Pan Wenjing,Zhao Jindu,Gao Qun.A ferroptosis-based prognostic signature for soft tissue sarcoma: a study integrating bioinformatics analysis and experimental validation[J].Journal of Clinical Pediatric Surgery,2026,(06):584-590.[doi:10.3760/cma.j.cn101785-20251105-00045]
基于铁死亡相关基因的软组织肉瘤预后模型:一项整合生物信息学分析与实验验证的研究
- Title:
- A ferroptosis-based prognostic signature for soft tissue sarcoma: a study integrating bioinformatics analysis and experimental validation
- Keywords:
- Solt Tissue Sarcoma; Bioinformatics; Ferroptosis; Genes; Prognosis; Risk Factors
- 摘要:
- 目的 基于铁死亡相关基因(ferroptosis-related genes,FRGs)构建软组织肉瘤(soft tissue sarcoma,STS)的预后风险模型,为STS患儿的预后评估以及个体化治疗提供理论依据。方法 本研究采用公共数据库回顾性队列研究及体外细胞实验方法。从癌症基因组图谱(The Cancer Genome Atlas,TCGA)肉瘤(Sarcoma)队列中获取TCGA-SARC作为训练集,通过单因素Cox回归、LASSO回归及多因素Cox回归分析,构建基于FRGs的多基因预后模型;另从基因表达综合数据库(gene expression omnibus,GEO)中获取GSE30929数据集作为验证集;最终通过RT-qPCR实验验证横纹肌肉瘤细胞系(A-204)与正常骨骼肌细胞系(human skeletal muscle cell,HSKMC)中核心基因的表达。结果 本研究成功构建包含ADIPOR1、SLC16A1、KAT5、HNRNPD、ACTL6A、NFKB2六个基因的预后模型。在训练集中,高风险组患儿总生存期明显缩短(Log-rank P＜0.001)。该模型用来预测1年、3年、5年生存率时,曲线下面积(area under the curve,AUC)分别为0.862、0.822和0.845,一致性指数(C-index)达到0.783,且组间的风险评分分布存在显著差异。实时定量PCR检测结果表明,6个基因在实验组A204和对照组HSKMC中的相对表达量分别为:ACTL6A(1.000±0.011),(0.485±0.036);SLC16A1(1.003±0.091),(0.678±0.046);HNRNPD(1.001±0.055),(0.794±0.038);NFKB2(1.003±0.092),(2.135±0.097);KAT5(0.430±0.033),(1.003±0.097);ADIPOR1(0.471±0.010),(1.000±0.018),差异均具有统计学意义(P<0.01)。结论 本研究构建的多基因预后模型揭示了铁死亡与肿瘤微环境重塑之间的潜在联系,且可有效预测STS患儿的生存结局,具备较好的风险分层能力,为STS患儿的预后评估及精准治疗提供了新思路。
- Abstract:
- Objective To develop a prognostic signature based upon ferroptosis-related genes (FRGs) for soft tissue sarcoma (STS),aiming to provide theoretical rationales for prognostic assessments and personalized treatments. Methods This study was conducted using a retrospective cohort analysis based upon public databases plus in vitro cell experiments.Transcriptomic and clinical data from the TCGA-SARC dataset within the item of sarcoma of The Cancer Genome Atlas (TCGA) were utilized as training cohort.A multi-gene prognostic signature was constructed through univariate Cox regression,LASSO regression and multivariate Cox regression analyses.The GSE30929 dataset from the Gene Expression Omnibus (GEO) database served as an independent validation cohort.Finally,RT-qPCR was performed for validating the expression of core genes in rhabdomyosarcoma cell line (A-204) and normal human skeletal muscle cell line (HSKMC). Results A six-gene prognostic signature comprising ADIPOR1,SLC16A1,KAT5,HNRNPD,ACTL6A and NFKB2 was successfully established.In training cohort,high-risk group exhibited significantly shorter overall survival (Log-rank P<0.001).And time-dependent receiver operating characteristic (ROC) analysis revealed that areas under the curve (AUC) for predicting 1/3/5-year survival rates were 0.862,0.822 and 0.845.Concordance index (C-index) was 0.783 and significant difference existed in risk score distribution between high- and low-risk groups.These findings were consistently confirmed in validation cohort.RT-qPCR results indicated that the relative expression levels of six genes in rhabdomyosarcoma cell line A-204 (experimental group) and normal human skeletal muscle cell line HSKMC (control group) were as follows (presented as mean±standard deviation): ACTL6A (1.000±0.011) vs. (0.485±0.036); SLC16A1 (1.003±0.091) vs. (0.678±0.046); HNRNPD (1.001±0.055) vs. (0.794±0.038); NFKB2 (1.003±0.092) vs. (2.135±0.097); KAT5 (0.430±0.033) vs. (1.003±0.097); ADIPOR1 (0.471±0.010) vs. (1.000±0.018).All differences were statistically significant (P<0.01). Conclusions This study has established a multi-gene prognostic model that not only highlighting potential interplay between ferroptosis and tumor microenvironment remodeling but also proving to be a reliable predictor of survival with significant risk stratification power in STS.These findings offer a promising new avenue for prognostic assessments and advancing precision medicine for STS.
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备注/Memo
收稿日期:2025-11-5。
基金项目:安徽省卫生健康科研项目(AHWJ2024Ab0085)
通讯作者:高群,Email:gaoqun@ahmu.edu.cn