Su Jiaming, Zhong Guanlin, Qin Weiling, Zhou Lu, Ye Jiemei, Ye Yinxing, Chen Chang, Liang Pan, Zhao Weilin, Xiao Xue, Wen Wensheng, Luo Wenqi, Zhou Xiaoying, Zhang Zhe, Cai Yonglin, Li Cheng
Department of Otolaryngology-Head and Neck Surgery, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.
Department of Clinical Laboratory, Wuzhou Red Cross Hospital, #3-1 Xinxing Yi Road, Wuzhou, 543002, Guangxi, China.
Discov Oncol. 2024 Apr 11;15(1):112. doi: 10.1007/s12672-024-00969-3.
Dysregulation of iron metabolism has been shown to have significant implications for cancer development. We aimed to investigate the prognostic and immunological significance of iron metabolism-related genes (IMRGs) in nasopharyngeal carcinoma (NPC).
Multiple Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) datasets were analyzed to identify key IMRGs associated with prognosis. Additionally, the immunological significance of IMRGs was explored.
A novel risk model was established using the LASSO regression algorithm, incorporating three genes (TFRC, SLC39A14, and ATP6V0D1).This model categorized patients into low and high-risk groups, and Kaplan-Meier analysis revealed significantly shorter progression-free survival for the high-risk group (P < 0.0001). The prognostic model's accuracy was additionally confirmed by employing time-dependent Receiver Operating Characteristic (ROC) curves and conducting Decision Curve Analysis (DCA). High-risk patients were found to correlate with advanced clinical stages, specific tumor microenvironment subtypes, and distinct morphologies. ESTIMATE analysis demonstrated a significant inverse relationship between increased immune, stromal, and ESTIMATE scores and lowered risk score. Immune analysis indicated a negative correlation between high-risk score and the abundance of most tumor-infiltrating immune cells, including dendritic cells, CD8 T cells, CD4 T cells, and B cells. This correlation extended to immune checkpoint genes such as PDCD1, CTLA4, TIGIT, LAG3, and BTLA. The protein expression patterns of selected genes in clinical NPC samples were validated through immunohistochemistry.
This study presents a prognostic model utilizing IMRGs in NPC, which could assist in assessing patient prognosis and provide insights into new therapeutic targets for NPC.
铁代谢失调已被证明对癌症发展具有重要影响。我们旨在研究铁代谢相关基因（IMRGs）在鼻咽癌（NPC）中的预后和免疫学意义。
分析多个基因表达综合数据库（GEO）和癌症基因组图谱（TCGA）数据集，以鉴定与预后相关的关键IMRGs。此外，还探讨了IMRGs的免疫学意义。
使用LASSO回归算法建立了一个新的风险模型，纳入了三个基因（TFRC、SLC39A14和ATP6V0D1）。该模型将患者分为低风险和高风险组，Kaplan-Meier分析显示高风险组的无进展生存期明显缩短（P < 0.0001）。通过使用时间依赖性受试者操作特征（ROC）曲线和进行决策曲线分析（DCA），进一步证实了预后模型的准确性。发现高风险患者与晚期临床分期、特定肿瘤微环境亚型和不同形态相关。ESTIMATE分析表明，免疫、基质和ESTIMATE评分增加与风险评分降低之间存在显著的负相关。免疫分析表明，高风险评分与大多数肿瘤浸润免疫细胞的丰度呈负相关，包括树突状细胞、CD8 T细胞、CD4 T细胞和B细胞。这种相关性扩展到免疫检查点基因，如PDCD1、CTLA4、TIGIT、LAG3和BTLA。通过免疫组织化学验证了临床NPC样本中所选基因的蛋白质表达模式。
本研究提出了一种利用NPC中IMRGs的预后模型，该模型可有助于评估患者预后，并为NPC的新治疗靶点提供见解。
