A protein interaction landscape of breast cancer.
A protein interaction landscape of breast cancer.
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DOI：
10.1126/science.abf3066
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发表时间：
2021-10
期刊：
影响因子：
56.9
通讯作者：
Krogan, Nevan J.
中科院分区：
文献类型：
--
作者：
Kim, Minkyu;Park, Jisoo;Bouhaddou, Mehdi;Kim, Kyumin;Rojc, Ajda;Modak, Maya;Soucheray, Margaret;McGregor, Michael J.;O'Leary, Patrick;Wolf, Denise;Stevenson, Erica;Foo, Tzeh Keong;Mitchell, Dominique;Herrington, Kari A.;Munoz, Denise P.;Tutuncuoglu, Beril;Chen, Kuei-Ho;Zheng, Fan;Kreisberg, Jason F.;Diolaiti, Morgan E.;Gordan, John D.;Coppe, Jean-Philippe;Swaney, Danielle L.;Xia, Bing;van 't Veer, Laura;Ashworth, Alan;Ideker, Trey;Krogan, Nevan J.
癌症与多种多样的基因组改变有关。为了帮助机械地理解乳腺浸润癌中的这种改变，我们应用亲和纯化质谱来描绘40种经常改变的乳腺癌（BC）蛋白质的全面生物物理相互作用网络，有和没有相关突变，在三个人乳腺细胞系中。这些网络识别癌症特异性蛋白质-蛋白质相互作用（PPI），互连和富集常见和罕见的癌症突变，并通过引入关键BC突变而基本上重新连接。我们的分析鉴定了抑制AKT信号传导的PIK 3CA相互作用蛋白，并发现USP 28和UBE 2N是BRCA 1的功能相关相互作用物。我们还表明，PP 1磷酸酶调节亚基，Spinophilin，相互作用，并调节BRCA 1的去磷酸化，以促进DNA双链断裂修复。因此，PPI景观为机械解释疾病基因组数据提供了一个强大的框架，并可以识别有价值的新治疗靶点。乳腺癌基因的大规模蛋白质相互作用图谱提供了一个框架，以识别以前未识别的致癌驱动程序。
Cancers have been associated with a diverse array of genomic alterations. To help mechanistically understand such alterations in breast invasive carcinoma, we have applied affinity-purification mass spectrometry to delineate comprehensive biophysical interaction networks for 40 frequently altered breast cancer (BC) proteins, with and without relevant mutations, across three human breast cell lines. These networks identify cancer-specific protein-protein interactions (PPIs), interconnect and enrich for common and rare cancer mutations, and are substantially rewired by the introduction of key BC mutations. Our analysis identified PIK3CA-interacting proteins which repress AKT signaling and has uncovered USP28 and UBE2N as functionally relevant interactors of BRCA1. We also show that the PP1 phosphatase regulatory subunit, Spinophilin, interacts with and regulates dephosphorylation of BRCA1 to promote DNA double-strand break repair. Thus, PPI landscapes provide a powerful framework for mechanistically interpreting disease genomic data and can identify valuable new therapeutic targets. Large-scale protein interaction maps of breast cancer genes provide a framework to recognize previously unidentified oncogenic drivers.
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影响因子：
64.5
作者：
Bassermann, Florian;Frescas, David;Guardavaccaro, Daniele;Busino, Luca;Peschiaroli, Angelo;Pagano, Michele
通讯作者：
Pagano, Michele
影响因子：
56.9
作者：
Cortez, D;Wang, Y;Elledge, SJ
通讯作者：
Elledge, SJ
影响因子：
12.3
作者：
Cho A;Shim JE;Kim E;Supek F;Lehner B;Lee I
通讯作者：
Lee I
影响因子：
--
作者：
Beckta, Jason M.;Dever, Seth M.;Valerie, Kristoffer
通讯作者：
Valerie, Kristoffer
影响因子：
3.8
作者：
Aihara, T;Fujiwara, Y;Monden, M
通讯作者：
Monden, M