Patient derived organoids to model rare prostate cancer phenotypes.
Patient derived organoids to model rare prostate cancer phenotypes.
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患者衍生的类器官为罕见的前列腺癌表型建模。
DOI:
10.1038/s41467-018-04495-z
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发表时间:
2018-06-19
影响因子:
16.6
通讯作者:
Beltran H
中科院分区:
文献类型:
--
作者:
Puca L;Bareja R;Prandi D;Shaw R;Benelli M;Karthaus WR;Hess J;Sigouros M;Donoghue A;Kossai M;Gao D;Cyrta J;Sailer V;Vosoughi A;Pauli C;Churakova Y;Cheung C;Deonarine LD;McNary TJ;Rosati R;Tagawa ST;Nanus DM;Mosquera JM;Sawyers CL;Chen Y;Inghirami G;Rao RA;Grandori C;Elemento O;Sboner A;Demichelis F;Rubin MA;Beltran H
A major hurdle in the study of rare tumors is a lack of existing preclinical models. Neuroendocrine prostate cancer is an uncommon and aggressive histologic variant of prostate cancer that may arise de novo or as a mechanism of treatment resistance in patients with pre-existing castration-resistant prostate cancer. There are few available models to study neuroendocrine prostate cancer. Here, we report the generation and characterization of tumor organoids derived from needle biopsies of metastatic lesions from four patients. We demonstrate genomic, transcriptomic, and epigenomic concordance between organoids and their corresponding patient tumors. We utilize these organoids to understand the biologic role of the epigenetic modifier EZH2 in driving molecular programs associated with neuroendocrine prostate cancer progression. High-throughput organoid drug screening nominated single agents and drug combinations suggesting repurposing opportunities. This proof of principle study represents a strategy for the study of rare cancer phenotypes. There are few available models to study neuroendocrine prostate cancer. Here they develop and characterize patient derived organoids from metastatic lesions, use these models to show the role of EZH2 in driving neuroendocrine phenotype, and perform high throughput organoid screening to identify therapeutic drug combinations.
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影响因子:
82.9
作者:
Beltran H;Prandi D;Mosquera JM;Benelli M;Puca L;Cyrta J;Marotz C;Giannopoulou E;Chakravarthi BV;Varambally S;Tomlins SA;Nanus DM;Tagawa ST;Van Allen EM;Elemento O;Sboner A;Garraway LA;Rubin MA;Demichelis F
通讯作者:
Demichelis F
影响因子:
64.5
作者:
Karthaus WR;Iaquinta PJ;Drost J;Gracanin A;van Boxtel R;Wongvipat J;Dowling CM;Gao D;Begthel H;Sachs N;Vries RGJ;Cuppen E;Chen Y;Sawyers CL;Clevers HC
通讯作者:
Clevers HC
影响因子:
64.5
作者:
Gao D;Vela I;Sboner A;Iaquinta PJ;Karthaus WR;Gopalan A;Dowling C;Wanjala JN;Undvall EA;Arora VK;Wongvipat J;Kossai M;Ramazanoglu S;Barboza LP;Di W;Cao Z;Zhang QF;Sirota I;Ran L;MacDonald TY;Beltran H;Mosquera JM;Touijer KA;Scardino PT;Laudone VP;Curtis KR;Rathkopf DE;Morris MJ;Danila DC;Slovin SF;Solomon SB;Eastham JA;Chi P;Carver B;Rubin MA;Scher HI;Clevers H;Sawyers CL;Chen Y
通讯作者:
Chen Y
影响因子:
5.7
作者:
Clermont PL;Lin D;Crea F;Wu R;Xue H;Wang Y;Thu KL;Lam WL;Collins CC;Wang Y;Helgason CD
通讯作者:
Helgason CD
影响因子:
14.8
作者:
Drost J;Karthaus WR;Gao D;Driehuis E;Sawyers CL;Chen Y;Clevers H
通讯作者:
Clevers H