关键词: Comprehensive analysis Mitochondrial damage Oral squamous cell carcinoma Prognosis

Mesh : Humans Mouth Neoplasms / genetics pathology Prognosis Female Male Carcinoma, Squamous Cell / genetics pathology Mitochondria / genetics Middle Aged Biomarkers, Tumor / genetics Gene Expression Regulation, Neoplastic Kaplan-Meier Estimate Nomograms

来  源:   DOI:10.1186/s12920-024-01985-6   PDF(Pubmed)

Abstract:
Oral squamous cell carcinoma (OSCC), the most prevalent form of oral cancer, poses significant challenges to the medical community due to its high recurrence rate and low survival rate. Mitochondrial Damage-Related Genes (MDGs) have been closely associated with the occurrence, metastasis, and progression of OSCC. Consequently, we constructed a prognostic model for OSCC based on MDGs and identified potential mitochondrial damage-related biomarkers. Gene expression profiles and relevant clinical information were obtained from The Cancer Genome Atlas (TCGA) database. Differential analysis was conducted to identify MDGs associated with OSCC. COX analysis was employed to screen seven prognosis-related MDGs and build a prognostic prediction model for OSCC. Cases were categorized into low-risk or high-risk groups based on the optimal risk score threshold. Kaplan-Meier (KM) analysis revealed significant survival differences (P < 0.05). Additionally, the area under the ROC curve (AUC) for patient survival at 1 year, 3 years, and 5 years were 0.687, 0.704, and 0.70, respectively, indicating a high long-term predictive accuracy of the prognostic model. To enhance predictive accuracy, age, gender, risk score, and TN staging were incorporated into a nomogram and verified using calibration curves. Risk scoring based on MDGs was identified as a potential independent prognostic biomarker. Furthermore, BID and SLC25A20 were identified as two potential independent mitochondrial damage-related prognostic biomarkers, offering new therapeutic targets for OSCC.
摘要:
口腔鳞状细胞癌(OSCC),口腔癌最常见的形式,由于其高复发率和低生存率,给医学界带来了重大挑战。线粒体损伤相关基因(MDGs)的发生与发生密切相关,转移,以及OSCC的进展。因此,我们构建了基于MDG的OSCC预后模型,并确定了潜在的线粒体损伤相关生物标志物.从癌症基因组图谱(TCGA)数据库获得基因表达谱和相关临床信息。进行了差异分析,以确定与OSCC相关的千年发展目标。采用COX分析筛选7个与预后相关的MDG,建立OSCC的预后预测模型。根据最佳风险评分阈值将病例分为低风险或高风险组。Kaplan-Meier(KM)分析显示生存差异有统计学意义(P<0.05)。此外,患者1年生存率的ROC曲线下面积(AUC),3年,和5年分别为0.687、0.704和0.70,表明预后模型的长期预测准确性很高。为了提高预测准确性,年龄,性别,风险评分,将TN分期纳入列线图中,并使用校准曲线进行验证。基于MDG的风险评分被确定为潜在的独立预后生物标志物。此外,BID和SLC25A20被鉴定为两个潜在的独立线粒体损伤相关预后生物标志物,为OSCC提供新的治疗靶点。
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