437 results for "《云南省人民政府办公厅关于印发云南省省级信息化项目管理办法的通知》（云政办发〔2024〕21号）"

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• Center for Technology Licensing at Cornell University for data associated with Nature Medicine 2024 paper

  For data access to plasma/tumor/normal samples from the manuscript "Ultrasensitive plasma-based monitoring of tumor burden using machine learning-guided signal enrichment" from Widman et al. Nature Medicine 2024

  Dac EGAC50000000207

• Large B cell lymphomas with CCND1 rearrangement have different immunoglobulin gene breakpoints and genomic profile than mantle cell lymphoma

  Next-generation sequencig data including whole-genome sequencing, whole-exome sequencing, and capture-based gene panels of large B cell lymphomas with CCND1 rearrangementas described in Özoğul,Montaner, Pol et al 2024.

  Study EGAS50000000564

• REL-2017-07-2024

  HipSci - Alport Syndrome - Expression Array - July 2017

  Dataset EGAD00010001376

• DAC - organotypic co-cultures @IEO

  DAC for RNAseq data on patient-derived organotypic models (Battistini et al, CDDis 2024)

  Dac EGAC50000000238

• eQTL-CHiC DAC

  The Data Access Committee for eQTL-CHiC and related data from Ray-Jones et al., 2024.

  Dac EGAC50000000445

• HDBR exome sequencing data (August 2024)

  Exome sequencing data from fourteen phenotypically abnormal human fetal samples.

  Dataset EGAD50000000722

• HDBR exome sequencing data (December 2024)

  Exome sequencing data from sixteen phenotypically abnormal human fetal samples.

  Dataset EGAD50000001809

• WGS of Five Pancreatic Cancer Patients-Tumor and Normal

  We performed whole genome sequence on tumor-derived and normal cell lines from patients who had terminal pancreatic cancer and consented for rapid autopsy upon their death. The 5 samples are from Dr. Christine Iacobuzio-Donahue's rapid autopsy program as reported in Boland et al. (PLOSOne, 2024, In Press, PMID 38352348).

  Study phs003775

• TCRseq

  TCRseq data from Lauss et al Nat Comm 2024: Molecular patterns of resistance to immune checkpoint blockade in melanoma.

  Dataset EGAD50000000379

• ECL_onc_biology_DAC

  This DAC can be used by biology members of the oncology-related domain and function of ECL when depositing data. (DAA was reviewed by the legal department in March 2024.)

  Dac EGAC50000000275

• WES

  Whole Exome Sequencing data from Lauss et al Nat Comm 2024. Molecular patterns of resistance to immune checkpoint blockade in melanoma.

  Dataset EGAD50000000380

• tRCC UTSW 2024 Cohort

  This submission contains the WES and RNA-Seq raw data for the study titled 'Comparative Genomics of a Translocation Renal Cell Carcinoma Mouse Model Reveals Molecular Mechanisms of Tumorigenesis.

  Dac EGAC50000000105

• Walter and Eliza Hall Institute - University of Melbourne

  Data Access Committee for Gocuk, Lancaster et al. 2024: nanopore sequencing data of patients with choroideremia and X-linked retinitis pigmentosa, to determine X inactivation skew.

  Dac EGAC50000000301

• Next-generation sequencing raw data from metastatic prostate cancer biopsies - observational study Vall d'Hebron Institute of Oncology (Ethics committee code PR-AG-5248)

  Paired tumor-normal whole exome sequencing data from patients with metastatic prostate cancer; dataset from Arce-Gallego et al, Cell Reports Med 2024

  Dac EGAC50000000448

• Testicular large B-cell lymphoma is genetically similar to PCNSL and distinct from nodal DLBCL

  Next generation sequencing (NGS) data analyzed in Rivas-Delgado, López, et al. HemaSphere 2024. Single nucleotide variants (SNVs) and short insertions /deletions (indels) were evaluated in 42 samples using a B-cell malignancy-oriented targeted panel covering 115 genes (SureSelectXT, Agilent Technologies and sequenced in a MiSeq instrument (Illumina; 2x150bp; mean coverage of 599x). The NGS data of 39 samples is provided here. The 3 additional samples were previously published. Please, see the original publication for additional details.

  Study EGAS50000000521

• Genome-wide SNP data of Fulani populations from the Sahel belt

  This project seeks to uncover the genetic structure and ancestry of the Fulani populations across the Sahel/Savannah Belt. The study includes two datasets (''WGA_Fulani_Database'' and ''Saliva_Fulani_Ddatabase''), and SNP-genotyping data was generated using the Illumina Infinium H3Africa Consortium array (BeadChip type: H3Africa_2019_20037295_B1) in two genotyping batches (TE-2559_201029 and TE-2559_201020). In total, 419 were genotyped for this study and the key results were presented in Fortes-Lima et al. 2024 (doi: 10.1101/2024.06.22.600206).

  Study EGAS50000000451

• Solve-RD Solving the Unsolved Rare Dieseases

  Solve-RD – solving the unsolved rare diseases is a research project funded by the European Union’s Horizon 2020 research and innovation programme under grant agreement No 779257 from 1 January 2018 to 31 March 2024. Six European Reference Networks (ERNs; ERN-RND, -ITHACA, -EuroNMD, -GENTURIS, -RITA and -EpiCare) contributed data and samples to one or more of the four cohorts for data re-analysis and novel omics. For more information see https://solve-rd.eu/results/solve-rd-data/.

  Study EGAS00001003851

• cfDNA sWGS BAM — Metastatic colorectal cancer

  Plasma cirDNA sWGS for metastatic colorectal adenocarcinoma at diagnosis prior to systemic therapy. Libraries DSP/SSP (per sample). Sequencing by IntegraGen (2022–2024). Alignment: GRCh38 with BWA-MEM; BAMs sorted/indexed; delivered as primary mapped reads only (filters/MAPQ in analysis metadata). Controlled access

  Dataset EGAD50000001879

• cfDNA sWGS BAM — NSCLC stage I–III

  Plasma cfDNA sWGS for NSCLC patients (stage I–III), blood drawn pre-operatively, CHU Montpellier/LUNGDOC study. Libraries: DSP as recorded. Sequencing provider IntegraGen (2022–2024). Alignment to GRCh38 (hg38 canonical), BWA-MEM; BAMs sorted/indexed; only primary mapped reads retained (analysis pages list -F/MAPQ). Controlled access.

  Dataset EGAD50000001878

• Organoid Derivation Project - RNAseq (2024-10-14)

  Sequencing of tissue samples and their derived organoids. This dataset contains a subset of colorectal and colorectal liver metastasis samples.

  Dataset EGAD00001015425

• Diversity of the immune microenvironment and response to checkpoint inhibitor immunotherapy in mucosal melanoma

  Mucosal melanoma (MucM) is a rare cancer with a poor prognosis and low response rate to immune checkpoint inhibition (ICI) compared to cutaneous melanoma (CM). To explore the immune microenvironment and potential drivers of MucM’s relative resistance to ICI drugs, we characterized 101 MucM tumors (43 head and neck, 31 female urogenital, 13 male urogenital, 11 anorectal, and 3 other gastro-intestinal) using bulk RNA-sequencing (RNAseq). The original publication is written by JL Vos, JJH Traets, et al. and published in JCI Insight in 2024.

  Study EGAS50000000631

• Whole Exome Sequencing of a Lung Adenocarcinoma Patient Across Three Time Points

  A 65-year-old female patient with a significant smoking history (40 pack-years) was first diagnosed with lung adenocarcinoma (LUAD) in the left lung in May 2020 (L1-T1). One year later, in May 2021, the patient progressed with a new LUAD in the right lung (L1-T2) and in May 2024, another LUAD emerged in the right lung (L1-T3). Whole Exome Sequencing (WES) analysis was conducted on three tumor biopsies obtained at different time points from the same patient to investigate clonal trajectories.

  Study EGAS50000000812

• The light chain IgLV3-21 defines a new poor prognostic subgroup in Chronic Lymphocytic Leukemia: results from a multicenter study

  Purpose: Unmutated (UM) immunoglobulin heavy chain region (IgHV) status or IgHV3-21 gene usage is associated with poor prognosis in chronic lymphocytic leukemia (CLL). Interestingly, IgHV3-21 is often co-expressed with light chain IgLV3-21 which is potentially able to trigger cell-autonomous BCR-mediated signaling. However this light chain has never been characterized independently of the heavy chain IgHV3-21.Experimental Design: we performed total RNA sequencing to characterize IgLV3-21 patients (n=32) and investigated IgLV3-21 prognostic impact in terms of treatment-free (TFS) and overall (OS) survival in 3 other independent cohorts for a total of 813 patients where IgLV3-21 presence was tested by real-time PCR and confirmed by Sanger sequencing.Results: Using total RNA sequencing to characterize 32 patients with high-risk CLL, we found a high frequency (28%) of IgLV3-21 rearrangements. Gene set enrichment analysis revealed that these patients present higher expression of genes responsible for ribosome biogenesis and translation initiation (P<0.0001) and MYC target genes (P=0.0003). Patients with IgLV3-21 rearrangements displayed a significantly shorter TFS and OS (P<0.05), in particular in IgHV mutated patients. In each of the 3 independent validation cohorts (n=813), we showed that IgLV3-21 rearrangements -similar to UM IgHV status- conferred poor prognosis compared to mutated IgHV (P<0.0001). Importantly, we confirmed in multivariate analysis that this was independent of IgHV mutational status or subset #2 stereotyped receptor (P<0.0001). Conclusions: We therefore demonstrate for the first time that a light chain can impact on CLL prognosis and that IgLV3-21 light chain usage defines a new poor prognostic subgroup in CLL.

  Study EGAS00001002894

• Targeted capture, whole genome sequencing, and RNAseq to identify rearrangements in B-cell lymphomas

  This study contains whole genome and custom targeted capture sequencing of mature B-cell lymphomas (DLBCL, FL, BL, HGBCL-DH-BCL2, HGBCL-DH-BCL6) to identify translocation breakpoints of common oncogene rearrangements (MYC, BCL2, BCL6). It is complemented by RNAseq data where available. Complete details are available in the publication Hilton et al, 2024, Blood. Capture sequencing: 357 samples; 364 unique libraries; cram file format aligned to hg38 Whole genome sequencing: 12 samples; 12 unique libraries; cram file format aligned to grch37 RNAseq: 257 samples; 257 unique libraries; fastq file format

  Study EGAS50000000328

• cfDNA sWGS BAM — Breast cancer stage II-III (HR+/HER2−)

  Plasma cfDNA sWGS for breast cancer patients (HR+/HER2−, stage II–III), blood drawn pre-operatively (no neoadjuvant), Centre Léon Bérard/MyProbe (France). Libraries: DSP and/or SSP as recorded. Sequencing by IntegraGen (2022–2024); alignment to GRCh38 with BWA-MEM; BAMs sorted/indexed; primary mapped reads only (see analysis metadata for exact filters/MAPQ). Controlled access.

  Dataset EGAD50000001877

• Gene Expression Study of Individuals with Sex Chromosome Aneuploidies

  Males and females show dramatic differences in their vulnerability to the same diseases. For example, compared to men, lupus is six times more prevalent, thyroid cancer is three times more prevalent, and unipolar depression is twice as prevalent in women. Diseases with a strong male bias include autism (5:1), dilated cardiomyopathy (3:1), and ankylosing spondylitis (5:1). Historically, such differences have been attributed solely to extrinsic factors such as circulating sex hormones or environmental influences. We hypothesized that intrinsic factors - genetic differences between XX and XY cells - have unappreciated biological consequences throughout the body and contribute to sex differences in disease incidence and severity. This hypothesis stems from our long-term effort to sequence the sex chromosomes of diverse mammalian species, which has identified a set of homologous genes on the X and Y chromosomes that are dosage-sensitive, expressed throughout the body, and encode regulators of chromatin modification, transcription, translation, and protein stability. These X- and Y-encoded genes differ in sequence and expression pattern, which likely manifests in genome-wide differences in gene regulation between XX and XY cells and influences all aspects of human biology, including sex differences in disease susceptibility. These hard-wired molecular sex differences have been largely overlooked and understudied, representing a significant gap in our knowledge of human biology.The gene expression study of individuals with sex chromosome aneuploidies takes advantage of natural human variation in sex chromosome number, i.e. sex chromosome aneuploidy, to investigate alterations in genome-wide gene expression that correlate with changes in X- and Y-chromosome dosage. We analyzed samples from 114 individuals with a variety of sex chromosome aneuploidies, including 45,X; 47,XXY; 47,XYY; 47,XXX; 48,XXYY; and 49,XXXXY. We generated lymphoblastoid cell lines (LCLs) from blood samples and, in some cases, fibroblast cultures from skin biopsies. We supplemented our collection with previously-derived cell lines. To evaluate gene expression, we performed deep profiling of the transcriptome (RNA-seq) from these LCLs and fibroblasts. We performed parallel analyses on samples collected from 62 control 46,XX and 46,XY individuals, 6 individuals with trisomy 21, and 14 individuals with structural variations of the X and Y chromosomes. In addition, we performed CRISPRi knockdowns on 3 of the 46,XX and 3 of the 46,XY fibroblast samples for the homologous transcription factors ZFX and ZFY, encoded on the X and Y chromosomes, respectively.In the April 2024 update, we added RNA-seq datasets derived from isolated CD4+ T cells and monocytes from 76 and 72 adults, respectively, with the following sex chromosome constitutions: 45,X; 46,XX; 46,XY; 47,XXX; 47,XXY; 47,XYY. These individuals are largely a subset of the same cohort described above. In addition, we performed RNA-seq on in-vitro stimulated CD4+ T cells with the following sex chromosome constitutions: 45,X; 46,XX; 46,XY; 47,XXY.In the August 2024 update, we added RNA-seq datasets generated from the following: 1) LCLs derived from individuals with AZFa deletions of the Y chromosome, 2) DDX3X and DDX3Y knockdown (via CRISPRi) in XY fibroblasts, and 3) 5-ethyl uridine (5-EU) treatment in XY and XYYYY LCLs.

  Study phs002481

• Potential Modulatory Role of Osteoprotegerin in Bone Metabolism of Patients with 21-Hydroxylase Deficiency

  21-hydroxylase deficiency (21-OHD) is an inherited disorder that results from a mutation on the CYP21A2 gene. It affects the adrenal glands and is the most common cause of congenital adrenal hyperplasia (CAH). 21-OHD CAH causes the body to produce an insufficient amount of cortisol and an excess of androgen, the type of hormone that produces male characteristics. The primary treatment for 21-OHD CAH, glucocorticoid replacement therapy, has been shown to cause bone loss. However, the elevated hormone levels caused by 21-OHD CAH may increase production of the protein osteoprotegerin (OPG), which in turn may protect against bone loss. This study will compare bone density and OPG levels in women who have 21-OHD CAH and have undergone a lifetime of glucocorticoid replacement therapy to that in women who have neither of these criteria. In doing so, the study will aim to determine the relationship between OPG and bone loss. Because of the excess of androgen caused by 21-OHD CAH, women with CAH may exhibit some male-like characteristics. Glucocorticoids are a member of a class of drugs called corticosteroids, which are used in hormone replacement therapy. In order to counteract the effects of 21-OHD CAH, women with the disease are given hormone replacement therapy with glucocorticoids beginning at infancy. Glucocorticoids are known to cause bone loss. Despite many years of treatment with glucocorticoids, however, young women with 21-OHD CAH seem to be protected against bone loss. Researchers believe that the increased androgen levels in these women lead to increased estrogen levels, which in turn increase OPG production. The increase in OPG levels may protect women against bone loss. This study will evaluate bone density and OPG levels in women with and without 21-OHD CAH to determine the relationship between OPG and bone loss. Participants in this observational study will attend only one study visit. At this visit, they will undergo a blood draw; a scan of their lower spine, hip, and forearm; height and weight measurements; and a body fat analysis test. This last test will entail a weak and painless electrical signal being sent from foot to foot. Participants will not attend any follow-up visits for this study.

  Study phs001314

• Lessons learned from the exome sequencing of nine cases of infertility and the way forward

  This study investigated the role of exome sequencing in the diagnosis of male and female infertility. Nine unrelated cases referred between 2019 and 2024 were analysed using exome sequencing, with segregation confirmed by Sanger sequencing and functional assays for splicing variants. We identified nine causative variants in genes including TUBB8, PATL2, CCDC39, STAG3, KIAA0319, FBXO43, AGBL5/BBS7, PLCZ1, and HS6ST1, six of which were novel. The findings highlight diverse reproductive phenotypes such as oocyte maturation arrest, early embryonic arrest, spermatogenic failure, and syndromic infertility. This work demonstrates the value of combining genetic, functional, and clinical approaches to improve diagnostic yield and patient care in reproductive failure.

  Study EGAS50000001320

• Genetics and transcriptomes of pediatric B cell precursor leukemia with gain of chromosome 21

  Down syndrome (DS, constitutive trisomy 21) children have a 27-fold increased risk of developing B-ALL (DS-ALL), face a worse outcome due to treatment-related morbidities, and an increased rate of relapses compared to other children. This highlights the need to better understand the mechanisms of DS-associated leukemogenesis to develop more adapted treatment. In this study, we characterized the genetic and transcriptomic landscapes of DS-ALL and found a high incidence of somatic mutations leading to RAS/MAPK pathway activation in DS-ALL, as seen in other pediatric B-ALL presenting somatic gains of the chromosome 21 (B-ALL+21).

  Study EGAS00001003760

• Single-cell RNA-seq of immune cell subsets isolated from human tumors (Kaptein et al., 2024)

  Single-cell RNA-seq profiling of effector (KLRG1+ PD1-), transitional (KLRG1+ PD1-intermediate), dysfunctional (CD39+ PD1+) and memory (IL7Rα+) CD8 T cells isolated from 4 human tumors (1 melanoma, 1 renal carcinoma and 2 ovarian carcinoma). Respective cell populations were identified and isolated using FACS. FASTQ files contain gene expression data, feature barcode antibody capture or TCR data on individual CD8 T cell subsets across the 4 different samples.

  Dataset EGAD50000000376

• RNAseq from 6 organotypic co-cultures (OC cells bulk/OCSC with or without TME)

  The dataset contains samples of 6 organotypic co-cultures, assembled with patient-derived material from ovarian cancer (OC) patients. Tumor cells, both as bulk and as cancer stem cells-enriched (OCSC) populations, are cultured or not with in vitro peritoneal TME (for details see Battistini C et al, Tumor microenvironment-induced FOXM1 regulates ovarian cancer stemness, CDDis 2024). Dataset is composed by fastq file (paired end) type from bulk RNA-Seq.

  Dataset EGAD50000000523

• Whole transcriptome sequencing data of 3 histiocytic tumors with CLTC::SYK fusions

  The 3 tumor samples are PMLBM000JFR, PMLBM000JFT, and PMLBM000JFF. All samples are from different patients: Case 9 (PMLBM000JFR), Case 10 (PMLBM000JFT), and Case 12 (PMLBM000JFF) from the article by Kemps et al (Blood 2024 - In production). Methods: Total RNA was isolated and the generated libraries were sequenced on a NovaSeq 6000 (as described in Hehir-Kwa, et al. JCO Precis Oncol 2022). Data files: Provided are .cram and .crai files.

  Dataset EGAD50000000834

• Transcriptome and Exome from longitudinal samples of human glioblastoma (newly added after 2015)

  We expanded our previous collection of longitudinal GBM patients (EGAS00001001041) by recruiting 21 additional patients. Tumor specimens were subjected to whole-exome sequencing (16 of 21 cases, with the matched normal/blood) and transcriptome sequencing (16 of 21 cases).

  Dataset EGAD00001002143

• Paired-end Hi-C analysis of the 3D spatially mapped GBM samples.

  Dataset contains 21 paired-end Hi-C samples from 9 patients.

  Dataset EGAD00001010312

• Targeted capture ctDNA Library CRCQV34Run002-21

  Targeted capture ctDNA Library CRCQV34Run002-21 from patient PBC0002429, saliva sample

  Dataset EGAD00001010335

• Targeted capture ctDNA Library CRCQV34Run011-21

  Targeted capture ctDNA Library CRCQV34Run011-21 from patient PBC0002255, saliva sample

  Dataset EGAD00001010372

• Targeted capture ctDNA Library CRCQV42Run021-21

  Targeted capture ctDNA Library CRCQV42Run021-21 from patient PBC0001323, saliva sample

  Dataset EGAD00001010442

• Targeted capture ctDNA Library CRCQV42Run026-21

  Targeted capture ctDNA Library CRCQV42Run026-21 from patient PBC0003587, saliva sample

  Dataset EGAD00001010493

• Targeted capture ctDNA Library CRCQV42Run029-21

  Targeted capture ctDNA Library CRCQV42Run029-21 from patient PBC0001353, saliva sample

  Dataset EGAD00001010515

• Targeted capture ctDNA Library CRCQV42Run048-21

  Targeted capture ctDNA Library CRCQV42Run048-21 from patient PBC0005373, buffy coat sample

  Dataset EGAD00001010753

• Targeted capture ctDNA Library CRCQV42Run024-21

  Targeted capture ctDNA Library CRCQV42Run024-21 from patient PBC0002853, saliva sample

  Dataset EGAD00001010471

• Targeted capture ctDNA Library CRCQV42Run030-21

  Targeted capture ctDNA Library CRCQV42Run030-21 from patient PBC0003641, buffy coat sample

  Dataset EGAD00001010524

• Targeted capture ctDNA Library CRCQV42Run044-21

  Targeted capture ctDNA Library CRCQV42Run044-21 from patient PBC0005373, plasma baseline sample

  Dataset EGAD00001010671

• Targeted capture ctDNA Library CRCQV42Run047-21

  Targeted capture ctDNA Library CRCQV42Run047-21 from patient PBC0005444, buffy coat sample

  Dataset EGAD00001010733

• Targeted capture ctDNA Library CRCQV42Run049-21

  Targeted capture ctDNA Library CRCQV42Run049-21 from patient PBC0001456, buffy coat sample

  Dataset EGAD00001010774

• Targeted capture ctDNA Library CRCQV42Run050-21

  Targeted capture ctDNA Library CRCQV42Run050-21 from patient PBC0001828, buffy coat sample

  Dataset EGAD00001010794

• Targeted capture ctDNA Library CRCQV42Run051-21

  Targeted capture ctDNA Library CRCQV42Run051-21 from patient PBC0001665, buffy coat sample

  Dataset EGAD00001010814

• Targeted capture ctDNA Library CRCQV42Run039-21

  Targeted capture ctDNA Library CRCQV42Run039-21 from patient PBC0003014, plasma 3 month sample

  Dataset EGAD00001010616

• Targeted capture ctDNA Library CRCQV42Run031-21

  Targeted capture ctDNA Library CRCQV42Run031-21 from patient PBC0001413, buffy coat sample

  Dataset EGAD00001010532

• Targeted capture ctDNA Library CRCQV42Run032-21

  Targeted capture ctDNA Library CRCQV42Run032-21 from patient PBC0001627, buffy coat sample

  Dataset EGAD00001010544