RESUMO
Background: Early identification of response to neoadjuvant chemotherapy (NAC) is instrumental in predicting patients prognosis. However, since a fixed criterion with high accuracy cannot be generalized to molecular subtypes, our study first aimed to redefine grades of clinical response to NAC in invasive breast cancer patients (IBC). And then developed a prognostic model based on clinical features and ultrasound semantics. Methods: A total of 480 IBC patients were enrolled who underwent anthracycline and taxane-based NAC between 2018 and 2020. The decrease rate of the largest diameter was calculated by ultrasound after NAC and their cut-off points were determined among subtypes. Thereafter, a nomogram was constructed based on clinicopathological and ultrasound-related data, and validated using the calibration curve, receiver operating characteristic (ROC) curve, decision curve analysis (DCA), and clinical impact curve (CIC). Results: The optimal cut-off points for predicting pCR were 53.23%, 51.56%, 41.89%, and 53.52% in luminal B-like (HER2 negative), luminal B-like (HER2 positive), HER2 positive, and triple-negative, respectively. In addition, time interval, tumor size, molecular subtypes, largest diameter decrease rate, and change of blood perfusion were significantly associated with pCR (all p < 0.05). The prediction model based on the above variables has great predictive power and clinical value. Conclusion: Taken together, our data demonstrated that calculated cut-off points of tumor reduction rates could be reliable in predicting pathological response to NAC and developed nomogram predicting prognosis would help tailor systematic regimens with high precision.
RESUMO
BACKGROUND: Breast cancer has become the most frequently diagnosed cancer worldwide. Increasing evidence indicated that zinc finger proteins (ZNFs), the largest family of transcription factors, contribute to cancer development and progression. Although ZNF384 is overexpressed in several types of human cancer, the role of ZNF384 in breast cancer remains unknown. Therefore, our research focused on ZNF384 regulation of the malignant phenotype of breast cancer and the underlying molecular mechanisms. METHODS: CCK-8 and colony formation assays were used to evaluate cell proliferation. Transwell and scratch assays were used to evaluate the cell migration and invasion. Chromatin immunoprecipitation (ChIP)-qPCR and luciferase reporter assays were used to confirm the target relationship between ZNF384 and zinc finger E-box binding homeobox 1 (ZEB1). Xenografts were used to monitor the targets in vivo effects. RESULTS: We noted that ZNF384 was significantly overexpressed in breast cancer and highlighted the oncogenic mechanism of ZNF384. ZNF384 transactivated ZEB1 expression and induced an epithelial and mesenchymal-like phenotype, resulting in breast cancer metastasis. Furthermore, ZNF384 may be a target of miR-485-5p, and ZEB1 can up-regulate ZNF384 expression by repressing miR-485-5p expression. Together, we unveiled a feedback loop of ZNF384-ZEB1 in breast cancer metastasis. CONCLUSIONS: The findings suggest that ZNF384 can serve as a prognostic factor and a therapeutic target for breast cancer patients.
