Towards targeting of shared mechanisms of cancer metastasis and therapy resistance.
Towards targeting of shared mechanisms of cancer metastasis and therapy resistance.
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DOI：
10.1038/s41568-021-00427-0
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发表时间：
2022-03
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对治疗性治疗的抗性和转移性进展共同决定了癌症的致死性结局。传统上，癌症转移和治疗耐药性作为使用非重叠策略的单独领域进行研究。然而，新出现的证据，包括从体内成像和体外器官型培养，现在表明，这两个方案合作，并加强彼此的入侵生态位，并坚持转移逃避。因此，表现出转移性侵袭的癌细胞亚群经历多步重编程，其-除了迁移信号传导-支持修复程序、抗凋亡过程、代谢适应、干性和存活。共享的转移和治疗抗性信号传导由多种机制介导，例如整合素和其他背景受体的接合、细胞-细胞通信、应激反应和代谢重编程，其与活化的肿瘤微环境中存在的自分泌和旁分泌趋化因子和生长因子线索引起的效应协同作用。这些信号使转移细胞能够科普治疗攻击并存活。识别在转移和治疗抗性信号网络中共享的节点应该提供新的机会，以改善现有策略之外的抗癌治疗，以消除结节性病变和转移转运中的细胞。
Resistance to therapeutic treatment and metastatic progression jointly determine a fatal outcome of cancer. Cancer metastasis and therapeutic resistance are traditionally studied as separate fields using non-overlapping strategies. However, emerging evidence, including from in vivo imaging and in vitro organotypic culture, now suggests that both programmes cooperate and reinforce each other in the invasion niche and persist upon metastatic evasion. As a consequence, cancer cell subpopulations exhibiting metastatic invasion undergo multistep reprogramming that — beyond migration signalling — supports repair programmes, anti-apoptosis processes, metabolic adaptation, stemness and survival. Shared metastasis and therapy resistance signalling are mediated by multiple mechanisms, such as engagement of integrins and other context receptors, cell–cell communication, stress responses and metabolic reprogramming, which cooperate with effects elicited by autocrine and paracrine chemokine and growth factor cues present in the activated tumour microenvironment. These signals empower metastatic cells to cope with therapeutic assault and survive. Identifying nodes shared in metastasis and therapy resistance signalling networks should offer new opportunities to improve anticancer therapy beyond current strategies, to eliminate both nodular lesions and cells in metastatic transit.
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影响因子：
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作者：
Blockhuys S;Liu N;Agarwal NR;Enejder A;Loitto V;Sun XF
通讯作者：
Sun XF
影响因子：
9.3
作者：
Brubaker, Douglas K.;Paulo, Joao A.;Haigis, Kevin M.
通讯作者：
Haigis, Kevin M.
影响因子：
6.4
作者：
Brozovic, A;Fritz, G;Kaina, B
通讯作者：
Kaina, B
影响因子：
7.3
作者：
Bronsert, P.;Enderle-Ammour, K.;Wellner, U. F.
通讯作者：
Wellner, U. F.
影响因子：
6.2
作者：
Bierbaumer L;Katschnig AM;Radic-Sarikas B;Kauer MO;Petro JA;Högler S;Gurnhofer E;Pedot G;Schäfer BW;Schwentner R;Mühlbacher K;Kromp F;Aryee DNT;Kenner L;Uren A;Kovar H
通讯作者：
Kovar H