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PDX-derived organoids model in vivo drug response and secrete biomarkers. ​

文献信息 ​

PMID32990680
期刊JCI insight
影响因子6.1
JCR 分区Q1
发表年份2020
被引次数67
关键词癌症, 糖生物学, 肿瘤学
文献类型Journal Article, Research Support, N.I.H., Extramural, Research Support, Non-U.S. Gov't
ISSN2379-3708
期号5(21)
作者Ling Huang, Bruno Bockorny, Indranil Paul, Dipikaa Akshinthala, Pierre-Oliver Frappart, Omar Gandarilla, Arindam Bose, Veronica Sanchez-Gonzalez, Emily E Rouse, Sylvain D Lehoux, Nicole Pandell, Christine M Lim, John G Clohessy, Joseph Grossman, Raul Gonzalez, Sofia Perea Del Pino, George Daaboul, Mandeep S Sawhney, Steven D Freedman, Alexander Kleger, Richard D Cummings, Andrew Emili, Lakshmi B Muthuswamy, Manuel Hidalgo, Senthil K Muthuswamy

一句话小结 ​

本研究系统分析了在无WNT培养条件下生长的胰腺导管腺癌类器官的药物反应及其与体内肿瘤生长的关系，发现了潜在的循环生物标志物，尤其是四种细胞外小泡蛋白可用于PDAC的诊断。此研究展示了患者来源类器官模型在药物反应模拟和临床生物标志物发现中的重要应用价值。

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癌症 · 糖生物学 · 肿瘤学

摘要 ​

患者来源的类器官模型被证明是基础研究和转化研究中一个强有力的平台。在这里，我们对在无WNT培养条件下生长的胰腺导管腺癌（PDAC）肿瘤类器官的药物反应进行了系统分析，这些类器官来源于配对的患者来源异种移植（PDX）和PDX衍生类器官（PXO）模型。我们报告了类器官药物剂量反应的曲线下面积（AUC）值与体内肿瘤生长之间的特定关系，无论药物处理如何。此外，我们分析了PDX和PXO模型的糖组，证明PXO重现了体内糖链的全景。此外，我们识别出一组核心的57种N-糖，在所有10个模型中均有检测到，这些N-糖代表了每个模型中检测到的所有N-糖相对丰度的50%-94%。最后，我们利用类器官培养的培养基上清液开发了一个分泌生物标志物发现管道，并识别出可能的新型细胞外小泡（EV）蛋白标志物。我们使用来自PDAC患者、良性胃肠疾病和慢性胰腺炎患者的血浆样本验证了我们的发现，发现4种EV蛋白是PDAC的潜在循环生物标志物。因此，我们展示了类器官培养在模拟体内药物反应方面的实用性，并作为发现临床可操作的血清生物标志物的强大平台。

英文摘要 ​

Patient-derived organoid models are proving to be a powerful platform for both basic and translational studies. Here we conduct a methodical analysis of pancreatic ductal adenocarcinoma (PDAC) tumor organoid drug response in paired patient-derived xenograft (PDX) and PDX-derived organoid (PXO) models grown under WNT-free culture conditions. We report a specific relationship between area under the curve value of organoid drug dose response and in vivo tumor growth, irrespective of the drug treatment. In addition, we analyzed the glycome of PDX and PXO models and demonstrate that PXOs recapitulate the in vivo glycan landscape. In addition, we identify a core set of 57 N-glycans detected in all 10 models that represent 50%-94% of the relative abundance of all N-glycans detected in each of the models. Last, we developed a secreted biomarker discovery pipeline using media supernatant of organoid cultures and identified potentially new extracellular vesicle (EV) protein markers. We validated our findings using plasma samples from patients with PDAC, benign gastrointestinal diseases, and chronic pancreatitis and discovered that 4 EV proteins are potential circulating biomarkers for PDAC. Thus, we demonstrate the utility of organoid cultures to not only model in vivo drug responses but also serve as a powerful platform for discovering clinically actionable serologic biomarkers.

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主要研究问题 ​

  1. 在PDX衍生的类器官模型中，如何优化药物反应的评估方法以提高其临床相关性？
  2. 有哪些其他类型的肿瘤可以通过类似的PDX衍生类器官模型进行药物反应研究？
  3. PDX和PXO模型在生物标志物发现方面的具体优势和局限性是什么？
  4. 如何将发现的外泌体蛋白标志物应用于PDAC的早期诊断和监测？
  5. 在不同的培养条件下，PDX衍生类器官的药物反应和生物标志物分泌是否会有显著差异？

核心洞察 ​

研究背景和目的 ​

胰腺导管腺癌（PDAC）是一种具有高度侵袭性和低生存率的癌症，早期诊断和治疗选择有限。患者来源的肿瘤模型（如PDX和PDO）被广泛应用于癌症研究，以更好地理解肿瘤生物学和药物反应。本研究旨在开发和评估PDX衍生的类器官（PXO）模型，以预测药物反应并发现潜在的生物标志物。

主要方法/材料/实验设计 ​

本研究使用PDX模型和PXO模型进行比较，主要方法包括：

  1. 类器官培养：从PDX肿瘤中提取细胞并在无WNT培养基中培养，以保留肿瘤的基因组特征和表型。
  2. 药物反应测试：对PXO进行单药和组合药物处理，评估细胞存活率，并计算药物反应的曲线下面积（AUC）。
  3. 糖基化分析：通过质谱分析比较PDX和PXO的N-糖基化特征。
  4. 生物标志物发现：分析PXO培养基中的外泌体（EV）蛋白，并在PDAC患者血浆中验证这些标志物。

以下是技术路线的流程图：

Mermaid diagram

关键结果和发现 ​

  1. 药物反应一致性：PXO对化疗药物的反应与PDX模型高度一致，AUC值可以预测体内药物反应。
  2. 糖基化特征：PXO模型保留了PDX模型中的复杂糖基化特征，发现57种N-糖基在所有样本中占据了50%-94%的相对丰度。
  3. 生物标志物发现：通过分析PXO培养基中的EV，识别出4种潜在的PDAC循环生物标志物，并在患者血浆中验证了这些标志物的特异性。

主要结论/意义/创新性 ​

本研究证明了PDX衍生的类器官（PXO）在模拟体内药物反应和发现生物标志物方面的有效性。PXO不仅能够保留肿瘤的基因组和表型特征，还可以作为快速筛选新药物和生物标志物的平台。这一研究为PDAC的个性化治疗提供了新的工具和思路。

研究局限性和未来方向 ​

尽管本研究展示了PXO模型的潜力，但仍存在一些局限性：

  • 样本量有限：当前的临床验证仅在小规模患者群体中进行，未来需要更大规模的研究以确认发现的生物标志物的临床有效性。
  • 模型多样性：PXO模型的构建和应用可能受到不同患者肿瘤异质性的影响，未来研究应考虑更广泛的患者样本。

未来的研究方向可以集中在：

  • 扩大样本量进行多中心验证。
  • 探索PXO模型在其他类型癌症中的应用。
  • 结合多组学数据进一步解析肿瘤生物学和治疗反应。

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引用本文的文献 ​

  1. Drug Inhibition of SARS-CoV-2 Replication in Human Pluripotent Stem Cell-Derived Intestinal Organoids. - Jana Krüger;Rüdiger Groß;Carina Conzelmann;Janis A Müller;Lennart Koepke;Konstantin M J Sparrer;Tatjana Weil;Desiree Schütz;Thomas Seufferlein;Thomas F E Barth;Steffen Stenger;Sandra Heller;Jan Münch;Alexander Kleger - Cellular and molecular gastroenterology and hepatology (2021)
  2. Organotypic Modeling of the Tumor Landscape. - Maria M Haykal;Clara Nahmias;Christine Varon;Océane C B Martin - Frontiers in cell and developmental biology (2020)
  3. Exploring the Potential of Drug Response Assays for Precision Medicine in Ovarian Cancer. - Tanya Singh;Adam S Neal;Neda A Moatamed;Sanaz Memarzadeh - International journal of molecular sciences (2020)
  4. 3D Cell Cultures as Prospective Models to Study Extracellular Vesicles in Cancer. - Guillermo Bordanaba-Florit;Iratxe Madarieta;Beatriz Olalde;Juan M Falcón-Pérez;Félix Royo - Cancers (2021)
  5. A Prospective Feasibility Trial to Challenge Patient-Derived Pancreatic Cancer Organoids in Predicting Treatment Response. - Alica K Beutel;Lena Schütte;Jeanette Scheible;Elodie Roger;Martin Müller;Lukas Perkhofer;Annika M T U Kestler;Johann M Kraus;Hans A Kestler;Thomas F E Barth;Johannes Lemke;Marko Kornmann;Thomas J Ettrich;Johann Gout;Thomas Seufferlein;Alexander Kleger - Cancers (2021)
  6. Exploring the Complementarity of Pancreatic Ductal Adenocarcinoma Preclinical Models. - Owen Hoare;Nicolas Fraunhoffer;Abdessamad Elkaoutari;Odile Gayet;Martin Bigonnet;Julie Roques;Rémy Nicolle;Colin McGuckin;Nico Forraz;Emilie Sohier;Laurie Tonon;Pauline Wajda;Sandrine Boyault;Valéry Attignon;Séverine Tabone-Eglinger;Sandrine Barbier;Caroline Mignard;Olivier Duchamp;Juan Iovanna;Nelson J Dusetti - Cancers (2021)
  7. Three-Dimensional Culture Models to Study Innate Anti-Tumor Immune Response: Advantages and Disadvantages. - Alessandro Poggi;Federico Villa;Jordi Leonardo Castrillo Fernadez;Delfina Costa;Maria Raffaella Zocchi;Roberto Benelli - Cancers (2021)
  8. Dynamic Stromal Alterations Influence Tumor-Stroma Crosstalk to Promote Pancreatic Cancer and Treatment Resistance. - Kendelle J Murphy;Cecilia R Chambers;David Herrmann;Paul Timpson;Brooke A Pereira - Cancers (2021)
  9. The somatic molecular evolution of cancer: Mutation, selection, and epistasis. - Krishna Dasari;Jason A Somarelli;Sudhir Kumar;Jeffrey P Townsend - Progress in biophysics and molecular biology (2021)
  10. Novel 3D µtissues Mimicking the Fibrotic Stroma in Pancreatic Cancer to Study Cellular Interactions and Stroma-Modulating Therapeutics. - Kunal P Pednekar;Marcel A Heinrich;Joop van Baarlen;Jai Prakash - Cancers (2021)

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