Short-term recovery in patients suffering hypoparathyroid after thyroidectomy: a case control study.

BACKGROUND: Postoperative hypoparathyroidism is the main reason for outpatient follow-up and long-term oral calcium and calcitriol treatment. Our study investigated the influencing factors and powerful predictors of short-term postoperative parathyroid function recovery. METHODS: Logistic regression was used to compare the clinicopathological characteristics; surgical details; and serum calcium (Ca), magnesium (Mg), and phosphorus (P) concentrations of patients. A receiver operating characteristic (ROC) curve was used to analyze the predictors of normal parathyroid hormone (PTH). RESULTS: Among the 111 patients with PTH < 10 pg/mL on the first postoperative day, most patients experienced a return to normal PTH (PTH > 15 pg/mL) within 30 days postoperatively. Univariate analysis showed that Pod (postoperative day) 1 PTH, Pod3 PTH, Pod7 Ca, Pod7 Mg, and Pod7 P (P < 0.05) were associated with parathyroid function recovery to normal on the seventh postoperative day. Multivariate logistic regression analysis revealed the following independent risk factors for normal PTH levels at Pod7 after thyroidectomy: Pod3 PTH (P = 0.038), Pod1 PTH (P = 0.056), Pod7 Mg (P = 0.001), Pod7 P (P = 0.020), and the number of parathyroid glands in situ intraoperatively. The combined sensitivity of serum magnesium concentration and phosphorus concentration to predict parathyroid function recover to normal on the seventh postoperative day was 82.76%, with a sensitivity of 76.83%. CONCLUSION: Serum magnesium, phosphorus and PTH concentrations are important influencing factors and effective predictors of short-term postoperative parathyroid function recovery to normal. Serum ion is an effective auxiliary diagnostic method for hypoparathyroidism after thyroidectomy.

Long Noncoding RNA HOXA-AS2 Promotes Papillary Thyroid Cancer Progression by Regulating miR-520c-3p/S100A4 Pathway.

BACKGROUND/AIMS: Thyroid cancer is one of the most prevalent endocrine tumors. The present study examined the effects of lncRNA HOXA cluster antisense RNA2 (HOXA-AS2) on the progression of papillary thyroid cancer (PTC), and explored the underlying molecular mechanisms. METHODS: Quantitative real-time PCR was used to detect HOXA-AS2, miR-520c-3p and S100 calcium-binding protein A4 (S100A4) expression. Furthermore, the effects of HOXA-AS2 silencing and overexpression on cell proliferation, migration, and invasion were assessed in PTC in vitro by CCK8 and transwell assay. Furthermore, bioinformatics online programs predicted and luciferase reporter assay were used to validate the association of HOXA-AS2 and miR-520c-3p in PTC. RESULTS: We observed that HOXA-AS2 was up-regulated in PTC tissues. In vitro experiments revealed that HOXA-AS2 knockdown significantly inhibited cell growth in PTC in vitro and in vivo. Further functional assays indicated that HOXA-AS2 significantly promoted PTC cell migration and invasion by promoting EMT. Bioinformatics online programs predicted that HOXA-AS2 sponge miR-520c-3p at 3'-UTR with complementary binding sites, which was validated using luciferase reporter assay. HOXA-AS2 could negatively regulate the expression of miR-520c-3p in PTC cells. MiR-520c-3p was down-regulated in PTC tissues, and S100A4 was predicted as a downstream target of miR-520c-3p, which was confirmed by luciferase reporter assay. CONCLUSION: In summary, our results suggested that the HOXA-AS2/miR-520c-3p/S100A4 axis may play an important role in the regulation of PTC progression, which provides us with new insights into understanding the PTC.

Prognostic costimulatory molecule-related signature risk model correlates with immunotherapy response in colon cancer.

Costimulatory molecules can promote the activation and proliferation of T cells and play an essential role in immunotherapy. However, their role in the prognosis of colon adenocarcinoma remains elusive. In this study, the expression data of costimulatory molecules and clinicopathological information of 429 patients with colon adenocarcinoma were obtained from The Cancer Genome Atlas database. The patients were divided into training and verification cohorts. Correlation, Cox regression, and Lasso regression analyses were performed to identify costimulatory molecules related to prognosis. After mentioning the construction of the risk mode, a nomogram integrating the clinical characteristics and risk scores of patients was constructed to predict prognosis. Eventually, three prognostic costimulatory molecules were identified and used for constructing a risk model. High expression of these three molecules indicated a poor prognosis. The predictive accuracy of the risk model was verified in the GSE17536 dataset. Subsequently, multivariate regression analysis showed that the signature based on the three costimulatory molecules was an independent risk factor in the training cohort (HR = 2.12; 95% CI = 1.26, 3.56). Based on the risk model and clinicopathological data, the AUC values for predicting the 1-, 3-, and 5-year survival probability of patients with colon adenocarcinoma were 0.77, 0.77, and 0.71, respectively. To the best of our knowledge, this study is the first to report a risk signature constructed based on the costimulatory molecules TNFRSF10c, TNFRSF13c, and TNFRSF11a. This risk signature can serve as a prognostic biomarker for colon adenocarcinoma and is related to the immunotherapeutic response of patients.