Vasculogenic mimicry and breast cancer prognosis: Insights into predictive model development

血管生成拟态与乳腺癌预后:对预测模型开发的启示

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Abstract

Breast cancer remains one of the most prevalent malignancies among women worldwide. Although advances in multimodal therapies have markedly improved clinical outcomes, recurrence and metastasis continue to pose major challenges. Vasculogenic mimicry (VM), a process in which tumor cells form vessel-like channels in the absence of endothelial cells, provides an alternative blood supply for tumor growth. The aim of the present study was to elucidate the association between VM and breast cancer prognosis and to establish a prognostic prediction model incorporating VM. The present study retrospectively analyzed 120 patients diagnosed with breast cancer and treated with curative surgery at Affiliated Hospital of Guangdong Medical University (Zhanjiang, China) between January 2020 and April 2022. Routine postoperative pathological assessment was performed, followed by CD34/periodic acid-Schiff double staining to detect VM structures within tumor tissues. Associations between VM and baseline characteristics, peripheral blood indices, pathological features and clinical variables were examined. Cox proportional hazards regression analysis was used to evaluate the prognostic significance of VM and a predictive model was constructed by integrating VM with other independent prognostic factors. Disease-free survival (DFS) was defined as the study endpoint. Model performance was evaluated and survival analysis was performed for individual risk factors as well as for the composite model. The presence of VM was reported to be significantly associated with advanced T stage (P=0.030), N stage (P=0.022), higher overall tumor stage (P=0.006) and elevated serum total cholesterol (P=0.015). VM positivity was associated with worse prognosis, with DFS significantly reduced in VM(+) patients (log-rank test; P<0.001). Multivariate analysis identified VM, N stage and Kiel-67 antigen (Ki-67) index as independent prognostic factors. A prediction model incorporating these variables demonstrated a robust performance, with a concordance index of 0.876 and a time-dependent area under the curve of 0.923, thereby providing strong support for individualized risk stratification and prognostic assessment in breast cancer. VM positivity, advanced nodal stage and a high Ki-67 index were reported to independently predict a reduced DFS following surgery. A prognostic model integrating VM, N stage and Ki-67 index exhibits high predictive accuracy and may serve as a valuable tool in evaluating the risk of recurrence and metastasis in the future.

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