Preoperative liquid biopsy transcriptomic panel for risk assessment of lymph node metastasis in T1 gastric cancer

Preoperative liquid biopsy transcriptomic panel for risk assessment of lymph node metastasis in T1 gastric cancer

Abstract Background The increasing incidence of early-stage T1 gastric cancer (GC) underscores the need for accurate preoperative risk stratification of lymph node metastasis (LNM). Current pathological assessments often misclassify patients, leading to unnecessary radical surgeries. Methods Through...

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Main Authors: Ping’an Ding, Jiaxiang Wu, Haotian Wu, Wenqian Ma, Tongkun Li, Peigang Yang, Honghai Guo, Yuan Tian, Jiaxuan Yang, Limian Er, Renjun Gu, Lilong Zhang, Ning Meng, Xiaolong Li, Zhenjiang Guo, Lingjiao Meng, Qun Zhao
Format: Article
Language:English
Published: BMC 2025-02-01
Series:Journal of Experimental & Clinical Cancer Research
Subjects:
Gastric cancer
Lymph node metastases
Liquid biopsy
Transcriptomics panel
Risk stratification assessment
Online Access:https://doi.org/10.1186/s13046-025-03305-x
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Summary:Abstract Background The increasing incidence of early-stage T1 gastric cancer (GC) underscores the need for accurate preoperative risk stratification of lymph node metastasis (LNM). Current pathological assessments often misclassify patients, leading to unnecessary radical surgeries. Methods Through analysis of transcriptomic data from public databases and T1 GC tissues, we identified a 4-mRNA panel (SDS, TESMIN, NEB, and GRB14). We developed and validated a Risk Stratification Assessment (RSA) model combining this panel with clinical features using surgical specimens (training cohort: n = 218; validation cohort: n = 186), gastroscopic biopsies (n = 122), and liquid biopsies (training cohort: n = 147; validation cohort: n = 168). Results The RSA model demonstrated excellent predictive accuracy for LNM in surgical specimens (training AUC = 0.890, validation AUC = 0.878), gastroscopic biopsies (AUC = 0.928), and liquid biopsies (training AUC = 0.873, validation AUC = 0.852). This model significantly reduced overtreatment rates from 83.9 to 44.1% in tissue specimens and from 84.4 to 56.0% in liquid biopsies. The 4-mRNA panel showed specificity for T1 GC compared to other gastrointestinal cancers (P < 0.001). Conclusions We developed and validated a novel liquid biopsy-based RSA model that accurately predicts LNM in T1 GC patients. This non-invasive approach could significantly reduce unnecessary surgical interventions and optimize treatment strategies for high-risk T1 GC patients.
ISSN:1756-9966

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