Department of General Surgery, Shengjing Hospital of China Medical University, Shenyang, Liaoning Province, China.
BMC Cancer. 2022 Nov 4;22(1):1131. doi: 10.1186/s12885-022-10175-5.
Cuproptosis, a new form of programmed cell death, has been recently reported to be closely related to tumor progression. However, the significance of cuproptosis-related genes (CRGs) in papillary thyroid carcinoma (PTC) is still unclear. Therefore, this study aimed to investigate the role of the CRG signature in prognosis prediction and immunotherapeutic effect estimation in patients with PTC.
RNA-seq data and the corresponding clinical information of patients with PTC were obtained from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Comprehensive analyses, namely, consensus clustering, immune analyses, functional enrichment, least absolute shrinkage and selection operator-multivariate Cox regression, and nomogram analysis, were performed to identify new molecular subgroups, determine the tumor immune microenvironment (TIME) status of the identified subgroups, and construct a clinical model. Independent verification cohort data and quantitative real-time polymerase chain reaction (qPCR) was performed to validate the expression of specific prognosis-related and differentially expressed CRGs (P-DECRGs).
In the TCGA database, 476 patients with PTC who had complete clinical and follow-up information were included. Among 135 CRGs, 21 were identified as P-DECRGs. Two molecular subgroups with significantly different disease-free survival and TIME statuses were identified based on these 21 P-DECRGs. The differentially expressed genes between the two subgroups were mainly associated with immune regulation. The risk model and nomogram were constructed based on four specific P-DECRGs and validated as accurate prognostic predictions and TIME status estimation for PTC by TCGA and GEO verification cohorts. Finally, the qPCR results of 20 PTC and paracancerous thyroid tissues validated those in the TCGA database.
Four specific P-DECRGs in PTC were identified, and a clinical model based on them was established, which may be helpful for individualized immunotherapeutic strategies and prognostic prediction in patients with PTC.
铜死亡是一种新的程序性细胞死亡形式，最近有报道称其与肿瘤进展密切相关。然而，铜死亡相关基因（CRGs）在甲状腺乳头状癌（PTC）中的意义尚不清楚。因此，本研究旨在探讨 CRG 特征在 PTC 患者预后预测和免疫治疗效果评估中的作用。
从癌症基因组图谱（TCGA）和基因表达综合数据库（GEO）中获取 PTC 患者的 RNA-seq 数据和相应的临床信息。进行综合分析，包括共识聚类、免疫分析、功能富集、最小绝对收缩和选择算子多变量 Cox 回归以及列线图分析，以识别新的分子亚群，确定鉴定亚群的肿瘤免疫微环境（TIME）状态，并构建临床模型。使用独立验证队列数据和定量实时聚合酶链反应（qPCR）验证特定预后相关和差异表达 CRGs（P-DECRGs）的表达。
在 TCGA 数据库中，纳入了 476 例具有完整临床和随访信息的 PTC 患者。在 135 个 CRGs 中，有 21 个被鉴定为 P-DECRGs。基于这 21 个 P-DECRGs，确定了两个具有显著不同无病生存率和 TIME 状态的分子亚群。两个亚群之间差异表达的基因主要与免疫调节有关。基于四个特定的 P-DECRGs 构建了风险模型和列线图，并通过 TCGA 和 GEO 验证队列验证其对 PTC 的准确性预后预测和 TIME 状态评估。最后，对 20 例 PTC 和癌旁甲状腺组织的 qPCR 结果验证了 TCGA 数据库中的结果。
鉴定出 PTC 中的四个特定 P-DECRGs，并建立了基于它们的临床模型，这可能有助于 PTC 患者的个体化免疫治疗策略和预后预测。
