甲状腺乳头状癌中免疫相关预后特征及关键基因的鉴定与验证
Identification and validation of an immune-related prognostic signature and key gene in papillary thyroid carcinoma.
作者信息
Qin Rujia, Li Chunyan, Wang Xuemin, Zhong Zhaoming, Sun Chuanzheng
机构信息
Department of Head and Neck Surgery Section II, The Third Affiliated Hospital of Kunming Medical University/Yunnan Cancer Hospital, 519 Kunzhou Road, Kunming, 650118, China.
Department of Medical Oncology, the First Affiliated Hospital of Kunming Medical University, 295 Xichang Road, Kunming, 650032, China.
出版信息
Cancer Cell Int. 2021 Jul 15;21(1):378. doi: 10.1186/s12935-021-02066-9.
BACKGROUND
Papillary thyroid carcinoma (PTC) is the most common pathological type of thyroid cancer. The effect of traditional anti-tumor therapy is not ideal for the patients with recurrence, metastasis and radioiodine resistance. The abnormal expression of immune-related genes (IRGs) has critical roles in the etiology of PTC. However, the effect of IRGs on PTC prognosis remains unclear.
METHODS
Based on The Cancer Genome Atlas (TCGA) and ImmPort databases, we integrated IRG expression profiles and progression-free intervals (PFIs) of PTC patients. First, we identified the differentially expressed IRGs and transcription factors (TFs) in PTC. Subsequently, an IRG model that can predict the PFI was constructed by using univariate Cox regression, least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox regression analyses of the differentially expressed IRGs in the TCGA. Additionally, a protein-protein interaction (PPI) network showed the interactions between the differentially expressed genes (DEGs), and the top 30 genes with the highest degree were extracted from the network. Then, the key IRG was identified by the intersection analysis of the PPI network and univariate Cox regression, which was verified the differential expression of by western blotting and immunohistochemistry (IHC). ssGSEA was performed to understand the correlation between the key IRG expression level and immune activity.
RESULTS
A total of 355 differentially expressed IRGs and 43 differentially expressed TFs were identified in PTC patients. Then, eight IRGs were finally utilized to construct an IRG model. The respective areas under the curve (AUCs) of the IRG model reached 0.948, 0.820, and 0.831 at 1, 3 and 5 years in the training set. In addition, lactotransferrin (LTF) was determined as the key IRG related to prognosis. The expression level of LTF in tumor tissues was significantly lower than that in normal tissues. And the results of ssGSEA showed the expression level of LTF is closely related to immune activity.
CONCLUSIONS
These findings show that the prognostic model and key IRG may become promising molecular markers for the prognosis of PTC patients.
背景
甲状腺乳头状癌（PTC）是甲状腺癌最常见的病理类型。传统抗肿瘤治疗对复发、转移及对放射性碘耐药的患者效果不理想。免疫相关基因（IRGs）的异常表达在PTC的病因中起关键作用。然而，IRGs对PTC预后的影响仍不清楚。
方法
基于癌症基因组图谱（TCGA）和免疫数据库（ImmPort），我们整合了PTC患者的IRG表达谱和无进展生存期（PFIs）。首先，我们鉴定了PTC中差异表达的IRGs和转录因子（TFs）。随后，通过对TCGA中差异表达的IRGs进行单变量Cox回归、最小绝对收缩和选择算子（LASSO）回归以及多变量Cox回归分析，构建了一个可以预测PFI的IRG模型。此外，蛋白质-蛋白质相互作用（PPI）网络展示了差异表达基因（DEGs）之间的相互作用，并从网络中提取了度数最高的前30个基因。然后，通过PPI网络与单变量Cox回归的交集分析确定关键IRG，并通过蛋白质印迹法和免疫组织化学（IHC）验证其差异表达。进行单样本基因集富集分析（ssGSEA）以了解关键IRG表达水平与免疫活性之间的相关性。
结果
在PTC患者中总共鉴定出355个差异表达的IRGs和43个差异表达的TFs。然后，最终利用8个IRGs构建了一个IRG模型。在训练集中，IRG模型在1年、3年和5年时的曲线下面积（AUCs）分别达到0.948、0.820和0.831。此外，乳铁传递蛋白（LTF）被确定为与预后相关的关键IRG。LTF在肿瘤组织中的表达水平显著低于正常组织。ssGSEA的结果表明LTF的表达水平与免疫活性密切相关。
结论
这些发现表明，该预后模型和关键IRG可能成为PTC患者预后有前景的分子标志物。
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