Colon adenocarcinoma (COAD) is a special pathological subtype of colorectal cancer (CRC) with highly heterogeneous solid tumors with poor prognosis, and novel biomarkers are urgently required to guide its prognosis. RNA-Seq data of COAD were downloaded through The Cancer Genome Atlas (TCGA) database to determine cuproptosis-related lncRNAs (CRLs) using weighted gene co-expression network analysis (WGCNA). The scores of the pathways were calculated by single-sample gene set enrichment analysis (ssGSEA). CRLs that affected prognoses were determined via the univariate COX regression analysis to develop a prognostic model using multivariate COX regression analysis and LASSO regression analysis. The model was assessed by applying Kaplan-Meier (K-M) survival analysis and receiver operating characteristic curves and validated in GSE39582 and GSE17538. The tumor microenvironment (TME), single nucleotide variants (SNV), and immunotherapy response/chemotherapy sensitivity were assessed in high- and low-score subgroups. Finally, the construction of a nomogram was adopted to predict survival rates of COAD patients during years 1, 3, and 5. We found that a high cuproptosis score reduced the survival rates of COAD significantly. A total of five CRLs affecting prognosis were identified, containing AC008494.3, EIF3J-DT, AC016027.1, AL731533.2, and ZEB1-AS1. The ROC curve showed that RiskScore could perform well in predicting the prognosis of COAD. Meanwhile, we found that RiskScore showed good ability in assessing immunotherapy and chemotherapy sensitivity. Finally, the nomogram and decision curves showed that RiskScore would be a powerful predictor for COAD. A novel prognostic model was constructed using CRLs in COAD, and the CRLs in the model were probably a potential therapeutic target. Based on this study, RiskScore was an independent predictor factor, immunotherapy response, and chemotherapy sensitivity for COAD, providing a new scientific basis for COAD prognosis management.