Expression of the Bcl-2 protein BAD promotes prostate cancer growth.

Expression of the Bcl-2 protein BAD promotes prostate cancer growth.
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DOI:
10.1371/journal.pone.0006224
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发表时间:
2009-07-13
期刊:
影响因子:
3.7
通讯作者:
Kulik G
Kulik G
中科院分区:
综合性期刊3区
文献类型:
--
作者:
Smith AJ;Karpova Y;D'Agostino R Jr;Willingham M;Kulik G

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BAD是Bcl - 2家族的一种促凋亡蛋白,最近被确定为前列腺癌细胞中几种抗凋亡信号通路的整合因子。因此,表皮生长因子受体(EGFR)、G蛋白偶联受体(GPCRs)或磷脂酰肌醇 - 3 - 激酶(PI3K)通路的激活会导致BAD磷酸化并抑制细胞凋亡。也有报道称前列腺癌中BAD水平升高。前列腺癌细胞不是限制促凋亡蛋白的表达,而是选择提高BAD水平同时使其处于严格的磷酸化控制之下,这似乎是矛盾的。对BAD对前列腺癌异种移植物影响的分析表明,BAD表达增加会促进肿瘤生长,而通过短发夹RNA(shRNA)敲低BAD表达则会抑制肿瘤生长。组织培养实验证明,BAD表达增加会刺激前列腺癌细胞的增殖。这些结果表明,BAD表达增加为前列腺肿瘤提供了增殖优势,而BAD去磷酸化会增加前列腺癌细胞对凋亡的敏感性。增殖和凋亡特性的结合促使前列腺癌细胞“依赖”于磷酸化BAD水平的升高。因此,使BAD磷酸化的激酶是合理的治疗靶点;同时监测BAD磷酸化可用于预测肿瘤对治疗的反应。
BAD, a pro-apoptotic protein of the Bcl-2 family, has recently been identified as an integrator of several anti-apoptotic signaling pathways in prostate cancer cells. Thus, activation of EGFR, GPCRs or PI3K pathway leads to BAD phosphorylation and inhibition of apoptosis. Increased levels of BAD in prostate carcinomas have also been reported. It appears contradictory that instead of limiting expression of pro-apoptotic protein, prostate cancer cells choose to increase BAD levels while keeping it under tight phosphorylation control. Analysis of the effect of BAD on prostate cancer xenografts has shown that increased BAD expression enhances tumor growth, while knockdown of BAD expression by shRNA inhibits tumor growth. Tissue culture experiments demonstrated that increased BAD expression stimulates proliferation of prostate cancer cells. These results suggest that increased expression of BAD provides a proliferative advantage to prostate tumors, while BAD dephosphorylation increases sensitivity of prostate cancer cells to apoptosis. Combination of proliferative and apoptotic properties prompts prostate cancer cells to be “addicted” to increased levels of phosphorylated BAD. Thus, kinases that phosphorylate BAD are plausible therapeutic targets; while monitoring BAD phosphorylation could be used to predict tumor response to treatments.
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