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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.

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

Introduction:Monitoring the therapeutic response of pancreatic ductal adenocarcinoma (PDAC) patients is crucial to determine treatment strategies. Several studies have examined the effectiveness of FOLFIRINOX as a first-line treatment in patients with locally advanced pancreatic cancer, but little attention has been paid to the immunologic alterations in peripheral blood caused by this chemotherapy regimen. Furthermore, the influence of the measurement type (e.g., flow cytometry and targeted gene expression) on the clinical discoveries is unknown. Therefore, we aimed to scrutinize the influence of using flow cytometry or targeted immune gene expression to study the immunological changes in blood samples of PDAC patients who were treated with a single-cycle FOLFIRINOX combined with lipegfilgrastim (FFX-Lipeg). Material and Methods: Whole-blood samples from 44 PDAC patients were collected at two time points: before the first FOLFIRINOX cycle and 14 days after the first cycle. EDTA blood tubes were used for multiplex flow cytometry analyses to quantify 18 immune cell populations and for complete blood count tests as the standard clinical routine. The flow cytometry data were analyzed with FlowJo software. In addition, Tempus blood tubes were used to isolate RNA and measure 1230 immune-related genes using NanoString Technology®. Data quality control, normalization, and analysis were performed using nSolver™ software and the Advanced Analysis module. Results: FFX-Lipeg treatment increased the number of neutrophils and monocytes, as shown by flow cytometry and complete blood count in concordance with elevated gene expression measured via targeted gene expression profiling analysis. Interestingly, flow cytometry analysis showed an increase in the number of B and T cells after treatment, while targeted gene expression analysis showed a decrease in B and T cell-specific gene expression. Conclusio

Metastases in the brain are the most severe and devastating complication of cancer. The incidence of brain metastasis is increasing. Therefore, the need of finding specific druggable targets for brain metastasis is demanding. The aim of this study was to compare the brain (immune) response to brain metastases of the most common tumor lineages, viz., lung adenocarcinoma and breast cancer. Targeted gene expression profiles of 11 brain metastasis of lung adenocarcinoma (BM-LUAD) were compared to 11 brain metastasis of breast cancer (BCBM) using NanoString nCounter PanCancer IO 360™ Panel. The most promising results were validated spatially using the novel GeoMx™ Digital Spatial Profiler (DSP) Technology. Additionally, Immune cell profiles and expression of drug targets were validated by multiplex immunohistochemistry. We found a more active immune response in BM-LUAD as compared to BCBM. In the BM-LUAD, 138 genes were upregulated as compared to BCBM (adj. p ≤ 0.05). Conversely, in BCBM 28 genes were upregulated (adj. p ≤ 0.05). Additionally, genes related to CD45 + cells, T cells, and cytotoxic T cells showed to be expressed higher in BM-LUAD compared to BCBM (adj. p = 0.01, adj. p = 0.023, adj. p = 0.023, respectively). The spatial quantification of the immune cells using the GeoMx DSP technique revealed the significantly higher quantification of CD14 and CD163 in tumor regions of BM-LUAD as compared to BCBM. Importantly, the immune checkpoint VISTA and IDO1 were identified as highly expressed in the BM-LUAD. Multiplex immunohistochemistry confirmed the finding and showed that VISTA is expressed mainly in BM-LUAD tumor cells, CD3 + cells, and to fewer levels in some microglial cells in BM-LUAD. This is the first report on differences in the brain immune response between metastatic tumors of different lineages. We found a far more extensive infiltration of immune cells in BM-LUAD as compared to BCBM. In addition, we found higher expression of VISTA and IDO1 in BM-LU

Background and aim: Only 10% of pancreatic ductal adenocarcinoma (PDAC) patients survive longer than five years. Factors underlining long-term survivorship in PDAC are not well understood. Therefore, we aimed to identify the key players in the tumor immune microenvironment (TIME) associated with long-term survivorship in PDAC patients. Methods: The immune-related gene expression profiles of resected PDAC tumors of patients who survived and remained recurrence-free of disease for ≥36 months (long-term survivors, n=10) were compared to patients who had survived ≤6 months (short-term survivors, n=10) due to tumor recurrence. Validation was performed by the spatial protein expression profile of immune cells using the GeoMx™ Digital Spatial Profiler. An independent cohort of samples consisting of 12 long-term survivors and 10 short-term survivors, was used for additional validation. The independent validation was performed by combining qualitative immunohistochemistry and quantitative protein expression profiling. Results: B cells were found to be significantly increased in the TIME of long-term survivors by gene expression profiling (p=0.018). The high tumor infiltration of B cells was confirmed by spatial protein profiling in the discovery and the validation cohorts (p=0.002 and p=0.01, respectively). The higher number of infiltrated B cells was found mainly in the stromal compartments of PDAC samples and was exclusively found within tumor cells in long-term survivors. Conclusion: This is the first comprehensive study that connects the immune landscape of gene expression profiles and protein spatial infiltration with the survivorship of PDAC patients. We found a higher number and a specific location of B cells in TIME of long-term survivors which emphasizes the importance of B cells and B cell-based therapy for future personalized immunotherapy in PDAC patients.

Background. Transcriptome analysis could be an additional diagnostic parameter in diagnosing kidney transplant (KTx) rejection. Here, we assessed feasibility and potential of NanoString nCounter analysis of KTx biopsies to aid the classification of rejection in clinical practice using both the Banff-Human Organ Transplant (B-HOT) panel and a customized antibody-mediated rejection (AMR)-specific NanoString nCounter Elements (Elements) panel. Additionally, we explored the potential for the classification of KTx rejection building and testing a classifier within our dataset. Methods. Ninety-six formalin-fixed paraffin-embedded KTx biopsies were retrieved from the archives of the ErasmusMC Rotterdam and the University Hospital Cologne. Biopsies with AMR, borderline or T cell-mediated rejections (BLorTCMR), and no rejection were compared using the B-HOT and Elements panels. Results. High correlation between gene expression levels was found when comparing the 2 chemistries pairwise (r = 0.76-0.88). Differential gene expression (false discovery rate; P < 0.05) was identified in biopsies diagnosed with AMR (B-HOT: 294; Elements: 76) and BLorTCMR (B-HOT: 353; Elements: 57) compared with no rejection. Using the most predictive genes from the B-HOT analysis and the Element analysis, 2 least absolute shrinkage and selection operators-based regression models to classify biopsies as AMR versus no AMR (BLorTCMR or no rejection) were developed achieving an receiver-operating-characteristic curve of 0.994 and 0.894, sensitivity of 0.821 and 0.480, and specificity of 1.00 and 0.979, respectively, during cross-validation. Conclusions. Transcriptomic analysis is feasible on KTx biopsies previously used for diagnostic purposes. The B-HOT panel has the potential to differentiate AMR from BLorTCMR or no rejection and could prove valuable in aiding kidney transplant rejection classification.

Aims: Lung tissue from COVID-19 patients shares similar histomorphological features with chronic lung allograft disease, also suggesting activation of autoimmune-related pathways in COVID-19. To more clearly understand the underlying spectrum of pathophysiology in COVID-19 pneumonia, we analysed mRNA expression of autoimmune-related genes in post-mortem lung tissue from COVID-19 patients. Methods and results: Formalin-fixed, paraffin-embedded lung tissue samples of 18 COVID-19 patients and eight influenza patients were used for targeted gene expression profiling using NanoString technology. Multiplex immunofluorescence for tryptase and chymase was applied for validation. Genes related to mast cells were significantly increased in COVID-19. This finding was strengthened by multiplex immunofluorescence also showing a significant increase of tryptase- and chymase-positive cells in COVID-19. Furthermore, receptors for advanced glycation end-products (RAGE) and pro-platelet basic protein (PPBP) were up-regulated in COVID-19 compared to influenza. Genes associated with Type I interferon signalling showed a significant correlation to detected SARS-CoV2 pathway-related genes. The comparison of lung tissue samples from both groups based on the presence of histomorphological features indicative of acute respiratory distress syndrome did not result in finding any specific gene or pathways. Conclusion: Two separate means of measuring show a significant increase of mast cells in SARS-CoV-2-infected lung tissue compared to influenza. Additionally, several genes involved in fibrosis and thrombosis, among which are RAGE and PPBP, are up-regulated in COVID-19. As mast cells are able to induce thrombosis and fibrosis, they may play an important role in the pathogenesis of COVID-19.

Galaxy is a mature, browser accessible workbench for scientific computing. It enables scientists to share, analyze and visualize their own data, with minimal technical impediments. A thriving global community continues to use, maintain and contribute to the project, with support from multiple national infrastructure providers that enable freely accessible analysis and training services. The Galaxy Training Network supports free, self-directed, virtual training with >230 integrated tutorials. Project engagement metrics have continued to grow over the last 2 years, including source code contributions, publications, software packages wrapped as tools, registered users and their daily analysis jobs, and new independent specialized servers. Key Galaxy technical developments include an improved user interface for launching large-scale analyses with many files, interactive tools for exploratory data analysis, and a complete suite of machine learning tools. Important scientific developments enabled by Galaxy include Vertebrate Genome Project (VGP) assembly workflows and global SARS-CoV-2 collaborations., Galaxy is a mature, browser accessible workbench for scientific computing. It enables scientists to share, analyze and visualize their own data, with minimal technical impediments. A thriving global community continues to use, maintain and contribute to the project, with support from multiple national infrastructure providers that enable freely accessible analysis and training services. The Galaxy Training Network supports free, self-directed, virtual training with >230 integrated tutorials. Project engagement metrics have continued to grow over the last 2 years, including source code contributions, publications, software packages wrapped as tools, registered users and their daily analysis jobs, and new independent specialized servers. Key Galaxy technical developments include an improved user interface for launching large-scale analyses with many files, interactive tools for exploratory data analysis, and a complete suite of machine learning tools. Important scientific developments enabled by Galaxy include Vertebrate Genome Project (VGP) assembly workflows and global SARS-CoV-2 collaborations.

Galaxy is a mature, browser accessible workbench for scientific computing. It enables scientists to share, analyze and visualize their own data, with minimal technical impediments. A thriving global community continues to use, maintain and contribute to the project, with support from multiple national infrastructure providers that enable freely accessible analysis and training services. The Galaxy Training Network supports free, self-directed, virtual training with >230 integrated tutorials. Project engagement metrics have continued to grow over the last 2 years, including source code contributions, publications, software packages wrapped as tools, registered users and their daily analysis jobs, and new independent specialized servers. Key Galaxy technical developments include an improved user interface for launching large-scale analyses with many files, interactive tools for exploratory data analysis, and a complete suite of machine learning tools. Important scientific developments enabled by Galaxy include Vertebrate Genome Project (VGP) assembly workflows and global SARS-CoV-2 collaborations., Galaxy is a mature, browser accessible workbench for scientific computing. It enables scientists to share, analyze and visualize their own data, with minimal technical impediments. A thriving global community continues to use, maintain and contribute to the project, with support from multiple national infrastructure providers that enable freely accessible analysis and training services. The Galaxy Training Network supports free, self-directed, virtual training with >230 integrated tutorials. Project engagement metrics have continued to grow over the last 2 years, including source code contributions, publications, software packages wrapped as tools, registered users and their daily analysis jobs, and new independent specialized servers. Key Galaxy technical developments include an improved user interface for launching large-scale analyses with many files, interactive tools for exploratory data analysis, and a complete suite of machine learning tools. Important scientific developments enabled by Galaxy include Vertebrate Genome Project (VGP) assembly workflows and global SARS-CoV-2 collaborations.

Background: Patients with locally advanced pancreatic cancer (LAPC) are treated with chemotherapy. In selected cases, stereotactic body radiotherapy (SBRT) can be added to the regimen. We hypothesized that adding an adjuvant containing a heat-killed mycobacterium (IMM-101) to SBRT may lead to beneficial immuno-modulatory effects, thereby improving survival. This study aims to investigate the safety of adding IMM-101 to SBRT and to investigate the immuno-modulatory effects of the combination treatment in the peripheral blood of LAPC patients. Methods: LAPC patients were treated with SBRT (40 Gy) and six intradermal vaccinations of one milligram IMM-101. The primary endpoint was an observed toxicity rate of grade 4 or higher. Targeted gene-expression profiling and multicolor flow cytometry were performed for longitudinal immune-monitoring of the peripheral blood. Results: Twenty patients received study treatment. No treatment-related adverse events of grade 4 or higher occurred. SBRT/IMM-101 treatment induced a transient decrease in different lymphocyte subsets and an increase in CD14+CD16−CD11b+HLA−DRlow myeloid-derived suppressor cells. Importantly, treatment significantly increased activated ICOS+, HLA-DR+ and Ki67+PD1+ T and NK cell frequencies. This was not accompanied by increased levels of most inhibitory markers, such as TIM-3 and LAG-3. Conclusions: Combination therapy with SBRT and a heat-killed mycobacterium vaccine was safe and had an immune-stimulatory effect.

Cervical cancer is one of the most common cancers in women worldwide. Patients diagnosed with early-stage cervical cancer have a good prognosis, however, 10-20% suffer from local or distant recurrent disease after primary treatment. Treatment options for recurrent cervical cancer are limited. Therefore, it is crucial to identify factors that can predict patients with an increased risk of recurrence to optimize treatment to prevent the recurrence of cervical cancer. We aimed to identify biomarkers in early-stage primary cervical cancer which recurred after surgery. Formalin-Fixed, Paraffin-Embedded surgical specimens of 34 patients with early-stage cervical cancer (FIGO 2009 stage 1B1) and 7 healthy controls were analyzed. Targeted gene expression profiling using the PanCancer IO 360 panel of NanoString Technology was performed. The findings were confirmed by performing immunohistochemistry stainings. Various genes, namely GLS, CD36, WNT5a, HRAS, DDB2, PIK3R2, and CDH2 were found to be differentially highly expressed in primary cervical cancer samples of patients who developed distant recurrence. In addition, The relative infiltration score of CD8+ T cells, CD80+CD86+ macrophages, CD163+MRC1+ macrophages, and FOXP3+IL2RA+ regulatory T cells were significantly higher in this group of samples. In contrast, no significant differences in gene expression and relative immune infiltration were found in samples of patients who developed local recurrence. The infiltration of CD8 and FOXP3 cells were validated by immunohistochemistry using all samples included in the study. We identified molecular alterations in primary cervical cancer samples from patients who developed recurrent disease. These findings can be utilized towards developing a molecular signature for the early detection of patients with a high risk to develop metastasis.

The immune response affects tumor biological behavior and progression. The specific immune characteristics of pancreatic ductal adenocarcinoma (PDAC) can determine the metastatic abilities of cancerous cells and the survival of patients. Therefore, it is important to characterize the specific immune landscape in PDAC tissue samples, and the effect of various types of therapy on that immune composition. Previously, a set of marker genes was identified to assess the immune cell composition in different types of cancer tissue samples. However, gene expression and subtypes of immune cells may vary across different types of cancers. The aim of this study was to provide a method to identify immune cells specifically in PDAC tissue samples. The method is based on defining a specific set of marker genes expressed by various immune cells in PDAC samples. A total of 90 marker genes were selected and tested for immune cell type-specific definition in PDAC; including 43 previously used, and 47 newly selected marker genes. The immune cell-type specificity was checked mathematically by calculating the “pairwise similarity” for all candidate genes using the PDAC RNA-sequenced dataset available at The Cancer Genome Atlas. A set of 55 marker genes that identify 22 different immune cell types for PDAC was created. To validate the method and the set of marker genes, an independent mRNA expression dataset of 24 samples of PDAC patients who received various types of (neo)adjuvant treatments was used. The results showed that by applying our method we were able to identify PDAC specific marker genes to characterize immune cell infiltration in tissue samples. The method we described enabled identifying different subtypes of immune cells that were affected by various types of therapy in PDAC patients. In addition, our method can be easily adapted and applied to identify the specific immune landscape in various types of tissue samples.

Lower respiratory tract infections (LRTIs) in children are common and, although often mild, a major cause of mortality and hospitalization. Recently, the respiratory microbiome has been associated with both susceptibility and severity of LRTI. In this current study, we combined respiratory microbiome, viral, and clinical data to find associations with the severity of LRTI. Nasopharyngeal aspirates of children aged one month to five years included in the STRAP study (Study to Reduce Antibiotic prescription in childhood Pneumonia), who presented at the emergency department (ED) with fever and cough or dyspnea, were sequenced with nanopore 16S-rRNA gene sequencing and subsequently analyzed with hierarchical clustering to identify respiratory microbiome profiles. Samples were also tested using a panel of 15 respiratory viruses and Mycoplasma pneumoniae, which were analyzed in two groups, according to their reported virulence. The primary outcome was hospitalization, as measure of disease severity. Nasopharyngeal samples were isolated from a total of 167 children. After quality filtering, microbiome results were available for 54 children and virology panels for 158 children. Six distinct genus-dominant microbiome profiles were identified, with Haemophilus-, Moraxella-, and Streptococcus-dominant profiles being the most prevalent. However, these profiles were not found to be significantly associated with hospitalization. At least one virus was detected in 139 (88%) children, of whom 32.4% had co-infections with multiple viruses. Viral co-infections were common for adenovirus, bocavirus, and enterovirus, and uncommon for human metapneumovirus (hMPV) and influenza A virus. The detection of enteroviruses was negatively associated with hospitalization. Virulence groups were not significantly associated with hospitalization. Our data underlines high detection rates and co-infection of viruses in children with respiratory symptoms and confirms the predominant presence of Hae

Severe acute respiratory virus-2 (SARS-CoV-2) has spread globally leading to a devastat-ing loss of life. Large registry studies have begun to shed light on the epidemiological and clinical vulnerabilities of cancer patients who succumb to or endure poor outcomes of SARS-CoV-2. Specific treatment for COVID-19 infections in cancer patients is lacking while the demand for treatment is increasing. Therefore, we explored the effect of Rintatolimod (Ampligen®) (AIM ImmunoTech, Flor-ida, USA), a Toll-like receptor 3 (TLR3) agonist, to treat uninfected human pancreatic cancer cells (HPACs). The direct effect of Rintatolimod was measured by targeted gene expression profiling and by proteomics measurements. Our results show that Rintatolimod induces an antiviral effect in HPACs by inducing RNase-L-dependent and independent pathways of the innate immune system. Treatment with Rintatolimod activated the interferon signaling pathway, leading to the overexpres-sion of several cytokines and chemokines in epithelial cells. Furthermore, Rintatolimod treatment increased the expression of angiogenesis-related genes without promoting fibrosis, which is the main cause of death in patients with COVID-19. We conclude that Rintatolimod could be considered an early additional treatment option for cancer patients who are infected with SARS-CoV-2 to pre-vent the complicated severity of the disease.