Drug combination sci-Plex Data
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA851906 | ENA |
REPOSITORIES: ENA
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Project description:Recent advances in multiplexed single-cell transcriptomics experiments are facilitating the high-throughput study of drug and genetic perturbations. However, an exhaustive exploration of the combinatorial perturbation space is experimentally unfeasible, so computational methods are needed to predict, interpret, and prioritize perturbations. Here, we present the compositional perturbation autoencoder (CPA), which combines the interpretability of linear models with the flexibility of deep-learning approaches for single-cell response modeling. CPA encodes and learns transcriptional drug responses across different cell type, dose, and drug combinations. The model produces easy-to-interpret embeddings for drugs and cell types, which enables drug similarity analysis and predictions for unseen dosage and drug combinations. We show that CPA accurately models single-cell perturbations across compounds, doses, species, and time. We further demonstrate that CPA predicts combinatorial genetic interactions of several types, implying that it captures features that distinguish different interaction programs. Finally, we demonstrate that CPA can generate in-silico 5,329 missing genetic combination perturbations ($97.6% of all possibilities) with diverse genetic interactions. We envision our model will facilitate efficient experimental design and hypothesis generation by enabling in-silico response prediction at the single-cell level, and thus accelerate therapeutic applications using single-cell technologies.
2022-06-25 | GSE206741 | GEO
Project description:Sci-Space E14 Mouse Embryo Data
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Project description:With a critical need for more complete in vitro models of human development and disease, organoids hold immense potential. Their complex cellular composition makes single-cell sequencing of great utility; however, the limitation of current technologies to a handful of treatment conditions restricts their use in screens or studies of organoid heterogeneity. Here, we apply sci-Plex, a single-cell combinatorial indexing (sci)-based RNA-seq multiplexing method to retinal organoids. We demonstrate that sci-Plex and 10x methods produce highly concordant cell type compositions and then expand sci-Plex to analyze the cell type composition of 410 organoids upon modulation of critical developmental pathways. Leveraging individual organoid data, we develop a method to measure organoid heterogeneity, and we identify that activation of Wnt signaling early in retinal organoid cultures increases retinal cell types up to six weeks later. Our data show sci-Plex’s potential to dramatically scale-up the analysis of treatment conditions on relevant human models.
2022-12-14 | GSE220661 | GEO
Project description:Spatial patterns of gene expression span many scales, and are shaped by both local (e.g. cell-cell interactions) and global (e.g. tissue, organ) context. However, most in situ methods for profiling gene expression either average local contexts or are restricted to limited fields of view. Here we introduce sci-Space, a scale-flexible method that retains single cell resolution while resolving spatial heterogeneity in gene expression at larger scales. As a proof-of-concept, we apply sci-Space to the developing mouse embryo (E14), capturing the approximate spatial coordinates of profiled cells from whole embryo serial sections.
2021-07-01 | GSE166692 | GEO
Project description:Drug Combination Signatures for Prediction and Mitigation of Toxicity
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Project description:Drug Combination Signatures for Prediction and Mitigation of Toxicity.
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Project description:Drug Matrix Data - Affymetrix Arrays
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Project description:We asked what genes are significantly differentially regulated in the spinal cord of SCI trkB.T1 WT and trkB.T1 KO mice. TrkB.T1 is upregulated shortly after SCI although the precise mechanisms underyling this upregulation are poorly understood. In the trkB.T1 null, we show less mechanical allodynia and better locomotor recovery following SCI. The microarray studies helped us to elucidate a signaling pathway that is differently regulated in the WT versus KO mice at 1 day after SCI. In this study, we did not examine gene changes within a genotype after SCI. Rather, we examined DGE by genotype at each time point. Spinal cord tissue from WT and KO mice in a sham condition (intact spinal cord) versus 1D, 3D and 7D following SCI was harvested for microarray analyses.
2015-12-07 | E-GEOD-42828 | biostudies-arrayexpress
Project description:Drug tolerant persister cells of EGFR-mutant PC9 cell lines surviving treatment with kinase inhibitor combination. Cells were treated with combination of erlotinib, osimertinib, trametinib and dasatinib and surviving cells were harvested for RNA extraction. 3' UTR RNA-seq profiles were compared to parental control cells and to outgrowing cells after treatment had been removed
2023-06-30 | E-MTAB-13045 | biostudies-arrayexpress
Project description:Breast cancer is the most common cancer that threatens women's health. While the strategy of drug combination can help to reduce adverse effects and to overcome the resistance of clinical treatment of single drug. In this work, we report the synergetic effect between a HSP90 inhibitor 17-AAG and a HDAC inhibitor Belinostat, on the triple-negative breast cancer MDA-MB-231 cells. The RNA-Seq data analysis showed that the most over-represented KEGG pathways in the combination group came from migration or invasion related genes, which were not observed in the differentially expressed genes after the treatment of 17-AAG or Belinostat alone.
2019-05-17 | GSE129944 | GEO