ArticleEMBO molecular medicine2024
Diagnosis and prognosis prediction of gastric cancer by high-performance serum lipidome fingerprints.
Article in EMBO molecular medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
14 citing papers in PubMed.
- Liquid Biopsy for Molecular Residual Disease Detection and Postoperative Surveillance in Gastric Cancer: Current Evidence and Future Directions.International journal of molecular sciences · 2026Review
- Liquid biopsies for the diagnosis of early-stage gastric cancer: A 5-year systematic review.The journal of liquid biopsy · 2026Review
- Extracellular vesicle and particle biomarkers in cancer: a machine learning blueprint for liquid biopsy.Journal of nanobiotechnology · 2026Review
- Early detection of gastric cancer: a novel circulating microbiome DNA based liquid biopsy assay.NPJ precision oncology · 2026Article
- Multi-phase hybrid metabolomics framework identifies clinically applicable plasma signatures for early detection of gastric cancer.Nature communications · 2026Article
- Overcoming missing data in spatial metabolomics with machine learning imputation to accelerate downstream discovery.iScience · 2026Article
- Review
- Multi-Modal Metabolomics Deciphers Pan-Cancer Metabolic Landscapes and Spatial-Niche-Specific Alternations.Metabolites · 2026Article
- Transforming Gastric Biopsy Diagnostics: Integrating Omics Technologies and Artificial Intelligence.Biomedicines · 2026Article
- Lipidomics and single-cell transcriptomics uncover aberrant lipid metabolism in metaplasia lesions during gastric carcinogenesis.Journal of gastroenterology · 2026Article
- Lipid metabolism and the immune microenvironment in gastric cancer.Frontiers in immunology · 2026Review
- S-palmitoylation of MTDH regulates ferroptosis resistance in breast cancer cell.Journal of lipid research · 2026Article
- Liquid biopsy - a narrative review with an update on current US governmental clinical trials targeting immunotherapy.Future science OA · 2025Review
- Multi-omics perspectives for gastrointestinal malignancy: A systematic review.World journal of gastrointestinal surgery · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
18 authors.
Funding
Abstract
Early detection is warranted to improve prognosis of gastric cancer (GC) but remains challenging. Liquid biopsy combined with machine learning will provide new insights into diagnostic strategies of GC. Lipid metabolism reprogramming plays a crucial role in the initiation and development of tumors. Here, we integrated the lipidomics data of three cohorts (n = 944) to develop the lipid metabolic landscape of GC. We further constructed the serum lipid metabolic signature (SLMS) by machine learning, which showed great performance in distinguishing GC patients from healthy donors. Notably, the SLMS also held high efficacy in the diagnosis of early-stage GC. Besides, by performing unsupervised consensus clustering analysis on the lipid metabolic matrix of patients with GC, we generated the gastric cancer prognostic subtypes (GCPSs) with significantly different overall survival. Furthermore, the lipid metabolic disturbance in GC tissues was demonstrated by multi-omics analysis, which showed partially consistent with that in GC serums. Collectively, this study revealed an innovative strategy of liquid biopsy for the diagnosis of GC on the basis of the serum lipid metabolic fingerprints.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.