Zhou Xiaojuan, Tan Jiaqi, Wang Xueying, Zhang Xin, Miao Susheng, Liu Yong, Wang Junrong, Tan Guolin
Department of Otolaryngology Head and Neck Surgery, The Third Xiangya Hospital, Central South University Changsha 410013, Hunan, China.
Department of Otolaryngology Head and Neck Surgery, Xiangya Hospital, Central South University Changsha 410013, Hunan, China.
Am J Cancer Res. 2025 Mar 15;15(3):976-990. doi: 10.62347/MKFI3976. eCollection 2025.
Head and neck carcinomas are the sixth most common cancers worldwide, with laryngeal squamous cell carcinoma (LSCC) being the second most prevalent subtype. Improving survival outcomes in LSCC patients remains a critical clinical challenge. This retrospective study aimed to develop a nomogram model integrating tumor-infiltrating lymphocytes (TILs) and clinicopathological characteristics to predict the prognosis of LSCC patients. The nomogram model was constructed using Cox and Lasso regression analyses and was subsequently evaluated through receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). Data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) were utilized for model validation and to further elucidate the role of TILs and immune responses in LSCC. This study cohort included LSCC patients diagnosed by pathological examination between 2011 and 2014 at Xiangya Hospital and Harbin Medical University Cancer Hospital. A total of 412 patients were assigned to the training cohort and 140 patients to the test cohort for validation. The final nomogram model integrated TNM stage, TILs, PLR, BMI, age, differentiation and NLR. The area under the curve (AUC) was 0.745, indicating strong calibration and clinical utility. Kaplan-Meier survival curves demonstrated significant discrimination. TILs were positively correlated with immune cell abundance and the expression of immune-related genes. In conclusion, the nomogram model based on TILs and clinicopathological features effectively predicts the prognosis of LSCC patients.
头颈癌是全球第六大常见癌症,其中喉鳞状细胞癌(LSCC)是第二大常见亚型。改善LSCC患者的生存结果仍然是一项关键的临床挑战。这项回顾性研究旨在开发一种整合肿瘤浸润淋巴细胞(TILs)和临床病理特征的列线图模型,以预测LSCC患者的预后。该列线图模型采用Cox和Lasso回归分析构建,随后通过受试者工作特征(ROC)曲线、校准曲线和决策曲线分析(DCA)进行评估。利用来自癌症基因组图谱(TCGA)和基因表达综合数据库(GEO)的数据进行模型验证,并进一步阐明TILs和免疫反应在LSCC中的作用。本研究队列包括2011年至2014年期间在湘雅医院和哈尔滨医科大学附属肿瘤医院经病理检查确诊的LSCC患者。共有412例患者被分配到训练队列,140例患者被分配到测试队列进行验证。最终的列线图模型整合了TNM分期、TILs、血小板与淋巴细胞比率(PLR)、体重指数(BMI)、年龄、分化程度和中性粒细胞与淋巴细胞比率(NLR)。曲线下面积(AUC)为0.745,表明具有良好的校准和临床实用性。Kaplan-Meier生存曲线显示出显著的区分度。TILs与免疫细胞丰度和免疫相关基因的表达呈正相关。总之,基于TILs和临床病理特征的列线图模型能有效预测LSCC患者的预后。