Relating Clinical Outcomes in Multiple Myeloma to Personal Assessment of Genetic Profiles
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ABSTRACT:
PROVIDER: PRJNA248538 | ENA |
REPOSITORIES: ENA
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Project description:Relating Clinical Outcomes in Multiple Myeloma to Personal Assessment of Genetic Profiles
| PRJNA248539 | ENA
Project description:STAGING: Relating Clinical Outcomes in Multiple Myeloma to Personal Assessment of Genetic Profiles
| PRJNA248536 | ENA
Project description:STAGING: Relating Clinical Outcomes in Multiple Myeloma to Personal Assessment of Genetic Profiles
| PRJNA248537 | ENA
Project description:The historical lack of pre-clinical models reflecting the genetic heterogeneity of multiple myeloma (MM) hampers advancing therapeutic discoveries. To circumvent this limitation, we have generated fifteen genetically diverse models that developed bone marrow tumors fulfilling MM pathogenesis. Transcriptomic analysis of tumor plasma cells revealed that MYC activation regulates time to progression. Bone marrow cell composition analysis classified myeloma tumors into immune-cold and inflamed categories, which condition immune checkpoint blockade responses in mouse multiple myeloma models.
2023-03-17 | GSE205644 | GEO
Project description:<p>The Multiple Myeloma Research Foundation (MMRF) CoMMpass (Relating <u>C</u>linical <u>O</u>utcomes in <u>MM</u> to <u>P</u>ersonal <u>Ass</u>essment of Genetic Profile) trial (NCT01454297) is a longitudinal observation study of 1000 newly diagnosed myeloma patients receiving various standard approved treatments that aim at collecting tissue samples, genetic information, Quality of Life (QoL) and various disease and clinical outcomes over 10 years.</p>
| phs000748 | dbGaP
Project description:Personal Neoantigen Cancer Vaccines
| PRJNA401959 | ENA
Project description:Organisms can gain information about their environment from their ancestors, their parents, or their own personal experience. “Cue integration” models often start with the simplifying assumption that information from different sources is additive. Here, we test key assumptions and predictions of cue integration theory at both the phenotypic and molecular level in threespined sticklebacks (Gasterosteus aculeatus). We show that regardless of whether cues about predation risk were provided by their father or acquired through personal experience, sticklebacks produced the same set of predator-adapted phenotypes. Moreover, there were nonadditive effects of personal and paternal experience: animals that received cues from both sources resembled animals that received cues from a single source. A similar pattern was detected at the molecular level: there was a core set of genes that were differentially expressed in the brains of offspring regardless of whether risk was experienced by their father, themselves or both. These results provide strong support for cue integration theory because they show that cues provided by parents and personal experience are comparable at both the phenotypic and molecular level, and draw attention to the importance of nonadditive responses to multiple cues.
2018-06-13 | GSE113548 | GEO
Project description:An overall goal of functional genomics has been to measure the impact of variants on molecular endophenotypes (e.g. gene expression levels or the degree of TF binding) and relate this to organismal traits and disease phenotypes. However, all the experiments to date have been described relative to a generic reference genome, significantly hobbling their interpretation. Here, we describe a strategy for finding significant relationships between disease variation and genomic annotation via personal functional genomics, by performing personal genome sequencing and paired functional genomics experiments, on the same individual.
2024-05-22 | PXD022787 | Pride
Project description:We surveyed the variation and dynamics of active regulatory elements genome-wide in CD4+ T cells, using Assay of Transposase Accessible Chromatin with sequencing (ATAC-seq) in longitudinal samples from healthy volunteers and during T cell activation. We created robust pipelines that enable accurate single molecule counting and allelic discrimination from clinical material. Over 4000 regulatory elements (7.2%) showed reproducible personal variation in activity. Gender was the most significant attributable source of regulome variation. ATAC-seq revealed novel elements that escape X chromosome inactivation and predicted gender-specific gene regulatory networks across autosomes, which coordinately impact genes with immune function. Noisy regulatory elements with personal variation in accessibility are significantly enriched for autoimmune disease loci. Over one third of regulome variation lacked genetic variation in cis, suggesting contributions from environmental or epigenetic factors. These results refine concepts of human individuality and provide foundational reference to compare disease-associated regulomes.
2015-06-23 | GSE60682 | GEO
Project description:Approximately 90% of pre-clinically validated drugs fail in clinical trials due to unanticipated clinical outcomes, costing over several hundred million US dollars per drug. Despite such critical importance, translating pre-clinical data to clinical outcomes remain a major challenge. Herein, we designed a modality-independent and unbiased approach to predict clinical outcomes of drugs. The approach exploits their multi-organ transcriptome patterns induced in mice and a unique mouse-transcriptome database “humanized” by machine learning algorithms and human clinical outcome datasets. The cross-validation with small-molecule, antibody and peptide drugs shows effective and efficient identification of the previously known outcomes of 5,519 adverse events and 11,312 therapeutic indications. In addition, the approach is adaptable to deducing potential molecular mechanisms underlying these outcomes. Furthermore, the approach identifies previously unsuspected repositioning targets. These results, together with the fact that it requires no prior structural or mechanistic information of drugs, illustrate its versatile applications to drug development process.
2020-01-09 | GSE142068 | GEO