Evidence map›Paper›PMID 41530647›Full record

ArticleScience China. Life sciences2026

Comprehensive metabolic profiling uncovers early variation and biomarkers of esophageal squamous cell carcinoma.

Xia Shen, Yaqi Zhang, Qinqin Wang, Xumiao Li, Min Gao, Jun Li, Chen Li, Hui Wang

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Article in Science China. Life sciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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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.

2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Xia Shen *State Key Laboratory of Systems Medicine for Cancer, Center for Single-Cell Omics, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
Yaqi Zhang *State Key Laboratory of Systems Medicine for Cancer, Center for Single-Cell Omics, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
Qinqin WangState Key Laboratory of Systems Medicine for Cancer, Center for Single-Cell Omics, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
Xumiao LiState Key Laboratory of Systems Medicine for Cancer, Center for Single-Cell Omics, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
Min GaoState Key Laboratory of Systems Medicine for Cancer, Center for Single-Cell Omics, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
Jun LiCancer Prevention and Treatment Office, Yanting Cancer Hospital, Mianyang, 621600, China.
Chen LiState Key Laboratory of Systems Medicine for Cancer, Center for Single-Cell Omics, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China. cli@shsmu.edu.cn.
Hui WangState Key Laboratory of Systems Medicine for Cancer, Center for Single-Cell Omics, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China. huiwang@shsmu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Esophageal squamous cell carcinoma (ESCC) is a highly aggressive malignancy with a poor prognosis, primarily due to late-stage diagnosis. This study aimed to elucidate the metabolic alterations associated with the development and early progression of ESCC and to identify potential biomarkers for its early diagnosis. Using two independent cohorts comprising 245 individuals in total, with 161 individuals in cohort 1 (a cross-sectional cohort) and 84 LGIN patients in cohort 2 (a follow-up cohort) at baseline, untargeted metabolomic profiling of 329 serum samples revealed 1,431 metabolites. Significant dysregulation was observed in steroid hormone biosynthesis, primary bile acid biosynthesis, and glycine, serine, and threonine metabolism. Combining metabolomics and transcriptomics data, multi-omics integration identified key metabolites and genes driving these pathways, particularly in early tumorigenesis. Furthermore, 9 blood-based metabolites were identified as potential non-invasive biomarkers for early ESCC detection and achieved high predictive accuracy. The findings provide critical insights into the metabolic underpinnings of ESCC progression and underscore the value of blood-based metabolite biomarkers for early diagnosis.

Indexed as

Biomarkers, TumorEsophageal NeoplasmsEsophageal Squamous Cell CarcinomaMetabolomeMetabolomicsCarcinoma, Squamous CellCross-Sectional StudiesDisease ProgressionEarly Detection of CancerFemaleGene Expression ProfilingHumansMaleMiddle AgedMultiomicsTranscriptomeBiomarkers, Tumorearly detection biomarkersearly progressionesophageal squamous cell carcinoma processmetabolomicsmulti-omics integrationtranscriptomics

Identifiers

PMID41530647

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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.