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Updated: Mar 13, 2026
Evaluating the Angiogenetic Properties of Ovarian Cancer Stem-Like Cells using the Three-Dimensional Co-Culture System, NICO-1
Published on: December 5, 2020
A novel prognostic model based on vasculogenic mimicry in ovarian cancer
Yunjing Song1,2, Sijing Cai3, Jing Ma4
1Department of Gynecology, Ganzhou People's Hospital, Ganzhou, China.
Background:
High-grade serious ovarian cancer (HGSOC) is a heterogeneous gynecological malignancy with high mortality, often diagnosed at advanced stages, and its prognosis remains poor despite therapeutic advances. Discovering innovative prognostic markers and developing predictive models are critical to improving treatment strategies in patients with HGSOC. Vasculogenic mimicry (VM), a tumor cell-derived vessel-like structure formation process, plays a critical role in tumor progression and is linked to poor prognosis, making it a potential target for prognostic biomarker development. In this study, we aimed to construct a VM-related prognostic risk model for HGSOC.
Methods:
We analyzed transcriptomic and clinical data of HGSOC patients from the GSE9891 and The Cancer Genome Atlas (TCGA) database, identified VM-related genes, and developed a prognostic model using least absolute shrinkage and selection operator (LASSO)-Cox regression. The model's performance was validated via survival analysis, receiver operating characteristic (ROC) curves, and independent prognostic factor assessment in both training and test sets. Additionally, a nomogram integrating the model with clinical variables was established to optimize prognostic prediction. At the same time, we performed gene ontology (GO) analysis of differential genes in high- and low-risk HGSOC patients to obtain common enrichment pathways. Finally, after the survival analysis, we selected LRIG1 as a target gene and assessed the effect on tube formation using HGSOC cell lines OVCAR3.
Results:
In this study, we systematically developed an HGSOC prognostic risk model founded on seven VM genes. Furthermore, we formulated a new nomogram that combines risk characteristics and clinical pathological features, which provided good predictive performance for the clinical prognosis of HGSOC patients. At the same time, we found that LRIG1 was a key gene related to a better prognosis of HGSOC and inhibited tube formation capacity of OVCAR3.
Conclusions:
We identified VM-related genes, constructed a prognostic risk model for HGSOC, and found that LRIG1 was a prognostic factor for HGSOC.
