Predicting therapeutic responses in metastatic colorectal cancer through personalized functional profiling of...

Drug resistance of metastatic colorectal cancer (mCRC) remains a major therapeutic challenge. Screening patient-derived tumor cells with diverse compounds in 3D models may overcome the limitations of genomics-based drug response predictions. We describe a personalized functional profiling (PFP) approach in mCRC using patient-derived spheroids (PDS) and assess its utility in predicting drug responses. PDS were established from twelve patients' tumors and validated by immunohisto(cyto)chemistry and genomic sequencing. Forty-two small molecule anti-cancer drugs, along with five standard-of-care (SOC) drugs in CRC were screened as single agents or in combination, and cell viability was measured using calcein staining or ATP-based assay. Ex vivo results were compared with clinical treatment responses. PDS closely mirrored histopathological and genetic features of the original tumors, supporting their use in PFP. Sensitivity to anti-EGFR drugs distinguished responsive from resistant patients and revealed candidates for anti-ERBB2 therapy, whereas anti-VEGFR screening failed to recapitulate clinical outcomes. SOC drug screening results correlated with clinical outcomes or tumor genetic features in a subset of PDS. This work underscores the predictive value of PFP, its complementarity with genomic sequencing, and the need for refinement to enhance its clinical applicability.