Xiaoyan Wang

TIPE2 inhibits the migration and invasion of epithelial ovarian cancer cells by targeting Smad2 to reverse TGF ‐β1‐induced EMT

Abstract Epithelial ovarian cancer is the deadliest gynecologic malignancy, characterized by high metastasis. Transforming growth factor‐β1 (TGF‐β1) drives epithelial‐ mesenchymal transformation (EMT), a key process in tumor metastasis. Tumor necrosis factor‐α‐induced protein 8 (TNFAIP8)‐like 2 (TIPE2) acts as a negative regulator of innate and adaptive immunity and involves in various cancers. However, its relationship with TGF‐β1 in ovarian cancer and its role in reversing TGF‐β1‐induced EMT remain unclear. This study examined TIPE2 mRNA and protein expression using quantitative RT‐PCR (qRT‐PCR), western blot and immunohistochemistry. The effects of TIPE2 overexpression and knockdown on the proliferation, migration and invasion of epithelial ovarian cancer cells were assessed through 5‐ethynyl‐2‐deoxyuridine, colony‐forming, transwell migration and invasion assays. The relationship between TIPE2 and TGF‐β1 was investigated using qRT‐PCR and enzyme‐linked immunosorbent assay, while the interaction between TIPE2 and Smad2 was identified via co‐immunoprecipitation. The results revealed that TIPE2 protein was significantly down‐regulated in epithelial ovarian cancer tissues and correlated with the pathological type of tumor, patients' age, tumor differentiation degree and FIGO stage. TIPE2 and TGF‐β1 appeared to play an opposite role to each other during the progression of human ovarian cancer cells. Furthermore, TIPE2 inhibited the metastasis and EMT of ovarian cancer cells by combining with Smad2 in vitro or in an intraperitoneal metastasis model. Consequently, these findings suggest that TIPE2 plays a crucial inhibitory role in ovarian cancer metastasis by modulating the TGF‐β1/Smad2/EMT signaling pathway and may serve as a potential target for ovarian cancer, providing important direction for future diagnostic and therapeutic strategies.

MRI Using Artificial Intelligence Algorithm to Evaluate Concurrent Chemoradiotherapy for Local Recurrence and Distant Metastasis of Cervical Squamous Cell Carcinoma

The aim of this study was to investigate the magnetic resonance imaging (MRI) features of patients with local recurrence and distant metastasis of cervical squamous cell carcinoma before and after concurrent chemoradiotherapy based on artificial intelligence algorithm. In this study, 100 patients with cervical squamous cell carcinoma with local recurrence and distant metastasis who underwent concurrent chemoradiotherapy were collected as the research subjects, and all underwent MRI multisequence imaging scans. At the same time, according to the evaluation criteria of solid tumor efficacy, patients with complete remission were classified into the effective group, and patients with partial remission, progressive disease, and stable disease were classified into the ineffective group. In addition, an image segmentation algorithm based on Balloon Snake model was proposed for MRI image processing, and simulation experiments were carried out. The results showed that the Dice coefficient of the proposed model segmentation of the reconstructed image was significantly higher than that of the level set model and the greedy algorithm, while the running time was the opposite ( P < 0.05 ). The lesion volume ( 38.76 ± 5.34  cm3) in the effective group after treatment was significantly smaller than that in the noneffective group ( 46.33 ± 4.64  cm3), and the rate of lesion volume shrinkage (28.71%) was significantly larger than that in the noneffective group (12.49%) ( P < 0.05 ). The relative apparent diffusion coefficient (rADC) value and rADC value change rate of the lesion after treatment in the effective group were significantly greater than those in the noneffective group ( P < 0.05 ). In summary, the image segmentation and reconstruction algorithm based on Balloon Snake model can not only improve the quality of MRI images but also shorten the processing time and improve the diagnostic efficiency. The volume regression rate and rADC value change rate of cervical squamous cell carcinoma lesion can reflect the early efficacy of concurrent chemoradiotherapy for cervical squamous cell carcinoma and have predictive value.