Establishment of patient-derived tumor organoids to functionally inform treatment decisions in metastatic colorectal cancer

Abstract

Background Metastatic colorectal cancer (mCRC) patients tend to have modest benefits from molecularly driven therapeutics. Patient-derived tumor organoids (PDTOs) represent an unmatched model to elucidate tumor resistance to therapy, due to their high capacity to resemble tumor characteristics. Materials and methods We used viable tumor tissue from two cohorts of patients with mCRC, naïve or refractory to treatment, respectively, for generating PDTOs. The derived models were subjected to a 6-day drug screening assay (DSA) with a comprehensive pipeline of chemotherapy and targeted drugs against almost all the actionable mCRC molecular drivers. For the second cohort DSA data were matched with those from PDTO genotyping. Results A total of 40 PDTOs included in the two cohorts were derived from mCRC primary tumors or metastases. The first cohort included 31 PDTOs derived from patients treated in front line. For this cohort, DSA results were matched with patient responses. Moreover, RAS/BRAF mutational status was matched with DSA cetuximab response. Ten out of 12 (83.3%) RAS wild-type PDTOs responded to cetuximab, while all the mutant PDTOs, 8 out of 8 (100%), were resistant. For the second cohort (chemorefractory patients), we used part of tumor tissue for genotyping. Four out of nine DSA/genotyping data resulted applicable in the clinic. Two RAS-mutant mCRC patients have been treated with FOLFOX–bevacizumab and mitomycin–capecitabine in third line, respectively, based on DSA results, obtaining disease control. One patient was treated with nivolumab–second mitochondrial-derived activator of caspases mimetic (phase I trial) due to high tumor mutational burden at genotyping, experiencing stable disease. In one case, the presence of BRCA2 mutation correlated with DSA sensitivity to olaparib; however, the patient could not receive the therapy. Conclusions Using CRC as a model, we have designed and validated a clinically applicable methodology to potentially inform clinical decisions with functional data. Undoubtedly, further larger analyses are needed to improve methodology success rates and propose suitable treatment strategies for mCRC patients.