Prognostic Value of Ferroptosis-Immunity-Related Signature Genes in Cervical Cancer Radiotherapy Resistance and Risk Modeling.

IF 2.5 4区 医学 Q3 ONCOLOGY
Cancer Management and Research Pub Date : 2025-03-12 eCollection Date: 2025-01-01 DOI:10.2147/CMAR.S501663
Xianzhen Zhang, Aihua Li, Wanqi Zhu, Qiufen Guo, Qian Wu, Hong Zhao, Yunbei Yu, Peng Xie, Xiaolin Li
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引用次数: 0

Abstract

Introduction: The aim of this study was to clarify the genome of ferroptosis in the genes involved in radiotherapy resistance and regulation of tumor immune microenvironment by multigene analysis of cervical cancer (CC) patients.

Methods: Different radiation sensitivity samples from CC patients were collected for RNA sequencing. Differentially expressed genes (DEGs) between the RNA dataset and the GSE9750 dataset were considered as radiotherapy-DEGs. The intersection genes of radiotherapy-DEGs with ferroptosis-related genes (FRGs) and the intersection genes of radiotherapy-DEGs with immune-related genes (IRGs) were labeled as FRGs-IRGs-DEGs (FIGs). A risk model was established by prognostic genes selected from FIGs by univariate Cox analysis and least absolute shrinkage and selection operator (LASSO) analysis. The results were further validated using samples from CC tissue samples.

Results: The 329 DEGs related to CC radiotherapy were identified. LSAAO analysis was utilized to identify five prognostic genes (CALCRL, UCHL1, GNRH1, ACVRL1, and MUC1) from six candidate prognosis genes and construct a risk model. The risk model demonstrated favorable effectiveness in predicting outcomes at 1, 3, and 5 years, as evidenced by ROC curves. Univariate and multivariate Cox regression analysis demonstrated that CALCRL, GNRH1, and MUC1 were independent prognostic factors. The results of functional similarity analysis showed that CALCRL, UCHL1, ACVRL1 and MUC1 had high average functional similarity. The results of PCR and IHC showed the same trend with the results above.

Discussion: A novel prognostic model related to ferroptosis and immune microenvironment in CC radiotherapy was developed and validated, providing valuable guidance for personalized anti-cancer therapy.

凋亡铁免疫相关标记基因在宫颈癌放疗抵抗和风险建模中的预后价值。
前言:本研究旨在通过对宫颈癌(CC)患者的多基因分析,阐明与放疗耐药和肿瘤免疫微环境调控相关的铁上吊基因的基因组。方法:采集CC患者不同辐射敏感性标本进行RNA测序。RNA数据集和GSE9750数据集之间的差异表达基因(DEGs)被认为是放射治疗-DEGs。将放射治疗- degs与凋亡相关基因(FRGs)的交叉基因和放射治疗- degs与免疫相关基因(IRGs)的交叉基因标记为FRGs-IRGs- degs (FIGs)。通过单变量Cox分析和最小绝对收缩和选择算子(LASSO)分析,从FIGs中选择预后基因,建立风险模型。使用CC组织样本进一步验证了结果。结果:共鉴定出329例与CC放疗相关的deg。利用LSAAO分析从6个候选预后基因中鉴定出5个预后基因(CALCRL、UCHL1、GNRH1、ACVRL1、MUC1),构建风险模型。ROC曲线证明,风险模型在预测1、3和5年预后方面具有良好的有效性。单因素和多因素Cox回归分析显示,CALCRL、GNRH1和MUC1是独立的预后因素。功能相似度分析结果显示,CALCRL、UCHL1、ACVRL1和MUC1具有较高的平均功能相似度。PCR和免疫组化结果与上述结果一致。讨论:建立并验证了CC放疗中铁下垂与免疫微环境相关的新型预后模型,为个性化抗癌治疗提供有价值的指导。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Cancer Management and Research
Cancer Management and Research Medicine-Oncology
CiteScore
7.40
自引率
0.00%
发文量
448
审稿时长
16 weeks
期刊介绍: Cancer Management and Research is an international, peer reviewed, open access journal focusing on cancer research and the optimal use of preventative and integrated treatment interventions to achieve improved outcomes, enhanced survival, and quality of life for cancer patients. Specific topics covered in the journal include: ◦Epidemiology, detection and screening ◦Cellular research and biomarkers ◦Identification of biotargets and agents with novel mechanisms of action ◦Optimal clinical use of existing anticancer agents, including combination therapies ◦Radiation and surgery ◦Palliative care ◦Patient adherence, quality of life, satisfaction The journal welcomes submitted papers covering original research, basic science, clinical & epidemiological studies, reviews & evaluations, guidelines, expert opinion and commentary, and case series that shed novel insights on a disease or disease subtype.
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