Homo sapiens
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ABSTRACT:
PROVIDER: PRJNA386303 | ENA |
REPOSITORIES: ENA
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Project description:Integrated time course omics analysis distinguishes immediate therapeutic response from acquired resistance.
| PRJNA386291 | ENA
Project description:Integrated time course omics analysis distinguishes immediate therapeutic response from acquired resistance (RNA-Seq)
| PRJNA386287 | ENA
Project description:BACKGROUND: Targeted therapies specifically act by blocking the activity of proteins that are encoded by genes critical for tumorigenesis. However, most cancers acquire resistance and long-term disease remission is rarely observed. Understanding the time course of molecular changes responsible for the development of acquired resistance could enable optimization of patients treatment options. Clinically, acquired therapeutic resistance can only be studied at a single time point in resistant tumors. To determine the dynamics of these molecular changes, we obtained high throughput omics data weekly during the development of cetuximab resistance in a head and neck cancer in vitro model. RESULTS: An unsupervised algorithm, CoGAPS, was used to quantify the evolving transcriptional and epigenetic changes. Applying a PatternMarker statistic to the results from CoGAPS enabled novel heatmap-based visualization of the dynamics in these time course omics data. We demonstrate that transcriptional changes result from immediate therapeutic response or resistance, whereas epigenetic alterations only occur with resistance. Integrated analysis demonstrates delayed onset of changes in DNA methylation relative to transcription, suggesting that resistance is stabilized epigenetically. CONCLUSIONS: Genes with epigenetic alterations associated with resistance that have concordant expression changes are hypothesized to stabilize resistance. These genes include FGFR1, which was associated with EGFR inhibitor resistance previously. Thus, integrated omics analysis distinguishes the timing of molecular drivers of resistance. Our findings provide a relevant towards better understanding of the time course progression of changes resulting in acquired resistance to targeted therapies. This is an important contribution to the development of alternative treatment strategies that would introduce new drugs before the resistant phenotype develops.
2018-04-24 | GSE98813 | GEO
Project description:BACKGROUND: Targeted therapies specifically act by blocking the activity of proteins that are encoded by genes critical for tumorigenesis. However, most cancers acquire resistance and long-term disease remission is rarely observed. Understanding the time course of molecular changes responsible for the development of acquired resistance could enable optimization of patients treatment options. Clinically, acquired therapeutic resistance can only be studied at a single time point in resistant tumors. To determine the dynamics of these molecular changes, we obtained high throughput omics data weekly during the development of cetuximab resistance in a head and neck cancer in vitro model. RESULTS: An unsupervised algorithm, CoGAPS, was used to quantify the evolving transcriptional and epigenetic changes. Applying a PatternMarker statistic to the results from CoGAPS enabled novel heatmap-based visualization of the dynamics in these time course omics data. We demonstrate that transcriptional changes result from immediate therapeutic response or resistance, whereas epigenetic alterations only occur with resistance. Integrated analysis demonstrates delayed onset of changes in DNA methylation relative to transcription, suggesting that resistance is stabilized epigenetically. CONCLUSIONS: Genes with epigenetic alterations associated with resistance that have concordant expression changes are hypothesized to stabilize resistance. These genes include FGFR1, which was associated with EGFR inhibitor resistance previously. Thus, integrated omics analysis distinguishes the timing of molecular drivers of resistance. Our findings provide a relevant towards better understanding of the time course progression of changes resulting in acquired resistance to targeted therapies. This is an important contribution to the development of alternative treatment strategies that would introduce new drugs before the resistant phenotype develops.
2018-04-24 | GSE98812 | GEO
Project description:Therapeutic approaches to treat melanoma include small molecule drugs that target activating protein mutations in pro-growth signaling pathways like the MAPK pathway. While beneficial to the approximately 50% of patients with activating BRAFV600 mutation, mono- and combination therapy with MAPK inhibitors is ultimately associated with acquired resistance. To better characterize the mechanisms of MAPK inhibitor resistance in melanoma, we utilize patient-derived xenografts and apply proteogenomic approaches leveraging genomic, transcriptomic, and proteomic technologies that permit the identification of resistance-specific alterations and therapeutic vulnerabilities. A specific challenge for proteogenomic applications comes at the level of data curation to enable multi-omics data integration. Here, we present a proteogenomic approach that uses custom curated databases to identify unique resistance-specific alternations in melanoma PDX models of acquired MAPK inhibitor resistance. We demonstrate this approach with a NRASQ61L melanoma PDX model from which resistant tumors were developed following treatment with a MEK inhibitor. Our multi-omics strategy addresses current challenges in bioinformatics by leveraging development of custom curated proteogenomics databases derived from individual resistant melanoma that evolves following MEK inhibitor treatment and is scalable to comprehensively characterize acquired MAPK inhibitor resistance across patient-specific models and genomic subtypes of melanoma.
2024-05-10 | GSE266762 | GEO
Project description:Therapeutic approaches to treat melanoma include small molecule drugs that target activating protein mutations in pro-growth signaling pathways like the MAPK pathway. While beneficial to the approximately 50% of patients with activating BRAFV600 mutation, mono- and combination therapy with MAPK inhibitors is ultimately associated with acquired resistance. To better characterize the mechanisms of MAPK inhibitor resistance in melanoma, we utilize patient-derived xenografts and apply proteogenomic approaches leveraging genomic, transcriptomic, and proteomic technologies that permit the identification of resistance-specific alterations and therapeutic vulnerabilities. A specific challenge for proteogenomic applications comes at the level of data curation to enable multi-omics data integration. Here, we present a proteogenomic approach that uses custom curated databases to identify unique resistance-specific alternations in melanoma PDX models of acquired MAPK inhibitor resistance. We demonstrate this approach with a NRASQ61L melanoma PDX model from which resistant tumors were developed following treatment with a MEK inhibitor. Our multi-omics strategy addresses current challenges in bioinformatics by leveraging development of custom curated proteogenomics databases derived from individual resistant melanoma that evolves following MEK inhibitor treatment and is scalable to comprehensively characterize acquired MAPK inhibitor resistance across patient-specific models and genomic subtypes of melanoma.
2024-05-10 | GSE266735 | GEO
Project description:Melanoma resistance to MAPK- or T cell checkpoint-targeted therapies represents a major clinical challenge, and treatment failures of MAPK-targeted therapies due to acquired resistance often require salvage immunotherapies. We show that genomic analysis of acquired resistance to MAPK inhibitors revealed key driver genes but failedto adequately account for clinical resistance. From a large-scale comparative analysis of temporal transcriptomes from patient-matched tumor biopsies, we discovered highly recurrent differential expression and signature outputs of c-MET, LEF1 and YAP1 as drivers of acquired MAPK inhibitor resistance. Moreover, integration of gene- and signature-based transcriptomic analysis revealed profound CD8 T cell deficiency detected in half of resistant melanomas in association with downregulation of dendritic cells and antigen presentation. We also propose a major methylomic basis to transcriptomic evolution under MAPK inhibitor selection. Thus, this database provides a rich informational resource, and the current landscape represents a benchmark to understanding melanoma therapeutic resistance. Melanoma biopsies pre and post MAPKi treatment were sent for DNA methylation analysis using Illumina Human Methylation 450K bead chips
2015-09-15 | E-GEOD-65183 | biostudies-arrayexpress
Project description:Integrated multi-omics investigation of novel rat models of acquired hydrocephalus, Blood or bacteria in CSF trigger similar choroid plexus (ChP) immune-secretory responses, Crosstalk between ChP immune and epithelial cells drives CSF hypersecretion and ventriculomegaly, Repurposed systemic immunomodulators ameliorate acquired hydrocephalus, Identification of a druggable hub of ChP function relevant for multiple neurological diseases.
2023-02-17 | GSE218143 | GEO
Project description:Integrated multi-omics investigation of novel rat models of acquired hydrocephalus, Blood or bacteria in CSF trigger similar choroid plexus (ChP) immune-secretory responses, Crosstalk between ChP immune and epithelial cells drives CSF hypersecretion and ventriculomegaly, Repurposed systemic immunomodulators ameliorate acquired hydrocephalus, Identification of a druggable hub of ChP function relevant for multiple neurological diseases.
2023-02-17 | GSE192946 | GEO
Project description:Endocrine therapies targeting the proliferative effect of 17β-estradiol (17βE2) through estrogen receptor α (ERα) are the most effective systemic treatment of ERα-positive breast cancer. However, most breast tumors initially responsive to these therapies develop resistance through a molecular mechanism that is not yet fully understood. The long-term estrogen-deprived (LTED) MCF7 cell model has been proposed to recapitulate acquired resistance to aromatase inhibitors (AIs) in postmenopausal women. To elucidate this resistance, genomic, transcriptomic and molecular data were integrated into the time course of MCF7-LTED adaptation. Dynamic and widespread genomic changes were observed, including amplification of the ESR1 locus consequently linked to an increase in ERα. Dynamic transcriptomic profiles were also observed that correlated significantly with genomic changes and were influenced by transcription factors known to be involved in acquired resistance or cell proliferation (e.g. IRF1 and E2F1, respectively) but, notably, not by canonical ERα transcriptional function. Consistently, at the molecular level, activation of growth factor signaling pathways by EGFR/ERBB/AKT and a switch from phospho-Ser118 (pS118)- to pS167-ERα were observed during MCF7-LTED adaptation. Evaluation of relevant clinical settings identified significant associations between MCF7-LTED and breast tumor transcriptome profiles that characterize ERα-negative status, early response to letrozole and recurrence after tamoxifen treatment. This study proposes a mechanism for acquired resistance to estrogen deprivation that is coordinated across biological levels and independent of canonical ERα function. LTED (long term estrogen deprived) cell line was generated from MCF-7 cells by long-term culture under estrogen deprivated conditions. And RNA samples were obtained after 3, 15, 30, 90, 120, 150 and 180 days.
2010-09-01 | E-GEOD-20361 | biostudies-arrayexpress