03918nas a2200841   4500000000100000000000100001008004100002260001500043653002000058653001800078100001900096700002300115700001800138700001500156700002100171700001800192700001400210700001700224700001800241700002300259700001900282700001700301700002600318700001900344700002300363700002000386700002600406700002100432700002400453700001900477700002200496700001600518700001800534700001700552700002200569700001700591700001800608700002500626700002200651700002200673700001700695700001700712700001700729700001800746700001700764700002800781700001700809700001800826700002100844700001600865700001900881700002100900700002100921700002300942700002400965700001900989700001901008700002101027700002501048700002201073700002101095700002001116700002101136700001901157700002301176700002001199700001901219245007901238856005501317300000901372520168101381022001403062       2026                            d  c2026-08-0510aCancer genomics10aCancer models1 aDina ElHarouni1 aMushriq Al-Jazrawe1 aSeongmin Choi1 aMerve Dede1 aToshinori Hinoue1 aSean A. Misek1 aHeeju Noh1 aLuca Zanella1 aYuen-Yi Tseng1 aHayley E. Francies1 aDennis Plenker1 aCindy W. Kyi1 aJulyann Perez-Mayoral1 aMegan J. Stine1 aEva Tonsing-Carter1 aRachana Agarwal1 aJean Claude Zenklusen1 aJames M. Clinton1 aJennifer M. Shelton1 aTimothy R. Chu1 aWilliam F. Hooper1 aXavi Loinaz1 aPaula Keskula1 aJordan Tagle1 aPeyton C. Kuhlers1 aBahar Tercan1 aSylvia F. Boj1 aAlessandro Vasciaveo1 aLorenzo Tomassoni1 aJames M. Crawford1 aShawna Walsh1 aClaire Sinai1 aSonam Bhatia1 aPriya Sridevi1 aHardik Patel1 aMaria Antonietta Cerone1 aKyle Ellrott1 aCalvin J. Kuo1 aOlivier Elemento1 aSemir Beyaz1 aVincenzo Corbo1 aDavid L. Spector1 aRameen Beroukhim1 aMartin L. Ferguson1 aAndrew D. Cherniack1 aPeter W. Laird1 aNicolas Robine1 aAndrew McPherson1 aKatherine A. Hoadley1 aMathew J. Garnett1 aDavid A. Tuveson1 aAndrea Califano1 aPaul T. Spellman1 aKeith L. Ligon1 aDaniela S. Gerhard1 aLouis M. Staudt1 aJesse S. Boehm00aA compendium of next-generation patient-derived models for diverse cancers  uhttps://www.nature.com/articles/s41586-026-10806-y  a1-143 aThe 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.  a1476-4687