EFHD2 suppresses intestinal inflammation by blocking intestinal epithelial cell TNFR1 internalization and cell death.

TNF acts as one pathogenic driver for inducing intestinal epithelial cell (IEC) death and substantial intestinal inflammation. How the IEC death is regulated to physiologically prevent intestinal inflammation needs further investigation. Here, we report that EF-hand domain-containing protein D2 (EFHD2), highly expressed in normal intestine tissues but decreased in intestinal biopsy samples of ulcerative colitis patients, protects intestinal epithelium from TNF-induced IEC apoptosis. EFHD2 inhibits TNF-induced apoptosis in primary IECs and intestinal organoids (enteroids). Mice deficient of Efhd2 in IECs exhibit excessive IEC death and exacerbated experimental colitis. Mechanistically, EFHD2 interacts with Cofilin and suppresses Cofilin phosphorylation, thus blocking TNF receptor I (TNFR1) internalization to inhibit IEC apoptosis and consequently protecting intestine from inflammation. Our findings deepen the understanding of EFHD2 as the key regulator of membrane receptor trafficking, providing insight into death receptor signals and autoinflammatory diseases.

A Novel Predictive Nomogram including Serum Lipoprotein a Level for Nonsentinel Lymph Node Metastases in Chinese Breast Cancer Patients with Positive Sentinel Lymph Node Metastases.

BACKGROUND: We developed a new nomogram combining serum biomarkers with clinicopathological features to improve the accuracy of prediction of nonsentinel lymph node (SLN) metastases in Chinese breast cancer patients. METHODS: We enrolled 209 patients with breast cancer who underwent SLN biopsy and axillary lymph node dissection. We evaluated the relationships between non-SLN metastases and clinicopathologic features, as well as preoperative routine tests of blood indexes, tumor markers, and serum lipids, including lipoprotein a (Lp(a)). Risk factors for non-SLN metastases were identified by logistic regression analysis. The nomogram was created using the R program to predict the risk of non-SLN metastases in the training set. Receiver operating characteristic (ROC) analysis was applied to assess the predictive value of the nomogram model in the validation set. RESULTS: Lp(a) was significantly associated with non-SLN metastasis status. Compared with the MSKCC model, the predictive ability of our new nomogram that combined Lp(a) level and clinical variables (pathologic tumor size, lymphovascular invasion, multifocality, and positive/negative SLN numbers) was significantly greater (AUC: 0.732, 95% CI: 0.643-0.821) (C-index: 0.703, 95% CI: 0.656-0.791) in the training cohorts and also performed well in the validation cohorts (C-index: 0.773, 95% CI: 0.681-0.865). Moreover, the new nomogram with Lp(a) improved the accuracy (12.10%) of identification of patients with non-SLN metastases (NRI: 0.121; 95% CI: 0.081-0.202; P = 0.011). CONCLUSIONS: This novel nomogram based on preoperative serum indexes combined with clinicopathologic features facilitates accurate prediction of risk of non-SLN metastases in Chinese patients with breast cancer.