TY - JOUR
KW - Cancer genomics
KW - Cancer models
AU - Dina ElHarouni
AU - Mushriq Al-Jazrawe
AU - Seongmin Choi
AU - Merve Dede
AU - Toshinori Hinoue
AU - Sean A. Misek
AU - Heeju Noh
AU - Luca Zanella
AU - Yuen-Yi Tseng
AU - Hayley E. Francies
AU - Dennis Plenker
AU - Cindy W. Kyi
AU - Julyann Perez-Mayoral
AU - Megan J. Stine
AU - Eva Tonsing-Carter
AU - Rachana Agarwal
AU - Jean Claude Zenklusen
AU - James M. Clinton
AU - Jennifer M. Shelton
AU - Timothy R. Chu
AU - William F. Hooper
AU - Xavi Loinaz
AU - Paula Keskula
AU - Jordan Tagle
AU - Peyton C. Kuhlers
AU - Bahar Tercan
AU - Sylvia F. Boj
AU - Alessandro Vasciaveo
AU - Lorenzo Tomassoni
AU - James M. Crawford
AU - Shawna Walsh
AU - Claire Sinai
AU - Sonam Bhatia
AU - Priya Sridevi
AU - Hardik Patel
AU - Maria Antonietta Cerone
AU - Kyle Ellrott
AU - Calvin J. Kuo
AU - Olivier Elemento
AU - Semir Beyaz
AU - Vincenzo Corbo
AU - David L. Spector
AU - Rameen Beroukhim
AU - Martin L. Ferguson
AU - Andrew D. Cherniack
AU - Peter W. Laird
AU - Nicolas Robine
AU - Andrew McPherson
AU - Katherine A. Hoadley
AU - Mathew J. Garnett
AU - David A. Tuveson
AU - Andrea Califano
AU - Paul T. Spellman
AU - Keith L. Ligon
AU - Daniela S. Gerhard
AU - Louis M. Staudt
AU - Jesse S. Boehm
AB - 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.
BT - Nature
DA - 2026-08-05
DO - 10.1038/s41586-026-10806-y
LA - en
N2 - 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.
PY - 2026
SP - 1
EP - 14
T2 - Nature
TI - A compendium of next-generation patient-derived models for diverse cancers
UR - https://www.nature.com/articles/s41586-026-10806-y
Y2 - 2026-08-10
SN - 1476-4687
ER -