Patient-derived organoids (PDOs) have recently emerged as robust preclinical models; however, their potential to predict clinical outcomes in patients has remained unclear. We report on a living biobank of PDOs from metastatic, heavily pretreated colorectal and gastroesophageal cancer patients recruited in phase 1/2 clinical trials. Phenotypic and genotypic profiling of PDOs showed a high degree of similarity to the original patient tumors. Molecular profiling of tumor organoids was matched to drug-screening results, suggesting that PDOs could complement existing approaches in defining cancer vulnerabilities and improving treatment responses. We compared responses to anticancer agents ex vivo in organoids and PDO-based orthotopic mouse tumor xenograft models with the responses of the patients in clinical trials. Our data suggest that PDOs can recapitulate patient responses in the clinic and could be implemented in personalized medicine programs.

These findings suggested that KRAS mutations and PI3KCA/PTEN deregulation significantly correlate with resistance to cetuximab. In line with this, patients carrying KRAS mutations or with activated PI3K profiles can benefit from targeted treatments only by switching off molecules belonging to the downstream signalling of activated EGFR, such as mammalian target of rapamycin.

PurposeThe Medical Research Council Adjuvant Gastric Infusional Chemotherapy (MAGIC) trial established perioperative epirubicin, cisplatin, and fluorouracil chemotherapy as a standard of care for patients with resectable esophagogastric cancer. However, identification of patients at risk for relapse remains challenging. We evaluated whether pathologic response and lymph node status after neoadjuvant chemotherapy are prognostic in patients treated in the MAGIC trial.Materials and MethodsPathologic regression was assessed in resection specimens by two independent pathologists using the Mandard tumor regression grading system (TRG). Differences in overall survival (OS) according to TRG were assessed using the Kaplan-Meier method and compared using the log-rank test. Univariate and multivariate analyses using the Cox proportional hazards method established the relationships among TRG, clinical-pathologic variables, and OS.ResultsThree hundred thirty resection specimens were analyzed. In chemotherapy-treated patients with a TRG of 1 or 2, median OS was not reached, whereas for patients with a TRG of 3, 4, or 5, median OS was 20.47 months. On univariate analysis, high TRG and lymph node metastases were negatively related to survival (Mandard TRG 3, 4, or 5: hazard ratio [HR], 1.94; 95% CI, 1.11 to 3.39; P = .0209; lymph node metastases: HR, 3.63; 95% CI, 1.88 to 7.0; P < .001). On multivariate analysis, only lymph node status was independently predictive of OS (HR, 3.36; 95% CI, 1.70 to 6.63; P < .001).ConclusionLymph node metastases and not pathologic response to chemotherapy was the only independent predictor of survival after chemotherapy plus resection in the MAGIC trial. Prospective evaluation of whether omitting postoperative chemotherapy and/or switching to a noncross-resistant regimen in patients with lymph node-positive disease whose tumor did not respond to preoperative epirubicin, cisplatin, and fluorouracil may be appropriate.

Sequential profiling of plasma cell-free DNA (cfDNA) holds immense promise for early detection of patient progression. However, how to exploit the predictive power of cfDNA as a liquid biopsy in the clinic remains unclear. RAS pathway aberrations can be tracked in cfDNA to monitor resistance to anti-EGFR monoclonal antibodies in patients with metastatic colorectal cancer. In this prospective phase II clinical trial of single-agent cetuximab in wild-type patients, we combine genomic profiling of serial cfDNA and matched sequential tissue biopsies with imaging and mathematical modeling of cancer evolution. We show that a significant proportion of patients defined as wild-type based on diagnostic tissue analysis harbor aberrations in the RAS pathway in pretreatment cfDNA and, in fact, do not benefit from EGFR inhibition. We demonstrate that primary and acquired resistance to cetuximab are often of polyclonal nature, and these dynamics can be observed in tissue and plasma. Furthermore, evolutionary modeling combined with frequent serial sampling of cfDNA allows prediction of the expected time to treatment failure in individual patients. This study demonstrates how integrating frequently sampled longitudinal liquid biopsies with a mathematical framework of tumor evolution allows individualized quantitative forecasting of progression, providing novel opportunities for adaptive personalized therapies. Liquid biopsies capture spatial and temporal heterogeneity underpinning resistance to anti-EGFR monoclonal antibodies in colorectal cancer. Dense serial sampling is needed to predict the time to treatment failure and generate a window of opportunity for intervention. .