Wang Weihua, Ruan Suyu, Xie Yuhang, Fang Shengjian, Yang Junxian, Li Xueyan, Zhang Yu
Department of Otolaryngology-Head and Neck Surgery, Shanghai East Hospital, School of Medicine, Tongji University, Shanghai, China.
Department of Nursing, Shanghai East Hospital, School of Medicine, Tongji University, Shanghai, China.
Clin Exp Otorhinolaryngol. 2024 Feb;17(1):85-97. doi: 10.21053/ceo.2023.00026. Epub 2024 Jan 22.
The necessity to develop a method for prognostication and to identify novel biomarkers for personalized medicine in patients with head and neck squamous cell carcinoma (HNSCC) cannot be overstated. Recently, pathomics, which relies on quantitative analysis of medical imaging, has come to the forefront. CXCL8, an essential inflammatory cytokine, has been shown to correlate with overall survival (OS). This study examined the relationship between CXCL8 mRNA expression and pathomics features and aimed to explore the biological underpinnings of CXCL8.
Clinical information and transcripts per million mRNA sequencing data were obtained from The Cancer Genome Atlas (TCGA)-HNSCC dataset. We identified correlations between CXCL8 mRNA expression and patient survival rates using a Kaplan-Meier survival curve. A retrospective analysis of 313 samples diagnosed with HNSCC in the TCGA database was conducted. Pathomics features were extracted from hematoxylin and eosin-stained images, and then the minimum redundancy maximum relevance, with recursive feature elimination (mRMR-RFE) method was applied, followed by screening with the logistic regression algorithm.
Kaplan-Meier curves indicated that high expression of CXCL8 was significantly associated with decreased OS. The logistic regression pathomics model incorporated 16 radiomics features identified by the mRMR-RFE method in the training set and demonstrated strong performance in the testing set. Calibration plots showed that the probability of high gene expression predicted by the pathomics model was in good agreement with actual observations, suggesting the model's high clinical applicability.
The pathomics model of CXCL8 mRNA expression serves as an effective tool for predicting prognosis in patients with HNSCC and can aid in clinical decision-making. Elevated levels of CXCL8 expression may lead to reduced DNA damage and are associated with a pro-inflammatory tumor microenvironment, offering a potential therapeutic target.
开发一种用于头颈部鳞状细胞癌（HNSCC）患者预后预测方法并识别个性化医疗新生物标志物的必要性再怎么强调都不为过。最近，依赖医学影像定量分析的病理组学已成为前沿领域。CXCL8是一种重要的炎性细胞因子，已被证明与总生存期（OS）相关。本研究探讨了CXCL8 mRNA表达与病理组学特征之间的关系，并旨在探索CXCL8的生物学基础。
从癌症基因组图谱（TCGA）-HNSCC数据集中获取临床信息和每百万转录本mRNA测序数据。我们使用Kaplan-Meier生存曲线确定CXCL8 mRNA表达与患者生存率之间的相关性。对TCGA数据库中313例诊断为HNSCC的样本进行回顾性分析。从苏木精和伊红染色图像中提取病理组学特征，然后应用最小冗余最大相关与递归特征消除（mRMR-RFE）方法，随后用逻辑回归算法进行筛选。
Kaplan-Meier曲线表明，CXCL8的高表达与OS降低显著相关。逻辑回归病理组学模型纳入了训练集中通过mRMR-RFE方法识别的16个放射组学特征，并在测试集中表现出强大性能。校准图显示，病理组学模型预测的高基因表达概率与实际观察结果高度一致，表明该模型具有较高的临床适用性。
CXCL8 mRNA表达的病理组学模型是预测HNSCC患者预后的有效工具，有助于临床决策。CXCL8表达水平升高可能导致DNA损伤减少，并与促炎性肿瘤微环境相关，提供了一个潜在的治疗靶点。
