Characterization of anticancer drug resistance by reverse-phase protein array: new targets and strategies.
Characterization of anticancer drug resistance by reverse-phase protein array: new targets and strategies.
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通过反相蛋白阵列表征抗癌药物耐药性：新靶点和策略。
DOI：
10.1080/14789450.2022.2070065
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发表时间：
2022-03
影响因子：
3.4
通讯作者：
Mills, Gordon B.
中科院分区：
文献类型：
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作者：
Cathcart, Ann M.;Smith, Hannah;Labrie, Marilyne;Mills, Gordon B.
关键词：
耐药性是通过药物治疗实现癌症治愈的主要障碍。癌症耐药的发生部分是由于肿瘤和微环境在蛋白质组水平上对治疗应激的适应。反相蛋白阵列（RPPA）由于其高样品通量、对磷酸化蛋白的灵敏检测以及对大量关键细胞途径的验证，非常适合于耐药性的蛋白质组学分析。本文综述了RPPA在认识和抗击耐药性方面的贡献。特别是，RPPA对了解PARP抑制剂、BRAF抑制剂、免疫检查点抑制剂和乳腺癌研究性治疗的耐药性的贡献进行了讨论。通过MEDLINE、Scopus和Cochrane检索关键词“蛋白质组学”、“逆相蛋白阵列”、“耐药性”、“PARP抑制剂”、“BRAF抑制剂”、“免疫检查点抑制剂”和“I-SPY”，检索时间跨度为1960年10月1日至2021年10月1日。迄今为止，精确肿瘤学未能将靶向治疗的武器转化为大多数患者的持久反应，这突出表明仅靠基因测序不足以指导治疗选择和克服耐药性。结合基因组学和蛋白质组学分析，结合创造性的药物组合和给药策略，有望使成熟的精确肿瘤学进入一个改善患者预后的时代。
Drug resistance is the main barrier to achieving cancer cures with medical therapy. Cancer drug resistance occurs, in part, due to adaptation of the tumor and microenvironment to therapeutic stress at a proteomic level. Reverse-phase protein arrays (RPPA) are well-suited to proteomic analysis of drug resistance due to high sample throughput, sensitive detection of phosphoproteins, and validation for a large number of critical cellular pathways. This review summarizes contributions of RPPA to understanding and combating drug resistance. In particular, contributions of RPPA to understanding resistance to PARP inhibitors, BRAF inhibitors, immune checkpoint inhibitors, and breast cancer investigational therapies are discussed. Articles reviewed were identified by MEDLINE, Scopus, and Cochrane search for keywords “proteomics,” “reverse-phase protein array,” “drug resistance,” “PARP inhibitor,” “BRAF inhibitor,” “immune checkpoint inhibitor,” and “I-SPY” spanning October 1 1960 – October 1 2021. Precision oncology has thus far failed to convert the armament of targeted therapies into durable responses for most patients, highlighting that genetic sequencing alone is insufficient to guide therapy selection and overcome drug resistance. Combined genomic and proteomic analyses paired with creative drug combinations and dosing strategies hold promise for maturing precision oncology into an era of improved patient outcomes.
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关于癌症基因组地图集的泛伴奏蛋白质组学观点。
影响因子：
16.6
作者：
Akbani, Rehan;Ng, Patrick Kwok Shing;Werner, Henrica M. J.;Shahmoradgoli, Maria;Zhang, Fan;Ju, Zhenlin;Liu, Wenbin;Yang, Ji-Yeon;Yoshihara, Kosuke;Li, Jun;Ling, Shiyun;Seviour, Elena G.;Ram, Prahlad T.;Minna, John D.;Diao, Lixia;Tong, Pan;Heymach, John V.;Hill, Steven M.;Dondelinger, Frank;Stadler, Nicolas;Byers, Lauren A.;Meric-Bernstam, Funda;Weinstein, John N.;Broom, Bradley M.;Verhaak, Roeland G. W.;Liang, Han;Mukherjee, Sach;Lu, Yiling;Mills, Gordon B.
通讯作者：
Mills, Gordon B.
影响因子：
9.3
作者：
Oliveira ÉA;Chauhan J;Silva JRD;Carvalho LADC;Dias D;Carvalho DG;Watanabe LRM;Rebecca VW;Mills G;Lu Y;da Silva ASF;Consolaro MEL;Herlyn M;Possik PA;Goding CR;Maria-Engler SS
通讯作者：
Maria-Engler SS
影响因子：
5.2
作者：
De Koning, Leanne;Decaudin, Didier;Nemati, Fariba
通讯作者：
Nemati, Fariba
影响因子：
28.2
作者：
Abdel-Wahab O;Klimek VM;Gaskell AA;Viale A;Cheng D;Kim E;Rampal R;Bluth M;Harding JJ;Callahan MK;Merghoub T;Berger MF;Solit DB;Rosen N;Levine RL;Chapman PB
通讯作者：
Chapman PB
影响因子：
64.8
作者：
通讯作者：
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