Evidence map›Paper›PMID 34976312›Full record

ArticleComputational and structural biotechnology journal2022

LCMD: Lung Cancer Metabolome Database.

Wei-Sheng Wu, Hsin-Yi Wu, Pin-Hsuan Wang, Ting-Yu Chen, Kuan-Ru Chen, Chih-Wei Chang, Dong-En Lee, Bo-Heng Lin, William Chih-Wei Chang, Pao-Chi Liao

Abstract read
In one paragraph

Article in Computational and structural biotechnology journal, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–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

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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

8 citing papers in PubMed.

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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

10 authors.

Wei-Sheng WuDepartment of Electrical Engineering, National Cheng Kung University, Tainan 70101, Taiwan.
Hsin-Yi WuInstrumentation Center, National Taiwan University, Taipei 10617, Taiwan.
Pin-Hsuan WangDepartment of Environmental and Occupational Health, National Cheng Kung University, Tainan 70101, Taiwan.
Ting-Yu ChenDepartment of Electrical Engineering, National Cheng Kung University, Tainan 70101, Taiwan.
Kuan-Ru ChenDepartment of Electrical Engineering, National Cheng Kung University, Tainan 70101, Taiwan.
Chih-Wei ChangDepartment of Environmental and Occupational Health, National Cheng Kung University, Tainan 70101, Taiwan.
Dong-En LeeDepartment of Electrical Engineering, National Cheng Kung University, Tainan 70101, Taiwan.
Bo-Heng LinDepartment of Electrical Engineering, National Cheng Kung University, Tainan 70101, Taiwan.
William Chih-Wei ChangDepartment of Environmental and Occupational Health, National Cheng Kung University, Tainan 70101, Taiwan.
Pao-Chi LiaoDepartment of Environmental and Occupational Health, National Cheng Kung University, Tainan 70101, Taiwan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lung cancer, one of the most common causes of cancer-related death worldwide, has been associated with high treatment cost and imposed great burdens. The 5-year postoperative survival rate of lung cancer (13%) is lower than many other leading cancers indicating the urgent needs to dissect its pathogenic mechanisms and discover specific biomarkers. Although several proteins have been proposed to be potential candidates for the diagnosis of lung cancer, they present low accuracy in clinical settings. Metabolomics has thus emerged as a very promising tool for biomarker discovery. To date, many lung cancer-related metabolites have been highlighted in the literature but no database is available for scientists to retrieve this information. Herein, we construct and introduce the first Lung Cancer Metabolome Database (LCMD), a freely available online database depositing 2013 lung cancer-related metabolites identified from 65 mass spectrometry-based lung cancer metabolomics studies. Researchers are able to explore LCMD via two ways. Firstly, by applying various filters in the "Browse Metabolites" mode, users can access a list of lung cancer-related metabolites that satisfy the filter specifications. For each metabolite, users can acquire the value of the fold change (cancer/normal), statistical significance (p-value) of the fold change, and the comparative research designs of all the mass spectrometry-based lung cancer metabolomics studies that identify this metabolite. Secondly, by applying various filters in the "Browse Studies" mode, users can obtain a list of mass spectrometry-based lung cancer metabolomics studies that satisfy the filter specifications. For each study, users can view the type of studied specimen, mass spectrometry (MS) method, MS data processing software, and differential analysis method, as well as all the identified lung cancer-related metabolites. Furthermore, the overview of each study is clearly illustrated by a graphical summary. The LCMD (http://cosbi7.ee.ncku.edu.tw/LCMD/) is the first database that brings together the meaningful information of lung cancer-related metabolites. The development of the LCMD is envisioned to promote the biomarker discovery of lung cancer.

Indexed as

BiomarkerDatabaseHMDB, Human Metabolome DatabaseLCMD, Lung Cancer Metabolome DatabaseLung cancerMass spectrometryMetaboliteMetabolomeMetabolomicsNSCLC, Non-Small-Cell Lung CarcinomaVIP, Variable Importance in Projection

Identifiers

PMID34976312
PMCPMC8683384

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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.