Conclusion
Overall, the inflammation-related gene signature can be used for prognostic prediction in patients with COAD.
Methods
Inflammatory response-related genes were obtained from Molecular Signatures database. Univariate and multivariate Cox regression analyses were used for model construction based on TCGA dataset. GSE39582 dataset and qRT-PCR dataset were used for validation. Gene set variation analysis and gene set enrichment analysis were performed to explore the potential regulatory pathways. The immune cell infiltration level was analyzed via CIBERSORT. Immunohistochemistry analysis and experiments were used to explore the function of genes in model.
Purpose
The inflammatory response plays a crucial role in the occurrence and development of colon cancer. In this study, we aimed to explore a novel prognostic model for patients with colon cancer (COAD) based on inflammatory response-related genes.
Results
In this study, a novel prognostic signature was identified using stepwise Cox proportional hazards regression analysis based on TCGA dataset. The results were subsequently validated in 562 patients from GSE39582 and a qRT-PCR data set from 70 tumor samples. Functional analysis indicated that the tumor microenvironment and immune cell infiltrate were different between high- and low-risk groups. Additionally, IHC results showed that the protein levels of prognostic genes were significantly different between COAD tissues and adjacent non-tumorous tissues, and prognostic genes could regulate the malignant phenotype of COAD cells.