Trellis Single-Cell Screening Reveals Stromal Regulation of Patient-Derived Organoid Drug Responses
Trellis Single-Cell Screening Reveals Stromal Regulation of Patient-Derived Organoid Drug Responses
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网格单细胞筛选揭示了患者源性类器官药物反应的基质调节
DOI:
10.1101/2022.10.19.512668
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发表时间:
2022
期刊:
影响因子:
--
通讯作者:
Zapatero M
中科院分区:
文献类型:
--
作者:
Zapatero M
Patient-derived organoids (PDOs) can model personalized therapy responses, however current screening technologies cannot reveal drug response mechanisms or study 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 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 developedTrellis— 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 patient-specific. We found drug-induced apoptosis does not correlate with genotype or clinical staging but does align with cell-intrinsic PTM signaling in PDOs. CAFs protect chemosensitive PDOs by shifting cancer cells into a slow-cycling cell-state and CAF chemoprotection can be reversed by inhibiting YAP.Highlights>2,500 single-cell PTM signaling, DNA-damage, cell-cycle, and apoptosis responses from drug-treated PDOs and CAFs.Trellis: hierarchical tree-based treatment effect method for single-cell screening analysis.PDOs have patient-specific drug responses that align with cell-intrinsic PTM signaling states.CAFs chemoprotect PDOs by altering PDO cell-state via YAP signaling.
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影响因子:
28.2
作者:
Pauli C;Hopkins BD;Prandi D;Shaw R;Fedrizzi T;Sboner A;Sailer V;Augello M;Puca L;Rosati R;McNary TJ;Churakova Y;Cheung C;Triscott J;Pisapia D;Rao R;Mosquera JM;Robinson B;Faltas BM;Emerling BE;Gadi VK;Bernard B;Elemento O;Beltran H;Demichelis F;Kemp CJ;Grandori C;Cantley LC;Rubin MA
通讯作者:
Rubin MA
影响因子:
28.2
作者:
Tiriac H;Belleau P;Engle DD;Plenker D;Deschênes A;Somerville TDD;Froeling FEM;Burkhart RA;Denroche RE;Jang GH;Miyabayashi K;Young CM;Patel H;Ma M;LaComb JF;Palmaira RLD;Javed AA;Huynh JC;Johnson M;Arora K;Robine N;Shah M;Sanghvi R;Goetz AB;Lowder CY;Martello L;Driehuis E;LeComte N;Askan G;Iacobuzio-Donahue CA;Clevers H;Wood LD;Hruban RH;Thompson E;Aguirre AJ;Wolpin BM;Sasson A;Kim J;Wu M;Bucobo JC;Allen P;Sejpal DV;Nealon W;Sullivan JD;Winter JM;Gimotty PA;Grem JL;DiMaio DJ;Buscaglia JM;Grandgenett PM;Brody JR;Hollingsworth MA;O'Kane GM;Notta F;Kim E;Crawford JM;Devoe C;Ocean A;Wolfgang CL;Yu KH;Li E;Vakoc CR;Hubert B;Fischer SE;Wilson JM;Moffitt R;Knox J;Krasnitz A;Gallinger S;Tuveson DA
通讯作者:
Tuveson DA
影响因子:
46.9
作者:
Moon, Kevin R.;van Dijk, David;Krishnaswamy, Smita
通讯作者:
Krishnaswamy, Smita
影响因子:
78.5
作者:
Sahai, Erik;Astsaturov, Igor;Werb, Zena
通讯作者:
Werb, Zena
影响因子:
50.3
作者:
Letai A;Bhola P;Welm AL
通讯作者:
Welm AL