Heterogeneous pathway activation and drug response modelled in colorectal-tumor-derived 3D cultures.

Organoid cultures derived from colorectal cancer (CRC) samples are increasingly used as preclinical models for studying tumor biology and the effects of targeted therapies under conditions capturing in vitro the genetic make-up of heterogeneous and even individual neoplasms. While 3D cultures are initiated from surgical specimens comprising multiple cell populations, the impact of tumor heterogeneity on drug effects in organoid cultures has not been addressed systematically. Here we have used a cohort of well-characterized CRC organoids to study the influence of tumor heterogeneity on the activity of the KRAS/MAPK-signaling pathway and the consequences of treatment by inhibitors targeting EGFR and downstream effectors. MAPK signaling, analyzed by targeted proteomics, shows unexpected heterogeneity irrespective of RAS mutations and is associated with variable responses to EGFR inhibition. In addition, we obtained evidence for intratumoral heterogeneity in drug response among parallel "sibling" 3D cultures established from a single KRAS-mutant CRC. Our results imply that separate testing of drug effects in multiple subpopulations may help to elucidate molecular correlates of tumor heterogeneity and to improve therapy response prediction in patients.

Molecular dissection of colorectal cancer in pre-clinical models identifies biomarkers predicting sensitivity to EGFR inhibitors.

Colorectal carcinoma represents a heterogeneous entity, with only a fraction of the tumours responding to available therapies, requiring a better molecular understanding of the disease in precision oncology. To address this challenge, the OncoTrack consortium recruited 106 CRC patients (stages I-IV) and developed a pre-clinical platform generating a compendium of drug sensitivity data totalling >4,000 assays testing 16 clinical drugs on patient-derived in vivo and in vitro models. This large biobank of 106 tumours, 35 organoids and 59 xenografts, with extensive omics data comparing donor tumours and derived models provides a resource for advancing our understanding of CRC. Models recapitulate many of the genetic and transcriptomic features of the donors, but defined less complex molecular sub-groups because of the loss of human stroma. Linking molecular profiles with drug sensitivity patterns identifies novel biomarkers, including a signature outperforming RAS/RAF mutations in predicting sensitivity to the EGFR inhibitor cetuximab.