Tumorigenesis is a complex, multistage process characterized by progressive molecular and morphological changes in cells1,2. Esophageal squamous cell carcinoma (ESCC), a prevalent malignancy with poor prognosis3,4, exemplifies this stepwise progression through four distinct stages: normal mucosa, low-grade intraepithelial neoplasia (LGIN), high-grade intraepithelial neoplasia (HGIN), and invasive carcinoma5. Throughout these stages, epithelial cells exhibit dynamic changes in molecular expression patterns and spatial organization, accompanied by systematic alterations in tissue morphology as it advances from a normal to a malignant state6,7. Despite advances in understanding ESCC pathogenesis, the lack of experimental models that faithfully recapitulate spatial and temporal aspects of tumor evolution-while enabling systematic histological and molecular analyses-has hindered deeper mechanistic understanding of disease progression and therapeutic development.
While 2D immortalized cancer cell lines have made significant contributions to the understanding of oncogenesis, they are inherently limited in replicating the biological complexity and pathological features of native tumors8. Animal models, though providing in vivo context, often poorly predict human responses due to species-specific differences9. In contrast, organoids have emerged as a transformative preclinical platform that faithfully preserves the cellular heterogeneity, architecture, and functionality of human tissues10,11,12,13. As preclinical models, organoids better capture the characteristics of primary tumors, enabling detailed investigation of key molecular events and cellular changes during tumor progression14. For instance, Chen et al. utilized patient-derived esophageal organoids from different stages of ESCC to elucidate epithelial-fibroblast interactions, ultimately validating the ANXA1-FPR2 signaling axis as a critical driver of ESCC pathogenesis6. Similarly, Ko et al. employed genetically engineered esophageal organoids to identify key genetic determinants driving ESCC initiation and immune evasion, demonstrating how organoid models can effectively recapitulate disease features and reveal novel therapeutic targets15.
The present methodology resolves significant issues in esophageal cancer modeling by establishing a reproducible protocol for generating multistage ESCC organoids that mirror histological progression from normal epithelium to invasive carcinoma. This system integrates optimized culture conditions using an L-WRN-conditioned medium to maintain epithelial stemness, combined with standardized protocols for histological processing and multiplex immunofluorescence (mIF) analysis, providing an ideal platform to longitudinally analyze spatial and molecular changes during tumorigenesis. Compared to alternative techniques such as 2D cultures, this organoid platform uniquely preserves tissue architecture, enabling the visualization of spatially organized molecular markers, including the immune checkpoint protein PD-L1 (CD274), which mediates tumor immune evasion by inhibiting T cell responses16,17,18, and the proliferation marker Ki-67. The protocol enables organoids from normal esophageal and precancerous tissues passage, helping researchers build a continuous organoid model from normal tissue to tumor19. By enabling detailed analysis of spatial and molecular changes during tumorigenesis, this protocol offers researchers a powerful tool for understanding the mechanisms underlying cancer development and progression, potentially leading to improved therapeutic strategies.
This methodology is particularly suited for researchers investigating epithelial carcinogenesis, tumor microenvironment interactions, or therapeutic responses in ESCC and related squamous malignancies. Its modular design allows adaptation to study other molecular markers or signaling pathways, provided appropriate validation steps are incorporated. By offering a standardized yet flexible platform, this protocol aims to advance preclinical research in tumor biology and accelerate the translation of mechanistic insights into targeted therapies.