Jin-Ku Lee

Systematic growth factor profiling platform for 3D tumor models reveals estradiol-responsive cellular mechanisms of immunotherapy resistance

Abstract Current organoid culture systems face critical limitations: standardized growth factor formulations fail to capture patient-specific signaling requirements, while single-cell-type approaches overlook tumor-stromal interactions essential for understanding immunotherapy resistance. To address these challenges, we developed an automated biofabrication platform that systematically integrates patient-derived three-dimensional (3D) cultures with comprehensive growth factor profiling across 128 combinations. Through rigorous optimization of Matrigel concentration and gelation kinetics, we established standardized conditions achieving uniform signal distribution and quantitative reproducibility. Screening of 23 ovarian cancer patient samples identified universal growth factor combinations that consistently promoted robust cell growth while preserving parental tumor characteristics. Integration of growth factor response profiles with multi-scale genomic analysis revealed two estradiol-responsive cellular populations coordinating immunosuppression: a malignant cell fraction (MAL.PDCD5) that suppresses immune infiltration and a cancer-associated fibroblast fraction (FB.TNFSF10) that promotes immune exclusion through enhanced TGF- β signaling. Spatial transcriptomic validation demonstrated striking mutual exclusivity between FB.TNFSF10 cells and T/NK cells in native tissue architecture. Most significantly, FB.TNFSF10 abundance emerged as a robust predictor of immune checkpoint inhibitor therapy resistance across multiple cancer cohorts, independent of conventional biomarkers. This biofabrication platform provides a scalable, reproducible framework with broad applicability beyond oncology. The systematic optimization methodology is readily adaptable to other tissue types, disease models, and high-throughput drug screening applications, representing a significant advancement in functional tissue engineering for precision medicine.

High-throughput organo-on-pillar (high-TOP) array system for three-dimensional ex vivo drug testing

The development of organoid culture technologies has triggered industrial interest in ex vivo drug test-guided clinical response prediction for precision cancer therapy. The three-dimensional culture encapsulated with basement membrane (BM) components is extremely important in establishing ex vivo organoids and drug sensitivity tests because the BM components confer essential structures resembling tumor histopathology. Although numerous studies have demonstrated three-dimensional culture-based drug screening methods, establishing a large-scale drug-screening platform with matrix-encapsulated tumor cells is challenging because the arrangement of microspots of a matrix-cell droplet onto each well of a microwell plate is inconsistent and difficult to standardize. In addition, relatively low scales and lack of reproducibility discourage the application of three-dimensional organoid-based drug screening data for precision treatment or drug discovery. To overcome these limitations, we manufactured an automated organospotter-integrated high-throughput organo-on-pillar (high-TOP) drug-screening platform. Our system is compatible with various extracellular matrices, including BM extract, Matrigel, collagen, and hydrogel. In addition, it can be readily utilized for high-content analyses by simply exchanging the bottom plates without disrupting the domes. Our system demonstrated considerable robustness, consistency, reproducibility, and biological relevancy in three-dimensional drug sensitivity analyses using Matrigel-encapsulated ovarian cancer cell lines. We also demonstrated proof-of-concept cases representing the clinical feasibility of high-TOP-assisted ex vivo drug tests linked to clinical chemo-response in ovarian cancer patients. In conclusion, our platform provides an automated and standardized method for ex vivo drug-sensitivity-guided clinical response prediction, suggesting effective chemotherapy regimens for patients with cancer.

Unraveling the Transcriptomic Signatures of Homologous Recombination Deficiency in Ovarian Cancers

AbstractHomologous recombination deficiency (HRD) is a crucial driver of tumorigenesis by inducing impaired repair of double‐stranded DNA breaks. Although HRD possibly triggers the production of numerous tumor neoantigens that sufficiently stimulate and activate various tumor‐immune responses, a comprehensive understanding of the HRD‐associated tumor microenvironment is elusive. To investigate the effect of HRD on the selective enrichment of transcriptomic signatures, 294 cases from The Cancer Genome Atlas‐Ovarian Cancer project with both RNA‐sequencing and SNP array data are analyzed. Differentially expressed gene analysis and network analysis are performed to identify HRD‐specific signatures. Gene‐sets associated with mitochondrial activation, including enhanced oxidative phosphorylation (OxPhos), are significantly enriched in the HRD‐high group. Furthermore, a wide range of immune cell activation signatures is enriched in HRD‐high cases of high‐grade serous ovarian cancer (HGSOC). On further cell‐type‐specific analysis, M1‐like macrophage genes are significantly enriched in HRD‐high HGSOC cases, whereas M2‐macrophage‐related genes are not. The immune‐response‐associated genomic features, including tumor mutation rate, neoantigens, and tumor mutation burdens, correlated with HRD scores. In conclusion, the results of this study highlight the biological properties of HRD, including enhanced energy metabolism, increased tumor neoantigens and tumor mutation burdens, and consequent exacerbation of immune responses, particularly the enrichment of M1‐like macrophages in HGSOC cases.