麻省理工学院和哈佛大学的布罗德研究所Jesse S. Boehm小组在研究中取得进展。他们开发出多种癌症新一代患者来源模型汇编。2026年8月5日，国际知名学术期刊《自然》发表了这一成果。

在这里，该课题组研究人员展示了一个大型国际项目——人类癌症模型倡议——的结果，该项目涉及从2780名25种癌症类型的捐赠者中生成665个下一代模型，并整合了肿瘤模型的全基因组、外显子组、甲基组和转录组分析。该研究提供了522个具有综合临床数据的模型，153个罕见癌症模型和71个非欧洲血统参与者模型。对421对匹配的肿瘤模型对的分析显示了高遗传（97.8%）和表观遗传（95%）一致性，并定义了模型不一致性的相关因素。

肿瘤模型对的单核RNA测序揭示了培养条件显著影响细胞状态的模型子集。最后，该课题组人员描述了染色体外DNA和治疗后突变特征的模型保存，为研究治疗耐药性提供了机会。该模型库正在向社区开放，包括多模态分子分析、临床信息和集成软件工具，它们为癌症发病机制和治疗反应的临床前研究提供了宝贵的依据。

研究人员表示，新疗法的开发和癌症发病机制的验证需要有代表性的实验室模型。然而，现有的收集只代表了人类癌症中观察到的多样性的一小部分。最近的技术已经实现了有效的体外模型衍生（例如，肿瘤类器官）。然而，在长期扩张过程中，这些物质是否维持患者肿瘤的基本特性还没有系统的研究。

附：英文原文

Title: A compendium of next-generation patient-derived models for diverse cancers

Author: ElHarouni, Dina, Al-Jazrawe, Mushriq, Choi, Seongmin, Dede, Merve, Hinoue, Toshinori, Misek, Sean A., Noh, Heeju, Zanella, Luca, Tseng, Yuen-Yi, Francies, Hayley E., Plenker, Dennis, Kyi, Cindy W., Perez-Mayoral, Julyann, Stine, Megan J., Tonsing-Carter, Eva, Agarwal, Rachana, Zenklusen, Jean Claude, Clinton, James M., Shelton, Jennifer M., Chu, Timothy R., Hooper, William F., Loinaz, Xavi, Keskula, Paula, Tagle, Jordan, Kuhlers, Peyton C., Tercan, Bahar, Boj, Sylvia F., Vasciaveo, Alessandro, Tomassoni, Lorenzo, Crawford, James M., Walsh, Shawna, Sinai, Claire, Bhatia, Sonam, Sridevi, Priya, Patel, Hardik, Cerone, Maria Antonietta, Ellrott, Kyle, Kuo, Calvin J., Elemento, Olivier, Beyaz, Semir, Corbo, Vincenzo, Spector, David L., Beroukhim, Rameen, Ferguson, Martin L., Cherniack, Andrew D., Laird, Peter W., Robine, Nicolas, McPherson, Andrew, Hoadley, Katherine A., Garnett, Mathew J., Tuveson, David A., Califano, Andrea, Spellman, Paul T., Ligon, Keith L., Gerhard, Daniela S., Staudt, Louis M., Boehm, Jesse S.

Issue&Volume: 2026-08-05

Abstract: The development of new therapeutics and the validation of pathogenetic cancer mechanisms require representative laboratory models1,2. However, existing collections represent only a fraction of the diversity observed in human cancer2,3,4. Recent technologies have enabled efficient in vitro model derivation (for example, tumour organoids)5. However, whether these maintain essential properties of patient tumours during long-term expansion has not been systematically investigated. Here we present results of a large-scale international programme—the Human Cancer Models Initiative—which involved the generation of a resource of 665 next-generation models from 2,780 donors with 25 cancer types and integrated tumour–model whole genome, exome, methylome and transcriptome analyses. The resource provides 522 models with comprehensive clinical data, 153 models of rare cancers and 71 models from participants with non-European ancestry. Analyses of 421 matched tumour–model pairs reveal high genetic (97.8%) and epigenetic (95%) concordance and define correlates of model discordance. Single-nucleus RNA sequencing of tumour–model pairs reveals subsets of models in which culture conditions significantly influence cell states. Finally, we characterize model preservation of extrachromosomal DNA and post-treatment mutational signatures to provide opportunities to study therapeutic resistance. This model repository is being made available to the community—including multimodal molecular profiling, clinical information and integrative software tools—thus providing a valuable resource for preclinical investigation of cancer pathogenesis and treatment response.

DOI: 10.1038/s41586-026-10806-y

Source: https://www.nature.com/articles/s41586-026-10806-y