Early diagnosis and molecular classification of gastric cancer peritoneal metastasis by deep learning-driven single-cell lipidomics
Deep sequencing of peritoneal fluid can detect hidden gastric cancer spread undetectable by standard imaging, addressing a previously difficult diagnostic gap.
Published in Cell Reports Medicine, this study demonstrates that deep sequencing of peritoneal lavage can detect and molecularly classify gastric cancer peritoneal metastasis at an occult stage undetectable by conventional diagnostics. This approach addresses the most lethal complication of gastric cancer with no current reliable early-detection method.
What the study was
- Study design
- Prospective biomarker study / Deep sequencing
- Population
- Patients with gastric cancer at risk of peritoneal metastasis
- Category
- Early Detection
- Maturity
- Exploratory
- Journal
- Cell reports. Medicine
Why it surfaced
Cell Reports Medicine study addressing an unmet need in gastric cancer peritoneal metastasis — highest lethality phenotype with no early detection; novel deep sequencing approach.
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