Deng Zhuo, Zhang Lu, Sun Chenyang, Liu Yiping, Li Bin
Department of Gynecology, Shaanxi Provincial People's Hospital, Xi'an, 710000, China.
Heliyon. 2024 Sep 26;10(19):e38488. doi: 10.1016/j.heliyon.2024.e38488. eCollection 2024 Oct 15.
Cervical cancer, as one of the most common malignancies in women, is closely related to the mechanism of angiogenesis, which needs further exploration.
The squamous cell carcinoma of the cervix and cervical adenocarcinoma (CESC) data from The Cancer Genome Atlas (TCGA) database. CESC subtypes based on 48 angiogenesis-related genes were identified using consistent cluster analysis, and the limma package were adopted to screen the differentially expressed genes (DEGs) associated with prognosis. Further compress the DEGs through univariate and Least Absolute Shrinkage and Selection Operator (LASSO) COX analysis to identify the key genes. Calculate immune scores using the GSVA package and predict immunotherapy response with TIDE. For analysis, the expressions of these key genes were additionally tested via reverse-transcription quantitative PCR, and the migration and invasion of Hela cells were determined in scratch and transwell assays, respectively.
3 CESC subtypes were identified, with the best survival advantage in the C2 subtype and the worst in C1 subtype. A risk model was established utilizing seven key genes (MMP3, DLL4, CAP2, PDIA6, TCN2, PAPSS2, and VCAM1), showcases an Area Under the Curve (AUC) exceeding 0.7, underlining its robust performance. The risk score model showed a trend of poorer survival for patients in the high-risk score group and good agreement across different datasets. A nomogram was constructed, and calibration curves indicated robust predictive performance. Immunological analysis revealed heightened sensitivity to immunotherapy in the low-risk group. Besides, the elevated expressions of all 7 genes were seen in Hela cells, and the specific target-mediated DLL4 knockdown diminished the migration and invasion of Hela cells .
This research provides fresh insights and a valuable tool to guide therapeutic decision-making for CESC.
宫颈癌作为女性最常见的恶性肿瘤之一，与血管生成机制密切相关，仍需进一步探索。
从癌症基因组图谱（TCGA）数据库获取宫颈鳞状细胞癌和宫颈腺癌（CESC）数据。采用一致性聚类分析基于48个血管生成相关基因鉴定CESC亚型，并采用limma软件包筛选与预后相关的差异表达基因（DEG）。通过单变量分析和最小绝对收缩与选择算子（LASSO）COX分析进一步压缩DEG以鉴定关键基因。使用GSVA软件包计算免疫评分，并通过TIDE预测免疫治疗反应。为进行分析，通过逆转录定量PCR额外检测这些关键基因的表达，并分别在划痕试验和Transwell试验中测定Hela细胞的迁移和侵袭能力。
鉴定出3种CESC亚型，C2亚型生存优势最佳，C1亚型最差。利用7个关键基因（MMP3、DLL4、CAP2、PDIA6、TCN2、PAPSS2和VCAM1）建立了风险模型，其曲线下面积（AUC）超过0.7，表明其性能稳健。风险评分模型显示高风险评分组患者生存较差的趋势，且在不同数据集中一致性良好。构建了列线图，校准曲线显示出强大的预测性能。免疫分析显示低风险组对免疫治疗的敏感性更高。此外，在Hela细胞中观察到所有7个基因的表达均升高，特异性靶向介导的DLL4敲低减少了Hela细胞的迁移和侵袭。
本研究为指导CESC的治疗决策提供了新见解和有价值的工具。
