Background: Colon cancer (CC) is a prevalent malignant tumor that affects the colon in the gastrointestinal tract. Its aggressive nature, strong invasiveness, and rapid progression make it a significant health concern. In addition, oxidative stress can lead to the production of reactive oxygen species (ROS) that surpass the body's antioxidant defense capacity, causing damage to proteins, lipids, and DNA, potentially promoting tumor development. However, the relationship between CC and oxidative stress requires further investigation.
Methods: We collected gene expression data and clinical data from 473 CC patients from The Cancer Genome Atlas (TCGA) dataset. Additionally, we obtained 433 oxidative stress genes from Genecards ( https://www.genecards.org/ ). Using univariate, multivariate, and LASSO Cox regression analyses, we developed predictive models for oxidative stress-related genes in CC patients. To validate the models, we utilized data from the Gene Expression Omnibus (GEO) database. We assessed the accuracy of the models through various techniques, including the creation of a nomogram, receiver operating characteristic curve (ROC) analysis, and principal component analysis (PCA). The Cytoscape program was utilized to identify hub genes among differentially expressed genes (DEGs) in tumor patients using the TCGA dataset. Subsequently, we conducted survival analysis, clinical relevance analysis, and immune cell relevance analysis for the intersected genes obtained by combining the hub genes with the genes from the predictive models. Moreover, we investigated the mRNA expression and potential functions of these intersected genes using a range of experimental approaches.
Results: In both the TCGA and GSE17538 datasets, patients classified as high-risk had significantly shorter overall survival compared to those in the low-risk group (TCGA: p < 0.001; GSE17538: p = 0.010). As a result, we decided to further investigate the role of SERPINE1. Our survival analysis revealed that patients with high expression of SERPINE1 had a significantly lower probability of survival compared to those with low expression (p < 0.05). Additionally, our clinical correlation analysis showed a significant relationship between SERPINE1 expression and T, N, and M stages, as well as tumor grade. Furthermore, our immune infiltration correlation analysis demonstrated notable differences in multiple immune cells between the high- and low-expression groups of SERPINE1. To validate our findings, we conducted experimental tests and observed that knocking down SERPINE1 in colon cancer cells resulted in significant reductions in cell viability and proliferation. Interestingly, we also noticed an increase in oxidative stress parameters, such as ROS and MDA levels, while the levels of reduced GSH decreased upon SERPINE1 knockdown. These findings suggest that the antineoplastic effect of silencing SERPINE1 may be associated with the induction of oxidative stress.
Conclusion: In conclusion, this study introduces a new approach for the early diagnosis and treatment of CC, and further exploration of SERPINE1 could potentially lead to a significant advancement.
Keywords: Bioinformatics analysis; Colon cancer; Oxidative stress; Prognosis model; SERPINE1.
© 2023. The Author(s).