Background: Tumor recurrence and metastasis lead to a poor prognosis in colorectal cancer (CRC). Necroptosis is closely related to the tumor microenvironment (TME) and affects tumor recurrence and metastasis. We aimed to stratify CRC patients according to necroptosis-related long noncoding RNAs (lncRNAs), which can be used to not only evaluate prognosis and improve precision medicine in clinical practice but also evaluate the efficacy of immunotherapy and guide the selection of immunotherapeutic methods.
Methods: A lncRNA expression profile was collected from The Cancer Genome Atlas (TCGA). Necroptosis-related lncRNAs were identified by coexpression analysis. Cox regression analysis identified a necroptosis-related lncRNA signature. Then, the value of this signature was comprehensively and multidimensionally evaluated, and its fidelity was assessed with clinical CRC data and compared with that of six other lncRNA signatures for CRC prognosis prediction. Gene set enrichment analysis (GSEA), TME analysis and prediction of the half-maximal inhibitory concentration (IC50) were also performed according to the risk score (RS) of the signature.
Results: An 8-lncRNA signature significantly associated with overall survival (OS) was constructed, and its fidelity was validated with clinical CRC data. Most of the areas under the receiver operating characteristic (ROC) curve (AUCs) for 1-, 3- and 5-year OS for this signature were higher than those for the other six lncRNA signatures. OS, disease-specific survival (DSS) and the progression-free interval (PFI) were all significantly poorer in the high-risk group. The RS of the signature showed good concordance with the predicted prognosis, with AUCs for 1-, 3- and 5-year OS of 0.79, 0.81 and 0.77, respectively. Additionally, the calibration plots for this signature combined with clinical factors could effectively improve the ability to predict OS. The RS was correlated with tumor stage, lymph node metastasis and distant metastasis. Most of the enriched Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) terms were tumor metastasis-related pathways in the high-risk group, which showed greater infiltration of immunosuppressive cells, such as cancer-associated fibroblasts (CAFs), hematopoietic stem cells and M2 macrophages, but fewer infiltrating antitumor effector immune cells, such as CD8+ T cells and regulatory T cells (Tregs). We explored additional potential immune checkpoint genes and immunotherapeutic and chemotherapeutic drugs with relatively low IC50 values.
Conclusions: We identified a signature with strong fidelity that could stably predict prognosis and might be implicated in the TME and metastasis of CRC. Furthermore, additional potential immune checkpoint genes and immunotherapeutic and chemotherapeutic drugs were explored.