Tac2-N Promotes Glioma Proliferation and Indicates Poor Clinical Outcomes

Antidepressant advantage of Chaihushugan san in female mice: A novel signaling mechanism in hippocampus

ETHNOPHARMACOLOGICAL RELEVANCY

Chaihushugan san (CSS), a classic formula for soothing the liver and relieving depression, has been identified to produce rapid antidepressant-like effects in female mice. However, the gender predominance and underlying mechanisms of CSS's antidepressant remain unclear.

AIM OF THE STUDY

In this study, we focused on unraveling the gender predominance of CSS in antidepressant and the specific neuronal mechanisms that mediate this predominance.

METHODS AND MATERIALS

Tail suspension test (TST), forced swimming test (FST) and sucrose preference test (SPT) were used to evaluate depressive phenotypes or antidepressant-like effects of CSS in female and male chronic unpredictable mild stress (CUMS) mice model. RNA-sequencing was used to screen specific target for CSS antidepressant gender dominance. RT-PCR and elisa were used to detect the expressions of specific molecule, hormones, and inflammatory factors in the hippocampus. hippocampal viral overactivation and pharmacological blockade were used to detect the correlation between CSS antidepressant gender dominance and related targets.

RESULTS

In the present study, both female and male mice displayed depressive phenotypes including significant increasing immobility time in TST and reducing sucrose preference ratio in SPT after exposing CUMS for 3 weeks. However, acute administration of CSS (2, 4 g/kg) improved the depressive phenotypes only in female mice or not male mice at 2 h later. Moreover, the expressions of TC2N were increased only in female mice after exposing CUMS for 3 weeks, which were also reversed by CSS after a single administration 2 h later, but no alterations in male mice. The hippocampal expressions of estrogen receptor β (Erβ), pro-inflammatory factors (IL-1β and TNF-α) and anti-inflammatory factors (IL-10, TGF-β and IL-1Rα) were all abnormal in female CUMS mice model, which were all normalized by CSS. Furthermore, overactivation of hippocampal TC2N by AAV-TC2N+/+ blocked the antidepressant-like effects of CSS and the up-regulation of hippocampal Erβ in female mice. However, inhibition of Erβ blunted the antidepressant-like effects of CSS and CSS's suppression of pro-inflammatory factors (IL-1β and TNF-α), which had no any effect on hippocampal TC2N and anti-inflammatory factors (IL-10 and TGF-β).

CONCLUSIONS

The study revealed that CSS had antidepressant superiority in female mice depending on inhibiting hippocampal TC2N and then activating Erβ, further inhibiting the release of pro-inflammatory factors to produce antidepressant effects, which provided a basis for the guidance of CSS in clinical application, new ideas and targets for the development of drugs for depression with gender differences.

TC2N Promotes Cell Proliferation and Metastasis in Hepatocellular Carcinoma by Targeting the Wnt/β-Catenin Signaling Pathway

Hepatocellular carcinoma (HCC), one of the most prevalent types of cancer worldwide, has an exceedingly poor prognosis. Tandem C2 domain nuclear protein (TC2N) has been implicated in tumorigenesis and serves as an oncogene or tumor suppressor in different types of cancer. Here, we explore the possible regulatory activities and molecular mechanisms of TC2N in HCC progression. However, TC2N expression was significantly upregulated in HCC tissues and hepatoma cell lines, and this upregulation was positively correlated with tumor progression in HCC patients. The ectopic overexpression of TC2N accelerated the proliferation, migration, and invasion of HCC cells, whereas its knockdown showed the opposite effects. Bioinformatics analysis showed that TC2N participates in the regulation of the Wnt/β-catenin signaling pathway. Mechanistically, TC2N activated the Wnt/β-catenin signaling pathway by regulating the expression levels of β-catenin and its downstream targets CyclinD1, MMP7, c-Myc, c-Jun, AXIN2, and glutamine synthase. Furthermore, the deletion of β-catenin effectively neutralized the regulation of TC2N in HCC proliferation and metastasis. Overall, this study showed that TC2N promotes HCC proliferation and metastasis by activating the Wnt/β-catenin signaling pathway, indicating that TC2N might be a potential molecular target for the treatment of HCC.

Subtyping and grading of lower-grade gliomas using integrated feature selection and support vector machine

Classifying lower-grade gliomas (LGGs) is a crucial step for accurate therapeutic intervention. The histopathological classification of various subtypes of LGG, including astrocytoma, oligodendroglioma and oligoastrocytoma, suffers from intraobserver and interobserver variability leading to inaccurate classification and greater risk to patient health. We designed an efficient machine learning-based classification framework to diagnose LGG subtypes and grades using transcriptome data. First, we developed an integrated feature selection method based on correlation and support vector machine (SVM) recursive feature elimination. Then, implementation of the SVM classifier achieved superior accuracy compared with other machine learning frameworks. Most importantly, we found that the accuracy of subtype classification is always high (>90%) in a specific grade rather than in mixed grade (~80%) cancer. Differential co-expression analysis revealed higher heterogeneity in mixed grade cancer, resulting in reduced prediction accuracy. Our findings suggest that it is necessary to identify cancer grades and subtypes to attain a higher classification accuracy. Our six-class classification model efficiently predicts the grades and subtypes with an average accuracy of 91% (±0.02). Furthermore, we identify several predictive biomarkers using co-expression, gene set enrichment and survival analysis, indicating our framework is biologically interpretable and can potentially support the clinician.