Department of Radiation Oncology, Qilu Hospital of Shandong University, Jinan, China.
Biomedical Sciences College & Shandong Medicinal Biotechnology Centre, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, China.
Int Immunopharmacol. 2024 Nov 15;141:112909. doi: 10.1016/j.intimp.2024.112909. Epub 2024 Aug 17.
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.
食管鳞状细胞癌（ESCC）是一种常见且侵袭性强的癌症，尽管治疗选择有所进步，但预后仍然较差。为了弥补 ESCC 环状 RNA 表达谱综合预后信息的空白，我们的研究旨在建立环状 RNA 表达与 ESCC 预后之间的联系。为此，我们首先开发了一种名为 T 细胞相关风险评分（TRRS）的优化预后模型，该模型将 T 细胞相关特征与机器学习算法相结合。同时，我们重新分析了现有的 RNA-seq 数据集，以重新定义环状 RNA 和 mRNA 的表达谱。利用 TRRS 作为基础“桥梁”，我们鉴定出与 TRRS 相关的环状 RNA，从而开发出一种新的基于环状 RNA 对的预后模型，即 TCRS，该模型独立于特定的表达水平。进一步的研究揭示了两个具有潜在功能意义的环状 RNA，circNLK(5,6,7).1 和 circRC3H1(2).1。这些发现强调了这些风险评分作为预测总生存期和识别 ESCC 患者潜在治疗靶点的工具的实用性。
