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Pan-Cancer PDOs Preserve Tumor Heterogeneity and Uncover Therapeutic Vulnerabilities

Kuo, H.-H.; Bhinder, B.; Gokozan, H. N.; Gorski, K.; Chandra, P.; Manohar, J.; Guevara, D.; Otilano, J.; Moyer, J.; Tranquille, M.; Ackermann, S.; Capuano, J.; Cheung, C.; Caiazza, T. A.; Reuben, P. L.; Irizarry, A.; Tsomides, A. M.; Sigouros, M.; Wilkes, D.; King, A.; Kane, T.; Al Assaad, M.; Al Zoughbi, W.; Ohara, K.; Auh, J.; Waltman, P.; Madorsky Rowdo, F. P.; Podaza, E.; Gallegos, V.; Nguyen, J.; Shah, R.; Shah, M.; Ocean, A.; Scherr, D.; Altorki, N.; Frey, M.; Molina, A. M.; Newman, L.; Bea, V.; Chapman-Davis, E.; Goncalves, M. D.; Saxena, A.; Shukla, P. J.; Holcomb, K.; Simmons, R.; Tag

2025-04-17 cancer biology
10.1101/2025.04.10.647635 bioRxiv
Show abstract

We developed a tumor-matched, pan-cancer patient-derived organoid (PDO) platform comprising 220 PDOs from 190 patients across 15 cancer types to advance functional precision oncology. Our comprehensively characterized PDOs showed 93% histopathology concordance, 80% median genomic concordance for driver mutations, and a 0.85 median gene expression correlation with parent tumors. Gene expression in PDOs remained stable across [≥] 10 passages, supporting reproducibility for long-term drug screening. Even PDOs with low genomic concordance retained oncogenic drivers, supporting their use as disease models. Clonality analysis revealed that 85% of PDOs preserved dominant tumor clones. Higher genomic concordance was associated with greater clonal similarity, while lower genomic concordance was associated with clonal divergence. Functional assays showed that 58% of PDOs from a subset of patients ineligible for FDA-approved PARP inhibitors responded to Talazoparib, with sensitivity linked to alterations in DNA damage repair. Combination screens revealed drugs that effectively overcame resistance, especially in TP53-mutant PDOs. In summary, our platform supports investigation of targeted therapies, identification of molecular features linked to drug sensitivity, and translational discovery, offering insights into personalized cancer treatment beyond current biomarker guidelines.

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