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识别甲状腺癌中与铁死亡相关的长链非编码 RNA 预后模型和肿瘤免疫微环境。

Identification of Ferroptosis-Associated Long Noncoding RNA Prognostic Model and Tumor Immune Microenvironment in Thyroid Cancer.

机构信息

Department of Gastrointestinal and Gland Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning 530021, China.

Department of Urology Surgery, The Affiliated Hospital of Youjiang Medical University for Nationalities, Baise 533000, China.

出版信息

J Immunol Res. 2022 Jul 20;2022:5893998. doi: 10.1155/2022/5893998. eCollection 2022.

Abstract

BACKGROUND

Thyroid cancer (TC) is a rapidly increasing incidence of endocrine malignancies, occupying 3% of new cancer incidence, of which 10% has a heterogeneous prognosis. Ferroptosis is a form of cell death distinct from apoptosis, which involves antitumor drug-related research. Long noncoding RNAs (lncRNAs) could affect cancer prognosis by regulating the ferroptosis; thus, ferroptosis-associated lncRNAs are emerging as prospective biomarkers for cancer therapy and prognosis. However, the prognostic factors of ferroptosis-associated lncRNAs in this solid tumor and their mechanisms remain unknown.

METHODS

The TC lncRNA data were extracted from RNA sequencing files of The Cancer Genome Atlas (TCGA). Then, we performed a two-cluster analysis and grouped 502 patients with TC in a 7 : 3 ratio. Both the least absolute shrinkage and selection operator (LASSO) regression and Cox regression analysis were conducted to create and validate the ferroptosis-associated lncRNA prognostic model (Ferr-LPM). Based on the median Ferr-LPM-based risk score (LPM_score) of the training cohort, we categorized patients into high and low LPM_score groups, which were then subjected to prognostic correlation and difference analysis. We also created a nomogram and assessed its predictive ability. Furthermore, immune-related mechanisms were investigated by analyzing the tumor immune microenvironment (TIME) and applying algorithms such as CIBERSROT.

RESULTS

We built a highly accurate nomogram to promote the clinical applicability of Ferr-LPM. The area under the receiver operating characteristic curve (AUC-ROC) reached above 0.9. Survival analysis suggested that when the Ferr-LPM score was higher, the overall survival (OS) of patients within this group was shorter. Meanwhile, we found a strong association between Ferr-LPM and TIME. Interestingly, the LPM_score was inversely proportional to the tumor purity but positively related to immune checkpoint blockade (ICB) response.

CONCLUSION

We constructed a novel ferroptosis-associated lncRNA nomogram that could highly predict the prognosis of TC patients. Ferroptosis-associated lncRNAs might possess potential functions in regulating TIME, and lncRNAs provide TC patients with new prognostic biomarkers and therapeutic targets.

摘要

背景

甲状腺癌(TC)是一种发病率迅速上升的内分泌恶性肿瘤,占新发癌症的 3%,其中 10%具有异质性的预后。铁死亡是一种不同于细胞凋亡的细胞死亡形式,涉及抗肿瘤药物相关研究。长链非编码 RNA(lncRNA)可以通过调节铁死亡来影响癌症的预后;因此,铁死亡相关 lncRNA 正在成为癌症治疗和预后的有前途的生物标志物。然而,这种实体瘤中与铁死亡相关的 lncRNA 的预后因素及其机制尚不清楚。

方法

从癌症基因组图谱(TCGA)的 RNA 测序文件中提取 TC 的 lncRNA 数据。然后,我们进行了两聚类分析,并将 502 例 TC 患者按 7:3 的比例分组。采用最小绝对收缩和选择算子(LASSO)回归和 Cox 回归分析来创建和验证与铁死亡相关的 lncRNA 预后模型(Ferr-LPM)。基于训练队列中基于 Ferr-LPM 的风险评分(LPM_score)的中位数,我们将患者分为高和低 LPM_score 组,然后进行预后相关性和差异分析。我们还创建了一个列线图,并评估了其预测能力。此外,通过分析肿瘤免疫微环境(TIME)并应用 CIBERSROT 等算法来研究免疫相关机制。

结果

我们构建了一个高度准确的列线图,以提高 Ferr-LPM 的临床适用性。接收器操作特征曲线下的面积(AUC-ROC)达到 0.9 以上。生存分析表明,当 Ferr-LPM 评分较高时,该组患者的总体生存率(OS)更短。同时,我们发现 Ferr-LPM 与 TIME 之间存在很强的关联。有趣的是,LPM_score 与肿瘤纯度呈反比,但与免疫检查点阻断(ICB)反应呈正相关。

结论

我们构建了一个新的与铁死亡相关的 lncRNA 列线图,可以高度预测 TC 患者的预后。与铁死亡相关的 lncRNA 可能在调节 TIME 方面具有潜在的功能,并且 lncRNA 为 TC 患者提供了新的预后生物标志物和治疗靶点。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cdbb/9338734/3b8990f604f8/JIR2022-5893998.001.jpg

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