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Nature · 2026

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

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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, HCMI Network, 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

Аннотация

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 cancer2-4. 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.

Предметные рубрики MeSH

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

Реквизиты и контакты