New perspectives in prognostication of hepatocellular carcinoma: The role and clinical implications of transient receptor potential family genes.

The study titled "Transient receptor potential-related risk model predicts prognosis of hepatocellular carcinoma patients" is a significant contribution to hepatocellular carcinoma (HCC) research, highlighting the role of transient receptor potential (TRP) family genes in the disease's progression and prognosis. Utilizing data from The Cancer Genome Atlas database, it establishes a new risk assessment model, emphasizing the interaction of TRP genes with tumor proliferation pathways, key metabolic reactions like retinol metabolism, and the tumor immune microenvironment. Notably, the overexpression of the TRPC1 gene in HCC correlates with poorer patient survival outcomes, suggesting its potential as a prognostic biomarker and a target for personalized therapy, particularly in strategies combining immunotherapy and anti-TRP agents.

Development of an innovative nomogram of risk factors to predict postoperative recurrence of gastrointestinal stromal tumors.

BACKGROUND: There are many staging systems for gastrointestinal stromal tumors (GISTs), and the risk indicators selected are also different; thus, it is not possible to quantify the risk of recurrence among individual patients. AIM: To develop and internally validate a model to identify the risk factors for GIST recurrence after surgery. METHODS: The least absolute shrinkage and selection operator (LASSO) regression model was performed to identify the optimum clinical features for the GIST recurrence risk model. Multivariable logistic regression analysis was used to develop a prediction model that incorporated the possible factors selected by the LASSO regression model. The index of concordance (C-index), calibration curve, receiver operating characteristic curve (ROC), and decision curve analysis were used to assess the discrimination, calibration, and clinical usefulness of the predictive model. Internal validation of the clinical predictive capability was also evaluated by bootstrapping validation. RESULTS: The nomogram included tumor site, lesion size, mitotic rate/50 high power fields, Ki-67 index, intracranial necrosis, and age as predictors. The model presented perfect discrimination with a reliable C-index of 0.836 (95%CI: 0.712-0.960), and a high C-index value of 0.714 was also confirmed by interval validation. The area under the curve value of this prediction nomogram was 0.704, and the ROC result indicated good predictive value. Decision curve analysis showed that the predicting recurrence nomogram was clinically feasible when the recurrence rate exceeded 5% after surgery. CONCLUSION: This recurrence nomogram combines tumor site, lesion size, mitotic rate, Ki-67 index, intracranial necrosis, and age and can easily predict patient prognosis.

Pyroptosis-related genes play a significant role in the prognosis of gastric cancer.

BACKGROUND: Pyroptosis is an inflammatory form of programmed cell death, which has been shown to be related to the prognosis of many tumors. However, its role in gastric cancer (GC) is not fully understood. AIM: To evaluate the expression of pyroptosis-related genes in GC and its correlation with prognosis. METHODS: We constructed prognostic multigene markers of differentially expressed genes associated with pyroptosis by least absolute contraction and selection operator Cox regression. The risk model was analyzed by Kaplan-Meier curve, two-sided log-rank test and functional enrichment analysis. RESULTS: Sixty-three pyroptosis-related genes were differentially expressed in tumor tissues and adjacent nontumor tissues. Based on these differentially expressed genes, 5 gene signature were constructed and all GC patients were classified into two risk groups. Kaplan-Meier survival curve showed that the overall survival (OS) of patients in the high-risk group was significantly lower than that of the low-risk group. Multivariate Cox regression analyses showed that the risk score was an independent risk factor for OS. Receiver operating characteristic curve analysis confirmed the predictive ability of the model. External validation indicated increased OS in the low-risk group. The immune function and immune cell scores of the high-risk group were generally higher than those of the low-risk group. CONCLUSION: Pyroptosis-related genes play a significant role in tumor immune microenvironment. This novel model, which contains 5 pyroptosis-related genes, is an independent predicting factor for OS in GC patients, and may help to evaluate the prognosis of GC.

Extracellular vesicles derived from astrocytes facilitated neurite elongation by activating the Hippo pathway.

Spinal cord injury (SCI) often causes severe neurological dysfunction, and facilitating neurite elongation is particularly important in its treatment. Astrocytes (AS) play an important role in the central nervous system (CNS), and their high plasticity and versatility provide a feasible entry point for relevant research. Our purpose was to explore whether extracellular vesicles (EVs) from astrocytes (AS-EVs) and lipopolysaccharide (LPS)-preactivated astrocytes (LPAS-EVs) facilitate neurite elongation, to explore the underlying mechanism, and to verify whether these EVs promote locomotor recovery in rats. We used LPS to preactivate astrocytes and cocultured them with PC12 cells to observe neurite changes, then extracted and identified AS-EVs and LPAS-EVs and the role and mechanism of these EVs in facilitating neurite elongation was examined in vivo and vitro. We demonstrated that AS-EVs and LPAS-EVs facilitated the elongation of neurites and the recovery of rats with SCI. LPAS-EVs had a stronger effect than AS-EVs, by activating the Hippo pathway, promoting monopole spindle binding protein 1 (MOB1) expression, and reducing Yes-associated protein (YAP) levels. The data also suggest a feedback regulation between MOB1 and p-YAP/YAP. In sum, AS-EVs and LPAS-EVs can play an active role in facilitating neurite elongation by activating the Hippo pathway. These findings provide a new strategy for treating SCI and other CNS-related injuries.

Retraction Note: The diagnostic nomogram of platelet-based score models for hepatic alveolar echinococcosis and atypical liver cancer.

Editor's Note: this Article has been retracted; the Retraction Note is available at https://www.nature.com/articles/s41598-020-73758-x.

The diagnostic nomogram of platelet-based score models for hepatic alveolar echinococcosis and atypical liver cancer.

Hepatic alveolar echinococcosis (HAE) and liver cancer had similarities in imaging results, clinical characteristics, and so on. And it is difficult for clinicians to distinguish them before operation. The aim of our study was to build a differential diagnosis nomogram based on platelet (PLT) score model and use internal validation to check the model. The predicting model was constructed by the retrospective database that included in 153 patients with HAE (66 cases) or liver cancer (87 cases), and all cases was confirmed by clinicopathology and collected from November 2011 to December 2018. Lasso regression analysis model was used to construct data dimensionality reduction, elements selection, and building prediction model based on the 9 PLT-based scores. A multi-factor regression analysis was performed to construct a simplified prediction model, and we added the selected PLT-based scores and relevant clinicopathologic features into the nomogram. Identification capability, calibration, and clinical serviceability of the simplified model were evaluated by the Harrell's concordance index (C-index), calibration plot, receiver operating characteristic curve (ROC), and decision curve. An internal validation was also evaluated by the bootstrap resampling. The simplified model, including in 4 selected factors, was significantly associated with differential diagnosis of HAE and liver cancer. Predictors of the simplified diagnosis nomogram consisted of the API index, the FIB-4 index, fibro-quotent (FibroQ), and fibrosis index constructed by King's College Hospital (King's score). The model presented a perfect identification capability, with a high C-index of 0.929 (0.919 through internal validation), and good calibration. The area under the curve (AUC) values of this simplified prediction nomogram was 0.929, and the result of ROC indicated that this nomogram had a good predictive value. Decision curve analysis showed that our differential diagnosis nomogram had clinically identification capability. In conclusion, the differential diagnosis nomogram could be feasibly performed to verify the preoperative individualized diagnosis of HAE and liver cancer.

Clinicopathologic characteristics in patients with upper third gastric cancer following radical surgical treatment: A retrospective cohort study.

The incidences of upper third gastric cancer (UTGC) have been increasing. However, the prognostic factors for UTGC following radical surgical treatment remains largely unknown. This study was to investigate prognostic factors for overall survival (OS), lymph node metastasis and recurrence of UTGC.Clinicopathologic data of 126 UTGC patients who underwent radical surgical treatment were retrospectively analyzed. OS and univariate analysis were determined by Kaplan-Meier analysis and the significance of the difference between curves was calculated with the log-rank test. The Cox proportional hazards regression model was applied to perform multivariate analysis. Receiver operating characteristic (ROC) curve analysis was used to determine the prognostic accuracy.The 1-, 3-, and 5-year OS for patients with UTGC were 81%, 47.6%, and 38.6% respectively. Univariate analysis showed that tumor size (P = .019), tumor invasion depth (P < .001), and lymph node metastasis (P < .001) were the risk factors for 5-year OS. Multivariate analysis identified tumor invasion depth (P < .001) and lymph node metastasis (P < .001) as independent prognostic factors for the 5-year OS in patients with UTGC. In addition, ROC curve analysis showed that tumor invasion depth (P = .017) or lymph node metastasis (P = .001) alone showed significantly effective prognosis for the 5-year OS in patients with UTGC. For UTGC patients with lymph node metastasis, tumor size (P = .023), lym embolism (P = .003), tumor invasion depth (P = .002), and invasion of tunica serosa (P = .004) were the risk factors for the 5-year OS. Multivariate analysis identified tumor size (P = .048), lym embolism (P = .032), tumor invasion depth (P = .004), and invasion of tunica serosa (P = .031) as independent prognostic factors for the 5-year OS. For UTGC patients with distant metastasis or tumor recurrence, univariate and multivariate analyses demonstrated that tumor invasion depth and lymph node metastasis were independent prognostic factors for the 5-year OS.The results suggested that for UPGC patients undergoing the radical surgical treatment, tumor invasion depth and/or lymph node metastasis are the independent prognostic factors for the 5-year OS, lymph node metastasis, distant metastasis and tumor recurrence.