CD8⁺ T cells, a cytotoxic T lymphocyte, are a key component of the tumor immune system, but they enter a hyporeactive T cell state in long-term chronic inflammation, and how to rescue this depleted state is a key direction of research. Current studies on CD8⁺ T cell exhaustion have found that the mechanisms responsible for their heterogeneity and differential kinetics may be closely related to transcription factors and epigenetic regulation, which may serve as biomarkers and potential immunotherapeutic targets to guide treatment. Although the importance of T cell exhaustion in tumor immunotherapy cannot be overstated, studies have pointed out that gastric cancer tissues have a better anti-tumor T cell composition compared to other cancer tissues, which may indicate that gastrointestinal cancers have more promising prospects for the development of precision-targeted immunotherapy. Therefore, the present study will focus on the mechanisms involved in the development of CD8⁺ T cell exhaustion, and then review the landscapes and mechanisms of T cell exhaustion in gastrointestinal cancer as well as clinical applications, which will provide a clear vision for the development of future immunotherapies.

Anemia is common in patients with rheumatoid arthritis (RA), and it is unknown whether the dietary inflammatory index (DII) is linked to anemia. This study aimed to clarify the prevalence of anemia in RA patients and its association with the DII. The data utilized in this study were collected from the National Health and Nutrition Examination Survey database from 1999 to 2018. The prevalence of anemia in RA patients was estimated by ethnicity, sex, and age. Weighted multivariate logistic regression was utilized to explore the correlation between anemia risk and DII. The most crucial dietary factors related to the risk of anemia in RA patients were screened by stepwise regression. A nomogram model was established according to key dietary factors. A total of 10.25% (confidence interval, 8.58–11.92%) of RA patients will develop anemia, with the lowest prevalence around the age of 60. In addition, higher DII levels were discovered in anemic patients than in nonanemic patients. In multivariate regression models, an important positive association was revealed between anemia and growing quartiles of DII (Q4 vs Q1: odds ratio = 1.98; confidence interval, 1.25–3.15). In the subgroup analysis, the adjusted relation of DII with anemia in females, Mexicans, smokers, nondrinkers, and age groups ≥ 60 years was statistically significant. The same association was observed in the sensitivity analysis. A nomogram model based on stepwise regression screening of key dietary factors showed good discriminatory power to identify anemic risk in RA patients (area under the curve: 0.707). In patients with RA, high DII levels were associated with the risk of anemia. More attention should be given to controlling dietary inflammation to better prevent and treat anemia.

Gout is the most common inflammatory arthritis in adults. Gout is an arthritic disease caused by the deposition of monosodium urate crystal (MSU) in the joints, which can lead to acute inflammation and damage adjacent tissue. Hyperuricemia is the main risk factor for MSU crystal deposition and gout. With the increasing burden of gout disease, the identification of potential biomarkers and novel targets for diagnosis is urgently needed. For the analysis of this subject paper, we downloaded the human gout data set GSE160170 and the gout mouse model data set GSE190138 from the GEO database. To obtain the differentially expressed genes (DEGs), we intersected the two data sets. Using the cytohubba algorithm, we identified the key genes and enriched them through GO and KEGG. The gene expression trends of three subgroups (normal control group, intermittent gout group and acute gout attack group) were analyzed by Series Test of Cluster (STC) analysis, and the key genes were screened out, and the diagnostic effect was verified by ROC curve. The expression of key genes in dorsal root nerve and spinal cord of gout mice was analyzed. Finally, the clinical samples of normal control group, hyperuricemia group, intermittent gout group and acute gout attack group were collected, and the expression of key genes at protein level was verified by ELISA. We obtained 59 co-upregulated and 28 co-downregulated genes by comparing the DEGs between gout mouse model data set and human gout data set. 7 hub DEGs(IL1B, IL10, NLRP3, SOCS3, PTGS2) were screened out via Cytohubba algorithm. The results of both GO and KEGG enrichment analyses indicate that 7 hub genes play a significant role in regulating the inflammatory response, cytokine production in immune response, and the TNF signaling pathway. The most representative hub genes SOCS3 and PTGS2 were screened out by Series Test of Cluster, and ROC analysis results showed the AUC values were both up to 1.000. In addition, we found that PTGS2 expression was significantly elevated in the dorsal root ganglia and spinal cord in monosodium urate(MSU)-induced gout mouse model. The ELISA results revealed that the expression of SOCS3 and PTGS2 was notably higher in the acute gout attack and intermittent gout groups compared to the normal control group. This difference was statistically significant, indicating a clear distinction between the groups. Through cross-species comprehensive analysis and experimental verification, SOCS3 and PTGS2 were proved to be new biomarkers for diagnosing gout and predicting disease progression.

The aim of our study was to investigate whether the Dietary Inflammatory Index (DII) correlated with gout in American adults. The study used data from the 2007–2018 National Health and Nutrition Examination Survey, with 27,710 adults participating. Initially, multivariable analysis was performed, with controls for covariates, to assess the link of DII and gout. Then, restricted cubic splines (RCS) were applied to model the nonlinear relationship of DII and gout. Furthermore, propensity score matching (PSM) as a further study of potential relationships was established. Eventually, subgroup analysis was performed. Participants within the highest DII quartile would be more susceptible to increased risk of gout in the univariate regression model (Q4 vs. Q1, OR = 1.31, CI: 1.05–1.63). Additionally, a positive correlation was detected between gout risk and DII after adjusting on drinking, smoking, gender, race, age, and BMI. Based on RCS analysis, we observed that the risk of gout raised sharply as DII values increased, then flattened, and increased sharply again when the DII was greater than approximately 2.5. After performing the PSM, it was observed that DII correlated in a positive way to the presence of gout on a fully adjusted multivariable model. Subgroup analysis revealed that the link of DII and gout showed no statistical significance in females, blacks, Mexicans, nor in the population that smoked. Greater degrees of pro-inflammation correlate with a higher risk of gout and might be a predisposing factor for gout. Hence, tactics fostering an anti-inflammatory diet for preventing and improving gout in adults should be regarded.