Patient-derived Models Reveal Impact of the Tumor Microenvironment on Therapeutic Response.
Patient-derived Models Reveal Impact of the Tumor Microenvironment on Therapeutic Response.
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DOI：
10.1016/j.euo.2018.04.019
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发表时间：
2018-09
影响因子：
8.2
通讯作者：
Knudsen KE
中科院分区：
文献类型：
--
作者：
Shafi AA;Schiewer MJ;de Leeuw R;Dylgjeri E;McCue PA;Shah N;Gomella LG;Lallas CD;Trabulsi EJ;Centenera MM;Hickey TE;Butler LM;Raj G;Tilley WD;Cukierman E;Knudsen KE
雄激素剥夺疗法是播散性前列腺癌（PCa）的一线治疗方法。然而，几乎所有肿瘤都会产生耐药性，并以去势抵抗性 PCa 的形式复发，而这种疾病没有持久的治愈方法。开发更有效疗法的一个主要障碍是缺乏充分概括 PCa 异质性的临床前模型，这严重阻碍了准确预测治疗反应的能力。利用称为患者衍生外植体 (PDE) 的离体培养方法来检查 PCa 治疗对每个患者的影响。将接受根治性前列腺切除术的患者的新鲜 PCa 组织培养为 PDE，以检查治疗反应。使用各种参数（例如 AR 水平、Ki67 染色和促纤维增生指数）评估 PDE 中基因组和化学扰动的影响。 PDE 保持了天然肿瘤微环境 (TME)、肿瘤组织形态、活力和内源激素信号传导的完整性。该模型系统中的肿瘤细胞表现出从头增殖能力。对 PDE 中天然 TME 的检查揭示了对患者特异性促纤维增生基质指数的首次现场洞察，并预测了对 AR 导向治疗的反应。 PDE 模型可以对单个肿瘤在其原生 TME 中进行全面评估，最终开发出更有效的针对个体的治疗方案。新型基质标志物的识别可能为应用精准医学治疗晚期 PCa 提供基础，这将对患者的治疗结果产生变革性的影响。在这项研究中，使用了一种创新的模型系统来更有效地模拟人类疾病。患者来源的外植体（PDE）系统可用于预测治疗反应并识别晚期疾病的新靶标。因此，PDE 将成为开发在前列腺癌中实施精准医疗的新指标的资产。患者来源的外植体（PDE）模型可以对单个人类肿瘤在其天然肿瘤微环境（TME）中进行综合评估。 TME 分析揭示了通过评估患者特异性促纤维增生基质指数来预测肿瘤对 AR 导向治疗的反应性的首次现场洞察。
Androgen deprivation therapy is a first-line treatment for disseminated prostate cancer (PCa). However, virtually all tumors become resistant and recur as castration-resistant PCa, which has no durable cure. One major hurdle in the development of more effective therapies is the lack of preclinical models that adequately recapitulate the heterogeneity of PCa, significantly hindering the ability to accurately predict therapeutic response. To leverage the ex vivo culture method termed patient-derived explant (PDE) to examine the impact of PCa therapeutics on a patient-by-patient basis. Fresh PCa tissue from patients who underwent radical prostatectomy was cultured as PDEs to examine therapeutic response. The impact of genomic and chemical perturbations in PDEs was assessed using various parameters (eg, AR levels, Ki67 staining, and desmoplastic indices). PDE maintained the integrity of the native tumor microenvironment (TME), tumor tissue morphology, viability, and endogenous hormone signaling. Tumor cells in this model system exhibited de novo proliferative capacity. Examination of the native TME in the PDE revealed a first-in-field insight into patient-specific desmoplastic stromal indices and predicted responsiveness to AR-directed therapeutics. The PDE model allows for a comprehensive evaluation of individual tumors in their native TME to ultimately develop more effective therapeutic regimens tailored to individuals. Discernment of novel stromal markers may provide a basis for applying precision medicine in treating advanced PCa, which would have a transformative effect on patient outcomes. In this study, an innovative model system was used to more effectively mimic human disease. The patient-derived explant (PDE) system can be used to predict therapeutic response and identify novel targets in advanced disease. Thus, the PDE will be an asset for the development of novel metrics for the implementation of precision medicine in prostate cancer. The patient-derived explant (PDE) model allows for a comprehensive evaluation of individual human tumors in their native tumor microenvironment (TME). TME analysis revealed first-in-field insight into predicted tumor responsiveness to AR-directed therapeutics through evaluation of patient-specific desmoplastic stromal indices.
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DOI：
10.1158/1078-0432.ccr-08-2660
发表时间：
2009-08-01
期刊：
Clinical cancer research : an official journal of the American Association for Cancer Research
影响因子：
--
作者：
Knudsen KE;Scher HI
通讯作者：
Scher HI
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：
14.8
作者：
Drost J;Karthaus WR;Gao D;Driehuis E;Sawyers CL;Chen Y;Clevers H
通讯作者：
Clevers H
影响因子：
14
作者：
Fong EL;Wan X;Yang J;Morgado M;Mikos AG;Harrington DA;Navone NM;Farach-Carson MC
通讯作者：
Farach-Carson MC
影响因子：
7.5
作者：
Alexander, Jennifer;Cukierman, Edna
通讯作者：
Cukierman, Edna