16794 results for "sec+and+unspecified+malignant+neoplasm"

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• HCI-PDX Trial Center for Breast Cancer Therapy

  The HCI-PDX Trial Center for Breast Cancer Therapy study is a collection of patient-tumor samples that are serially established as patient-derived tumor xenografts (human tumor in mouse) and matching organoids. For this study, we describe valuable methods and resources to generate organoids and use them as cost-effective models for precision drug screens. This study leveraged whole-exome sequencing, RNAseq, and SNP-array data to illustrate how the heterogeneity of tumors is preserved in xenograft and organoid models. Sequencing files are provided for whole-exome and RNAseq data. Processed copy number variant calls from the SNP arrays are also available. A full description of the study can be found in the article entitled, "A human breast cancer-derived xenograft and organoid platform for drug discovery and precision oncology," written by Guillen et al., 2022 in Nature Cancer (PMID: 35221336).

  Study phs002479

• UCSF Center for Reproductive Health (CRH) Research Bank

  The purpose of this study is to provide a reference profile of small extracellular RNAs in body fluids. These samples were originally obtained in a study that had a different purpose. The purpose of the original study was to add excess biological materials during the course of IVF treatment to a tissue bank. These biological materials included follicular fluid (the liquid that comes out of the ovary with the egg), granulosa cells (cells that surround the egg and help it grow), and other biological materials that help eggs, sperm, and embryos stay healthy and grow outside the body. These banked specimens would allow researchers to learn more about infertility and how to treat it, including studying how to identify the healthiest eggs, sperm, and embryos and how to help them stay healthy and grow.

  Study phs001695

• Consortium on Asthma among African-ancestry Populations in the Americas (CAAPA)

  Asthma is a complex disease where the interplay between genetic factors and environmental exposures influences susceptibility and disease prognosis. Asthmatics of African descent tend to have more severe asthma and more severe clinical symptoms than individuals of European ancestry. Advances in genetic and genomic technologies have revolutionized gene discovery for several complex diseases, but going to the next step in gene discovery for asthma among populations of African descent requires considering unique characteristics of this ethnic group, including adequate sample sizes and population stratification due to (European and African) admixture. Thus far, coverage of common genetic markers both in public databases and commercially available SNP chips has been inadequate to detect and measure genetic associations among African admixed populations. The aim of this study was therefore to catalog genetic diversity in populations of African descent, especially those whose ancestry reflects the African Diaspora in the Americas.

  Study phs001123

• Genomic Characterization CS-MATCH-0007 Arm Z1B

  The CS-MATCH-0007 protocol is part of a collaboration between the Center for Cancer Genomics (CCG) and the Division of Cancer Treatment and Diagnosis (DCTD) to perform whole-exome sequencing and RNA sequencing using pre-and post-treatment tumor biopsy specimens from patients enrolled on a treatment arm of the NCI-MATCH Clinical Trial (EAY131). The goal of this study is to identify the molecular basis for response and resistance to targeted therapies that are matched to specific genomic alterations found in their cancers. Arm Z1B is one of the treatment sub-protocols within the NCI-MATCH Clinical Trial (EAY131) where patients with CCND1, CCND2, and/or CCND3 amplifications are treated with Palbociclib. This subprotocol is one of the treatment arms included in the CS-MATCH-0007 protocol and will provide specimens for the program including DNA from tumor tissue and whole blood.

  Study phs002180

• NHLBI TOPMed: Stanford Cardiovascular Institute iPSC Biobank Study (SCVI)

  The proposed Stanford Cardiovascular Institute (SCVI) Biorepository will curate and manage an expanded collection of human induced pluripotent stem cell (iPSC) lines and provide investigators with iPSC materials generated using standardized protocols, with the overall objective of promoting the continued adoption and development of iPSC technology in cardiovascular research. Human iPSCs have revolutionized disease modeling, drug screening, and therapeutic research. However, it is also recognized that the need for specialized technical expertise and the associated cost have largely prevented individual research laboratories from adopting iPSC models in their inquiries, particularly in studies requiring multiple cell lines. To address this bottleneck, the proposed Biorepository will maintain our existing collection of iPSC lines and further expand the collection of iPSCs by recruiting 1,000 healthy, hypertrophic cardiomyopathy (HCM), dilated cardiomyopathy (DCM) donors of both sexes and diverse racial/ethnic backgrounds (African Americans, Asians, Hispanics, and Whites).

  Study phs002338

• Genetic variants associated with paroxysmal atrial fibrillation in the Japanese population

  Paroxysmal atrial fibrillation (PAF) is often asymptomatic, making early-stage diagnosis difficult using routine clinical examinations alone. The genetic factors underlying PAF and the predictive utility of polygenic risk scores (PRSs) for PAF in Asian populations remain insufficiently understood. In this study, we aim to explore genetic variants associated with PAF in a Japanese cohort and to evaluate the predictive performance of PAF-specific PRSs. We analyze Japanese participants genotyped with the Illumina Infinium Asian Screening Array and perform a genome-wide association study (GWAS) after sample and variant quality control and genotype imputation based on the GRCh37 reference genome. Using the GWAS results, we construct multiple PRS models and assess their predictive ability both alone and in combination with clinical risk factors. These efforts are intended to provide a basis for personalized prevention and early detection strategies for PAF in the Japanese population.

  Study JGAS000866

• Comprehensive benchmarking of methods for mutation calling in circulating tumor DNA

  This study provides a comprehensive benchmarking resource for somatic variant detection in cell-free DNA (cfDNA) from cancer patients. Longitudinal plasma samples from colorectal and breast cancer cohorts were selected to create patient-matched dilution series spanning ultra-low to high circulating-tumour-DNA (ctDNA) fractions, while preserving each individual’s germline and clonal haematopoiesis background. Deep whole-genome sequencing (150×) and ultra-deep whole-exome sequencing (2,000×) generated a reference call set of ~37,000 single-nucleotide variants and ~58,000 insertions/deletions. These data enabled systematic evaluation of nine somatic variant callers across variable ctDNA levels and sequencing depths, and were further used to explore machine-learning–guided parameter tuning. The resulting dataset offers an openly accessible framework for developers and clinicians to assess and optimize somatic variant calling in liquid biopsy applications.

  Study EGAS50000001313

• Molecular Sub-grouping of CNS-PNET

  In our study we aimed to define CNS-PNET subgroups. We performed Expression, Genotyping and/or Immunohistochemistry on 142 samples from 20 worldwide centers. Using these techniques, we have identified three molecular subgroups with distinct expression and copy number patterns, as well as, unique clinical characteristics. Specifically, these molecular subgroups were distinguished by primitive neural (group 1), oligoneural (group 2), and mesenchymal lineage (group 3) gene-expression signatures with differential expression of cell-lineage markers LIN28 and OLIG2. Our report underscores the importance of concerted, collaborative efforts to study large retrospective cohorts of tumours and patients to accelerate biological and ultimately therapeutic studies of rare tumours. The outcome of such a collaboration allowed us to identify LIN28 and OLIG2 as promising diagnostic and prognostic molecular markers for CNS PNET that warrant further assessment in prospective clinical trials.

  Study EGAS00000000116

• Exome sequencing of early and late passage Patient Derived Xenogratf Tumoroids with matched Patient Derived Xenogratfs and matched normal liver

  The breadth and depth at which cancer models are interrogated contribute to successful translation of drug discovery efforts to the clinic. In colorectal cancer (CRC), model availability is limited by a dearth of large-scale collections of patient-derived xenografts (PDXs) and paired tumoroids from metastatic disease, the setting where experimental therapies are typically tested. XENTURION is a unique open-science resource that combines a platform of 129 PDX models and a sister platform of 129 matched PDX-derived tumoroids (PDXTs) from patients with metastatic CRC, with accompanying multidimensional molecular and therapeutic characterization. This specific dataset is focused on a comparison of early and late passage tumoroids transcriptomes. In this study we focused our attention on early (passage 3) and late (passage 8-12) PDXTs with their matched PDXs and normal liver

  Study EGAS50000000185

• Measuring the level of relatedness between NGS datasets

  Sequencing technologies are providing increasingly detailed insight in genetic makeup are paving their way into molecular diagnostics. The field will benefit from rigorous and bias-free measures for the quality of sequence data and for the proper representation of the complexity of the original samples. While current methodologies rely on the availability of a well-characterized reference genome, we propose kMer profiling for alignment-free assessment of the quality, comparability, and complexity of sequencing datasets. We show that kMer detects technical artefacts such as high duplication rates, library chimaeras, and differences in library preparation protocols in whole-genome, whole-exome, and RNA sequencing data. Additionally, it successfully captures the complexity and diversity of microbiomes. Thus, kMer allows for a robust evaluation of the quality and complexity of sequencing data without relying on any prior information and opens the way to a more reliable biological reasoning.

  Study EGAS00001000600