Liu Jun, Lu Jianjun, Wang Gefei, Gu Liming, Li Wenli
Department of Clinical Laboratory, Dongguan Hospital of Guangzhou University of Chinese Medicine, Dongguan 523005, China.
Guangdong Provincial Key Laboratory of Infectious Diseases and Molecular Immunopathology, Shantou University Medical College, Shantou 515000, China.
Aging (Albany NY). 2024 Jan 17;16(2):1536-1554. doi: 10.18632/aging.205443.
Sarcoma is a rare malignant tumor originating of the interstitial or connective tissue with a poor prognosis. Next-generation sequencing technology offers new opportunities for accurate diagnosis and treatment of sarcomas. There is an urgent need for new gene signature to predict prognosis and evaluate treatment outcomes.
We used transcriptome data from the Cancer Genome Atlas (TCGA) database and single sample gene set enrichment analysis (ssGSEA) to explore the cancer hallmarks most associated with prognosis in sarcoma patients. Then, weighted gene coexpression network analysis, univariate COX regression analysis and random forest algorithm were used to construct prognostic gene characteristics. Finally, the prognostic value of gene markers was validated in the TCGA and Integrated Gene Expression (GEO) (GSE17118) datasets, respectively.
MYC targets V1 and V2 are the main cancer hallmarks affecting the overall survival (OS) of sarcoma patients. A six-gene signature including VEGFA, HMGB3, FASN, RCC1, NETO2 and BIRC5 were constructed. Kaplan-Meier analysis suggested that higher risk scores based on the six-gene signature associated with poorer OS ( < 0.001). The receiver Operating characteristic curve showed that the risk score based on the six-gene signature was a good predictor of sarcoma, with an area under the curve (AUC) greater than 0.73. In addition, the prognostic value of the six-gene signature was validated in GSE17118 with an AUC greater than 0.72.
This six-gene signature is an independent prognostic factor in patients with sarcoma and is expected to be a potential therapeutic target for sarcoma.
肉瘤是一种起源于间质或结缔组织的罕见恶性肿瘤，预后较差。新一代测序技术为肉瘤的准确诊断和治疗提供了新机会。迫切需要新的基因特征来预测预后和评估治疗效果。
我们使用来自癌症基因组图谱（TCGA）数据库的转录组数据和单样本基因集富集分析（ssGSEA）来探索与肉瘤患者预后最相关的癌症特征。然后，使用加权基因共表达网络分析、单变量COX回归分析和随机森林算法构建预后基因特征。最后，分别在TCGA和综合基因表达（GEO）（GSE17118）数据集中验证基因标志物的预后价值。
MYC靶标V1和V2是影响肉瘤患者总生存期（OS）的主要癌症特征。构建了一个包含VEGFA、HMGB3、FASN、RCC1、NETO2和BIRC5的六基因特征。Kaplan-Meier分析表明，基于六基因特征的较高风险评分与较差的OS相关（<0.001）。受试者工作特征曲线显示，基于六基因特征的风险评分是肉瘤的良好预测指标，曲线下面积（AUC）大于0.73。此外，六基因特征的预后价值在GSE17118中得到验证，AUC大于0.72。
这个六基因特征是肉瘤患者的独立预后因素，有望成为肉瘤的潜在治疗靶点。
