Background: The present study aimed to investigate the expression and correlation of ITGB6 (integrin alphavbeta6) and Rac1 proteins in gastric cancer tissues, highlighting their crucial roles in the occurrence and progression of gastric cancer. By exploring the clinical significance of these proteins, we aimed to gain further insights into the mechanisms underlying gastric cancer development. Patients and Methods: In this study, a total of 198 patients diagnosed with gastric cancer and who underwent gastrectomy between October 2010 and December 2016 were included. The median follow-up time for these patients was 52.00 months. To evaluate the factors influencing overall survival, Kaplan-Meier survival curve analysis and Cox regression analysis were conducted. Furthermore, an independent prognostic factor-based nomogram was constructed and validated to predict survival outcomes in gastric cancer patients. Results: The expression levels of ITGB6 and Rac1 in gastric cancerous and paraneoplastic tissues were detected by tissue microarray (TMA) -immunohistochemistry, and the total number of samples was 198. And the correlation and clinical significance of the two proteins were also investigated. ITGB6 expression showed significant associations with tumor size (P=0.030), pathological grading (P=0.013), location (P=0.031), N stage (P=0.002), and clinical stage (P=0.002). Additionally, we found that tumor size (P=0.013), tumor’s anatomical location (P=0.031), N stage (P=0.002), clinical stage (P=0.035), and survival status (P<0.001) were significantly associated with the expression of Rac1. ITGB6 was moderately correlated with Rac1 (r=0.285, P<0.001). Both the Kaplan-Meier survival analysis and Cox regression model analysis demonstrated that the presence of positive expression of ITGB6 and Rac1 proteins served as independent prognostic factors for gastric cancer. These findings highlight the potential of ITGB6 and Rac1 as valuable markers for predicting the prognosis of gastric cancer patients(HR=2.212 P<0.001 and HR=2.073 P=0.001), with a significant poorer trend for 5-year survival (P<0.0001, respectively, the log-rank test). Conclusion: ITGB6 and Rac1 are indicators of poor prognosis and tumor progression in gastric cancer patients. The potential signaling pathways associated with both may provide useful targets for the prevention and treatment of gastric cancer.

Background: Hepatocellular carcinoma (HCC) is acknowledged as one of the most aggressive malignancies. Lamin B1 (LMNB1) serves a pivotal role as a key component in the structure of the nuclear skeleton. Recent studies have unveiled that LMNB1 plays a role in promoting cancer progression. However, the underlying mechanism remains unclear in HCC. Objective: This study aims to aimed to investigate the clinical significance of LMNB1 in HCC and the molecular mechanisms involved. Methods: The expression level of LMNB1 was assessed in HCC tissues and normal liver tissues using qRT-PCR and IHC. Functional assays were conducted to explore the impact of LMNB1 knockdown on cell proliferation both in vivo and in vitro. Additionally, Genes and Genomes enrichment analysis, recovery analysis, and CHIP assays were employed to investigate its underlying molecular mechanisms. Finally, we conducted an analysis of the relationship between LMNB1 and immune cell infiltration in HCC. Results: LMNB1 was found to be overexpressed in HCC and correlated with the pathological stage and unfavorable prognosis. Functional assays demonstrated that LMNB1 promotes HCC proliferation both in vitro and in vivo. Further analysis revealed that LMNB1 promotes the progression of HCC by regulating CDKN1A expression, Furthermore, the infiltration of immune cells in HCC tissues suggests a potential correlation between immune infiltration cell markers and the expression of LMNB1. Conclusions: LMNB1 emerged as a promising therapeutic target and prognostic biomarker for HCC, with its expression showing a correlation with several immune infiltration cell markers.

Colorectal cancer (CRC) is characterised by high mortality and recurrence rates, but good prognosis after early treatment. Therefore, it is very important to establish a model for early diagnosis. The gut microbiome is closely associated with the progression of CRC, and its metabolites influence disease progression in a variety of diseases by activating or inhibiting ferroptosis. However, this has not been reported in CRC. Therefore, we constructed an efficient early diagnosis model based on ferroptosis-related genes, and innovatively explored the possible mechanism between gut flora metabolites and ferroptosis signalling pathways. The genes associated with CRC ferroptosis were obtained by bioinformatics. 16S rDNA was used to analyse the gut flora of CRC patients and healthy controls. LC-MS/MS was used to analyse differential metabolites. MetaboAnalyst 5.0 was used to analyse associations between metabolites and ferroptosis genes. The results showed that 15 hub ferroptosis genes could be used as early diagnostic indicators for CRC. The ROC curve showed that the AUC value of NQO1 was 0.929, and the AUC value of the other 14 genes was 1, indicating that the diagnostic model was effective. At the top of the list for GO analysis were: "response to oxidative stress" (P = 2.28e-15), "plasma membrane region" (P = 1.22e-05) and "antioxidant activity" (P = 2.06e-09). KEGG pathway analysis showed that ferroptosis (P = 0.00251), metabolic pathways (P = 0.01068), and pathways in cancer (P = 0.00226) were enriched. Metabolic pathway in the CRC group were ABC transporters, aminoacyl tRNA biosynthesis, central carbon metabolism in cancer, and phenylalanine metabolism. Metabolite 5.0 analysis revealed 25 different metabolites associated with ferroptosis signalling pathways. In addition, the gut microbiome and its metabolites may be involved in CRC progression through the ferroptosis signalling pathway. This provides new insights into the diagnosis of CRC.