Construction and Validation of a Novel Prognosis Model in Colon Cancer Based on Cuproptosis-Related Long Non-Coding RNAs

Abstract

Colon cancer (CC) is one of the most common (6%) malignancies and leading cause of cancer-associated death (more than 0.5 million) worldwide, which demands reliable prognostic biomarkers. Cuproptosis is a novel modality of regulated cell death triggered by the accumulation of intracellular copper. LncRNAs have been reported as prognostic signatures in different types of tumors. However, the correlation between cuproptosis-related lncRNAs (CRLs) and CC remains unclear. Data of CC patients were downloaded from public databases. The prognosis-associated CRLs were identified by co-expression analysis and univariate Cox. Least absolute shrinkage and selection operator were utilized to construct the CRLs-based prognostic signature in silico for CC patients. CRLs level was validated in human CC cell lines and patient tissues. ROC curve and Kaplan–Meier curve results revealed that high CRLs-risk score was associated with poor prognosis in CC patients. Moreover, the nomogram revealed that this model possessed a steady prognostic prediction capability with C-index as 0.68. More importantly, CC patients with high CRLs-risk score were more sensitive to eight targeted therapy drugs. The prognostic prediction power of the CRLs-risk score was further confirmed by cell lines, tissues and two independent CC cohorts. This study constructed a novel ten-CRLs-based prognosis model for CC patients. The CRLs-risk score is expected to serve as a promising prognostic biomarker and predict targeted therapy response in CC patients.

Keywords

• colon cancer
• cuproptosis
• long non-coding RNA
• prognosis model
• targeted therapy