Wada Yuma, Nishi Masaaki, Takasu Chie, Tokunaga Takuya, Kashihara Hideya, Yoshimoto Toshiaki, Shimada Mitsuo
Department of Surgery, Tokushima University, Tokushima, Japan.
Ann Surg Oncol. 2025 Sep 2. doi: 10.1245/s10434-025-18088-w.
Additional surgical resection is required to achieve curative treatment in patients with early gastric cancer (EGC) due to the potential risk for lymph node metastasis (LNM) after pathological analysis; however, LNM is estimated to occur in approximately 10% of patients with high-risk EGC. In this study, we investigated a blood-based liquid biopsy assay of exosomal microRNA (miRNA) for the non-invasive detection of LNM in patients with high-risk EGC.
Two genome-wide miRNA expression profiling datasets [GSE164174 and The Cancer Genome Atlas (TCGA)] were analyzed to prioritize biomarkers in pretreatment plasma samples from clinical training and validation cohorts of GC patients. An integrated exosomal miRNA panel was developed and a risk stratification model combining the miRNA panel with clinical risk factors was established.
Using comprehensive expression profiling of public datasets, we identified a transcriptomic panel of four miRNAs (miR-34b, miR-130a, miR-375, and miR-627) that robustly identified patients with LNM [area under the curve (AUC) 0.86, 95% confidence interval (CI) 0.77-0.92]. We assessed panel performance in a training cohort (AUC 0.86, 95% CI 0.67-0.96) and validated it in an independent validation cohort (AUC 0.83, 95% CI 0.68-0.94). Our risk stratification model was more accurate than the panel and was an independent predictor of LNM identification (AUC 0.94).
A novel, non-invasive, liquid biopsy-based method for patients with EGC may predict those conventionally classified as high-risk patients with LNM who are unlikely to benefit from surgical resection.
由于早期胃癌（EGC）患者在病理分析后存在淋巴结转移（LNM）的潜在风险，需要进行额外的手术切除以实现根治性治疗；然而，估计约10%的高危EGC患者会发生LNM。在本研究中，我们调查了一种基于血液的外泌体微小RNA（miRNA）液体活检检测方法，用于高危EGC患者LNM的无创检测。
分析了两个全基因组miRNA表达谱数据集[GSE164174和癌症基因组图谱（TCGA）]，以确定GC患者临床训练和验证队列预处理血浆样本中的生物标志物优先级。开发了一个综合外泌体miRNA检测板，并建立了一个将miRNA检测板与临床风险因素相结合的风险分层模型。
通过对公共数据集进行全面的表达谱分析，我们确定了一个由四个miRNA（miR-34b、miR-130a、miR-375和miR-627）组成的转录组检测板，该检测板能可靠地识别出LNM患者[曲线下面积（AUC）为0.86，95%置信区间（CI）为0.77-0.92]。我们在一个训练队列中评估了检测板的性能（AUC为0.86，95%CI为0.67-0.96），并在一个独立的验证队列中进行了验证（AUC为0.83，95%CI为0.68-0.94）。我们的风险分层模型比检测板更准确，是LNM识别的独立预测指标（AUC为0.94）。
一种针对EGC患者的新型、无创、基于液体活检的方法可能预测出那些传统上被归类为有LNM的高危患者，这些患者不太可能从手术切除中获益。
