Introduction: The in vitro culture of primordial follicles is the only available option for preserving fertility in prepubertal girls with malignant tumors. The cultivation of primordial follicles in scaffolds as artificial ovaries is a promising approach for this. Methods: Dissociated follicles were placed into an artificial ovarian scaffold composed of fibrinogen and thrombin. The follicles were cultured in a dish dedicated to live cell imaging and observed for growth using immunofluorescence and development via optical microscopy. The morphology of the follicles in the scaffold was three-dimensionally reconstructed using the Imaris software. Growth and development were also quantified. Results: The morphology of artificial ovaries began to degrade over time. Within approximately 7 days, primordial follicles were activated and grew into secondary follicles. A comparison of optical and confocal microscopy results revealed the superior detection of live cells using confocal microscopy. The three-dimensional reconstruction of the confocal microscopy data enabled the automatic enumeration and evaluation of the overall morphology of many follicles. Conclusions: The novel artificial ovary-enabled primordial follicles to enter the growth cycle after activation and grow into secondary follicles. The use of a fibrin scaffold as a carrier preserves the developmental potential of primordial germ cells and is a potentially effective method for preserving fertility in prepubertal girls.

Ovarian cancer (OC) is the leading cause of death among women with gynecologic malignancies. High-grade serous ovarian carcinoma (HGSOC) is the deadliest subtype of OC, accounting for about 90 percent of all ovarian cancer subtypes. Recent studies have shown that HGSOC patients have mutations in proto-oncogenes within the genome. Genome-wide detection and diagnosis are helpful for the diagnosis and treatment of HGSOC. To explore the genomic and transcriptional characteristics of subtypes of HGSOC, achieve accurate typing of tumor types, and obtain genomic characteristics that can reflect the subtypes of HGSOC, Using NMF clustering, SAM, PAM and survival time analysis, copy number variation data and gene expression data of 698 HGSOC samples were analyzed and differential expression genes of different disease subtypes were enriched and analyzed. Functions of genes related to different disease subtypes were enriched. All patients with HGSOC could be stratified into three categories according to genetic variation information and gene expression value. There was significant difference in the survival time curves of patients in different subtypes. And we identified twenty-one genes as the ones with the strongest power to differentiate the samples, including FTH1, COL1A2, COL3A1, GFBP7, ACTB, SPARC, PTTG1IP, TIMP1 and HLA-DPA1. Furthermore, we found that JAK/STAT (Janus kinase and signal transducers and activators of transcription) signaling pathway changes obviously in different subtypes. By investigating the genetic features and gene expression features, subtypes of patients with HGSOC could be accurately judged, which is useful for selecting therapeutic methods.