Targeted RNA Sequencing of a panel of ovarian cancer cell lines
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE150942 | GEO | 2020/05/21
REPOSITORIES: GEO
Similar Datasets
Project description:Thirty-seven (37) human cell lines were submitted to HTG Molecular for analysis using the HTG EdgeSeq Oncology Biomarker Panel. The goal of this work is to characterize the gene expression pattern of different cell lines bearing sensitivity or resistance for specific drugs.
2018-01-01 | GSE103934 | GEO
Project description:Small cell neuroendocrine carcinoma (SCNEC) of the uterine cervix is a rare disease with a poor prognosis. The lack of established disease models has hampered therapy development. We established a panel of organoid from patients of SCNEC of the uterine cervix. Sensitivity assays against clinically used drugs revealed remarkable variations between the lines, and we successfully identified specific gene sets which likely contribute to the sensitivity to the tested drugs. Of note, we found one line which was exceptionally sensitive to irinotecan, and investigated the mode of action in the case. Chemotherapeutic drug sensitivity assays using SCNEC CTOS lines obtained from primary patient samples with a high success rate may provide useful information for treating SCNEC.
2021-01-07 | GSE164329 | GEO
Project description:Alterations in the histone methylation profiles are observed in various types of cancer and targeting of this epigenetic process has therapeutic potential. Here we provide proof-of-principle that pharmacological targeting of KDM5 histone-demethylases is a new strategy for the personalized treatment of HER2-positive breast cancer. This analysis demonstrates that cells characterized by HER2-positivity are particularly sensitive to KDM5 inhibition. The results are confirmed in an appropriate in vivo model with a close structural analogue (KDM5-inh1A). In selected HER2-positive breast cancer cells, we demonstrate synergistic interactions between KDM5-inh1 and HER2-targeting agents (trastuzumab and lapatinib). In addition, HER2-positive cell lines showing innate/acquired resistance to trastuzumab show sensitivity to KDM5-inh1. The levels of KDM5A/B/C proteins, which are selectively targeted by the agent, have no significant association with KDM5-inh1 responsiveness across our panel of breast cancer cell lines, suggesting the existence of other determinants of sensitivity. Using RNA-sequencing data of the breast cancer cell lines, we generate a gene-expression model, consisting of fifteen genes, which is a robust predictor of KDM5-inh1 sensitivity. In a test set of breast cancers, this model correctly predicts sensitivity to the compound in a large fraction of HER2+ tumors. In conclusion, KDM5 inhibition has potential in the treatment of HER2+ breast cancer and our gene-expression model can be developed into a diagnostic tool to select patients who may benefit from treatments based on KDM5-inhibitors.
2019-02-01 | E-MTAB-7433 | biostudies-arrayexpress
Project description:<p>We have used a "chemistry first" approach to discover druggable acquired vulnerabilities that arised in the pathogenesis of non-small cell lung cancer (NSCLC). We screened chemical libraries (~200,000 compounds) for chemical toxins that killed subsets of NSCLC but not normal human lung epithelial cells (HBECs). We first screened a panel of 12 NSCLC lines that represented a variety of known oncogenotypes and identified chemicals with large Z scores and appropriate properties including re-supply, chemistry, and reproducible drug response phenotypes. This was then narrowed down to a list of 202 chemicals and 18 drugs with known targeting (henceforth called "Precision Oncology Probe Set", or POPS). These, and a panel of 30 clinically available drugs, targeted therapies, and drug combinations, already in use or in trials for NSCLC treatment, were then tested on a panel of 96 NSCLC lines for their drug response phenotypes in 12-point dose response curves. This information was analyzed using scanning ranked KS (Kolmogorov-Smirnov) and elastic net biostatistics approaches to identify molecular biomarkers (mutations, mRNA expression, copy number variation, protein expression, and metabolomics) which could predict for sensitivity or resistance to a particular chemical toxin or treatment regimen. From this we have discovered that: our approach identifies already known molecular biomarker of drug sensitivities (e.g. EGFR mutations and EGFR TK inhibitors); many clinically available chemotherapy agents have molecular biomarkers predicting preclinical model drug responses; the POP set of chemical toxins provides novel drug response phenotype patterns in the large NSCLC panel different from those found with clinically available agents including a therapeutic window; many of the POP toxins only hit a small percentage (~5%) of the NSCLC panel but the POP set as a whole provides "coverage" of the entire NSCLC panel; there are simple, one or 2 component molecular biomarkers (mutations, mRNA expression) that predict responses to the different chemical toxins in the NSCLC panel; and that the molecular biomarkers provide some information on the targets and pathways involved in response to the chemical toxins. Thus, we have identified a group of chemical toxins with selectivity for subsets of NSCLC and associated tumor molecular biomarkers to facilitate their development for precision medicine, and also, in some cases, information on the targets and pathways interdicted by these chemical compounds. In addition, we have discovered NSCLC predictive biomarkers for clinically available agents.</p>
| phs001823 | dbGaP
Project description:We invastigated the baseline transcriptomic profiles of a panel of B-cell lymphoma cell lines
2023-05-10 | GSE221770 | GEO
Project description:MS Analysis of genetic KO in a panel of HEK293A cell lines with genetic deletion
2023-03-04 | PXD030368 | Pride
Project description:Therapeutic targeting of BRAFV600E has shown a significant impact on progression-free and overall survival in advanced melanoma, but only a fraction of patients benefit from these treatments, suggesting that additional signaling pathways involved in melanoma growth/survival need to be identified. In fact MAPK and PI3K/mTOR signaling pathways are constituively activated in most cancers, including melanoma, to sustain the melanoma growth/survival. A large panel of melanoma were characterized for resistance/susceptibility to different inhibitors targeting MAPK and PI3K/mTOR signaling pathways and the synergistic effect of combinatorial treatments affecting both pathways. These effects were evaluated in terms of cell viability (MTT), apoptosis (Annexin V-PI), caspase 3/7 activity and subG1 cell fraction, highlighting a hierarchy in the combination effects. Further, a smaller panel of melanoma cell lines, were treated with inhibitors singularly and in combination to test the effects on the expression of principal proteins involved in these two pathways. Gene expression profile was performed to analyse the gene modulation induced by inhibitors to identify new strategies to fight melanoma resistance.
2016-12-31 | GSE59882 | GEO
Project description:Bacterial WGS validation panel
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Project description:- Background & Aims: Considering the escalating prevalence of metabolic dysfunction-associated steatotic liver disease (MASLD) and MASLD-related fibrosis, accurate non-invasive biomarkers for diagnosis and staging of fibrosis are urgently needed. This study Aims to develop a blood-based biomarker panel for fibrosis detection in individuals with MASLD. - Approach & Results: Using a translational diet-induced LDLr-/-.Leiden MASLD mouse model, candidate biomarkers were identified focused on the mechanism of collagen deposition, by integrating hepatic gene expression and new extracellular matrix deposition, as detected by dynamic D2O-labeling. To translate these findings to humans, gene expression profiles and biomarkers were analyzed in liver biopsies and serum samples from 67 individuals with histologically characterized MASLD and variable degrees of fibrosis. This led to the selection of three biomarkers for a blood-based fibrosis biomarker panel: IGFBP7, SSc5D and Sema4D. The accuracy of the biomarker panel was tested in a separate cohort of 128 individuals with histologically characterized MASLD across different stages of fibrosis. A Light Gradient Boosting Machine (LGBM) model was applied to predict fibrosis stage in MASLD (F0/F1: AUC = 0.90; F2: AUC = 0.91; F3/F4: AUC = 0.87). - Conclusion & Discussion: Using a translational Approach to identify collagen turnover related proteins indicative of fibrosis, we developed an accurate blood-based biomarker panel to detect and stage hepatic fibrosis in individuals with MASLD.
2024-05-17 | GSE240729 | GEO