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.

The application of patient-derived three-dimensional culture systems as disease-specific drug sensitivity models has enormous potential to connect compound screening and clinical trials. However, the implementation of complex cell-based assay systems in drug discovery requires reliable and robust screening platforms. Here we describe the establishment of an automated platform in 384-well format for three-dimensional organoid cultures derived from colon cancer patients. Single cells were embedded in an extracellular matrix by an automated workflow and subsequently self-organized into organoid structures within 4 days of culture before being exposed to compound treatment. We performed validation of assay robustness and reproducibility via plate uniformity and replicate-experiment studies. After assay optimization, the patient-derived organoid platform passed all relevant validation criteria. In addition, we introduced a streamlined plate uniformity study to evaluate patient-derived colon cancer samples from different donors. Our results demonstrate the feasibility of using patient-derived tumor samples for high-throughput assays and their integration as disease-specific models in drug discovery.

Enthusiasm has emerged for the potential of liquid biopsies to provide easily accessible genetic biomarkers for early diagnosis and mutational cancer characterization. We here systematically investigated the suitability of circulating cell‐free DNA (cfDNA) analysis for mutation detection in colorectal cancer (CRC) patients with respect to clinicopathological disease stage. Droplet Digital PCR (ddPCR) was performed to detect common point mutations in the KRAS and BRAF oncogenes in cfDNA from 65 patients and compared to mutations in tumor tissue. Stage of disease was classified according to UICC (Union for International Cancer Control) criteria. In tumor tissue, KRAS or BRAF mutations were present in 35 of 65 cases (44% UICC stage I, 50% stage II, 47% stage III, and 62% stage IV). Although cfDNA was detected in 100% of patients, ddPCR displayed the tumor tissue mutation in only 1 of 6 (17%) stage II patients, whereas 10 of 18 (56%) reported variants were verified in cfDNA samples of the stage IV cohort. No BRAF or KRAS mutation was detected in cfDNA from patients with wild‐type tumor tissue. In one case of mutant stage II colon cancer ( KRAS ‐G12C), the G12D variant was detected in cfDNA instead. Further workup revealed that circulating tumor‐derived DNA and liver metastases originated from a synchronous KRAS ‐mutated cancer of the pancreas. Our results demonstrate that ddPCR‐based analysis is highly specific and useful for mutation monitoring, but the sensitivity limits its usefulness for early cancer detection.