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Abstract Ovarian cancer (OC) incidence and mortality rates continue to escalate globally. Early detection of OC is challenging due to extensive metastases and the ambiguity of biomarkers in advanced High-Grade Primary Tumors (HGPTs). In the present study, we conducted an in-depth in silico analysis in OC cell lines using the Gene Expression Omnibus (GEO) microarray dataset with 53 HGPT and 10 normal samples. Differentially-Expressed Genes (DEGs) were also identified by GEO2r. A variety of analyses, including gene set enrichment analysis (GSEA), ChIP enrichment analysis (ChEA), eXpression2Kinases (X2K) and Human Protein Atlas (HPA), elucidated signaling pathways, transcription factors (TFs), kinases, and proteome, respectively. Protein–Protein Interaction (PPI) networks were generated using STRING and Cytoscape, in which co-expression and hub genes were pinpointed by the cytoHubba plug-in. Validity of DEG analysis was achieved via Gene Expression Profiling Interactive Analysis (GEPIA). Of note, KIAA0101, RAD51AP1, FAM83D, CEP55, PRC1, CKS2, CDCA5, NUSAP1, ECT2, and TRIP13 were found as top 10 hub genes; SIN3A, VDR, TCF7L2, NFYA, and FOXM1 were detected as predominant TFs in HGPTs; CEP55, PRC1, CKS2, CDCA5, and NUSAP1 were identified as potential biomarkers from hub gene clustering. Further analysis indicated hsa-miR-215-5p, hsa-miR-193b-3p, and hsa-miR-192-5p as key miRNAs targeting HGPT genes. Collectively, our findings spotlighted HGPT-associated genes, TFs, miRNAs, and pathways as prospective biomarkers, offering new avenues for OC diagnostic and therapeutic approaches.

Abstract Nanomedicine has emerged as a promising therapeutic approach, but its translation to the clinic has been hindered by the lack of cellular models to anticipate how tumor cells will respond to therapy. Three-dimensional (3D) cell culture models are thought to more accurately recapitulate key features of primary tumors than two-dimensional (2D) cultures. Heterotypic 3D tumor spheroids, composed of multiple cell types, have become more popular than homotypic spheroids, which consist of a single cell type, as a superior model for mimicking in vivo tumor heterogeneity and physiology. The stromal interactions demonstrated in heterotypic 3D tumor spheroids can affect various aspects, including response to therapy, cancer progression, nanomedicine penetration, and drug resistance. Accordingly, to design more effective anticancer nanomedicinal therapeutics, not only tumor cells but also stromal cells (e.g., fibroblasts and immune cells) should be considered to create a more physiologically relevant in vivo microenvironment. This review aims to demonstrate current knowledge of heterotypic 3D tumor spheroids in cancer research, to illustrate current advances in utilizing these tumor models as a novel and versatile platform for in vitro evaluation of nanomedicine-based therapeutics in cancer research, and to discuss challenges, guidelines, and future directions in this field. Graphical Abstract