Background RNA adenosine modifications, which are primarily mediated by “writer” enzymes (RMWs), play a key role in epigenetic regulation in various biological processes, including tumorigenesis. However, the expression and prognostic role of these genes in osteosarcoma (OS) remain unclear. Methods Univariate and multivariate Cox analyses were used to construct the RMW signature for OS using Target datasets. RMW expression in OS tissue was detected by qPCR analysis. Xcell and GSVA were used to determine the relationship between RMWs and immune infiltration. The DGIdb and CMap databases were used for drug prediction. In vivo and in vitro experiments showed that strophanthidin elicited antitumor activity against OS. Results A 3-RMW (CSTF2, ADAR and WTAP) prognostic signature in OS was constructed using the Target dataset and verified using GEO datasets and 63 independent OS tissues via qPCR analysis. High-risk OS patients had poor overall survival, and the prognostic signature was an independent prognostic factor for OS. Functional studies showed that tumour-, metabolism-, cell cycle- and immune-related pathways were related to high risk. Next, we found that RMW-derived high-risk patients exhibited increased infiltration of M2 macrophages and cDCs. Furthermore, we predicted the potential drugs for OS using the DGIdb and CMap databases. In vivo and in vitro experiments showed that strophanthidin elicited antitumor activity against OS by repressing cell growth and inducing cell cycle arrest at the G1 phase. Conclusion The 3-RWM-based prognostic signature established in this study is a novel gene signature associated with immune infiltration, and strophanthidin was identified as a candidate therapy for OS by repressing OS cell growth and the cell cycle.

ObjectivesWe aimed to summarise the prevalence of atypical pathogens in patients with severe pneumonia to understand the prevalence of severe pneumonia caused by atypical pathogens, improve clinical decision-making and guide antibiotic use.DesignSystematic review and meta-analysis.Data sourcesPubMed, Embase, Web of Science and Cochrane Library were searched through November 2022.Eligibility criteriaEnglish language studies enrolled consecutive cases of patients diagnosed with severe pneumonia, with complete aetiological analysis.Data extraction and synthesisWe conducted literature retrieval on PubMed, Embase, Web of Science and The Cochrane Library to estimate the prevalence ofChlamydia,MycoplasmaandLegionellain patients with severe pneumonia. After double arcsine transformation of the data, a random-effects model was used for meta-analyses to calculate the pooled prevalence of each pathogen. Meta-regression analysis was also used to explore whether the region, different diagnostic method, study population, pneumonia categories or sample size were potential sources of heterogeneity.ResultsWe included 75 eligible studies with 18 379 cases of severe pneumonia. The overall prevalence of atypical pneumonia is 8.1% (95% CI 6.3% to 10.1%) In patients with severe pneumonia, the pooled estimated prevalence ofChlamydia,MycoplasmaandLegionellawas 1.8% (95% CI 1.0% to 2.9%), 2.8% (95% CI 1.7% to 4.3%) and 4.0% (95% CI 2.8% to 5.3%), respectively. We noted significant heterogeneity in all pooled assessments. Meta-regression showed that the pneumonia category potentially influenced the prevalence rate ofChlamydia. The mean age and the diagnostic method of pathogens were likely moderators for the prevalence ofMycoplasmaandLegionella, and contribute to the heterogeneity of their prevalence.ConclusionsIn severe pneumonia, atypical pathogens are notable causes, especiallyLegionella. The diagnostic method, regional difference, sample size and other factors contribute to the heterogeneity of prevalence. The estimated prevalence and relative heterogeneity factors can help with microbiological screening, clinical treatment and future research planning.PROSPERO registration numberCRD42022373950.

Background RNA adenosine modifications, mediated mainly by the “writer” enzymes (RMWs), play a key role in epigenetic regulation in various biological processes, including tumorigenesis. However, the expression and prognosis role of these genes in osteosarcoma (OS) remains unclear. Methods The univariate and multivariate cox analyses were used to construct the RMWs signature in OS using Target datasets. RMWs expression in OS tissue detected by qPCR analysis. Xcell and GSVA were used for the relationship between RMWs and immune infiltration. DGIdb and CMap databases were used for drug prediction. The vivo and vitro experiments showed that strophanthidin elicited the anti-tumor activity against OS. Results This study constructed the 3-RMWs (CSTF2, ADAR and WTAP) prognosis signature in OS using the Target dataset, and then verified the risk signature using GEO datasets and independent 63 OS tissues using qPCR analysis. The OS patients with high risk observed poor overall survival, and the prognosis signature was the independent prognostic factor in OS. Functional studies showed that tumor-, metabolism-, cell cycle- and immune-related pathways were related high risk. Next, we found that the RMWs- derived high-risk patients showed increased infiltration of Macrophages M2 and cDCs. Furthermore, we predicted the potential drugs for OS using DGIdb and CMap database. The vivo and vitro experiments showed that strophanthidin elicited the anti-tumor activity against OS via repressing cell growth and inducing cell cycle arrest at the G1 phase. Conclusion The 3-RMWs-based prognostic signature established in this study is a novel gene signature associated with immune infiltration, and strophanthidin was identified as a candidate therapy for OS via repressing the growth and cell cycle of OS cells.