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OBJECTIVE: Precancerous metaplasia transition to dysplasia poses a risk for subsequent intestinal-type gastric adenocarcinoma. However, the molecular basis underlying the transformation from metaplastic to cancerous cells remains poorly understood. DESIGN: An integrated analysis of genes associated with metaplasia, dysplasia was conducted, verified and characterised in the gastric tissues of patients by single-cell RNA sequencing and immunostaining. Multiple mouse models, including homozygous conditional knockout Klhl21-floxed mice, were generated to investigate the role of Klhl21 deletion in stemness, DNA damage and tumour formation. Mass-spectrometry-based proteomics and ribosome sequencing were used to elucidate the underlying molecular mechanisms. RESULTS: Kelch-like protein 21 (KLHL21) expression progressively decreased in metaplasia, dysplasia and cancer. Genetic deletion of Klhl21 enhances the rapid proliferation of Mist1+ cells and their descendant cells. Klhl21 loss during metaplasia facilitates the recruitment of damaged cells into the cell cycle via STAT3 signalling. Increased STAT3 activity was confirmed in cancer cells lacking KLHL21, boosting self-renewal and tumourigenicity. Mechanistically, the loss of KLHL21 promotes PIK3CB mRNA translation by stabilising the PABPC1-eIF4G complex, subsequently causing STAT3 activation. Pharmacological STAT3 inhibition by TTI-101 elicited anticancer effects, effectively impeding the transition from metaplasia to dysplasia. In patients with gastric cancer, low levels of KLHL21 had a shorter survival rate and a worse response to adjuvant chemotherapy. CONCLUSIONS: Our findings highlighted that KLHL21 loss triggers STAT3 reactivation through PABPC1-mediated PIK3CB translational activation, and targeting STAT3 can reverse preneoplastic metaplasia in KLHL21-deficient stomachs.
RESUMO
PURPOSE: To assess the predictive value of an ultrasound-based radiomics-clinical nomogram for grading residual cancer burden (RCB) in breast cancer patients. METHODS: This retrospective study of breast cancer patients who underwent neoadjuvant therapy (NAC) and ultrasound scanning between November 2020 and July 2023. First, a radiomics model was established based on ultrasound images. Subsequently, multivariate LR (logistic regression) analysis incorporating both radiomic scores and clinical factors was performed to construct a nomogram. Finally, Receiver operating characteristics (ROC) curve analysis and decision curve analysis (DCA) were employed to evaluate and validate the diagnostic accuracy and effectiveness of the nomogram. RESULTS: A total of 1122 patients were included in this study. Among them, 427 patients exhibited a favorable response to NAC chemotherapy, while 695 patients demonstrated a poor response to NAC therapy. The radiomics model achieved an AUC value of 0.84 in the training cohort and 0.83 in the validation cohort. The ultrasound-based radiomics-clinical nomogram achieved an AUC value of 0.90 in the training cohort and 0.91 in the validation cohort. CONCLUSIONS: Ultrasound-based radiomics-clinical nomogram can accurately predict the effectiveness of NAC therapy by predicting RCB grading in breast cancer patients.