Combining Senescence-related lncRNA and Bulk-RNA Transcriptome Sequencing to Construct a Prognostic Model and Identify TSPEAR−AS2 as a Potential Therapeutic Target for Colon Adenocarcinoma Patients

Background Senescence, a key characteristic of cancer, significantly influences various processes of tumor initiation and progression. Recent studies have highlighted the importance of long non-coding RNAs (lncRNAs) in cancer, particularly their correlation with the prognosis of colon cancer. However, the role of senescence-related lncRNAs (SRLs) in cancer remains unexplored. Aim The objective of this study is to establish a prognostic model for colon cancer patients based on senescence-related lncRNAs. Methods We utilized univariate Cox analysis and random survival forest variable hunting to identify SRLs with prognostic significance. Subsequently, a multivariate Cox regression analysis was conducted to construct a final prognostic risk score signature. We further validated our risk model using external datasets from Gene Expression Omnibus (GEO) and GSE. Additionally, we developed a nomogram for prognostic assessment and conducted a comprehensive analysis of clinicopathological characteristics, immune cell infiltration, chemotherapeutic drug sensitivity, and somatic mutation landscapes in the low- and high-risk groups. The most significant lncRNA TSPEAR − AS2 was selected and a knockdown cell line stably transfected with this lncRNA was constructed by the lentivirus technique. The function of lncRNA TSPEAR − AS2, which is associated with promoting senescence in cancer cells, was successfully verified by using methods such as CCK8, transwell, scratch assays, clonal formation assays, cell apoptosis rate detection experiment and subcutaneous tumor formation assays in mice. Results Upon systematically assessing the interactions between senescence-related lncRNA signatures and colon cancer, we constructed a novel risk model based on four SRLs. In particular, the SRL signature comprising MIR210HG, TSPEAR-AS2, APTR, and ZEB1-AS1 showed promising prognostic ability. The predictive value of our risk model was further confirmed in the validation dataset. Phenotypic assessments and animal experiment in this study have corroborated that suppression of TSPEAR − AS2 expression can curtail the malignant phenotype of CC. Conclusion We have successfully established an independent risk model, based on four SRLs (MIR210HG, TSPEAR-AS2, APTR, and ZEB1-AS1), which demonstrating high predictive accuracy for colon cancer patients. To further validate our findings, we focused on the most significant lncRNA, TSPEAR-AS2, conducting both in vivo and in vitro experiments. These experiments confirmed that inhibiting TSPEAR-AS2 expression can reduce the malignant phenotype of CC tumor cells and inhibit tumor formation in mice. Our research presents potential avenues for the development of personalized prediction strategies and the exploration of underlying pathways in colon cancer pathogenesis.