV-2 and RaTG13 divergence) levels. We made prior predictions of the proportion of each mutation type (nucleotide substitution) under different scenarios and compared the observed versus the expected. C-to-T alteration, representing C-to-U editing, is far more abundant that all other mutation types. Derived allele frequency (DAF) as well as novel mutation rate of C-to-T are the highest in SARS-CoV-2 population, and C-T substitution dominates the divergence sites between SARS-CoV-2 and RaTG13. This is compelling evidence suggesting that C-to-U RNA editing is the major source of SARS-CoV-2 mutation. While replication errors serve as a baseline of novel mutation rate, the C-to-U editing has elevated the mutation rate for orders of magnitudes and accelerates the evolution of the virus.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.