Patient-derived gastric cancer organoids model heterogeneity and stroma-mediated chemoresistance in poorly cohesive carcinoma.

OBJECTIVE

Gastric cancer (GC) remains a leading cause of cancer-related mortality, with poorly cohesive carcinoma (PCC) exhibiting rising incidence and poor therapeutic responses. In this study, we constructed a panel of patient-derived organoids of GC and used them to understand histological accuracy and sensitivity profiles as well as the influence of microenvironment on these special GC subtypes.

METHODS

A total of 23 patient-derived GC organoid models including 12 PCC and 11 non-poorly cohesive carcinoma (NPCC) were established. Histopathological and genetic fidelity to primary tumors was validated using immunohistochemistry (IHC), immunofluorescence (IF), and H&E staining. Relative growth kinetics between PCC and NPCC organoids were measured and compared. Sizes of subcutaneously xenografted tumors harbored by mice representing different types of GC organoids were analyzed. We further examined drug sensitivities between docetaxel, 5-fuorouracil (5-FU), oxaliplatin, and irinotecan against our collected samples of patient-derived organoids. The impact of cancer-associated fibroblasts (CAFs) on organoid growth and chemoresistance was analyzed via co-culture experiments.

RESULTS

Organoids retained genetic and histopathological features of primary tumors. PCC-derived organoids displayed rapid growth characteristics and produced more rapidly growing tumors than NPCC. PCC organoids showed heightened sensitivity to docetaxel with lower IC, but no significant differences were observed for 5-FU, oxaliplatin, or irinotecan. CAF co-culture enhanced organoid proliferation and conferred resistance to all tested chemotherapeutic agents.

CONCLUSION

Patient-derived GC organoids especially PCC subtypes reliably recapitulate the complexity of solid-tumors heterogeneity, predict drug responses, and elucidate stromal contributions to therapy resistance. This model could be used to develop tailoring treatments and improve personalization of therapy for clinical management of PCC.