Guo-Tian Ruan

Background: Several triglyceride-glucose (TyG)-related indices are used to assess insulin resistance (IR), but the better indicator for patients with cancer remains undetermined. The prognostic value of TyG-body mass index (TyG-BMI), its association with malnutrition, and underlying mediating mechanisms in large Chinese multicenter cohorts need further clarification. Methods: This prospective, multicenter study enrolled 5,221 patients with cancer from the INSCOC cohort. We compared the prognostic performance of TyG-BMI with other TyG-related IR indices. Logistic regression was used to explore the relationship between TyG-BMI and malnutrition (PGSGA). Cox regression and mediation analyses were performed to evaluate prognostic value and mediating pathways. Results: TyG-BMI was identified as a useful indicator TyG-related IR index, with the highest time-dependent AUC values and C-index. High TyG-BMI was independently associated with better overall survival (adjusted HR = 0.83, 95%CI: 0.76–0.91, p < 0.001) and lower malnutrition risk (adjusted OR = 0.42, 95%CI: 0.37–0.48, p < 0.001). The prognostic benefit was most significant in esophageal and colorectal cancer. Exploratory pathway decomposition analyses showed that PGSGA (48.2%), CRP (13.6%), KPS (18.5%), and ECOG PS (18.9%) accounted for partial components of the correlation between TyG-BMI and overall survival. Low TyG-BMI combined with malnutrition reduced 1-year survival in patients with cancer (1-year survival rate = 70.7%; median survival time = 27.2 months). Conclusion: TyG-BMI, a simple composite index based on routine clinical indicators, is a TyG-related insulin resistance index for Chinese patients with cancer. High TyG-BMI is significantly associated with a lower risk of malnutrition and better overall survival. Exploratory pathway analyses indicated nutritional status, systemic inflammation and physical function partially contributed to the crude correlation between TyG-BMI and survival. TyG-BMI and malnutrition are jointly associated with reduced survival outcomes in patients with cancer, supporting its clinical value for prognostic stratification and nutritional-metabolic management.

Cannabidiol (CBD), a major non-psychoactive phytocannabinoid derived from Cannabis sativa, has attracted increasing attention as a potential anticancer agent because of its pleiotropic biological activities and favorable safety profile. However, the mechanisms by which CBD regulates tumor cell death and their therapeutic relevance remain incompletely understood. This review summarizes current evidence on the molecular mechanisms by which CBD regulates tumor cell death across different cancer models. Available studies indicate that CBD exerts antitumor effects through multi-target and multi-pathway mechanisms involving oxidative stress, mitochondrial dysfunction, endoplasmic reticulum stress, calcium homeostasis imbalance, and modulation of signaling networks such as PI3K/Akt/mTOR, MAPK, NF-κB, and PPARγ. Through these interconnected processes, CBD can induce apoptosis, autophagy, ferroptosis, pyroptosis, and cell cycle arrest in a context-dependent manner. Notably, CBD may activate multiple regulated cell death pathways simultaneously or sequentially within the same tumor model, reflecting a broader stress-response network rather than a single cytotoxic mechanism. By coordinately engaging multiple cell death pathways and modulating the tumor microenvironment, CBD provides mechanistic insights and potential opportunities for the development of novel anticancer strategies. However, current evidence remains predominantly preclinical, while challenges related to oral bioavailability, pharmacokinetic variability, dose optimization, and potential drug interactions continue to limit translational progress. Collectively, available evidence suggests that CBD functions as a pleiotropic modulator of tumor cell fate rather than a classical single-target cytotoxic agent. Further mechanistic, pharmacological, and clinical studies are required to support the rational development of CBD-based anticancer therapies.

Background: Hyperuricaemia (HUA) is a common metabolic disease that has become a global public health burden. The Planetary Health Diet Index for the United States (PHDI-US), a sustainable dietary pattern emphasizing a plant-based diet, has great potential for chronic disease prevention and control, but its relationship with HUA is unclear.Methods: This study was based on nationally representative NHANES data. Multivariate logistic regression and restricted cubic spline models were used to assess the association between raw PHDI-US and HUA. The key dietary component Dairy was identified by machine learning, the optimized PHDI-Dairy index was constructed, and the association between dairy intake and HUA risk was verified in an independent self-built cohort.Results: Primitive PHDI-US was significantly negatively correlated with the risk of HUA, but its protective effect was weaker than traditional dietary indices such as AHEI, AEI, and MEDI. Machine learning results show that Dairy is the most critical component in PHDI-US composition. The PHDI-Dairy index, constructed after optimizing the weight of dairy products, was more negatively correlated with the risk of HUA, and the protection efficiency was better than that of other dietary indices. External validation further confirmed that increased dairy intake was associated with a low risk of HUA.Conclusion: PHDI-US was negatively correlated with the risk of HUA. After optimizing the weighting of dairy products, PHDI-Dairy demonstrated a significantly enhanced protective effect, outperforming both the original PHDI and other dietary indices. This result highlights its potential as a nutritional intervention tool for chronic diseases, contributing to both public health and environmental sustainability.

Background: Several studies give a superficial description that HEPACAM family member 2 (HEPACAM2) seems to be a prognostic biomarker in colon adenocarcinoma (COAD). While, systematic and in-depth research about diagnostic and prognostic value of HEPACAM2 in COAD patients is lacked. Besides, relationship between HEPACAM2 gene expression levels and immune cell infiltration is unclear. Methods: Firstly, we analyzed the differential expression levels of HEPACAM2 gene and diagnostic value from different databases. Secondly, a cohort of Guangxi COAD patients was established to verify HEPACAM2 expression pattern and diagnostic value. Thirdly, univariate and multivariate survival analysis of the prognostic value of HEPACAM2 gene in patients with COAD was performed. We also utilized joint-effects analysis and comprehensive prognosis analysis to investigate the prognostic value of HEPACAM2 and related genes. Finally, we explored the relationship between HEPACAM2 gene expression levels and immune cell infiltration.Results: In several biological databases, HEPACAM2 mRNA expression level in COAD tumor tissues was significantly lower than that of adjacent normal tissues. The diagnostic ROC curve results indicated that HEPACAM2 gene had a high diagnostic value in COAD. The qPCR verification results in the Guangxi cohort showed that HEPACAM2 expression level in COAD tumor tissues was significantly lower than that of adjacent normal tissues (PHEPACAM2 gene had a poorer overall survival (OS) in COAD patients when compared with those with high expression ((P = 0.038, HR (95% CI) = 0.635(0.414-0.976)). Joint-effects analysis and comprehensive prognosis analysis showed that high expression of HEPACAM2 combined with high expression of CLCA1, high expression of REP15, and high expression of B3GNT6 were associated with a better overall survival of COAD.Conclusion: This study suggested that the HEPACAM2 may be a diagnostic and prognostic biomarker for COAD. Besides, HEPACAM2 was involved with immune response progress, Chemokine signaling pathway, Ras signaling pathway and Hematopoietic cell lineage.