ICD-related risk model predicts the prognosis and immunotherapy response of patients with liver cancer.

Immunogenic cell death (ICD) is a novel cell death mechanism that activates and regulates the immune system against cancer. However, its prognostic value in liver cancer remains unclear. Here, several algorithms such as correlation analysis, Cox regression analysis, and Lasso regression analysis were carried out to evaluate the prognostic value of ICD-related genes in patients with liver cancer. Three ICD-related prognostic genes, the prion protein gene (PRNP), dynamin 1-like gene (DNM1L), and caspase-8 (CASP8), were identified and used to construct a risk signature. Patients with liver cancer were categorized into high- and low-risk groups using the ICD-related signature. Subsequently, a multivariate regression analysis revealed that the signature was an independent risk factor in liver cancer [hazard ratio (HR) = 6.839; 95% confidence interval (CI) = 1.625-78.785]. Patient survival was also predicted using the risk model, with area under the curve values of 0.75, 0.70, and 0.69 for 1-, 3-, and 5-year survival, respectively. Finally, a prognostic nomogram containing the clinical characteristics and risk scores of patients was constructed. The constructed ICD-related signature could serve as a prognostic and immunotherapeutic biomarker in liver cancer.

Immune cell death-related lncRNA signature as a predictive factor of clinical outcomes and immune checkpoints in gastric cancer.

Background: Immune cell death (ICD) is a type of tumor cell death that has recently been shown to activate and regulate tumor immunity. However, the role of ICD-related long non-coding RNAs (lncRNAs) in gastric cancer remains to be clarified. Methods: We obtained 375 tumor samples from the Cancer Genome Atlas (TCGA) database and randomly assigned them to training and verification groups. LASSO and Cox regression analysis were utilized to identify ICD-related lncRNAs and establish a risk model. The changes in the immune microenvironment of the two groups were compared by examining the tumor-infiltrating immune cells. Results: We established a tumor signature based on nine ICD-related lncRNAs. In light of the receiver operating characteristic and Kaplan-Meier curves, the prognostic values of this risk model were verified. Multivariate regression analysis showed that the risk score was an independent risk factor for the prognosis of patients in both the training cohort (HR 2.52; 95% CI: 1.65-3.87) and validation cohort (HR 2.70; 95% CI: 1.54-4.8). A nomogram was developed to predict the 1-, 3-, and 5-year survival of patients with gastric cancer, and the signature was linked to high levels of immunological checkpoint expression (B7-H3, VSIR). Conclusions: An ICD-related lncRNA signature could predict the immune response and prognosis of patients with gastric cancer. This prognostic signature could be employed to independently monitor the efficacy of immunotherapy for gastric cancer patients.

The safety, benefits and future development of overnight and outpatient thyroidectomy.

With the development of medical care, the safety of thyroidectomy is improving year by year. Due to economic benefits and other advantages of the overnight and outpatient thyroidectomy, more and more patients and medical institutions have favored overnight and outpatient thyroidectomy, and its proportion in thyroidectomy has increased year by year. However, overnight and outpatient thyroidectomy still faces many challenges and remains to be improved. In this review, we focused on the recent progress and the relevant clinical features of overnight and outpatient thyroidectomy, including its safety, economic benefits, etc., which may bring valuable clues and information for further improvements of patient benefits and promotions of overnight or outpatient thyroidectomy in the future.

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.

A prognostic exosome-related LncRNA risk model correlates with the immune microenvironment in liver cancer.

Background: Emerging studies have shown the important roles of long noncoding RNAs (lncRNAs) in the occurrence and development of liver cancer. However, the exosome-related lncRNA signature in liver cancer remains to be clarified. Methods: We obtained 371 tumor specimens and 50 normal tissues from the TCGA database. These samples were randomly divided into the training queue and verification queue. The exosome-related lncRNA risk model was verified by correlation analysis, Lasso regression analysis, and Cox regression analysis. The differences in the immune microenvironment in the two risk groups were obtained by analyzing the infiltration of different immune cells. Results: Five exosome-related lncRNAs associated (MKLN1-AS, TMCC1-AS1, AL031985.3, LINC01138, AC099850.3) with a poor prognosis were identified and used to construct the signature. Receiver operating curve (ROC) and survival curves were used to confirm the predictive ability of this signature. Based on multivariate regression analysis in the training cohort (HR: 3.033, 95% CI: 1.762-5.220) and validation cohort (HR: 1.998, 95% CI: 1.065-3.751), the risk score was found to be an independent risk factor for patient prognosis. Subsequently, a nomogram was constructed to predict the 1-, 3-, 5-years survival rates of liver cancer patients. Moreover, this signature was also related to overexpressed immune checkpoints (PD-1, B7-H3, VSIR, PD-L1, LAG3, TIGIT and CTLA4). Conclusion: Our study showed that exosome-related lncRNAs and the corresponding nomogram could be used as a better index to predict the outcome and immune regulation of liver cancer patients. This signature might provide a new idea for the immunotherapy of liver cancer in the future.

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.

Identifying the Transcriptional Regulatory Network Associated With Extrathyroidal Extension in Papillary Thyroid Carcinoma by Comprehensive Bioinformatics Analysis.

Extrathyroidal extension (ETE) affects papillary thyroid cancer (PTC) prognosis. The objective of this study was to identify biomarkers for ETE and explore the mechanisms controlling its development in PTC. We performed a comprehensive bioinformatics analysis using several datasets. Differential expression analysis and weighted gene co-expression network analysis (WGCNA) on 58 paired PTC samples from The Cancer Genome Atlas (TCGA) were used to detect ETE-related mRNA and long noncoding (lnc) RNA modules and construct an lncRNA/mRNA network. An independent TCGA dataset containing 438 samples was utilized to validate and characterize the WGCNA results. Functional annotation was used to identify the biological functions and related pathways of ETE modules. Two independent RNA sequencing datasets were combined to crossvalidate relationships between lncRNAs and mRNAs by Pearson correlation analysis. Transcription factors (TFs) for affected genes were predicted using the binding motif data from Ensembl Biomart to construct a TF/lncRNA/mRNA network. Other two independent datasets were used to crossvalidate TF-mRNA associations. Finally, receiver operating characteristic, survival analyses, and Cox proportional hazard regression model were performed to explore the significance of hub genes in ETE diagnosis and PTC prognosis. Three mRNA modules and two lncRNA modules were significantly associated with ETE. Enrichment analysis showed extracellular matrix changes was closely related to the development of ETE. A TF/lncRNA/mRNA regulatory network was constructed containing 33 validated hub genes, 64 lncRNAs, and 64 TFs, all differentially expressed between ETE and non-ETE samples. Unc-5 family C-terminal like [area under the curve (AUC): 0.711], sushi repeat containing protein X-linked 2 (AUC: 0.706), lysyl oxidase (AUC: 0.704), collagen type I alpha 1 chain (AUC: 0.704), and collagen type X alpha 1 chain (AUC: 0.704) were the most highly significant hub genes for ETE diagnosis. The Cox proportional hazard regression model constructed with hub genes showed significant survival differences between low- and high-risk groups (p = 0.00025) and performed good prediction for PTC prognosis(AUC = 0.794; C-index = 0.895). The identification of 33 biomarkers and TF/lncRNA/mRNA regulatory network would provide new insights into the molecular mechanisms of ETE besides the prognosis model may have important clinical implications in the improvement of PTC risk stratification, therapeutic decision-making, and prognosis prediction.

Hashimoto's thyroiditis elicits decreased diagnostic efficacy of thyroid nodule ultrasound-guided fine needle aspiration.

BACKGROUND: False negative (FN) or false positive (FP) results of thyroid ultrasound-guided fine needle aspiration (US-guided FNA) cause missed diagnosis of thyroid cancer or unnecessary thyroidectomy. PURPOSE: To explore the impact of Hashimoto's thyroiditis (HT) on the diagnostic efficacy of US-guided FNA and to analyze the differences in diagnostic efficacy between US-guided FNA and thyroid ultrasonography (US) in patients with HT. METHOD: Medical records were reviewed retrospectively. Patients with and without Hashimoto's thyroiditis (HT) were included in the exposure and non-exposure group, respectively. RESULTS: HT was not an independent risk factor for thyroid cancer. The percentage of undetermined results of US-guided FNA (Bethesda I, III, IV) in the exposure group was significantly higher. The US-guided FNA's diagnostic sensitivity, specificity, and accuracy were significantly lower, and FP rate (FPR) and FN rate (FNR) were higher in the exposure group. In the exposure group, US tended to give higher diagnostic sensitivity, accuracy, PPV, NPV, and lower FPR and FNR. Receiver operating characteristic (ROC) curve analysis showed that, in the exposure group the diagnostic efficacy of thyroid US was significantly higher than of US-guided FNA. CONCLUSION: HT tends to cause undetermined results and elicit lower diagnostic performance of US-guided FNA. In patients with HT, the diagnostic efficacy of thyroid US is, at least, not inferior to US-guided FNA.