Charting oncogenicity of genes and variants across lineages via multiplexed screens in teratomas.
Charting oncogenicity of genes and variants across lineages via multiplexed screens in teratomas.
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DOI:
10.1016/j.isci.2021.103149
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发表时间:
2021-10-22
期刊:
影响因子:
5.8
通讯作者:
Mali P
中科院分区:
文献类型:
--
作者:
Parekh U;McDonald D;Dailamy A;Wu Y;Cordes T;Zhang K;Tipps A;Metallo C;Mali P
Deconstructing tissue-specific effects of genes and variants on proliferation is critical to understanding cellular transformation and systematically selecting cancer therapeutics. This requires scalable methods for multiplexed genetic screens tracking fitness across time, across lineages, and in a suitable niche, since physiological cues influence functional differences. Towards this, we present an approach, coupling single-cell cancer driver screens in teratomas with hit enrichment by serial teratoma reinjection, to simultaneously screen drivers across multiple lineages in vivo. Using this system, we analyzed population shifts and lineage-specific enrichment for 51 cancer associated genes and variants, profiling over 100,000 cells spanning over 20 lineages, across two rounds of serial reinjection. We confirmed that c-MYC alone or combined with myristoylated AKT1 potently drives proliferation in progenitor neural lineages, demonstrating signatures of malignancy. Additionally, mutant MEK1S218D/S222D provides a proliferative advantage in mesenchymal lineages like fibroblasts. Our method provides a powerful platform for multi-lineage longitudinal study of oncogenesis. Developed multiplex in vivo screens of cancer driver genes across multiple lineages Couples teratoma differentiation, scRNA-seq readout and tumor serial injection c-MYC alone or with myristoylated AKT1 drives neural progenitor proliferation Mutant MEK1S218D/S222D enhances fitness of mesenchymal lineages like fibroblasts Molecular biology; Systems biology; Transcriptomics
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影响因子:
--
作者:
Barfeld SJ;Fazli L;Persson M;Marjavaara L;Urbanucci A;Kaukoniemi KM;Rennie PS;Ceder Y;Chabes A;Visakorpi T;Mills IG
通讯作者:
Mills IG
影响因子:
64.8
作者:
通讯作者:
--
影响因子:
48
作者:
Bian S;Repic M;Guo Z;Kavirayani A;Burkard T;Bagley JA;Krauditsch C;Knoblich JA
通讯作者:
Knoblich JA
DOI:
10.1126/science.aao3130
发表时间:
2017-10-13
期刊:
Science (New York, N.Y.)
影响因子:
--
作者:
Drost J;van Boxtel R;Blokzijl F;Mizutani T;Sasaki N;Sasselli V;de Ligt J;Behjati S;Grolleman JE;van Wezel T;Nik-Zainal S;Kuiper RP;Cuppen E;Clevers H
通讯作者:
Clevers H
DOI:
10.1007/978-1-4939-9236-2_14
发表时间:
2019-01-01
期刊:
HIGH-THROUGHPUT METABOLOMICS: METHODS AND PROTOCOLS
影响因子:
--
作者:
Cordes, Thekla;Metallo, Christian M.
通讯作者:
Metallo, Christian M.