13418 results for ""pdc"+"heritage+language"+census+study"

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• Proteogenomic Analysis of CALGB40601 (ALLIANCE) a Neoadjuvant Phase III HER2-Positive Breast Cancer Trial

  80 frozen core needle biopsies from 54 HER2+ breast cancer patients from the CALGB 40601 trial (NCT00770809) were processed for proteogenomic analysis to identify genes, proteins, and phosphosites associated with pathological complete response to neodjuvant anti-HER2 therapies. The final set included 22 patients treated with trastuzumab plus lapatinib in combination with pacletaxel (THL arm), 24 patients treated with trastuzumab in combination with pacletaxel (TH arm), and 8 patients treated lapatinib in combination with pacletaxel (TL arm). Principal findings of this study included identifying negative cases misdiagnosed as HER2+ that did not respond to targeted therapy and observing higher levels of two biomarker candidates in non-pCR tumors. Mass spec-based proteomics and phosphoproteomics data generated from 75 biopsies (all 54 patients) will be made available via the Proteomic Data Commons. Whole exome- (67 biopsies from 49 patients) and RNA-sequencing (52 biopsies from 39 patients) data for the subset profiled with proteogenomics will be made available through dbGaP, but genomic and transcriptomic profiling data for the whole cohort has previously been deposited (phs001570).

  Study phs003576

• Characterization of High-Grade Serous Ovarian Cancer Subtypes via Single-Cell and Spatial-Transcriptomics Profiling

  We measured gene expression in single-cell RNA sequencing samples from patients with high-grade serous ovarian cancer (HGSOC), for a study on improving HGSOC subtype definition by taking into account varying cell type proportions within tumors. The initial dataset (added October, 2020) contains 3 samples (3 individuals). The next dataset (added November, 2022) contains 34 samples from 8 individuals. The samples in the second dataset were sequenced in five different ways: 1) rRNA depletion and bulk RNA sequencing of tumor chunks, 2) rRNA depletion and bulk RNA sequencing of dissociated cells, 3) poly-A capture and bulk RNA sequencing of dissociated cells, 4) poly-A capture and scRNA sequencing of dissociated cells, 5) barcoding and pooling cells and scRNA sequencing (2 pools of 4 samples each). The third dataset (added June, 2024) contains data from one spatially resolved transcriptomics experiment (4 samples, one per Visium capture area, describing one tumor from one individual) and scRNA sequencing on 5 samples (5 individuals).

  Study phs002262

• 10x Multiome from Human Fetal Heart

  We hope to uncover the genetic basis of congenital heart disease by examining how genetic variants, especially those in non-coding regions, influence heart development. To achieve this goal, our research team created a single-cell atlas of human fetal heart development. The study population consists of 41 structurally normal fetal hearts spanning 6 to 22 weeks post-conception. We profiled close to 750,000 using single-cell RNA sequencing and ATAC sequencing technologies via the 10x Genomics Multiome platform.The molecular technologies employed allowed for simultaneous analysis of gene expression and chromatin accessibility at the single-cell level. This approach identified numerous distinct cell types and states within the developing heart, offering detailed insights into gene activity and enhancer usage during critical stages of heart development.Principal findings include the characterization of diverse cell populations and the identification of specific gene expression patterns and regulatory elements active during heart formation. This high-resolution atlas provides valuable insights into how genetic variants may disrupt normal heart development, particularly those in non-coding regions that affect gene regulation.

  Study phs003778

• Genomic Analysis of Relapsed/Refractory DLBCL

  Molecular phenotyping techniques have established a landscape of genomic variants in diagnostic Diffuse Large B Cell Lymphoma (DLBCL), however these have not yet been applied in large scale studies of relapsed/refractory DLBCL resulting in incomplete characterization of mechanisms driving tumor progression and treatment resistance. Here, we performed an integrated multiomic analysis on relapsed/refractory DLBCL samples. Tumors from 87 relapsed/refractory DLBCL patients were included in this study and were available for data deposition [Tumor whole exome sequencing (WES): n=75, Germline WES: n=73, RNA sequencing (RNA-Seq): n=72]. Tumor DNA was extracted from formalin-fixed, paraffin embedded (FFPE) tissue sections, germline DNA was extracted from blood, and WES of all samples was performed using the Agilent SureSelect XT All Exon v6 kit and sequencing was carried out on an Illumina NovaSeq, 100 x 2 paired end reads. Tumor RNA was extracted from FFPE tissue sections and RNA-Seq was performed using the Illumina TruSeq RNA Exome Kit (Illumina) for library preparation, sequencing platform HiSeq 4000, 100 x 2 paired end reads.

  Study phs003868

• Chromatin remodeler CHD7 regulates the stem cell identity of human neural progenitors

  Multiple congenital disorders often present complex phenotypes, but how the mutation of individual genetic factors can lead to multiple defects remains poorly understood. In the present study, we used human neuroepithelial (NE) cells and CHARGE patient-derived cells as an in vitro model system to identify the function of chromodomain helicase DNA-binding 7 (CHD7) in NE?neural crest bifurcation, thus revealing an etiological link between the central nervous system (CNS) and craniofacial anomalies observed in CHARGE syndrome. We found that CHD7 is required for epigenetic activation of superenhancers and CNS-specific enhancers, which support the maintenance of the NE and CNS lineage identities. Furthermore, we found that BRN2 and SOX21 are downstream effectors of CHD7, which shapes cellular identities by enhancing a CNS-specific cellular program and indirectly repressing non- CNS-specific cellular programs. Based on our results, CHD7, through its interactions with superenhancer elements, acts as a regulatory hub in the orchestration of the spatiotemporal dynamics of transcription factors to regulate NE and CNS lineage identities.

  Study JGAS000131

• Single cell RNA seq of breast cancer stem cells

  RNA sequences of breast cancer have been investigated for many patients. Recently it has been shown that there are intra-heterogeneity in tumor tissues. When the tumor cells were sequenced in bulk condition, only the major populations' mRNA will be detected. With respect to breast cancer, it has been also reported that cancer cells can sub-gropued into cancer stem cells and non-cancer stem cells. Although the mRNA expressions' difference between this two groups has been profoundly investigated, whether each group is composed by unique cell or not is yet to be elucidated. Since cancer stem cells are the thought to be the major contributor of metastasis and/or recurrence, we focused on cancer stem cells in this study. We separated cancer cells into cancer stem cells and non-cancer stem cells exploiting cancer stem cell specific surface markers. Thereafter, we sequenced mRNA of cancer stem cells in single cell resolution. From this result, we examined whether these cells can be sub-grouped or not.

  Study JGAS000305

• Impact of germline pathogenic variants in 27 cancer-predisposing genes on the risk of lymphoma

  The application of advanced molecular technology has significantly expanded lymphoma classification, allowing risk stratification and treatment optimization. Limited evidence suggests the presence of a genetic predisposition in lymphoma, indicating the potential for better individualized clinical management based on a novel lymphoma classification. Herein, we examined the impact of germline pathogenic variants in 27 cancer-predisposing genes with lymphoma risk and explored the clinical characteristics of pathogenic variant carriers. This study included 2,066 lymphoma patients and 38,153 cancer-free controls from the Japanese population. Following quality control of sequencing data, samples from 1,982 lymphoma patients and 37,592 controls were further analyzed. Sequencing data of controls were obtained from JGAD000721. Germline pathogenic variants in some cancer-predisposing genes were associated with a high risk of lymphoma. Furthermore, germline pathogenic variants in these genes were especially associated with the higher risk of a certain subtype. These results would provide novel insights concerning monogenic form into lymphoma classification. Some lymphoma patients may benefit from surveillance and targeted treatment like other neoplasms.

  Study JGAS000347

• Development of the prevention and therapy of CRC using patient derived culture tissues.

  Tumor tissues consist of functionally heterogeneous cells including those with high clonogenic potential called cancer stem cells (CSCs) which produce differentiated non-tumorigenic progenies. Transplantation assays have been performed to identify cell surface markers in solid tumors including colorectal cancers, which identified several CSC markers such as CD133 and CD44. In addition to the transplantation, the lineage tracing of genetically labelling cells in animal models of cancer qhas been employed to explore the cellular heterogeneity of tumors by identifying the CSCs and its progenies. This approach is particularly useful to investigate solid tumors, where cellular proliferation and differentiation are controlled by niche factors and cell-cell contact with adjacent cells. Lineage tracing of mouse model of cancer unravel the mode of growth of autochthonous tumor in their native environment. In this study, we used patient derived organoids (PDO) established from surgically resected CRC patients to identify the CSC. Single cell RNA-seq analysis identified potential CRC markers, which may exhibit self-renewal activity and produce progenitors

  Study JGAS000139

• Myasthenia gravis-specific aberrant neuromuscular gene expression by medullary thymic epithelial cells in thymoma

  Myasthenia gravis (MG) is a neurological disease caused by autoantibodies against neuromuscular-associated proteins. While MG is frequently developed in thymoma patients, the etiologic factors for MG are not well understood. Here, by constructing a comprehensive atlas of thymoma using bulk and single-cell RNA-seq, we identified ectopic expression of neuromuscular molecules in MG-associated thymoma (MG-thymoma). These molecules were originated from a distinct subpopulation of medullary thymic epithelial cells (mTECs), which we named neuromuscular mTECs (nmTECs). MG-thymoma also exhibited microenvironments dedicated to autoantibody production, including ectopic germinal center formation, T follicular helper cell accumulation, and type 2 conventional dendritic cell migration. Cell-cell interaction analysis also predicted the interaction between nmTECs and T/B cells via CXCL12-CXCR4. The enrichment of nmTECs presenting neuromuscular molecules within MG-thymoma was further confirmed by immunohistochemically and by cellular composition estimation from MG-thymoma transcriptome. Altogether, this study suggests that nmTECs play a significant role in MG pathogenesis via ectopic expression of neuromuscular molecules.

  Study JGAS000482

• Data upcycling, powered by EGA

  In 2012 a collaborative effort headed by the teams of Carlos Caldas in Cambridge, UK and Samuel Aparicio, Canada, produced a pivotal study aimed at defining the mutational landscape of breast cancer. They gathered a collection of over 2000 breast cancer samples (METABRIC) associated with long-term clinical follow-up. They delineated an array of inherited and somatically acquired genetic variants and associated them to gene expression. This led to the identification of putative cancer-driving events and improved stratification of breast cancer patients. The study elicited huge attention and was tackled as herculean effort by fellow researchers. Cristina Curtis and her colleagues deposited the data in the EGA archive (EGAS00000000083). What they probably could not foresee is that their data would be reused more than 100 times, becoming one of the most downloaded datasets at EGA. In 2015, Frederik S. Varn and colleagues accessed the above-mentioned data from the New Hampshire, USA, to correlate it to transcriptional programs of hematopoietic cells infiltrated in breast tumours and found that those can influence patients' prognosis. Their findings, published in Nature Communications, improved the understanding of the interplay between immune system and cancer. Again, in 2017 the dataset was downloaded by an Italian/Polish collaboration and used to corroborate their mechanistic study that demonstrate how a long non-coding RNA (lncRNA) is aberrantly localized into the chromatin, where it modulates oncogenic isoforms expression, thus contributing to breast cancer. To date, the METABRIC dataset has been reused to contribute to 147 publications. Its impact on breast cancer research is incalculable, and it even spread beyond that, with recent contributions to the understanding of pan-cancer mechanisms and features. Some of the publications are translating into improvements in diagnosis and treatment of different types of breast cancer. This is just an example of how data upcycling can amplify the potential of any dataset, well past the scope of its creation, the imagination of its owners and any geographical border. At EGA, we are proud to empower such fruitful worldwide cycles of knowledge, providing a platform that enables safe sharing of sensitive genetic data.

  Blog data-upcycling-powered-by-ega