Evidence map›Paper›PMID 35287685›Full record

ReviewJournal of translational medicine2022

Untargeted metabolomics analysis of esophageal squamous cell cancer progression.

Tao Yang, Ruting Hui, Jessica Nouws, Maor Sauler, Tianyang Zeng, Qingchen Wu

Abstract readReview
In one paragraph

Review in Journal of translational medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 67 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
67citing papers in PubMed, 3 pooled it
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

67 citing papers in PubMed, 3 syntheses or guidelines pooled it.

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7 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Tao YangDepartment of Thoracic and Cardiovascular Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China. xiangfei654@hotmail.com.ORCID 0000-0003-1273-0089
Ruting HuiDepartment of Rehabilitation Medicine, Chengdu First Peoples' Hospital, Chengdu, 610016, Sichuan, China.
Jessica NouwsDepartment of Pulmonary, Critical Care and Sleep Medicine, School of Medicine of Yale University, New Haven, CT, 06510, USA.
Maor SaulerDepartment of Pulmonary, Critical Care and Sleep Medicine, School of Medicine of Yale University, New Haven, CT, 06510, USA.
Tianyang ZengDepartment of Thoracic and Cardiovascular Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China.
Qingchen WuDepartment of Thoracic and Cardiovascular Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China. qcwucq@163.com.

Funding

Yale Clinical and Translational Science Award (U Component)UL1TR001863 · NCATS · YALE UNIVERSITY · PI John H. Krystal, LUCILA OHNO-MACHADO · 2016 to 2026
$102.9M
Chongqing Natural Science Foundation cstc2018jcyjAX0245NCATS NIH HHS UL1 TR001863
6 · The paper itself

Abstract

90% of esophageal cancer are esophageal squamous cell carcinoma (ESCC) and ESCC has a very poor prognosis and high mortality. Nevertheless, the key metabolic pathways associated with ESCC progression haven't been revealed yet. Metabolomics has become a new platform for biomarker discovery over recent years. We aim to elucidate dominantly metabolic pathway in all ESCC tumor/node/metastasis (TNM) stages and adjacent cancerous tissues. We collected 60 postoperative esophageal tissues and 15 normal tissues adjacent to the tumor, then performed Liquid Chromatography with tandem mass spectrometry (LC-MS/MS) analyses. The metabolites data was analyzed with metabolites differential and correlational expression heatmap according to stage I vs. con., stage I vs. stage II, stage II vs. stage III, and stage III vs. stage IV respectively. Metabolic pathways were acquired by Kyoto Encyclopedia of Genes and Genomes. (KEGG) pathway database. The metabolic pathway related genes were obtained via Gene Set Enrichment Analysis (GSEA). mRNA expression of ESCC metabolic pathway genes was detected by two public datasets: gene expression data series (GSE)23400 and The Cancer Genome Atlas (TCGA). Receiver operating characteristic curve (ROC) analysis is applied to metabolic pathway genes. 712 metabolites were identified in total. Glycerophospholipid metabolism was significantly distinct in ESCC progression. 16 genes of 77 genes of glycerophospholipid metabolism mRNA expression has differential significance between ESCC and normal controls. Phosphatidylserine synthase 1 (PTDSS1) and Lysophosphatidylcholine Acyltransferase1 (LPCAT1) had a good diagnostic value with Area under the ROC Curve (AUC) > 0.9 using ROC analysis. In this study, we identified glycerophospholipid metabolism was associated with the ESCC tumorigenesis and progression. Glycerophospholipid metabolism could be a potential therapeutic target of ESCC progression.

Indexed as

Carcinoma, Squamous CellEsophageal NeoplasmsEsophageal Squamous Cell CarcinomaChromatography, LiquidEpithelial CellsHumansMetabolomicsTandem Mass SpectrometryEsophageal squamous cell carcinomaGlycerophospholipid metabolismLPCAT1MetabolomicsPTDSS1

Identifiers

PMID35287685
PMCPMC8919643

What OpenQuestion holds

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Registered trials

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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.