Construction And Validation Of A Metal-dependent Cell Death-associated LncRNA Signature As A Novel Prognostic Model For Colorectal Cancer

Background:In the 21st century,the incidence of malignant tumors is increasing day by day in various countries in the world,and colorectal cancer is a common malignant tumor,and its incidence rate in the population ranks 3rd compared with other malignant tumors,while the death rate reaches 2nd,according to epidemiological surveys,the incidence rate of colorectal cancer in men is higher than that in women,and the incidence rate in developed countries is significantly higher than that in developing countries,but in recent years,with the increasing level of global economy,the incidence rate and mortality rate have been increasing in all regions of the world.Patients with colorectal cancer generally have no clinical manifestations in the early stage until the late stage when they may show nonspecific manifestations such as blood in stool,change in stool shape,and increased frequency of defecation,and the survival rate of patients in the early stage is much better than that of patients in the late stage.Therefore,it is necessary to develop prediction models for colorectal cancer patients.Metal-dependent cell death,such as iron death and copper death,are newly discovered forms of cell death that are thought to play an important role in tumorigenesis and progression.It has been shown that long-stranded non-coding RNA(Lnc RNA)is closely associated with the progression and prognosis of colorectal cancer.However,the role and value of Lnc RNAs associated with metal-dependent cell death in colorectal cancer are still unknown.This study aims to construct and validate a predictive model of metal-dependent cell death-related Lnc RNAs from two metal-dependent forms of cell death,iron death and copper death,which can be used to predict the prognosis of colorectal cancer patients.Method:The m RNA and Lnc RNA expression profiles and clinical data of colorectal cancer patients were downloaded from the TCGA database,and 259 genes related to iron death and 19 genes related to copper death were obtained from other literature.By Pearson correlation test,715 Lnc RNAs associated with metal-dependent cell death were obtained,and the relationship between copper and iron death-related genes and lnc RNAs was visualized using Cyto Scape,and protein-protein interaction network relationship was constructed by String database for the genes involved in the network map.Then a total of 8 metal-dependent cell death-related Lnc RNAs associated with prognosis of colorectal cancer patients were obtained by univariate Cox regression,multifactorial Cox regression and Lasso regression and used to construct a prediction model,and patients’ gene expression levels × expression coefficients were obtained as risk scores,and patients were divided into two groups of high and low risk according to the median value of risk scores,and K-M curves,ROC curves,and principal component analysis(PCA)were used to assess the predictive power of the model.To improve the utility of the risk score,the risk score was combined with clinical traits such as age and stage to construct a nomogram,and the C-index was used to assess the predictive power of the nomogram.The "limma" package in R was used to differentially analyze the genes of patients in the high-and low-risk groups,and KEGG and GO enrichment analyses were performed for differentially expressed genes.The "GSVA" package in R was used to study the immune function between the high and low risk groups,and the differences in tumor mutational burden and drug sensitivity between the high and low risk groups were also studied using R.Results:Patients in the high-risk group had lower survival rates and shorter survival times than those in the low-risk group;the high-risk score was an independent prognostic factor for colorectal cancer patients with higher predictive accuracy than other factors;and clinical traits such as age,stage,T,N,and M also had an impact on patient prognosis and gender had no impact on patient prognosis.The area under the curve for 1,3,and 5 years for this prediction model was 0.747,0.690,and 0.680,respectively;the C-index indicated that the predictive power of the column plots was similar to the ideal.GO and KEGG enrichment analysis showed that differentially expressed genes were associated with immunity and protein synthesis in biological processes;immune function and tumor mutational burden were significantly different between the high and low risk groups;the high risk group patients had higher tumor mutational burden and no survival difference between patients in high and low tumor mutational burden groups.Three drugs(Adriamycin,B-Raf inhibitor and THZ-2-49)were obtained as potentially therapeutic agents for patients with colorectal cancer.Conclusion:A predictive model containing eight lnc RNAs associated with metal-dependent cell death was constructed,and a nomogram was constructed combining risk scores with clinical traits that have an impact on patient prognosis.Differences in immune function and tumor mutational burden between high-and low-risk groups were also analyzed for the prognosis and treatment of colorectal cancer patients.