A liquid biopsy analysis of exosomal miRNA to detect lymph node metastasis in early gastric cancer.

469 Background: Additional surgical resection is required to achieve a complete cure 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 miRNA for the noninvasive detection of LNM in patients with high-risk EGC. Methods: Two genome-wide miRNA expression profiling datasets (GSE164174 and 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. Results: 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=0.84, 95% CI=0.64-0.95). Our risk stratification model was more accurate than the panel and was an independent predictor of LNM identification (AUC=0.97). Conclusions: A novel noninvasive, liquid biopsy-based method for patients with EGC may predict those traditionally classified as high-risk patients with LNM who are unlikely to benefit from surgical resection.

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Publication Details

Journal
Journal of Clinical Oncology
Published
2025-01-27
DOI
https://doi.org/10.1200/jco.2025.43.4_suppl.469
Primary Topic
Extracellular vesicles in disease
Type
article
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article

A liquid biopsy analysis of exosomal miRNA to detect lymph node metastasis in early gastric cancer.

Masaaki Nishi, Chie Takasu, Hideya Kashihara, Daichi Ishikawa et al.
Journal of Clinical Oncology
Extracellular vesicles in disease
article

A liquid biopsy analysis of exosomal miRNA to detect lymph node metastasis in early gastric cancer.

Masaaki Nishi, Chie Takasu, Hideya Kashihara, Daichi Ishikawa, Toshiaki Yoshimoto, Takuya Tokunaga, Yuma Wada, Mitsuo Shimada
article en

Abstract

469 Background: Additional surgical resection is required to achieve a complete cure 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 miRNA for the noninvasive detection of LNM in patients with high-risk EGC. Methods: Two genome-wide miRNA expression profiling datasets (GSE164174 and 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. Results: 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=0.84, 95% CI=0.64-0.95). Our risk stratification model was more accurate than the panel and was an independent predictor of LNM identification (AUC=0.97). Conclusions: A novel noninvasive, liquid biopsy-based method for patients with EGC may predict those traditionally classified as high-risk patients with LNM who are unlikely to benefit from surgical resection.

Journal of Clinical OncologyVol. 43(4_suppl)
Tokushima University (JP)
Openalex Percentile: Top 99%
Extracellular vesicles in disease
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