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• Human Dorsal Root Ganglion RNA Landscape Profiling for Neuropathic and Chronic Pain

  Bulk and spatial RNA sequencing were performed on human Dorsal Root Ganglia (DRGs), peripheral sensory nerves and nodose ganglia and relative gene abundances were calculated. Various analyses were performed: Human DRG gene expression profiles were contrasted with a panel of gene expression profiles of relevant tissues in human and mouse (integrating, among other sources, datasets from ENCODE and GTex) in order to identify. DRG-enriched gene expression, co-expression modules of DRG-expressed genes, and key transcriptional regulators in humans. Contrasting the human and mouse DRG transcriptomes to identify DRG-enriched gene expression patterns that were conserved between human and mouse, identifying putative cell types of expression of these genes, and potential known drugs that might target the corresponding gene products. Characterization of non-coding RNA profile of human and mouse DRGs. Characterization of DRG-enriched alternative splicing and alternative transcription start site usage based transcript variants in humans and mouse, and the overlap between these two species. Contrasting of human DRG and GTex human tibial nerve samples to identify putative axonally transported mRNAs in sensory neurons. Human DRG and peripheral nerves transcriptomes from donors suffering from neuropathic and/or chronic pain were contrasted with controls to identify. Differentially expressed genes, pathways and regulators path play a potential role in neuronal plasticity, electrophysiological activity, immune signaling and response. Predictive models (Random Forests) were built to jointly predict the sex and pain state of samples based on information contained solely in autosomal gene expression profile. Gene co-expression modules were identified and gene set enrichment analysis performed.to identify sample - pathway associations, and to broadly characterize plasticity in human DRG cell types. Spatial transcriptomics was performed on human DRGs and nodose ganglia to obtain near single-neuron resolution. We identified distinct clusters of human DRG sensory neurons. We characterized the expression of different gene families (e.g., GPCRs, sodium channels, potassium channels, etc.). We investigated differences between male and female neurons.

  Study phs001158

• NEOPREDICT-Lung: Neoadjuvant Immunotherapy for Resectable NSCLC

  Links via: DOI: https://doi.org/10.1038/s41591-024-02965-0 PubMed: https://pubmed.ncbi.nlm.nih.gov/38689060/ Journal: https://www.nature.com/articles/s41591-024-02965-0 Abstract Antibodies targeting the immune checkpoint molecules PD-1, PD-L1 and CTLA-4 administered alone or in combination with chemotherapy are standard of care in most patients with metastatic non-small cell lung cancers. When given prior to curative surgery, tumor responses and improved event-free survival are achieved. New antibody combinations may be more efficacious and tolerable. In an ongoing, open-label phase II study, 60 biomarker-unselected, treatment-naïve patients with resectable non-small cell lung cancer were randomized to receive two preoperative doses of nivolumab (anti-PD-1) with or without relatlimab (anti-LAG-3) antibody therapy. The primary study endpoint was feasibility of surgery within 43 days, which was met by all patients. Curative resection was achieved in 95% of patients. Secondary endpoints included pathological and radiographic response rates, pathologically complete resection rates, disease-free and overall survival rates, and safety. Major pathological (≤10% viable tumor cells) and objective radiographic responses were achieved in 27% and 10% (nivolumab), and 30% and 27% (nivolumab and relatlimab) of patients, respectively. In 100% (nivolumab) and 90% (nivolumab and relatlimab) of patients tumors and lymph nodes were pathologically completely resected. With 12 months median duration of follow-up, disease-free survival and overall survival rates at 12 months were 89% and 93% (nivolumab), and 93% and 100% (nivolumab and relatlimab). Both treatments were safe with grade ≥ 3 treatment-emergent adverse events reported in 10% and 13% of patients per study arm. Exploratory analyses provided insights into biological processes triggered by preoperative immunotherapy. This study establishes the feasibility and safety of dual targeting of PD-1 and LAG-3 prior to lung cancer surgery.

  Study EGAS00001007753

• Dataset for Sarcoma RNA sequencing linked from study EGAS00001004813

  Sequencing data of 410 sarcoma tumor runs, which were uploaded to EGAS00001004813. The sequencing was always paired.

  Dataset EGAD00001010276

• Solve-RD_RND_cohort-1_DF1+2_V1

  Solve-RD data submitted to the ERN-RND cohort for re-analysis (Data freeze 1+2) v1

  Dataset EGAD00001009769

• Ancient Yakuts genomes and metagenomes

  Read data and bam alignments for 124 ancient yakuts

  Dataset EGAD50000001903

• Solve-RD_ITHACA_cohort-1_DF1+2_V1

  Solve-RD data submitted to the ERN-ITHACA cohort for re-analysis (Data freeze 1+2) v1

  Dataset EGAD00001009770

• Irish Covid19 RNASeq Alignment Data files

  The Dataset contains 446 Covid19 patient's RNASeq Alignment files in BAM format for both genomic and transcriptomic alignment.

  Dataset EGAD00001010099

• Covid19 WGS variants analysis

  483 samples were collected for WGS and aligned with GRCh38 human genome. The variants were called using GATK (Sentieon v. 201808.03) in GVCF and VCF format.

  Dataset EGAD00001010138

• Irish Covid19 WGS Raw Reads

  Dataset contains 483 Irish origin Individuals with Covid19. paired end sequencing has been performed For WGS and later processed by using sention v 201808.03.

  Dataset EGAD00001010186

• WGS samples for study EGAS00001001623

  Dataset EGAD00001001856

• Solve-RD multi-omics data chud-faivre cohort

  The dataset includes short-read whole-genome sequencing (SR-WGS) data, SR-RNAseq data, OGM (Bionano) data, LR-WGS data, Epigenetics (RBSS) data and deep-WES data generated within the project Solve-RD from biosamples submitted by the group chud-faivre. The cohorts consists of 111 individuals recruited as part of Solve-RD cohorts 2-4 and aligns with ERN-ITHACA related disease entities (for a description of the Solve-RD cohorts see www.solve-rd.eu/fact-sheet-solve-rd-cohorts).

  Dataset EGAD00001015811