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ZENODO
Dataset . 2023
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Data sources: Datacite
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ZENODO
Dataset . 2023
License: CC BY
Data sources: Datacite
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ZENODO
Dataset . 2023
License: CC BY
Data sources: ZENODO
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Trellis Single-Cell Screening Reveals Stromal Regulation of Patient-Derived Organoid Drug Responses

Authors: Zapatero Ramos, Maria; Tong, Alexander; Opzoomer, James W.; O'Sullivan, Rhianna; Cardoso Rodriguez, Ferran; Sufi, Jahangir; Vlckova, Petra; +6 Authors

Trellis Single-Cell Screening Reveals Stromal Regulation of Patient-Derived Organoid Drug Responses

Abstract

Patient-derived organoids (PDOs) can model personalized therapy responses, however current screening technologies cannot reveal drug response mechanisms or how tumor microenvironment cells alter therapeutic performance. To address this, we developed a highly-multiplexed mass cytometry platform to measure post translational modification (PTM) signaling, DNA-damage, cell-cycle activity, and apoptosis in >2,500 colorectal cancer (CRC) PDOs and cancer associated fibroblasts (CAFs) in response to clinical therapies at single-cell resolution. To compare patient- and microenvironment-specific drug responses in thousands of single-cell datasets, we developed Trellis — a highly-scalable, hierarchical tree-based treatment effect analysis method. Trellis single-cell screening revealed that on-target cell-cycle blockage and DNA-damage drug effects are common, even in chemorefractory PDOs. However, drug-induced apoptosis is rare, patient-specific, and aligns with cancer cell PTM signaling. We find that CAFs can regulate cancer cell plasticity — shifting proliferative stem cells to slow-cycling revival stem cells via YAP to protect cancer cells from chemotherapy. This repo contains the processed scRNA-seq Scanpy AnnData objects generated from the study. More information describing the data can be found at: https://github.com/TAPE-Lab/Ramos-et-al-Trellis

Keywords

cell plasticity, organoid, scRNA-seq, colorectal cancer, single-cell, tumour microenvironment

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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