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Peer-reviewedCC BY-NC-ND 4.0NPJ Precision Oncology

Transcriptomics-driven non-invasive liquid biopsy for diagnosing peritoneal lavage cytology-positive gastric cancer

  • Ping’an Ding1,2,3
  • Honghai Guo1,2,3
  • Wenqian Ma2,3,4
  • Jiaxiang Wu1,2,3
  • Haotian Wu1,2,3
  • Tongkun Li1,2,3
  • Renjun Gu5,6
  • Lilong Zhang7
  • Ning Meng8
  • Xiaolong Li9
  • Zhenjiang Guo10
  • Lingjiao Meng11
1 more authors
  • Qun Zhao1,2,3
11 affiliations
  1. 1The Third Department of Surgery, The Fourth Hospital of Hebei Medical University, Shijiazhuang, China
  2. 2Hebei Key Laboratory of Precision Diagnosis and Comprehensive Treatment of Gastric Cancer, Shijiazhuang, China
  3. 3Big Data Analysis and Mining Application for Precise Diagnosis and Treatment of Gastric Cancer Hebei Provincial Engineering Research Center, Shijiazhuang, China
  4. 4Department of Endoscopy, The Fourth Hospital of Hebei Medical University, Shijiazhuang, China
  5. 5School of Chinese Medicine, Nanjing University of Chinese Medicine, Nanjing, China
  6. 6Department of Gastroenterology and Hepatology, Jinling Hospital, Medical School of Nanjing University, Nanjing, China
  7. 7Department of General Surgery, Renmin Hospital of Wuhan University, Wuhan, China
  8. 8Department of General Surgery, Shijiazhuang People’s Hospital, Shijiazhuang, China
  9. 9Department of General Surgery, Baoding Central Hospital, Baoding, China
  10. 10General Surgery Department, Hengshui People’s Hospital, Hengshui, China
  11. 11Research Center and Tumor Research Institute of the Fourth Hospital of Hebei Medical University, Shijiazhuang, China
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Abstract

Gastric cancer remains a leading cause of cancer-related mortality, with positive peritoneal lavage cytology (PLC) indicating early peritoneal metastasis and poor prognosis. However, conventional imaging and laparoscopy lack sufficient sensitivity for early detection. In this study, six mRNA biomarkers (NOX1, CHEK1, BUB1, NEK2, PRC1, SLCO1B3) were identified through transcriptomic analysis and integrated with clinical features to develop a Risk Stratification Assessment (RSA) model for predicting PLC-positive status. The six-mRNA panel was significantly upregulated in PLC-positive tissues and peripheral blood. The RSA model demonstrated strong diagnostic performance, with AUCs of 0.869 and 0.856 in training and validation cohorts, respectively, and 0.874 and 0.912 in peripheral blood analysis. Moreover, high-risk patients classified by the model had significantly lower 5-year overall survival rates than low-risk patients. This transcriptomics-based RSA model offers a non-invasive, accurate, and clinically meaningful tool for early identification of PLC-positive gastric cancer, potentially surpassing the sensitivity of current diagnostic methods. This study includes prospective analyses from two registered clinical trials: Chinese Clinical Trial Registry, ChiCTR1800014817 (registration date: January 8, 2018; http://www.chictr.org.cn) and ClinicalTrials.gov, NCT03718624 (registration date: October 26, 2018; https://clinicaltrials.gov/ct2/show/NCT03718624).

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Cite

BibTeXRIS
BibTeX
@article{ding2026transcriptomicsdriven,
  title = {{Transcriptomics-driven non-invasive liquid biopsy for diagnosing peritoneal lavage cytology-positive gastric cancer}},
  author = {Ping’an Ding and Honghai Guo and Wenqian Ma and Jiaxiang Wu and Haotian Wu and Tongkun Li and Renjun Gu and Lilong Zhang and Ning Meng and Xiaolong Li and Zhenjiang Guo and Lingjiao Meng and Qun Zhao},
  journal = {NPJ Precision Oncology},
  year = {2026},
  month = jul,
  doi = {10.1038/s41698-026-01531-w},
  url = {https://doi.org/10.1038/s41698-026-01531-w},
  note = {CC BY-NC-ND 4.0},
}
RIS
TY  - JOUR
TI  - Transcriptomics-driven non-invasive liquid biopsy for diagnosing peritoneal lavage cytology-positive gastric cancer
AU  - Ping’an Ding
AU  - Honghai Guo
AU  - Wenqian Ma
AU  - Jiaxiang Wu
AU  - Haotian Wu
AU  - Tongkun Li
AU  - Renjun Gu
AU  - Lilong Zhang
AU  - Ning Meng
AU  - Xiaolong Li
AU  - Zhenjiang Guo
AU  - Lingjiao Meng
AU  - Qun Zhao
PY  - 2026
DA  - 2026/07/15
JO  - NPJ Precision Oncology
DO  - 10.1038/s41698-026-01531-w
UR  - https://doi.org/10.1038/s41698-026-01531-w
AB  - Gastric cancer remains a leading cause of cancer-related mortality, with positive peritoneal lavage cytology (PLC) indicating early peritoneal metastasis and poor prognosis. However, conventional imaging and laparoscopy lack sufficient sensitivity for early detection. In this study, six mRNA biomarkers (NOX1, CHEK1, BUB1, NEK2, PRC1, SLCO1B3) were identified through transcriptomic analysis and integrated with clinical features to develop a Risk Stratification Assessment (RSA) model for predicting PLC-positive status. The six-mRNA panel was significantly upregulated in PLC-positive tissues and peripheral blood. The RSA model demonstrated strong diagnostic performance, with AUCs of 0.869 and 0.856 in training and validation cohorts, respectively, and 0.874 and 0.912 in peripheral blood analysis. Moreover, high-risk patients classified by the model had significantly lower 5-year overall survival rates than low-risk patients. This transcriptomics-based RSA model offers a non-invasive, accurate, and clinically meaningful tool for early identification of PLC-positive gastric cancer, potentially surpassing the sensitivity of current diagnostic methods. This study includes prospective analyses from two registered clinical trials: Chinese Clinical Trial Registry, ChiCTR1800014817 (registration date: January 8, 2018; http://www.chictr.org.cn) and ClinicalTrials.gov, NCT03718624 (registration date: October 26, 2018; https://clinicaltrials.gov/ct2/show/NCT03718624).
SN  - 2397-768X
ER  -