12498 results for ""non-traditional+communal+storytelling+approach"+novel+segment+noted+in+critical+commentary"

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• Integrated single cell analysis in transformed follicular lymphoma

  Histological transformation of follicular lymphoma to aggressive form occurs 2-3% per year with poor outcome. Divergent evolution and an altered tumour-microenvironment (TME) have been implicated during transformation. However, phenotypic consequences of this evolution and its implication in TME remain unknown. To address this, we performed single cell whole genome and whole transcriptome sequencing of paired pre/post transformation patient samples. We further performed scWTS of additional samples from patients without transformation. Our analysis revealed evolutionary dynamics of transformation at unprecedented resolution. Integration of scWGS and scWTS identified pathways upregulated during evolution. scWTS analysis revealed a shifting TME landscape, with an exhausted signature emerging during transformation. Using multi-color immunofluorescence we transferred these findings to a TME-based transformation biomarker, subsequently validated in independent pretreatment cohorts. Taken together, our results provide a comprehensive view of the combined genomic and phenotypic evolution of malignant cells during transformation, and shifting cross-talk between malignant cells and TME.

  Study EGAS00001007023

• Genomic Data of Pediatric MDS

  The dataset consists of - 126 whole exome sequencings (SAMD9/9Lmut: 64; GATA2mut 24, MDS wildtype 38/471) performed using SureSelect Human All Exon V6 enrichment (Agilent, cat# 5190-8863). The generated libraries were sequenced on the Illumina Hiseq 2500 with 150bp paired-end reads. FASTQ files were processed using SeqNext platform (JSI medical system, Germany), with gene-based alignment to a virtual panel of 300 genes (including 28 MDS-associated genes, SAMD9, and SAMD9L), consisting of genes relevant to bone marrow failure, MDS predisposition, and hematological cancers as per the Pan-Cancer studies with cohorts of >10,000 cancers. The respective BAM files are provided. - Custom panel targeting SAMD9, SAMD9L, and 22 single nucleotide polymorphisms (SNP) on chromosome 7q (allele frequency >35% in all ethnic sub-populations in gnomAD) (Ampliseq #IAD104171) were performed in 666/669 cases. And Custom panel targeting 28 MDS-associated genes (GATA2, RUNX1, HOXA9, CEBPA, GATA1, KRAS, NRAS, CBL, PTPN11, ASXL1, EZH2, SETBP1, FLT3, KIT, JAK2, JAK3, CSF3R, MPL, SH2, BCOR, BCORL1; RAD21, STAG2, CTCF, TP53, PTEN, CALR, VPS45) was performed in 544 cases (Ampliseq #IAD51150). Both custom panel libraries were prepared using NEBNext Ultra II DNA library prep kit (New England BioLabs, cat#E7645S/L) per manufacturer’s instruction and samples were sequenced on an Illumina Miseq 2000 with 2 x 150 bp reads. The respective BAM files are provided - 4 SAMD9/9L patients were subjected to MissionBio custom single-cell panel (CO-112) targeting 250 heterozygous gnomAD population polymorphisms on 7q arm and 69 amplicons in SAMD9/9L and other cancer genes. All libraries were sequenced on an Illumina NovaSeq6000 with 150 base-paired ending multiplexed runs. Fastq files were processed using the Tapestri Pipeline V2 and python-based Mosaic package (multi-omics analysis, data visualization). The derived BAM and loom files are provided.

  Dataset EGAD00001007856

• How to encrypt files with Crypt4gh

  File preparation Due to the processes used at the EGA for file archival the use of non-alphanumeric characters in a filename will cause issues in archival. By convention whitespaces in filenames are to be avoided and should be replaced with the underscore character (_). Before encrypting your files please make sure that any files that will be uploaded to EGA do not use special characters such as # ? ( ) [ ] / \ = + < > : ; " ' , * ^ | & Crypt4gh EGACryptor Files encrypted with Crypt4gh must be uploaded via INBOX Before uploading If you are not a registered EGA user, you will first need an EGA user account. Please note that it may take a few days for your account to be activated, as it needs to be vouched for by the EGA Helpdesk. Once your account is validated you will be able to request a submitter role. Meanwhile, you can create and add your public key to your EGA account profile. This option is not available for old submission accounts (e.g. ega-box-NNN). As soon as you have been granted a submitter role, you will be able to connect with your username and password to the EGA inbox using the SFTP protocol. If you have also registered a public key in your profile, you can also connect using this key. Encrypting your files Please note that you can also encrypt your files by uploading them directly to the "to-encrypt" folder in your upload area If your connection is unstable, please encrypt them using Crypt4gh The EGA encryption of this inbox is based on Crypt4GH. You can install a python implementation of it, with pip install crypt4gh or directly from the Github repository pip install git+https://github.com/EGA-archive/crypt4gh.git Save now the following Crypt4GH public key, into a file, say ingestion.pubkey. __EGA_INGESTION_PUBKEY__ Encrypt a given file with the following command: crypt4gh encrypt --recipient_pk ingestion.pubkey < file_to_encrypt > encrypted_file.c4gh The command reads the file from stdin (with < ) and output the encrypted version to stdout (with > ). Replace file_to_encrypt and encrypted_file.c4gh with the appropriate filenames but make sure to not use the same filename for both reading and writing because your SHELL would then truncate both files before you even read or write.

  Documentation submission/data/file-preparation/crypt4gh

• Data access committee (DAC) in the Graduate School of Medical Science and Engineering (GSMSE) at Korea Advanced Institute of Science and Technology (KAIST)

  Dac EGAC00001001643

• DAC of The polarity and specificity of antiviral T lymphocyte responses determine susceptibility to SARS-CoV-2 infection in cancer patients and healthy individuals

  Dac EGAC00001002517

• EGAD00010000722

  Pilot experiment on functional genomics in osteoarthritis (coreex)

  Dataset EGAD00010000722

• Transcriptional regulatory networks of tumor-associated macrophages that drive malignancy in mesenchymal glioblastoma

  Dataset EGAD00001003324

• LOPEZ_2019.vcf.gz

  Genotype data for new samples in Lopez et al 2021

  Dataset EGAD00010002100

• ITER-FIISC Data Access Committee

  DAC for whole-genome variant calling data of individuals from the study of allergic diseases in the Canary Islands.

  Dac EGAC50000000180

• resistance to FGFR inhibitor in FGR2 cancers from DNA sequencing

  WES from FGR2 resistant patient tumors

  Study EGAS50000000305

• Mutation and Microsatellite Burden Predict Response to PD-1 Inhibition in Children with Germline DNA Replication Repair Deficiency: An Observational Registry Study

  Study EGAS00001005579

• Circulating tumor DNA, pathological and immunologic responses to neoadjuvant nivolumab or nivolumab plus relatlimab and chemoradiotherapy in resectable esophageal/gastroesophageal junction cancer

  Study EGAS00001007299

• Single-cell multi-omics defines the cell-type-specific impact of splicing aberrations in human hematopoietic clonal outgrowths

  Study EGAS00001007402

• PREGO reference panel - 3234 individuals from Western France. Individuals' birthplaces are available in epsg.io/2154 (RGF93 v1 / Lambert-93 -- France) coordinates.

  Study EGAS00001007764

• Mechanism of Decitabine response in MDS/AML patients

  Data access agreement for access to scRNASeq data of serial AML/MDS patients undergoing decitabine treatment.

  Dac EGAC50000000550

• CFTR Gene Variant Detection in Moroccan Individuals via Nanopore Long-Read Sequencing

  This is data from LRS of CFTR gene on CF Moroccan patients

  Dac EGAC50000000815

• Landscape of AL mutations

  Exome Sequencing to Define the Landscape of Plasma Cells in Systemic Light chain Amyloidosis

  Dataset EGAD00001001861

• MDS Sequential Treatment Validation

  Validations of variants identified by exome sequencing in sequential samples derived after treatment cycle with AZA.

  Dataset EGAD00001000949

• Tracing the origins of relapse in AML to stem cells

  Aligned whole genome sequence from AML relapse project

  Dataset EGAD00001003234

• Exome sequencing Parkinson's disease patients

  In this project we will sequence the exomes of 250 patients with Parkinson's disease

  Dataset EGAD00001000405

• KRAS Mutations in Multiple Myeloma

  Fastq files for 80 Multiple Myeloma Patients and 12 cell-lines

  Dataset EGAD00001005743

• Evolution of an adenomacarcinoma in response to selection by targeted kinase inhibitors

  Background - Adenocarcinomas of the tongue are rare and represent the minority (20-25%) of salivary gland tumors affecting the tongue. We investigated the utility of massively parallel sequencing to characterize an adenocarcinoma of the tongue, before and after treatment. Results - In the pre-treatment tumor we identified 7,629 genes within regions of copy number gain. 1,078 genes exhibited increased expression relative to the blood and unrelated tumors and four genes contained somatic protein-coding mutations. Our analysis suggested the tumor cells were driven by the RET oncogene. Genes whose protein products are targeted by the RET inhibitors sunitinib and sorafenib correlated with being amplified and or highly expressed. Consistent with our observations administration of sunitinib was associated with stable disease lasting 4 months, after which the lung lesions began to grow. Administration of sorafenib and sulindac provided disease stabilization for an additional 3 months after which the cancer progressed and new lesions appeared. A recurring metastasis possessed 7,288 genes within copy number amplicons, 385 genes exhibiting increased expression relative to other tumours and 9 new somatic protein coding mutations. The observed mutations and amplif ications were consistent with therapeutic resistance arising through activation of the MAPK and AKT pathways. Conclusions - We conclude that complete genomic characterization of a rare tumour has the potential to aid in clinical decision making and identifying therapeutic approaches where no established treatment protocols exist. These results also provide direct in-vivo genomic evidence for mutational evolution within a tumor under drug selection and potential mechanisms of drug resistance accrual.

  Study EGAS00000000074

• Blood DNA Methylation in Post-Acute Sequelae of COVID-19 (PASC): a Prospective Cohort Study

  Background: DNA methylation integrates environmental signals with transcriptional programs. COVID-19 infection induces changes in the host methylome. While post-acute sequelae of COVID-19 (PASC) is a long-term complication of acute illness, its association with DNA methylation is unknown. No universal blood marker of PASC, superseding single organ dysfunctions, has yet been identified. Methods: In this single center prospective cohort study, PASC, post-COVID without PASC, and healthy participants were enrolled to investigate their symptoms association with peripheral blood DNA methylation data generated with state-of-the-art whole genome sequencing (WGS). PASC-induced quality-of-life deterioration was scored with a validated instrument, SF-36. Analyses were conducted to identify potential functional roles of differentially methylated loci, and machine learning algorithms were used to resolve PASC severity. Findings: 103 patients with PASC (22.3% male, 77.7% female), 15 patients with previous COVID-19 infection but no PASC (40.0% male, 60.0% female), and 27 healthy volunteers (48.1% male, 51.9% female) were enrolled. Whole genome methylation sequencing revealed 39 differentially methylated regions (DMRs) specific to PASC, each harboring an average of 15 consecutive positions, that differentiate patients with PASC from the two control groups. Motif analyses of PASC-regulated DMRs identify binding domains for transcription factors regulating circadian rhythm and others. Some DMRs annotated to protein coding genes were associated with changes of RNA expression. Machine learning support vector algorithm and random forest hierarchical clustering reveal 28 unique differentially methylated positions (DMPs) in the genome discriminating patients with better and worse quality of life.

  Study phs003658

• Single cell RNA-seq mapping of nasal and tracheobronchial airways in human healthy volunteers

  The respiratory tract constitutes an elaborated line of defense based on a unique cellular ecosystem. Single-cell profiling methods enable the investigation of cell population distributions and transcriptional changes along the airways. We have explored cellular heterogeneity of the human airway epithelium in 10 healthy living volunteers by single-cell RNA profiling. 77,969 cells were collected by bronchoscopy at 35 distinct locations, from the nose to the 12th division of the airway tree. The resulting atlas is composed of a high percentage of epithelial cells (89.1%), but also immune (6.2%) and stromal (4.7%) cells with peculiar cellular proportions in different sites of the airways. It reveals differential gene expression between identical cell types (suprabasal, secretory, and multiciliated cells) from the nose (MUC4, PI3, SIX3) and tracheobronchial (SCGB1A1, TFF3) airways. By contrast, cell-type specific gene expression was stable across all tracheobronchial samples. Our atlas improves the description of ionocytes, pulmonary neuro-endocrine (PNEC) and brush cells, which are likely derived from a common population of precursor cells. We also report a population of KRT13 positive cells with a high percentage of dividing cells which are reminiscent of “hillock” cells previously described in mouse. Robust characterization of this unprecedented large single-cell cohort establishes an important resource for future investigations. The precise description of the continuum existing from nasal epithelium to successive divisions of lung airways and the stable gene expression profile of these regions better defines conditions under which relevant tracheobronchial proxies of human respiratory diseases can be developed.

  Study EGAS00001004082

• Neoantigen responses to Immunotherapy in Prostate Cancer

  To determine whether antigen-specific T cell responses can be elicited following treatment with ICT in cancers that have a low TMB, a clinical trial with ipilimumab (anti-CTLA-4) was conducted in 30 patients with metastatic castration-resistant prostate cancer (CRPC). We identified 2 distinct groups of patients divided by clinical outcomes, which consisted of a cohort with Favorable and Unfavorable outcomes. Compared to the Unfavorable cohort, the patients in the Favorable cohort were more likely to have higher intratumoral CD8 T cell density and/or IFN-γ response gene signature, including five patients who had antigen-specific T cell responses that were only detectable after ipilimumab therapy. Three patients had T cell responses against tumor-associated antigens (PSMA and PAP). Importantly, two patients with a relatively low TMB had T cell responses against unique neoantigens. Collectively, our data indicate that a subset of patients with metastatic prostate cancer benefit from ICTs, particularly those who have immunological biomarkers associated with effector T cell responses. Publication: Sumit K. Subudhi, Luis Vence, Hao Zhao, Jorge Blando, Shalini S. Yadav, Qing Xiong, Alexandre Reuben, Ana Aparicio, Paul G. Corn, Brian F. Chapin, Louis L. Pisters, Patricia Troncoso, Rebecca Slack Tidwell, Peter Thall, Chang-Jiun Wu, Jianhua Zhang, Christopher L. Logothetis, Andrew Futreal, James P. Allison and Padmanee Sharma, 2020, Neoantigen responses, immune correlates, and favorable outcomes after ipilimumab treatment of patients with prostate cancer. Science Translational Medicine, 01 Apr 2020:Vol. 12, Issue 537, eaaz3577DOI: 10.1126/scitranslmed.aaz3577. https://pubmed.ncbi.nlm.nih.gov/32238575/

  Study EGAS00001004050