Heterogeneous pathway activation and drug response modelled in colorectal-tumor-derived 3D cultures
Author(s) -
Dirk Schumacher,
Geoffroy Andrieux,
Karsten Boehnke,
Marlen Keil,
Alessandra Silvestri,
Maxine Silvestrov,
Ulrich Keilholz,
Johannes Haybaeck,
Gerrit Erdmann,
Christoph Sachse,
Markus F. Templin,
Jens Hoffmann,
Melanie Boerries,
Reinhold Schäfer,
Christian Regenbrecht
Publication year - 2019
Publication title -
plos genetics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.587
H-Index - 233
eISSN - 1553-7404
pISSN - 1553-7390
DOI - 10.1371/journal.pgen.1008076
Subject(s) - kras , biology , organoid , colorectal cancer , genetic heterogeneity , cancer research , tumor heterogeneity , drug response , targeted therapy , mapk/erk pathway , drug , cancer , computational biology , signal transduction , phenotype , genetics , pharmacology , gene
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.
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