Background: Precisely forecasting the prognosis of esophageal squamous cell carcinoma (ESCC) patients is a formidable challenge. Cuproptosis has been implicated in ESCC pathogenesis; however, the prognostic value of cuproptosis-associated long noncoding RNAs (CuRLs) in ESCC is unclear.
Methods: Transcriptomic and clinical data related to ESCC were sourced from The Cancer Genome Atlas (TCGA). Using coexpression and Cox regression analysis to identify prognostically significant CuRLs, a prognostic signature was created. Nomogram models were established by incorporating the risk score and clinical characteristics. Tumor Immune Dysfunction and Rejection (TIDE) scores were derived by conducting an immune landscape analysis and evaluating the tumor mutational burden (TMB). Drug sensitivity analysis was performed to explore the underlying molecular mechanisms and guide clinical dosing.
Results: Our risk score based on 5 CuRLs accurately predicted poorer prognosis in high-risk ESCC patients across almost all subgroups. The nomogram that included the risk score provided more precise prognostic predictions. Immune pathways, such as the B-cell receptor signaling pathway, were enriched in the datasets from high-risk patients. High TMB in high-risk patients indicated a relatively poor prognosis. High-risk patients with lower TIDE scores were found to benefit more from immunotherapy. High-risk patients exhibited greater responsiveness to Nilotinib, BI-2536, P22077, Zoledronate, and Fulvestrant, as revealed by drug sensitivity analysis. Real-time PCR validation demonstrated significant differential expression of four CuRLs between ESCC and normal cell lines.
Conclusions: The above risk score and nomogram can accurately predict prognosis in ESCC patients and provide guidance for chemotherapy and immunotherapy.
Keywords: cuproptosis; drug sensitivity; esophageal squamous carcinoma; lncRNAs; prognosis.