PDF(Pubmed)
Abstract：
UNASSIGNED: While the widespread use of endoscopic submucosal dissection (ESD) has significantly reduced the incidence of early esophageal cancer (ESCA), the limited ability of ESD to strip deep infiltrating esophageal lesions results in a considerable risk of intraoperative perforation. Circulating-free DNA (cfDNA) is widely used in modern tumor screening due to its non-invasive detection capabilities. A methylation analysis offers vital insights into the condition and advancement of malignancies due to its unique positioning, such as a marker of cancer. This study investigated the potential of combining a non-invasive liquid biopsy technique, along with a methylation analysis, to assess the surgical perforation risk of ESCA patients.
UNASSIGNED: In this study, we conducted an analysis of gene expression differences between stage I esophageal squamous carcinoma samples and healthy tissue samples using data from The Cancer Genome Atlas (TCGA) database. We also identified the genes associated with progression-free survival (PFS) in esophageal squamous carcinoma. Integrating the framework of the methylation analysis, we explored the methylated sites of these distinct genes. To refine this process, we used the Shiny Methylation Analysis Resource Tool (SMART) to conduct a comprehensive analysis of these sites. We then confirmed the stability of the methylation sites in different lesion conditions using methylation-specific quantitative polymerase chain reaction (MS-qPCR) with paraffin tissue samples collected after ESD.
UNASSIGNED: We analyzed RNA-sequencing data from 42 early stage ESCA patients and 17 controls, identifying 1,263 up-regulated and 460 down-regulated genes. Functional analyses revealed involvement in key pathways such as cell cycle regulation and immune responses. Furthermore, we identified 38 differentially expressed genes associated with PFS. Using SMART analysis, we found 217 hyper-methylated regions in 38 genes, suggesting potential early markers for ESCA. Validation experiments confirmed the reliability of 29 hyper-methylated regions in FFPE tissue samples and 6 regions in cfDNA. A LunaCAM model showed high accuracy [area under the curve (AUC) =0.89] in discriminating early ESCA. Integrated assessment of six highly methylated regions significantly improved predictive performance, with 90.56% sensitivity, highlighting the importance of combinatorial biomarker evaluation for early cancer detection.
UNASSIGNED: This study established a novel approach that integrates non-invasive testing with a methylation analysis to assess the surgical risk of early ESCA patients. The significance of changes in methylation sites in relation to lesion status should not be underestimated, as they have the potential to offer vital insights for proactive risk assessments before surgery.
UNASSIGNED: In this study, we conducted an analysis of gene expression differences between stage I esophageal squamous carcinoma samples and healthy tissue samples using data from The Cancer Genome Atlas (TCGA) database. We also identified the genes associated with progression-free survival (PFS) in esophageal squamous carcinoma. Integrating the framework of the methylation analysis, we explored the methylated sites of these distinct genes. To refine this process, we used the Shiny Methylation Analysis Resource Tool (SMART) to conduct a comprehensive analysis of these sites. We then confirmed the stability of the methylation sites in different lesion conditions using methylation-specific quantitative polymerase chain reaction (MS-qPCR) with paraffin tissue samples collected after ESD.
UNASSIGNED: We analyzed RNA-sequencing data from 42 early stage ESCA patients and 17 controls, identifying 1,263 up-regulated and 460 down-regulated genes. Functional analyses revealed involvement in key pathways such as cell cycle regulation and immune responses. Furthermore, we identified 38 differentially expressed genes associated with PFS. Using SMART analysis, we found 217 hyper-methylated regions in 38 genes, suggesting potential early markers for ESCA. Validation experiments confirmed the reliability of 29 hyper-methylated regions in FFPE tissue samples and 6 regions in cfDNA. A LunaCAM model showed high accuracy [area under the curve (AUC) =0.89] in discriminating early ESCA. Integrated assessment of six highly methylated regions significantly improved predictive performance, with 90.56% sensitivity, highlighting the importance of combinatorial biomarker evaluation for early cancer detection.
UNASSIGNED: This study established a novel approach that integrates non-invasive testing with a methylation analysis to assess the surgical risk of early ESCA patients. The significance of changes in methylation sites in relation to lesion status should not be underestimated, as they have the potential to offer vital insights for proactive risk assessments before surgery.
摘要：
■尽管内镜黏膜下剥离术（ESD）的广泛使用已显着降低了早期食管癌（ESCA）的发生率，ESD剥离深部浸润性食管病变的能力有限,导致术中穿孔的风险相当大.无循环DNA（cfDNA）由于其非侵入性检测能力而广泛用于现代肿瘤筛查。甲基化分析由于其独特的定位，为恶性肿瘤的病情和进展提供了重要的见解。比如癌症的标志物。这项研究调查了结合非侵入性液体活检技术的潜力，以及甲基化分析，评估ESCA患者的手术穿孔风险。
■在这项研究中，我们使用来自癌症基因组图谱(TCGA)数据库的数据,对Ⅰ期食管鳞癌样本和健康组织样本之间的基因表达差异进行了分析.我们还确定了与食管鳞癌无进展生存期（PFS）相关的基因。整合甲基化分析的框架，我们探索了这些不同基因的甲基化位点。为了完善这个过程，我们使用了闪亮的甲基化分析资源工具（SMART）对这些位点进行了全面分析。然后，我们使用甲基化特异性定量聚合酶链反应（MS-qPCR）与ESD后收集的石蜡组织样品确认了甲基化位点在不同病变条件下的稳定性。
■我们分析了42例早期ESCA患者和17例对照的RNA测序数据，鉴定1,263个上调基因和460个下调基因。功能分析显示参与关键途径，如细胞周期调节和免疫反应。此外，我们确定了38个与PFS相关的差异表达基因。使用SMART分析，我们在38个基因中发现了217个高甲基化区域,提示ESCA的潜在早期标志物。验证实验证实了FFPE组织样品中29个超甲基化区域和cfDNA中6个区域的可靠性。LunaCAM模型在区分早期ESCA方面显示出高精度[曲线下面积（AUC）=0.89]。对六个高度甲基化区域的综合评估显着提高了预测性能，灵敏度为90.56%，强调组合生物标志物评估对早期癌症检测的重要性。
■这项研究建立了一种新颖的方法，该方法将非侵入性测试与甲基化分析相结合，以评估早期ESCA患者的手术风险。不应低估甲基化位点变化与病变状态相关的重要性，因为它们有可能为手术前的前瞻性风险评估提供重要的见解。
■在这项研究中，我们使用来自癌症基因组图谱(TCGA)数据库的数据,对Ⅰ期食管鳞癌样本和健康组织样本之间的基因表达差异进行了分析.我们还确定了与食管鳞癌无进展生存期（PFS）相关的基因。整合甲基化分析的框架，我们探索了这些不同基因的甲基化位点。为了完善这个过程，我们使用了闪亮的甲基化分析资源工具（SMART）对这些位点进行了全面分析。然后，我们使用甲基化特异性定量聚合酶链反应（MS-qPCR）与ESD后收集的石蜡组织样品确认了甲基化位点在不同病变条件下的稳定性。
■我们分析了42例早期ESCA患者和17例对照的RNA测序数据，鉴定1,263个上调基因和460个下调基因。功能分析显示参与关键途径，如细胞周期调节和免疫反应。此外，我们确定了38个与PFS相关的差异表达基因。使用SMART分析，我们在38个基因中发现了217个高甲基化区域,提示ESCA的潜在早期标志物。验证实验证实了FFPE组织样品中29个超甲基化区域和cfDNA中6个区域的可靠性。LunaCAM模型在区分早期ESCA方面显示出高精度[曲线下面积（AUC）=0.89]。对六个高度甲基化区域的综合评估显着提高了预测性能，灵敏度为90.56%，强调组合生物标志物评估对早期癌症检测的重要性。
■这项研究建立了一种新颖的方法，该方法将非侵入性测试与甲基化分析相结合，以评估早期ESCA患者的手术风险。不应低估甲基化位点变化与病变状态相关的重要性，因为它们有可能为手术前的前瞻性风险评估提供重要的见解。
