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• RNA sequencing of pretreatment, on-treatment and posttreatment gastric and gastroesophageal junction tumors treated with neoadjuvant anti-PD-L1 plus chemotherapy

  This set contains a total of 78 files cram files with RNA sequencing data from 20 patients included in the PANDA study treated with 1 cycle of monotherapy atezolizumab and 4 cycles atezolizumab plus chemotherapy (docetaxel, oxaliplatin and capecitabine). RNA was isolated from fresh frozen material and sequenced at 4 timepoints baseline, after monotherapy atezolizumab, after combination atezolizumab plus chemotherapy and at resection (due to 2 missing samples, there is a total of 78 samples).

  Dataset EGAD50000000241

• Combined Tumor and Immune Signals From Genomes or Transcriptomes Predict Outcomes of Checkpoint Inhibition in Melanoma

  Cancer immunotherapy with checkpoint blockade (CPB) leads to improved outcomes in melanoma and other tumor types, but a majority of patients do not respond. High tumor mutation burden (TMB) and high levels of tumor-infiltrating T cells have been associated with response to immunotherapy, and integrative models using DNA and RNA have improved predictions of clinical benefit. However, identification of immune and tumor-intrinsic features in models using DNA or RNA alone have not been comprehensively explored in melanoma. In this study, we sequenced DNA and RNA of tumors from 67 melanoma patients receiving CPB, and aggregated this cohort with previously published data, yielding whole exome sequencing (WES) data for 189 patients and bulk RNA sequencing data for 178 patients. Using these datasets, we derived genomic and transcriptomic factors that predict overall survival (OS) and response to immunotherapy. Using whole exome DNA data alone, we calculated T cell burden (TCB) and B cell burden (BCB) based on rearranged TCR/Ig DNA sequences, and found that melanoma patients with high TMB and either high TCB or high BCB survived longer and had higher response rates, as compared to patients with low TMB and either low TCB or low BCB. Next, using bulk RNA-Seq data, differential expression analysis identified 83 genes which are associated with high or low OS. By combining pairs of immune-expressed genes with tumor-expressed genes, we identified three gene pairs which are associated with response and survival (Bonferroni P<0.05). All three gene pair models were validated in an independent cohort (n=180) (Bonferroni P<0.05). The best performing gene pair model included the lymphocyte-expressed MAP4K1 (Gene ID: 11184) and the transcription factor TBX3 (Gene ID: 6926) which is overexpressed in poorly differentiated melanomas. We concluded that RNA-based (MAP4K1 and TBX3) or DNA-based (TCB and TMB) models combining with immune and tumor measures improve predictions of outcome after checkpoint blockade in melanoma.

  Study phs002683

• Exome sequencing in HIV+ Viremic Non-Progressors (VNPs) and HIV+ Progressors

  Viremic Non-Progressors (VNPs) maintain normal CD4+ T-cell counts despite uncontrolled HIV-1 replication, but mechanisms leading to CD4+ T-cell preservation are incompletely characterized. We aim to generate a comprehensive understanding of this infrequent phenotype by comparing rates of cellular infection, immunophenotype, genomics, single-cell transcriptomics, metabolomics, and levels of plasma biomarkers in 16 VNPs and 29 HIV+ Progressors. During chronic infection VNPs show lower frequency of HIV-1-infected cells in periphery, which is associated with reduced CCR5 expression and higher prevalence of CCR5Δ32 heterozygosity. The CD8+ T-cell compartment displays a less cytotoxic and less activated phenotype in VNPs. Moreover, despite similar viremia, we found lower bystander CD4+ T-cell death in the VNPs, together with weaker IFN responses, reduced plasma levels of zonulin (a biomarker of intestinal permeability), altered tryptophan catabolism, and preserved LPS responsiveness in vitro. Overall, a complex multifactorial mechanism, suggesting gut-associated lymphoid tissue preservation, underlies resistance to HIV pathogenesis in VNPs.

  Study EGAS50000000079

• Data Quality Control

  Data Quality Control High-throughput sequencing techniques have become the leading method to study, decode and discover the genomic origins of biological phenomenons. EGA provides a secure archival of such identifiable genomics data with the purpose of data-upcycling, i.e. to re-use these data for research. High-quality data standards are essential to ensure the quality and credibility of the research. Moreover, a quality check report can assure a researcher beforehand about the data that they will request access, therefore saving time and effort. The EGA has developed a File Quality Control Report (QC Report) to provide generic quality control reports for Fastq, SAM/BAM/CRAM, and VCF files deposited at EGA. This QC Report will allow users to get information regarding the files submitted within a specific dataset. The data requesters will obtain information such as the quality of reads, mapped reads, number of variants, and other features before starting the requesting process, which will save the efforts and time.Accessing file quality control reportsIn each dataset page, the user can explore the files that it contains by clicking the "files" tab. The Quality Control report of a file has two sections. The first one, contains general information about the file, such as the inferred assembly, total reads, the dataset or study where it comes from, etc. The second section contains plots that summarise interesting information about the file, for example, the base coverage distribution, base quality or mapped reads. The description of each plot is accessible by clicking the "i" button at the top-right corner of each plot box. Technical Description For analysing the fastq, SAM/BAM/CRAM and VCF files, the EGA applies a set of tools widely used in the bioinformatics community. FASTQ: FastQC, recognised as the gold standard tool by the community.Per base sequence quality, per sequence quality scores, per base sequence content, per sequence GC content, sequence duplication levels, etc.SAM/BAM/CRAM: samtools, also the gold standard, generates results plots useful to get an overall idea of the quality of the file.base coverage distribution, base quality, % of mapped reads, % of both mates mapped, singletons, duplicates, etc.VCF: vcftools and bcftools, combined with a custom script to infer the genome assembly.site frequency distribution, Ts/Tv, base changes, indel distribution, etc.

  Documentation access/request-data/quality-control-reports

• Bleomycin Induced Pneumonitis WGS dataset

  This is whole genome sequencing data from a cohort of 18 patients with germ cell tumours or Hodgkin Lymphoma, who developed clinically significant bleomycin-induced pneumonitis despite low clinical risk. DNA was extracted from whole blood, and 150-base paired-end reads were generated on an Illumina NovaSeq 6000 instrument to a minimum 30x depth. Sequence reads were aligned to the GRCh38 reference with BWA MEM, and germline variants were called following GATK best practice procedures. The dataset comprises per-sample read alignment files in BAM format, and a joint-called germline variant file in VCF format.

  Dataset EGAD50000002221

• The impact of BNT162b2 mRNA vaccine against SARS-CoV-2 on adaptive and innate immune responses

  The mRNA-based BNT162b2 protects against severe disease and mortality caused by SARS-CoV-2 through induction of specific antibody and T-cell responses. Much less is known about its broad effects on immune responses against other pathogens. In the present study, we investigated the specific adaptive immune responses induced by BNT162b2 vaccination against various SARS-CoV-2 variants, as well as its effects on the responsiveness of human immune cells upon stimulation with heterologous viral, bacterial, and fungal pathogens. BNT162b2 vaccination induced effective humoral and cellular immunity against SARS-CoV-2 that started to wane after six months. We also observed long-term transcriptional changes in immune cells after vaccination, as assessed by RNA sequencing. Additionally, vaccination with BNT162b2 modulated innate immune responses as measured by the production of inflammatory cytokines when stimulated with various microbial stimuli other than SARS-CoV-2, including higher IL-1/IL-6 release and decreased production of IFN-α. Altogether, these data expand our knowledge regarding the overall immunological effects of this new class of vaccines and underline the need of additional studies to elucidate their effects on both innate and adaptive immune responses.

  Study EGAS00001006818

• GenomeDenmark Phase 2 - HLA validation sequencing data

  Validation of HLA variation of 8 individuals from the GenomeDenmark Phase 2 study. Validation is performed Sanger sequencing of selected amplicons (5-10 amplicons per sample).

  Dataset EGAD00001003454

• RNA-seq cohort of non-tumorous breast tissue from BRCA1/2 carriers

  Non-tumorous breast tissues from BRCA1 or BRCA2 carriers were subject to RNA sequencing. The total number of samples is 130.

  Dataset EGAD00001006746

• An Unusual Genomic Variant of Pancreatic Ductal Adenocarcinoma with an Indolent Clinical Course

  We describe a patient with biopsy-proven locally advanced pancreatic ductal adenocarcinoma (PDA) who underwent a modified course of gemcitabine and stereotactic body radiation therapy. Whole exome sequencing of this patient's tumor revealed a simple genome landscape with no evidence of mutations, copy number changes, or structural alterations in genes most commonly associated with PDA, i.e. KRAS, CDKN2A, TP53 or SMAD4. An analysis of germline DNA revealed no pathogenic variants of significance. Whole exome and whole genome sequencing identified a somatic mutation of RNF213 and an inversion/deletion of CTNNA2 as the genetic basis of this PDA. Although PDA is classically characterized by a predictable set of mutations, these data suggest that alternate genetic paths to PDA may exist, which can be associated with a more indolent clinical course.

  Study EGAS00001002192

• Single-cell decoding of drug induced transcriptomic reprogramming in triple negative breast cancers

  Background The encoding of cell intrinsic drug resistance states in breast cancer reflects the contributions of genomic and non-genomic variations and requires accurate estimation of clonal fitness from co-measurement of transcriptomic and genomic data. Somatic copy number (CN) variation is the dominant mutational mechanism leading to transcriptional variation and notably contributes to platinum chemotherapy resistance cell states. Here, we deploy time series measurements of triple negative breast cancer (TNBC) single-cell transcriptomes, along with co-measured single-cell CN fitness, identifying genomic and transcriptomic mechanisms in drug associated transcriptional cell states. Results We present scRNA-seq data (53,641 filtered cells) from serial passaging TNBC patient-derived xenograft (PDX) experiments spanning 2.5 years, matched with genomic single-cell CN data from the same samples. Our findings reveal distinct clonal responses within TNBC tumors exposed to platinum. Clones with high drug fitness undergo clonal sweeps and show subtle transcriptional reversion, while those with weak fitness exhibit dynamic transcription upon drug withdrawal. Pathway analysis highlights convergence on epithelial-mesenchymal transition and cytokine signaling, associated with resistance. Furthermore, pseudotime analysis demonstrates hysteresis in transcriptional reversion, indicating generation of new intermediate transcriptional states upon platinum exposure. Conclusions Within a polyclonal tumor, clones with strong genotype-associated fitness under platinum remained fixed, minimizing transcriptional reversion upon drug withdrawal. Conversely, clones with weaker fitness display non-genomic transcriptional plasticity. This suggests CN-associated and CN-independent transcriptional states could both contribute to platinum resistance. The dominance of genomic or non-genomic mechanisms within polyclonal tumors has implications for drug sensitivity, restoration and re-treatment strategies.

  Study EGAS00001007242