Prognostic Model and Tumor Immune Microenvironment Analysis of Complement-Related Genes in Gastric Cancer.

Introduction: The complement system is integral to the innate and adaptive immune response, helping antibodies eliminate pathogens. However, the potential role of complement and its modulators in the tumor microenvironment (TME) of gastric cancer (GC) remains unclear. Methods: This study assessed the expression, frequency of somatic mutations, and copy number variations of complement family genes in GC derived from The Cancer Genome Atlas (TCGA). Lasso and Cox regression analyses were conducted to develop a prognostic model based on the complement genes family, with the training and validation sets taken from the TCGA-GC cohort (n=371) and the International Gene Expression Omnibus (GEO) cohort (n=433), correspondingly. The nomogram assessment model was used to predict patient outcomes. Additionally, the link between immune checkpoints, immune cells, and the prognostic model was investigated. Results: In contrast to patients at low risk, those at high risk had a less favorable outcome. The prognostic model-derived risk score was shown to serve as a prognostic marker of GC independently, as per the multivariate Cox analysis. Nomogram assessment showed that the model had high reliability for predicting the survival of patients with GC in the 1, 3, 5 years. Additionally, the risk score was positively linked to the expression of immune checkpoints, notably CTLA4, LAG3, PDCD1, and CD274, according to an analysis of immune processes. The core gene C5aR1 in the prognostic model was found to be upregulated in GC tissues in contrast to adjoining normal tissues, and patients with elevated expressed levels of C5aR1 had lower 10-year overall survival (OS) rates. Conclusion: Our work reveals that complement genes are associated with the diversity and complexity of TME. The complement prognosis model help improves our understanding of TME infiltration characteristics and makes immunotherapeutic strategies more effective.

C5aR1 shapes a non-inflammatory tumor microenvironment and mediates immune evasion in gastric cancer.

C5a receptor 1 (C5aR1) is associated with various inflammatory processes, the pathogenesis of immune diseases, and tumor growth. However, its role in the tumor microenvironment of gastric cancer (GC) remains unclear. In this study, the expression of C5aR1 in GC and normal gastric mucosa tissues was compared using data retrieved from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases, and the results were validated by in vitro qRT-PCR and immunohistochemical analyses. The relationship between C5aR1 expression and the overall survival of patients with GC was analyzed using the Kaplan-Meier method. Subsequently, enrichment analysis was performed, and the signaling pathways were screened. C5aR1 expression was also correlated with genes related to the immune checkpoint and immune cell infiltration. The results revealed that C5aR1 expression was enhanced in GC tissues compared to normal gastric tissues, and that patients with high expression of C5aR1 had a worse 10-year overall survival compared to those showing low expression of C5aR1. Functional analysis revealed that C5aR1 is a gene related to theimmune system and may play a crucial role in inflammatory and tumor immune responses. Additionally, C5aR1 showed a positive correlation with most immune checkpoint-related genes and a negative correlation with natural killer cells, dendritic cells, and CD8+ T cells. Immune evasion risk was observed to be significantly greater in patients with higher expression of C5aR1 than in those with lower expression. The results of this study reveal that C5aR1 shapes a non-inflammatory tumor microenvironment in GC and mediates immune evasion.

Serum level of calpains product as a novel biomarker of acute lung injury following cardiopulmonary bypass.

Objective: The aim of this study was to test the hypothesis whether serum level of calpains could become a meaningful biomarker for diagnosis of acute lung injury (ALI) in clinical after cardiac surgery using cardiopulmonary bypass (CPB) technology. Methods and results: Seventy consecutive adults underwent cardiac surgery with CPB were included in this prospective study. Based on the American-European Consensus Criteria (AECC), these patients were divided into ALI (n = 20, 28.57%) and non-ALI (n = 50, 71.43%) groups. Serum level of calpains in terms of calpains' activity which was expressed as relative fluorescence unit (RFU) per microliter and measured at beginning of CPB (baseline), 1 h during CPB, end of CPB as well as 1, 12, and 24 h after CPB. Difference of serum level of calpains between two groups first appeared at the end of CPB and remained different at subsequent test points. Univariate and multivariate logistic regression analysis indicated that serum level of calpains 1 h after CPB was an independent predictor for postoperative ALI (OR 1.011, 95% CI 1.001, 1.021, p = 0.033) and correlated with a lower PaO2/FiO2 ratio in the first 2 days (The first day: r = -0.389, p < 0.001 and the second day: r = -0.320, p = 0.007) as well as longer mechanical ventilation time (r = 0.440, p < 0.001), intensive care unit (ICU) length of stay (LOS) (r = 0.419, p < 0.001) and hospital LOS (r = 0.297, p = 0.013). Conclusion: Elevated serum level of calpains correlate with impaired lung function and poor clinical outcomes, indicating serum level of calpains could act as a potential biomarker for postoperative ALI following CPB in adults. Clinical trial registration: [https://clinicaltrials.gov/show/NCT05610475], identifier [NCT05610475].

Endometrial cancer prognosis prediction using correlation models based on CDK family genes.

Cyclin-dependent kinases (CDKs) play an important role in cell division. Given that abnormal cell proliferation caused by dysregulation of cell division is one of the major causes of endometrial cancer (EC), it is important to elucidate the role of CDK family genes in the diagnosis and prognosis of EC. In this study, The Cancer Genome Atlas (TCGA) database was used to analyze the frequency of copy number variations and somatic mutations in 26 CDK family genes. Subsequently, the expression of these genes in EC was assessed, and their relationship with overall survival (OS) was examined via Kaplan-Meier analysis to assess their prognostic significance. A prognostic model based on seven CDK genes was constructed using Lasso and Cox regression, and the predictive performance of the model was analyzed using Kaplan-Meier analysis and column line plots. The correlation between CDK genes and immune cells was also examined. Patients with EC in the high-risk group had a poorer prognosis. The results of qRT-PCR and immunohistochemical analyses validated that CDK16 is highly expressed in EC tissues. Patients with EC with high CDK16 expression had worse 10-year OS than patients with low CDK16 expression. These findings suggest that the prognostic model constructed based on CDK genes can help to develop individualized and targeted treatment strategies for patients with EC.