| Objective:Colorectal cancer has become the third most common cancer type worldwide and one of the main causes of death among cancer patients.Anoikis is a form of programmed cell death that has been shown to play an important role in tumor development and cancer cell metastasis.This study aimed to comprehensively analyze the potential functions and prognostic impact of anoikis-related genes(ARGs)in colorectal cancer patients.Method:Expression matrices and clinical data of colon cancer patients were downloaded from TCGA database and GEO database,while ARGs were downloaded from Genecards and Harmonizome database to filter out differentially expressed anoikis-related genes(DE-ARGs)between normal and colon cancer tissues as candidate genes.GO,KEGG and PPI analyses were performed on the above genes.Prognosis-related DE-ARGs were obtained using univariate cox regression and analyzed for single nucleotide variants(SNVs),copy number variants(CNVs)and methylation.The Consensus Cluster Plus package was also used to classify 626 patients with TCGA+GEO colon cancer into 2 subtypes.We compared the differences in survival status,clinical characteristics and immune cell infiltration between the 2 subtypes;colon cancer patients were randomly divided into training and validation groups in a 1:1 ratio.Risk prognostic models were constructed using LASSO regression with multifactorial Cox regression for the training group data,and the samples were divided into high-risk and low-risk groups using the median prognostic model risk score of the training group.Then,the value of the model in predicting patient prognosis was explored using survival curve analysis,ROC curve analysis,and column line plots.In addition,differences in immune cell infiltration were explored for samples with different risk groupings.Then,differences in tumor mutational load,drug sensitivity,microsatellite instability(MSI),and immune checkpoint gene expression between the high-and low-risk groups were assessed.Finally,we also identified NAT1 and OGT protein expression in colon adenocarcinoma tissues versus normal tissues by immunohistochemical experiments and explored the relationship between protein expression and clinical features and patient prognosis.Result:1.A total of 161 DE-ARGs were screened.GO enrichment analysis showed that DE-ARGs were mainly enriched in glandular proliferation,regulation of cell mitotic cycle,myoblast proliferation and intrinsic apoptotic signaling pathways;KEGG enrichment analysis showed that DE-ARGs were mainly enriched in tumor-associated mi RNAs,p53 signaling pathway,PI3K-Akt signaling pathway and cell cycle,etc.Univariate COX analysis showed that 32 genes were associated with the prognosis of colon cancer patients,and methylation of SNVs,CNVs and ARGs was associated with the expression level of ARGs,however,these factors did not have a significant effect on the prognosis of colon cancer patients.2.Patients with colon cancer were classified into two subtypes(Cluster A and Cluster B)based on the expression of 32 DE-ARGs,and most ARGs showed high expression in the Cluster B colon cancer subgroup.The different subtypes were associated with clinical traits,prognosis,metabolism-related pathways and immune cell infiltration in colon cancer patients,respectively.3.A prognostic risk model due to 5 ARGs(TIMP1,NAT1,EDAR,HOTAIR,OGT)was constructed.Prognostic analysis of high-and low-risk samples yielded a poorer prognosis for patients in the high-risk group;the ROC curve assessed the predictive power of the model at 1,3,and 5 years,and the area under the curve was0.754,0.708,and 0.689,respectively.based on the results of independent prognostic analysis,we constructed column line plots containing age,risk score,and Stage staging to predict patient survival at 1,3,and 5 years.4.For the immune infiltration analysis performed for the high-and low-risk groups,the main cell types infiltrated in the high-risk group were M0 and M2 macrophages.In addition,we assessed the tumor microenvironment scores of both groups of samples using ESTIMATE,and the results showed that the stromal score and ESTIMATE score were higher in the high-risk group.5.The association between immune checkpoints and risk models was analyzed in TCGA colon cancer patients,and the results showed that 15 immune checkpoints were differentially expressed between the two groups.The results of drug sensitivity analysis showed differences in response to chemotherapeutic agents and immunotherapy in patients with different scores.6.The immunohistochemical results validated the differential expression and prognostic differences between NATI and OGT in different samples,and these findings will improve our understanding of anoikis in colon cancer and provide new avenues for the development of more effective therapeutic strategies.Conclusion:1.Relevant subtypes based on 32 DE-ARGs were identified,with different typing correlating with patient clinicopathological features,immune infiltration,and patient prognosis.2.We identified a prognostic model based on the establishment of 5 genes with differences in prognosis,immune cell infiltration,TMB,MSI and drug sensitivity between high-and low-risk patients.3.Immunohistochemical results validated the difference in expression between NATI and OGT,and these findings will improve our understanding of anoikis in colon cancer and provide new avenues for developing more effective therapeutic strategies. |
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