ArticleThe clinical respiratory journal2026
Serum Metabolomics Study Reveals a Diagnostic Model for Lung Cancer Brain Metastasis.
Article in The clinical respiratory journal, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Lung cancer remains the leading cause of cancer-related deaths worldwide, with brain metastasis being one of the most common complications in advanced-stage disease. The development of noninvasive and efficient early diagnostic methods is therefore of critical clinical importance. In this study, untargeted liquid chromatography-mass spectrometry (LC-MS) was employed to perform metabolomic profiling of 66 serum samples from patients with lung cancer brain metastasis, early-stage lung cancer, and healthy controls. A total of 719 metabolites were identified with high data reliability. Comparative analysis revealed 20 significantly upregulated and 12 significantly downregulated metabolites in the lung cancer brain metastasis group. These differentially expressed metabolites were primarily enriched in amino acid and energy metabolism pathways. This specific metabolic signature was highly associated with the brain metastatic state. Although not yet validated for clinical application, this profile demonstrated robust discriminatory power within the current cohort and serves as a potential set of risk-stratification biomarkers. These findings identify a distinct metabolic phenotype associated with brain metastasis, laying the critical groundwork for future research into noninvasive diagnostic strategies. Nevertheless, further validation within independent, longitudinal cohorts is required.
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.