Chronic heat stress induces lung injury in broiler chickens by disrupting the pulmonary blood-air barrier and activating TLRs/NF-κB signaling pathway.

As an important respiratory organ, the lung is susceptible to damage during heat stress due to the accelerated breathing frequency caused by an increase in environmental temperature. This can affect the growth performance of animals and endanger their health. This study aimed to explore the mechanism of lung tissue damage caused by heat stress. Broilers were randomly divided into a control group (Control) and a heat stress group (HS). The HS group was exposed to 35°C heat stress for 12 h per d from 21-days old, and samples were taken from selected broilers at 28, 35, and 42-days old. The results showed a significant increase in lactate dehydrogenase (LDH) activity in the serum and myeloperoxidase (MPO) activity in the lungs of broiler chickens across all 3 age groups after heat stress (P < 0.01), while the total antioxidant capacity (T-AOC) was significantly enhanced at 35-days old (P < 0.01). Heat stress also led to significant increases in various proinflammatory factors in serum and expression levels of HSP60 and HSP70 in lung tissue. Histopathological results showed congestion and bleeding in lung blood vessels, shedding of pulmonary epithelial cells, and a large amount of inflammatory infiltration in the lungs after heat stress. The mRNA expression of TLRs/NF-κB-related genes showed an upward trend (P < 0.05) after heat stress, while the mRNA expression of MLCK, a gene related to pulmonary blood-air barrier, significantly increased after heat stress, and the expression levels of MLC, ZO-1, and occludin decreased in contrast. This change was also confirmed by Western blotting, indicating that the pulmonary blood-air barrier is damaged after heat stress. Heat stress can cause damage to the lung tissue of broiler chickens by disrupting the integrity of the blood-air barrier and increasing permeability. This effect is further augmented by the activation of TLRs/NF-κB signaling pathways leading to an intensified inflammatory response. As heat stress duration progresses, broiler chickens develop thermotolerance, which gradually mitigates the damaging effects induced by heat stress.

DNA Methylation-Specific Analysis of G Protein-Coupled Receptor-Related Genes in Pan-Cancer.

Tumor heterogeneity presents challenges for personalized diagnosis and treatment of cancer. The identification method of cancer-specific biomarkers has important applications for the diagnosis and treatment of cancer types. In this study, we analyzed the pan-cancer DNA methylation data from TCGA and GEO, and proposed a computational method to quantify the degree of specificity based on the level of DNA methylation of G protein-coupled receptor-related genes (GPCRs-related genes) and to identify specific GPCRs DNA methylation biomarkers (GRSDMs) in pan-cancer. Then, a ridge regression-based method was used to discover potential drugs through predicting the drug sensitivities of cancer samples. Finally, we predicted and verified 8 GRSDMs in adrenocortical carcinoma (ACC), rectum adenocarcinoma (READ), uveal Melanoma (UVM), thyroid carcinoma (THCA), and predicted 4 GRSDMs (F2RL3, DGKB, GRK5, PIK3R6) which were sensitive to 12 potential drugs. Our research provided a novel approach for the personalized diagnosis of cancer and informed individualized treatment decisions.

Exploring effects of DNA methylation and gene expression on pan-cancer drug response by mathematical models.

Since genetic alteration only accounts for 20%-30% in the drug effect-related factors, the role of epigenetic regulation mechanisms in drug response is gradually being valued. However, how epigenetic changes and abnormal gene expression affect the chemotherapy response remains unclear. Therefore, we constructed a variety of mathematical models based on the integrated DNA methylation, gene expression, and anticancer drug response data of cancer cell lines from pan-cancer levels to identify genes whose DNA methylation is associated with drug response and then to assess the impact of epigenetic regulation of gene expression on the sensitivity of anticancer drugs. The innovation of the mathematical models lies in: Linear regression model is followed by logistic regression model, which greatly shortens the calculation time and ensures the reliability of results by considering the covariates. Second, reconstruction of prediction models based on multiple dataset partition methods not only evaluates the model stability but also optimizes the drug-gene pairs. For 368,520 drug-gene pairs with P < 0.05 in linear models, 999 candidate pairs with both AUC ≥ 0.8 and P < 0.05 were obtained by logistic regression models between drug response and DNA methylation. Then 931 drug-gene pairs with 45 drugs and 491 genes were optimized by model stability assessment. Integrating both DNA methylation and gene expression markedly increased predictive power for 732 drug-gene pairs where 598 drug-gene pairs including 44 drugs and 359 genes were prioritized. Several drug target genes were enriched in the modules of the drug-gene-weighted interaction network. Besides, for cancer driver genes such as EGFR, MET, and TET2, synergistic effects of DNA methylation and gene expression can predict certain anticancer drugs' responses. In summary, we identified potential drug sensitivity-related markers from pan-cancer levels and concluded that synergistic regulation of DNA methylation and gene expression affect anticancer drug response.