T cell-related circRNA pairs to predict prognosis of patients with esophageal squamous cell carcinoma.

The prognosis for esophageal squamous cell carcinoma (ESCC), a prevalent and aggressive form of cancer, remains poor despite advancements in treatment options. Addressing the gap in comprehensive prognostic information derived from circRNA expression profiles for ESCC, our study aimed to establish a linkage between circRNA expressions and ESCC prognosis. To achieve this, we first developed an optimized prognostic model named T cell-related risk score (TRRS), which integrates T cell-associated features with machine learning algorithms. In parallel, we re-analyzed existing RNA-seq datasets to redefine the expression profiles of circRNAs and mRNAs. Utilizing the TRRS as a foundational "bridge," we identified circRNAs correlated with TRRS, leading to the development of a novel circRNA pair-based prognostic model, the TCRS, which is independent of specific expression levels. Further investigations uncovered two circRNAs, circNLK(5,6,7).1 and circRC3H1(2).1, with potential functional significance. These findings underscore the utility of these risk scores as tools for predicting overall survival and identifying potential therapeutic targets for ESCC patients.