Necroptosis-associated long noncoding RNA predicts prognosis for cervical cancer in a microenvironment signature associated with anti-tumor immune responses

Abstract

Abstract Background: Cancer has high incidence rate, poor prognosis and high intratumoral heterogeneity. Necrosis is an important cellular signaling pathway in tumor cells, which can overcome the resistance of tumor cells to apoptosis. To investigate the relationship between CC and necrosis, we established a prognostic model based on necrosis related genes to predict the overall survival (OS) of CC patients. Methods: We obtained gene expression data and clinical information of cervical cancer patients from the Cancer Genome Map (TCGA). By detecting differential gene expression between tumors and normal tissues, 43 differentially expressed necrosis related lncRNAs (NRLs) were identified. Subsequently, the Least Absolute Shrinkage and Selection Operator (LASSO) regression and univariate and multivariate Cox regression analysis were used to screen for NRLs associated with patient prognosis. We have established prognostic markers including AC022137.3, AC024270.3, AC010542.5, AC010536.2, U91328.1, and AL021978.1. According to the prognosis model, patients are divided into high-risk or low-risk subgroups with different survival rates. The receiver operating characteristic (ROC) curve analysis is used to determine the predictive accuracy of the model. We conducted stratified analysis on different clinical variables to demonstrate the correlation between the expression level of NRLs identified and clinical variables. We also explored the relationship between the prognostic NRLs and immune-cell infiltration and immune checkpoints. Results: Based on the differently expressed lncRNAs, we constructed lncRNA signatures. The area under the curve (AUC) of the ROC curve is used to predict 5-year survival rate with a characteristic of 0.757. Subsequent analysis indicates that our features can effectively distinguish adverse survival outcomes. High expression of immune checkpoint related lncRNAs is associated with low risk groups. Conclusion: We have constructed a new necrosis related lncRNA signal for predicting the prognosis of CC patients and may play a key role in the progression and immune microenvironment of CC.