The Galaxy platform for accessible, reproducible, and collaborative data analyses:2024 update

Galaxy (https://galaxyproject.org) is deployed globally, predominantly through free-to-use services, supporting user-driven research that broadens in scope each year. Users are attracted to public Galaxy services by platform stability, tool and reference dataset diversity, training, support and integration, which enables complex, reproducible, shareable data analysis. Applying the principles of user experience design (UXD), has driven improvements in accessibility, tool discoverability through Galaxy Labs/subdomains, and a redesigned Galaxy ToolShed. Galaxy tool capabilities are progressing in two strategic directions: integrating general purpose graphical processing units (GPGPU) access for cutting-edge methods, and licensed tool support. Engagement with global research consortia is being increased by developing more workflows in Galaxy and by resourcing the public Galaxy services to run them. The Galaxy Training Network (GTN) portfolio has grown in both size, and accessibility, through learning paths and direct integration with Galaxy tools that feature in training courses. Code development continues in line with the Galaxy Project roadmap, with improvements to job scheduling and the user interface. Environmental impact assessment is also helping engage users and developers, reminding them of their role in sustainability, by displaying estimated CO2 emissions generated by each Galaxy job.</p

The Galaxy platform for accessible, reproducible, and collaborative data analyses:2024 update

Galaxy (https://galaxyproject.org) is deployed globally, predominantly through free-to-use services, supporting user-driven research that broadens in scope each year. Users are attracted to public Galaxy services by platform stability, tool and reference dataset diversity, training, support and integration, which enables complex, reproducible, shareable data analysis. Applying the principles of user experience design (UXD), has driven improvements in accessibility, tool discoverability through Galaxy Labs/subdomains, and a redesigned Galaxy ToolShed. Galaxy tool capabilities are progressing in two strategic directions: integrating general purpose graphical processing units (GPGPU) access for cutting-edge methods, and licensed tool support. Engagement with global research consortia is being increased by developing more workflows in Galaxy and by resourcing the public Galaxy services to run them. The Galaxy Training Network (GTN) portfolio has grown in both size, and accessibility, through learning paths and direct integration with Galaxy tools that feature in training courses. Code development continues in line with the Galaxy Project roadmap, with improvements to job scheduling and the user interface. Environmental impact assessment is also helping engage users and developers, reminding them of their role in sustainability, by displaying estimated CO2 emissions generated by each Galaxy job.</p

Unlocking molecular mechanisms and identifying druggable targets in matched-paired brain metastasis of breast and lung cancers

Introduction: The incidence of brain metastases in cancer patients is increasing, with lung and breast cancer being the most common sources. Despite advancements in targeted therapies, the prognosis remains poor, highlighting the importance to investigate the underlying mechanisms in brain metastases. The aim of this study was to investigate the differences in the molecular mechanisms involved in brain metastasis of breast and lung cancers. In addition, we aimed to identify cancer lineage-specific druggable targets in the brain metastasis. Methods: To that aim, a cohort of 44 FFPE tissue samples, including 22 breast cancer and 22 lung adenocarcinoma (LUAD) and their matched-paired brain metastases were collected. Targeted gene expression profiles of primary tumors were compared to their matched-paired brain metastases samples using nCounter PanCancer IO 360™ Panel of NanoString technologies. Pathway analysis was performed using gene set analysis (GSA) and gene set enrichment analysis (GSEA). The validation was performed by using Immunohistochemistry (IHC) to confirm the expression of immune checkpoint inhibitors. Results:Our results revealed the significant upregulation of cancer-related genes in primary tumors compared to their matched-paired brain metastases (adj. p ≤ 0.05). We found that upregulated differentially expressed genes in breast cancer brain metastasis (BM-BC) and brain metastasis from lung adenocarcinoma (BM-LUAD) were associated with the metabolic stress pathway, particularly related to the glycolysis. Additionally, we found that the upregulated genes in BM-BC and BM-LUAD played roles in immune response regulation, tumor growth, and proliferation. Importantly, we identified high expression of the immune checkpoint VTCN1 in BM-BC, and VISTA, IDO1, NT5E, and HDAC3 in BM-LUAD. Validation using immunohistochemistry further supported these findings. Conclusion: In conclusion, the findings highlight the significance of using matched-paired samples to identify cancer lineage-specific therapies that may improve brain metastasis patients outcomes.</p

How is sport participation related to mortality, diabetes and prediabetes for different body mass index levels?

This study examined the association of sport participation with health outcomes and whether this relation differs between body mass index (BMI)-level subpopulations. Research outcomes for sport participation were compared with other types of leisure-time physical activity (PA). We used the Cox proportional hazards regression models to assess the associations of sport participation, and four other PA types (cycling, gardening, doing odd jobs, and walking), with the risk of prediabetes, type 2 diabetes mellitus (T2DM), and all-cause mortality in 97,212 individuals (58.4% women; mean age: 46.5 years) in the Dutch LifeLines cohort. Outcomes were stratified by three BMI levels: healthy weight (BMI: 18.5-24.9 kg/m(2)), overweight (BMI: 25.0-29.9 kg/m(2)), and obesity (BMI: 30.0 kg/m(2) or above). Sport participation was associated with lower health risks, but only significantly so for prediabetes (HR = 0.86, 95% CI: 0.81-0.92). For healthy weight persons, sport participation was associated with the largest risk reductions, with significantly lower risks of prediabetes (HR = 0.78, 95% CI: 0.68-0.90) and all-cause mortality (HR = 0.79, 95% CI 0.65-0.96). Other PA types were not associated with significantly lower health risks, with the exception of cycling, for which significantly lower health risks for persons with overweight were found. Our findings show that sport participation is associated with lower health risks, especially prediabetes, but the effect varies between BMI levels, with the strongest link for persons with a healthy weight. Sport participation, together with cycling, is likely to be more effective in reducing health risks than other types of PA