Background: Previous studies have indicated that chronic emotional stressors likely participate in the occurrence of cancers. However, direct evidence connecting stress and colorectal cancer development remains almost completely unexplored. Methods: Chronic stress mouse model was used to investigate the influence of stress on tumorigenesis. Several major agonists and antagonists of adrenergic receptors were applied to investigate the effects of β-adrenergic signaling on the development of CRC. Chromatin immunoprecipitation assays (CHIP) were used to investigate the binding of p53 and CEBPB to TRIM2 promoter. Mammosphere cultures, Cell Counting Kit-8 (CCK-8) assay, colony-formation assay, scratch wound healing assays, qPCR, immunofluorescence, coimmunoprecipitation and western blotting were used to explore the effect of stress-induced epinephrine on the CEBPB/TRIM2/P53 axis and the progress of CRC cells. Results: In this study, we found that stress-induced epinephrine (EPI) promotes the proliferation, metastasis and CSC generation of CRC primarily through the β2-adrenergic receptor. Furthermore, our studies also confirmed that chronic stress decreased the stability of p53 protein by promoting p53 ubiquitination. Results of transcriptome sequencing indicated that TRIM2 was overexpressed in cells treated with EPI. Further studies indicated that TRIM2 could regulate the stability of p53 protein by promoting p53 ubiquitination. Finally, we further proved that CEBPB was regulated by EPI and acts as the upstream transcription factor of TRIM2. Conclusions: Our studies proved that stress-induced EPI promotes the development and stemness of CRC through the CEBPB/TRIM2/P53 axis.

Background: Research has indicated that long-term sleep deprivation can lead to immune dysfunction and participate in the occurance and progression of tumors. However, the relationship between sleep deprivation and colon cancer remains unclear. This study explored the specific mechanism through which sleep deprivation promotes the proliferation and migration of colon cancer, with a focus on the neurotransmitter GABA. Methods: Chronic sleep deprivation mice model were used to investigate the effect of sleep disorder on tumors. We detected neurotransmitter levels in the peripheral blood of mice using ELISA. CCK-8 assay, colony formation assay, wound healing assay, and transwell assay were performed to investigate the effect of GABA on colon cancer cells, while immunofluorescence showed the distribution of macrophages in lung metastatic tissues. We isolated exosomes from a GABA-induced culture medium to explore the effects of GABA-induced colon cancer cells on macrophages. Gain- and loss-of-function experiments, luciferase report analysis, immunohistochemistry, and cytokine detection were performed to reveal the crosstalk between colon cancer cells and macrophages. Results: Sleep deprivation promote peripheral blood GABA level and colon cancer cell proliferation and migration. Immunofluorescence analysis revealed that GABA-induced colon cancer metastasis is associated with enhanced recruitment of macrophages in the lungs. The co-culture results showed that GABA intensified M2 polarization of macrophage induced by colon cancer cells. This effect is due to the activation of the macrophage MAPK pathway by tumor-derived exosomal miR-223-3p. Furthermore, M2-like macrophages promote tumor proliferation and migration by secreting IL-17. We also identified an endogenous miR-223-3p downregulation of the E3 ligase CBLB, which enhances the stability of cMYC protein and augments colon cancer cells proliferation and migration ability. Notably, cMYC acts as a transcription factor and can also regulate the expression of miR-223-3p. Conclusion: Our results suggest that sleep deprivation can promote the expression of miR-223-3p in colon cancer cells through GABA, leading to downregulation of the E3 ligase CBLB and inhibition of cMYC ubiquitination. Simultaneously, extracellular miR-223-3p promotes M2-like macrophage polarization, which leads to the secretion of IL-17, further enhancing the proliferation and migration of colon cancer cells.

Sleep deprivation (SD) has become a health problem in the modern society. Although probiotics supplementation has been proven to improve SD-induced gut dysbiosis, the potential neuroendocrine mechanisms remain elusive. In this study, thirty rhesus monkeys (RMs) were recruited. Paradoxical sleep, bright light, and noise were used to build an RM SD model. We examined the plasma γ-aminobutyric acid (GABA), stress hormones, and inflammatory cytokines using ELISAs. 16S ribosomal DNA sequencing and untargeted metabolomics sequencing were employed to detect gut microbial community and metabolites, respectively. The results of our study showed that RMs subjected to SD had elevated plasma stress hormones (such as cortisol and norepinephrine) and proinflammatory cytokines (such as TNF-α, IL-6, and IL-8), and a decreased anti‐inflammatory cytokine IL-10 level. Additionally, SD could give rise to a significant change in gut microbiota and metabolites. The differential gut microbiota and metabolites caused by SD were enriched in the signaling pathways related to GABA metabolism. Pearson correlation analysis revealed that there is a significant correlation between plasma GABA and SD-induced stress responses and gut dysbiosis. The supplementation of GABA-producing probiotics could significantly increase the relative abundance of Lactobacillus and plasma GABA levels, and reverse SD‐induced stress responses and gut dysbiosis. Therefore, we speculated that SD-induced stress response and gut dysbiosis might be an outcome of reduced gut-derived GABA absorption. The supplementation of GABA-producing Lactobacillus might be beneficial for the treatment of SD-induced intestinal dysfunction.

Accurately predicting survival in patients with early hepatocellular carcinoma (HCC) is essential for making informed decisions about treatment and prognosis. Herein, we have developed a machine learning (ML) model that can predict patient survival and guide treatment decisions. We obtained patient demographic information, tumor characteristics, and treatment details from the SEER database. To analyze the data, we employed a Cox proportional hazards (CoxPH) model as well as 3 ML algorithms: neural network multitask logistic regression (N-MLTR), DeepSurv, and random survival forest (RSF). Our evaluation relied on the concordance index (C-index) and Integrated Brier Score (IBS). Additionally, we provided personalized treatment recommendations regarding surgery and chemotherapy choices and validated models’ efficacy. A total of 1136 patients with early-stage (I, II) hepatocellular carcinoma (HCC) who underwent liver resection or transplantation were randomly divided into training and validation cohorts at a ratio of 3:7. Feature selection was conducted using Cox regression analyses. The ML models (NMLTR: C-index = 0.6793; DeepSurv: C-index = 0.7028; RSF: C-index = 0.6890) showed better discrimination in predicting survival than the standard CoxPH model (C-index = 0.6696). Patients who received recommended treatments had higher survival rates than those who received unrecommended treatments. ML-based surgery treatment recommendations yielded higher hazard ratios (HRs): NMTLR HR = 0.36 (95% CI: 0.25–0.51, P < .001), DeepSurv HR = 0.34 (95% CI: 0.24–0.49, P < .001), and RSF HR = 0.37 (95% CI: 0.26–0.52, P = <.001). Chemotherapy treatment recommendations were associated with significantly improved survival for DeepSurv (HR: 0.57; 95% CI: 0.4–0.82, P = .002) and RSF (HR: 0.66; 95% CI: 0.46–0.94, P = .020). The ML survival model has the potential to benefit prognostic evaluation and treatment of HCC. This novel analytical approach could provide reliable information on individual survival and treatment recommendations.

Immunosuppression often leads to drastic metabolic, hormonal, and physiological disorders. Changes in the gut microbiota are believed to be one of the factors contributing to these disorders, but the association remains uncertain. Clinical studies can be complicated by confounding variables, such as diet and other drivers of heterogeneity in human microbiomes. In this study, we identified pronounced gut microbiome signatures in rhesus macaques (RMs) with immunosuppression-induced lipid metabolism disorders following cyclosporine combined with dexamethasone. Furthermore, we observed similar changes in the gut microbiota of mice with immunosuppression-induced lipid metabolism disorders, which were associated with short-chain fatty acid metabolism. ELISA showed that immunosuppression significantly reduced the levels of butyric acid in both feces and serum of mice. Spearman correlation analysis identified a significant correlation between serum butyric acid levels and gut microbial dysbiosis induced by immunosuppression, particularly in relation to f_Lachnospiraceae, g_unidentified_Ruminococcaceae, and s_Clostridium leptum. Additionally, mice transplanted with gut microbiota from immunosuppressed mice exhibited hepatic lipid metabolism disorders, and RNA sequencing revealed significant downregulation of ABC transporters and PPARα in the liver, which was closely associated with lipid transport and metabolism, particularly Abca1. Moreover, butyric acid supplementation alleviated hepatic lipid metabolism disorders and upregulated the expression of Abca1 and PPARα in mice transplanted with immunosuppression-induced gut microbiota. Thus, we propose that the combination of cyclosporine and dexamethasone regulates the expression of hepatic Abca1 and PPARα by modulating the gut microbiota and its derived butyrate, particularly Lachnospiraceae and Clostridium leptum, further regulating hepatic lipid metabolism.