Mapping treatment response in metastatic colorectal cancer using organoids and genomic profiling

Abstract

This thesis focuses on improving personalized treatment strategies for patients with metastatic colorectal cancer. Although new targeted therapies have become available, many patients still do not respond to their treatment. To better match therapies to each individual, this research combines broad genomic analysis of the tumor with organoid models in the laboratory that mimic how a patient’s tumor responds to treatment. Evaluation of early-phase clinical trial results highlights a growing shift towards molecularly-driven treatments, with improved clinical benefit for patients selected on the molecular profile of the tumor. Whole genome sequencing allows us to look at the complete DNA profile of the tumor and identify more targets for treatments than routine tests can detect. However, genomic information alone does not always show which drugs will actually work. Patient-derived organoids can be used to identify promising or likely ineffective treatments early in the drug development process. We first improved and standardized these organoid drug screening methods to increase reliability. We showed that organoids can accurately predict how patients respond to chemotherapy and how treatment history affects drug resistance. The discovery that both tumor characteristics and laboratory conditions critically influence organoid growth, paves the way for optimizing organoid culture success. Finally, we developed a faster, smaller-scale screening method requiring less input material, to enable the implementation in the clinic. Together, these advances bring us closer to truly personalized cancer treatment based on each patient’s unique tumor profile.