Resveratrol activates CD8+ T cells through IL-18 bystander activation in lung adenocarcinoma

Dihydroartemisinin breaks the positive feedback loop of YAP1 and GLUT1-mediated aerobic glycolysis to boost the CD8+ effector T cells in hepatocellular carcinoma

Aerobic glycolysis is a hallmark of hepatocellular carcinoma (HCC). Dihydroartemisinin (DHA) exhibits antitumor activity towards liver cancer. Our previous studies have shown that DHA inhibits the Warburg effect in HCC cells. However, the mechanism still needs to be clarified. Our study aimed to elucidate the interaction between YAP1 and GLUT1-mediated aerobic glycolysis in HCC cells and focused on the underlying mechanisms of DHA inhibiting aerobic glycolysis in HCC cells. In this study, we confirmed that inhibition of YAP1 expression lowers GLUT1-mediated aerobic glycolysis in HCC cells and enhances the activity of CD8+T cells in the tumor niche. Then, we found that DHA was bound to cellular YAP1 in HCC cells. YAP1 knockdown inhibited GLUT1-mediated aerobic glycolysis, whereas YAP1 overexpression promoted GLUT1-mediated aerobic glycolysis in HCC cells. Notably, liver-specific Yap1 knockout by AAV8-TBG-Cre suppressed HIF-1α and GLUT1 expression in tumors but not para-tumors in DEN/TCPOBOP-induced HCC mice. Even more crucial is that YAP1 forms a positive feedback loop with GLUT1-mediated aerobic glycolysis, which is associated with HIF-1α in HCC cells. Finally, DHA reduced GLUT1-aerobic glycolysis in HCC cells through YAP1 and prevented the binding of YAP1 and HIF-1α. Collectively, our study revealed the mechanism of DHA inhibiting glycolysis in HCC cells from a perspective of a positive feedback loop involving YAP1 and GLUT1 mediated-aerobic glycolysis and provided a feasible therapeutic strategy for targeting enhanced aerobic glycolysis in HCC.

Resveratrol-βcd inhibited premature ovarian insufficiency progression by regulating granulosa cell autophagy

BACKGROUND

The ovarian environment of premature ovarian insufficiency (POI) patients exhibits immune dysregulation, which leads to excessive secretion of numerous proinflammatory cytokines that affect ovarian function. An abnormal level of macrophage polarization directly or indirectly inhibits the differentiation of ovarian granulosa cells and steroid hormone production, ultimately leading to POI. Resveratrol, as a health supplement, has been widely recognized for its safety. There is a substantial amount of evidence indicating that resveratrol and its analogs possess significant immune-regulatory functions. It has also been reported that resveratrol can effectively inhibit the progression of POI. However, the underlying immunological and molecular mechanisms through which resveratrol inhibits the progression of POI are still unclear.

RESULTS

Our preliminary reports have shown that resveratrol-βcd, the beta-cyclodextrin complex of resveratrol, significantly enhances the stability of resveratrol. Resveratrol-βcd could regulate the dysfunctional immune status of macrophages and T cells in the tumor microenvironment. In this study, we treated busulfan and cyclophosphamide (B/C)-treated mice, which were used as a POI model, with resveratrol-βcd. After resveratrol-βcd treatment, the levels of IL-6 in the ovaries were significantly increased, and the progression of POI was suppressed. IL-6 activated granulosa cells (GCs) through soluble IL-6R (sIL-6R), promoting autophagy in GCs. Resveratrol-βcd and IL-6 had a synergistic effect on enhancing autophagy in GCs and promoting E2 secretion.

CONCLUSIONS

We partially elucidated the immune mechanism by which resveratrol inhibits the progression of POI and the autophagy-regulating function of GCs. This provides a theoretical basis for using resveratrol to prevent POI in future studies and clinical guidance.

Establishment and validation of a novel risk model based on CD8T cell marker genes to predict prognosis in thyroid cancer by integrated analysis of single-cell and bulk RNA-sequencing

Papillary thyroid cancer (PTC) is a histological type of thyroid cancer, and CD8T is important for the immune response. The single-cell RNA data were acquired from Gene Expression Omnibus. SingleR package was used for cluster identification, and CellChat was exploited to evaluate the interaction among several cell types. Bulk RNA data obtained from the cancer genome atlas were used for determination of prognosis using Kaplan-Meier and Receiver Operating Characteristic curve. The Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis were applied for assessment of function enrichment. The drug sensitivity was calculated in Gene Set Cancer Analysis. The regulatory network was constructed by STRING and Cytoscape. We identified 23 cell clusters and 10 cell types. Cell communication results showed CD8T cell was vital among all immune cell types. Enrichment analysis found the marker genes of CD8T cell was enriched in some signal pathways related to tumor development. Overall, FAM107B and TUBA4A were considered as hub genes and used to construct a risk model. Most immune checkpoint expressions were upregulated in tumor group. Tumor mutation burden results indicated that prognosis of PTC was not related to the mutation of hub genes. Drug sensitivity analysis showed some drugs could be effectively used for the treatment of PTC, and regulatory network identified some targets for the immunotherapy. A 2-gene model of PTC was developed based on the single-cell RNA and bulk RNA data. Besides, we found CD8T was essential for the immune response in PTC.

Unraveling the role of disulfidptosis-related LncRNAs in colon cancer: a prognostic indicator for immunotherapy response, chemotherapy sensitivity, and insights into cell death mechanisms

Background: Colon cancer, a prevalent and deadly malignancy worldwide, ranks as the third leading cause of cancer-related mortality. Disulfidptosis stress triggers a unique form of programmed cell death known as disulfidoptosis, characterized by excessive intracellular cystine accumulation. This study aimed to establish reliable bioindicators based on long non-coding RNAs (LncRNAs) associated with disulfidptosis-induced cell death, providing novel insights into immunotherapeutic response and prognostic assessment in patients with colon adenocarcinoma (COAD). Methods: Univariate Cox proportional hazard analysis and Lasso regression analysis were performed to identify differentially expressed genes strongly associated with prognosis. Subsequently, a multifactorial model for prognostic risk assessment was developed using multiple Cox proportional hazard regression. Furthermore, we conducted comprehensive evaluations of the characteristics of disulfidptosis response-related LncRNAs, considering clinicopathological features, tumor microenvironment, and chemotherapy sensitivity. The expression levels of prognosis-related genes in COAD patients were validated using quantitative real-time fluorescence PCR (qRT-PCR). Additionally, the role of ZEB1-SA1 in colon cancer was investigated through CCK8 assays, wound healing experiment and transwell experiments. Results: disulfidptosis response-related LncRNAs were identified as robust predictors of COAD prognosis. Multifactorial analysis revealed that the risk score derived from these LncRNAs served as an independent prognostic factor for COAD. Patients in the low-risk group exhibited superior overall survival (OS) compared to those in the high-risk group. Accordingly, our developed Nomogram prediction model, integrating clinical characteristics and risk scores, demonstrated excellent prognostic efficacy. In vitro experiments demonstrated that ZEB1-SA1 promoted the proliferation and migration of COAD cells. Conclusion: Leveraging medical big data and artificial intelligence, we constructed a prediction model for disulfidptosis response-related LncRNAs based on the TCGA-COAD cohort, enabling accurate prognostic prediction in colon cancer patients. The implementation of this model in clinical practice can facilitate precise classification of COAD patients, identification of specific subgroups more likely to respond favorably to immunotherapy and chemotherapy, and inform the development of personalized treatment strategies for COAD patients based on scientific evidence.