16599 results for "sec+and+unspecified+malignant+neoplasm"

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• Oligodendroglia as functional effectors of Multiple Sclerosis risk variants (iPS derived hOPC scCRISPRi/a-seq)

  Study of the regulatory effect of a selection Multiple Sclerosis (MS) associated SNPs applying high-throughput functional genomics in human induced pluripotent stem cell-derived oligodendroglia (iPS-derived hOPCs). Selected cis-regulatory elements were assesed with lentiviral-based pooled single cell (sc)CRISPR-seq screens. CRISPRi/a (dCas9-KRAB and dCas9-p300 respectively) was performed, in combination with direct-capture Perturb-sequencing single-guide RNA (sgRNA) and droplet-based single-cell RNA-seq, allowing high sgRNA capture efficiency and identification of possible transcriptional regulatory mechanisms at a single cell/sgRNA level.

  Study EGAS50000001417

• Expression quantitative trait loci analysis using human immune cells in a Japanese population

  Recent evidence suggests that a substantial portion of complex disease risk alleles modify gene expression in a cell-specific manner. Therefore, it is reasonable to expect that cell-specific expression quantitative trait loci (eQTL) analysis can identify the candidate causal mechanisms of complex diseases (an eQTL is a variant whose polymorphism affects gene expression). We fractionated peripheral blood from 105 healthy Japanese volunteers into five major immune cell subsets (CD4+ T cells, CD8+ T cells, B cells, NK cells, and monocytes). We quantified gene and exon expression by RNA sequencing, and tested associations with neighboring common variants (MAF ? 0.05).

  Study JGAS000085

• Reconstruction of the personal information from human genome reads in gut metagenome sequencing data

  Human DNA present in fecal samples can result in a small number of human reads in gut shotgun metagenomic sequencing data. However, it is currently unclear how much personal information can be reconstructed from such reads and this has not been quantitatively evaluated. Such a quantitative evaluation is necessary to clarify the ethical concerns related to data sharing and to enable the efficient use of human genetic information in stool samples, such as for research and forensics. Here, we used genomic approaches to reconstruct personal information from fecal metagenomes of 343 Japanese individuals with associated human genotype data.

  Study JGAS000600

• RNAseq of MCL cell lines

  This study profiles the transcriptomic response of the Mino-VEN-R and Jeko-BTK-R mantle cell lymphoma (MCL) cell lines to pirtobrutinib (PBN) treatment using bulk RNA sequencing. Mino-VEN-R models drug-tolerant persister (DTP) cells that arise during exposure to non-covalent BTK inhibitors. Building on our recent findings that DTP cells undergo metabolic and phenotypic state transitions governed by TCA cycle reprogramming, this dataset aims to capture gene expression changes associated with treatment-induced plasticity. The results contribute to a broader multi-omic framework exploring mechanisms of resistance and therapeutic vulnerability in MCL.

  Study EGAS50000001087

• Bleomycin Induced Pneumonitis cohort of the Exceptional Responders Program of the Garvan Institute of Medical Research

  Bleomycin is a cytotoxic antibiotic and forms a key component of the curative-intent chemotherapy regimens for germ cell tumours (GCT) and lymphoma. However, the drug can be associated with a range of lung toxicity, including idiosyncratic inflammation termed bleomycin induced pneumonitis (BIP), which can lead to irreversible interstitial fibrosis and death. This study aims to identify germline genomic changes associated with BIP in patients receiving bleomycin as treatment for GCT or lymphoma, who develop clinically significant BIP despite low predicted risk based on absence of traditional risk factors.

  Study EGAS50000001545

• Neuroblastoma Smart-Seq2 Single Nuclei Sequencing Data

  Heterogeneity of tumors, including the presence of resistant clones, represents a great challenge for high-risk neuroblastoma (NB). Currently, there are no treatments that address cancer heterogeneity. Classification of bulk tumors and corresponding predictions are poor and too general. Understanding heterogeneity will provide critical insight for the development of targeted therapeutic strategies. In this study, we collected 10 human neuroblastoma tumor samples and performed whole-transcriptome profiling at single-nucleus resolution using SMART-Seq2 technology. This approach enables comprehensive characterization of transcriptional diversity within individual tumors, allowing us to identify distinct cellular subpopulations.

  Study EGAS50000001103

• Primary breast tumor heterogeneity through therapy

  We performed whole-exome sequencing on multiple regions (n=2-3) from four primary untreated breast tumors (n=1 HER2+, n=2 ER+/HER2-, n=1 triple-negative), as well as matched normal. We also performed whole-exome sequencing on one region from the pre-treatment diagnostic core biopsy and multiple regions (n=2-6) from the post-treatment surgical specimen for five HER2+ primary breast tumors, as well as matched normal; all were treated with combination chemotherapy and trastuzumab. Analysis of these specimens allows characterization of breast tumor heterogeneity and clonal evolution.

  Study EGAS00001003168

• The molecular landscape of glioma in patients with Neurofibromatosis 1.

  Neurofibromatosis type 1 (NF1) is a common tumor predisposition syndrome in which glioma is one of the most prominent tumor type. Gliomagenesis in NF1 results in heterogeneous spectrum of tumors, from low grade to high grade glioma, occurring during the entire patient lifespan. In this study, we present the molecular landscape of low- and high-grade glioma in children and adults affected by NF1 (NF1-glioma). 59 tumor samples from 56 NF1-glioma patients with 43 matched normal were profiled with Whole Exome Sequencing, DNA Methylation array (31 tumors) and RNA sequencing (29 tumors).

  Study EGAS00001003186

• Transcriptomic analysis of the Phase 3 COMPARZ clinical trial

  Metastasis remains the main reason for renal cell carcinoma (RCC)-associated mortality. Tyrosine kinase inhibitors (TKI) impart clinical benefit for most RCC patients but the determinants of response are poorly understood. We report an integrated genomic and transcriptomic analysis of metastatic clear cell RCC (ccRCC) patients treated with TKI therapy and identify predictors of response. Patients in the COMPARZ phase III trial received first-line sunitinib or pazopanib with comparable efficacy. Microarray-based transcriptomic analyses with results from Next-gen genomic analyses of targeted genes revealed distinct molecular subgroups associated with response and survival.

  Study EGAS00001004534

• The_Causes_of_Clonal_Blood_Cell_Disorders_Study___SCOR

  We will take a bone marrow aspirate and peripheral blood samples from a healthy patient aged around 60, and use flow cytometry to isolate 100 HSCs, 50 MEPs, and 50 GMPs. We will grow these up into colonies, then whole genome sequence each colony. Somatic mutations will act as a unique barcode for each clone. We will then design a panel for targeted resequencing of the mutations that we find. It will then be possible to look for these mutations in the peripheral blood over several years, to see the dynamics of how HSCs contribute to the peripheral blood in health.

  Study EGAS00001002132