Centromere proteins (CENPs) are nuclear proteins that are involved in centromere formation and chromosome segregation during mitosis. Some members of CENPs have been extensively studied in the initiation and development of cancers. However, the expression patterns and exact roles of CENPs in ovarian cancer (OC) have not been fully elucidated. In this study, we comprehensively assessed the genetic variation, expression patterns and prognostic value of CENPs in OC by several databases. The mRNA expression levels of CENPA/F/H/L/N/U/W were found to be significantly upregulated in OC and related to worse prognosis. Additionally, function enrichment analysis showed that CENPs were involved in DNA repair and cell division. Meanwhile, immune infiltration analysis elucidated that CENPs were associated with myeloid-derived suppressor cells (MDSCs) and major histocompatibility complex (MHC). These results suggested that CENPs might serve as potential diagnostic and prognostic markers and provide new insights for the development of CENPs-targeted therapeutics for ovarian cancer.

Ovarian cancer (OC) is one of the most common reproductive tumors in women, whereas current treatment options are limited. β-lactamase-like-protein 2 (LACTB2) has been observed to be associated with various cancers, but its function in OC is unknown. Therefore, we evaluate the prognostic value and the underlying function of LACTB2 in OC. In this study, high expression of LACTB2 was observed in OC compared with normal controls. Kaplan–Meier Plotter analysis revealed that overexpressed LACTB2 is strongly correlated with poor prognosis. We conducted GO/KEGG analysis to investigate the potential biological function of LACTB2 in OC. GESA analysis showed that LACTB2 was closely related to immune-related pathways. Subsequently, we explored the relationship between LACTB2 and 24 types of immune cells in OC. The results suggested that LACTB2 was positively associated with multiple tumor-infiltrating immune cells. Importantly, LACTB2 may modulate immune cell infiltration in OC to influence prognosis. In conclusion, LACTB2 can be used as a promising prognostic biomarker and immunotherapy target for OC.

Objective: To evaluate the practical value of DeepSeek-R1 and Doubao-1.5-pro in the context of ovarian cancer management by examining their diagnostic and treatment-related competencies. Methods: 20 key ovarian cancer diagnosis and treatment issues were identified, divided into 4 domains with 5 questions each. Two large language models answered these questions, and 5 gynecologic oncology chief physicians evaluated the answers on a 1–10 scale for completeness and accuracy. For each score and the mean score for each question, if it surpassed 7, it is evaluated as “Excellent.” The Kruskal–Wallis test compared scores within each LLM across 4 categories, and the Mann–Whitney-Wilcoxon test compared scores between the two LLMs in each category. Results: 200 scores were collected (100 per model). DeepSeek-R1 got 98 “Excellent” ratings, while Doubao-1.5-pro got 41. All 20 DeepSeek-R1 responses had “Excellent” average scores, compared to 9 for Doubao-1.5-pro. DeepSeek-R1 had less variability. Tests revealed significant differences between the models and showed DeepSeek-R1 outperformed Doubao-1.5-pro, and charts showed Doubao-1.5-pro scored lower in all aspects, especially “Medical”. Conclusions: DeepSeek-R1 shows potential in ovarian cancer diagnosis and treatment but has limitations like inaccuracies and overly technical responses due to outdated data and lack of humanistic elements. LLMs like DeepSeek-R1 are useful for medical education and assistive diagnosis, but they require ongoing updates and refinement for broader clinical use. Selecting the appropriate LLM for medical tasks and improving their clarity and accuracy is crucial for their future effectiveness.

Background: Ovarian cancer (OC) remains the most common cause of gynecological cancer-related death, and about 70% of these deaths are from advanced high-grade serous ovarian cancer (HGSOC). Cysteine-rich secretory protein 3 (CRISP3) is related to various human diseases; however, the roles and mechanisms of CRISP3 in HGSOC remain unclear. Methods: The clinical significance of CRISP3 in patients with OC was analyzed using the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus databases. CRISP3 expression in OC tissues was validated by RNA-sequencing (RNA-seq), quantitative PCR, and immunohistochemistry. Furthermore, we explored the effect of CRISP3 expression modulation on the biological behavior of HGSOC through CCK-8, EdU, and Transwell assays in vitro, and the differences in CRISP3 during the progression of HGSOC in vivo. We utilized RNA-seq, GSEA and Western blotting to detect CRISP3’s regulatory mechanisms. Finally, we employed data from the IMvigor210 cohort and TCGA to assess the correlation of CRISP3 with clinical response to immunotherapy, and the landscape of immune cell infiltration. Results: CRISP3 expression was markedly reduced in HGSOC. In vitro studies demonstrated that CRISP3 knockdown significantly enhanced proliferation, migration, and invasion of HGSOC cells, whereas its overexpression suppressed these malignant phenotypes. Moreover, CRISP3 expression was found to be downregulated during OC progression in vivo. Mechanistically, CRISP3 acted as a tumor suppressor through the PI3K/AKT signaling pathway to inhibit the progression and metastasis of HGSOC. Additionally, we observed an association between CRISP3 expression and CD8⁺ T cell, macrophage, neutrophil and Th1 cell infiltration. Conclusions: We demonstrate that CRISP3 suppresses tumorigenesis in HGSOC by regulating the PI3K/AKT pathway, and that alterations in its expression correlate with disease progression, supporting its utility as a biomarker.