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斑马鱼患者来源异种移植模型预测非小细胞肺癌的淋巴结侵犯和治疗结果。

Zebrafish patient-derived xenograft models predict lymph node involvement and treatment outcome in non-small cell lung cancer.

机构信息

BioReperia AB, Linköping, Sweden.

Pathology Department, Athens Chest Hospital "Sotiria", Athens, Greece.

出版信息

J Exp Clin Cancer Res. 2022 Feb 9;41(1):58. doi: 10.1186/s13046-022-02280-x.

DOI:10.1186/s13046-022-02280-x
PMID:35139880
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8827197/
Abstract

BACKGROUND

Accurate predictions of tumor dissemination risks and medical treatment outcomes are critical to personalize therapy. Patient-derived xenograft (PDX) models in mice have demonstrated high accuracy in predicting therapeutic outcomes, but methods for predicting tumor invasiveness and early stages of vascular/lymphatic dissemination are still lacking. Here we show that a zebrafish tumor xenograft (ZTX) platform based on implantation of PDX tissue fragments recapitulate both treatment outcome and tumor invasiveness/dissemination in patients, within an assay time of only 3 days.

METHODS

Using a panel of 39 non-small cell lung cancer PDX models, we developed a combined mouse-zebrafish PDX platform based on direct implantation of cryopreserved PDX tissue fragments into zebrafish embryos, without the need for pre-culturing or expansion. Clinical proof-of-principle was established by direct implantation of tumor samples from four patients.

RESULTS

The resulting ZTX models responded to Erlotinib and Paclitaxel, with similar potency as in mouse-PDX models and the patients themselves, and resistant tumors similarly failed to respond to these drugs in the ZTX system. Drug response was coupled to elevated expression of EGFR, Mdm2, Ptch1 and Tsc1 (Erlotinib), or Nras and Ptch1 (Paclitaxel) and reduced expression of Egfr, Erbb2 and Foxa (Paclitaxel). Importantly, ZTX models retained the invasive phenotypes of the tumors and predicted lymph node involvement of the patients with 91% sensitivity and 62% specificity, which was superior to clinically used tests. The biopsies from all four patient tested implanted successfully, and treatment outcome and dissemination were quantified for all patients in only 3 days.

CONCLUSIONS

We conclude that the ZTX platform provide a fast, accurate, and clinically relevant system for evaluation of treatment outcome and invasion/dissemination of PDX models, providing an attractive platform for combined mouse-zebrafish PDX trials and personalized medicine.

摘要

背景

准确预测肿瘤转移风险和治疗效果对于个体化治疗至关重要。在小鼠中建立的患者来源异种移植(PDX)模型已证明在预测治疗效果方面具有很高的准确性,但仍缺乏预测肿瘤侵袭性和早期血管/淋巴扩散的方法。在这里,我们展示了一种基于 PDX 组织片段植入的斑马鱼肿瘤异种移植(ZTX)平台,该平台在仅 3 天的测定时间内重现了患者的治疗效果和肿瘤侵袭性/扩散。

方法

我们使用了 39 个非小细胞肺癌 PDX 模型的小组,开发了一种基于直接将冷冻保存的 PDX 组织片段植入斑马鱼胚胎的小鼠-斑马鱼 PDX 联合平台,而无需预培养或扩增。通过直接植入来自 4 名患者的肿瘤样本,建立了临床验证的原理。

结果

由此产生的 ZTX 模型对厄洛替尼和紫杉醇有反应,其效力与小鼠-PDX 模型和患者本身相似,而耐药肿瘤在 ZTX 系统中同样无法对这些药物产生反应。药物反应与 EGFR、Mdm2、Ptch1 和 Tsc1(厄洛替尼)或 Nras 和 Ptch1(紫杉醇)的表达升高以及 Egfr、Erbb2 和 Foxa(紫杉醇)的表达降低相关。重要的是,ZTX 模型保留了肿瘤的侵袭表型,并以 91%的敏感性和 62%的特异性预测了患者的淋巴结受累,优于临床使用的测试。对所有 4 名患者进行的活检均成功植入,并且仅在 3 天内对所有患者进行了治疗效果和扩散的定量评估。

结论

我们得出结论,ZTX 平台为评估 PDX 模型的治疗效果和侵袭/扩散提供了一种快速、准确和临床相关的系统,为小鼠-斑马鱼 PDX 联合试验和个性化医学提供了一个有吸引力的平台。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2b20/8827197/2b4e45a2c34f/13046_2022_2280_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2b20/8827197/77fedd734c8a/13046_2022_2280_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2b20/8827197/fd4306b79dcd/13046_2022_2280_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2b20/8827197/642bcbb9c040/13046_2022_2280_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2b20/8827197/2fc83e1e2e85/13046_2022_2280_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2b20/8827197/e8abdcee3571/13046_2022_2280_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2b20/8827197/2b4e45a2c34f/13046_2022_2280_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2b20/8827197/77fedd734c8a/13046_2022_2280_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2b20/8827197/fd4306b79dcd/13046_2022_2280_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2b20/8827197/642bcbb9c040/13046_2022_2280_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2b20/8827197/2fc83e1e2e85/13046_2022_2280_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2b20/8827197/e8abdcee3571/13046_2022_2280_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2b20/8827197/2b4e45a2c34f/13046_2022_2280_Fig6_HTML.jpg

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