Xu Junfen, Ji Qinghua, Kong Quanming, Lv Lijuan, Zhu Bo, Huang Xiufeng, Chen Zhengyun, Xu Ping, Li Xiao, Yin Weiwei, Wang Hui
Department of Gynecologic Oncology, Women's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China; Zhejiang Key Laboratory of Precision Diagnosis and Therapy for Major Gynecological Diseases, Women's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China; Cancer Center, Zhejiang University, Hangzhou, Zhejiang, China.
Zhejiang Puluoting Health Technology Co Ltd, Hangzhou, Zhejiang, China.
Cell Rep Med. 2025 Jun 17;6(6):102149. doi: 10.1016/j.xcrm.2025.102149. Epub 2025 May 23.
Cervical cancer remains a major global health concern for women. Current screening methods are either invasive or lead to low participation and over-referral for colposcopy, particularly among high-risk human papillomavirus (HPV)-positive women. This study analyzes 613 participants with varying cervical lesions using mass cytometry by time-of-flight (CyTOF) to identify disease-specific peripheral immune signatures. A diagnostic model based on 23 immune features achieves ∼91% sensitivity and specificity for detecting precancerous and cancerous lesions. A separate model for HPV-positive women shows even higher accuracy (∼93% sensitivity, ∼95% specificity), especially in HPV16/18-positive cases (99% sensitivity, 100% specificity). In an independent validation cohort (n = 105), the model distinguishes cervical intraepithelial neoplasia (CIN) 2+ from ≤CIN1 with 86.5% sensitivity and 85.3% specificity (area under the curve [AUC] = 0.89). These findings support peripheral immune profiling as a minimally invasive and accurate biomarker strategy for early cervical cancer screening, particularly in HPV16/18-positive women.
宫颈癌仍然是全球女性主要的健康问题。目前的筛查方法要么具有侵入性，要么导致参与度低以及阴道镜检查转诊过多，尤其是在高危人乳头瘤病毒（HPV）阳性女性中。本研究使用飞行时间质谱流式细胞术（CyTOF）分析了613名患有不同宫颈病变的参与者，以识别疾病特异性外周免疫特征。基于23种免疫特征的诊断模型在检测癌前病变和癌性病变时，灵敏度和特异性达到了约91%。针对HPV阳性女性的单独模型显示出更高的准确性（约93%的灵敏度，约95%的特异性），尤其是在HPV16/18阳性病例中（99%的灵敏度，100%的特异性）。在一个独立验证队列（n = 105）中，该模型区分宫颈上皮内瘤变（CIN）2级及以上与CIN1级及以下的灵敏度为86.5%，特异性为85.3%（曲线下面积[AUC] = 0.89）。这些发现支持外周免疫谱分析作为一种微创且准确的生物标志物策略，用于早期宫颈癌筛查，尤其是在HPV16/18阳性女性中。
