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.

To collect lung cancer-related metabolites from mass spectrometry-based metabolomics studies in the literature, we searched PubMed using the keywords ((lung cancer [Title/Abstract]) OR (lung adenocarcinoma) [Title/Abstract])) AND (mass spec* [Title/Abstract]) AND (metabol* [Title/Abstract]) appeared in the Title/Abstract on Nov. 15, 2021 and found 447 papers. From these 447 papers, we manually checked each paper and kept 65 mass spectrometry-based lung cancer metabolomics studies which aimed to identify metabolite biomarkers for lung cancer in human specimens. For each study (cancer vs. normal), the following information were collected: 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.

From these 65 mass spectrometry-based lung cancer metabolomics studies, we extracted 2013 lung cancer-related metabolites which were identified in at least one of these 65 studies. For each metabolite, the following information was collected: the value of the fold change (cancer/normal), the statistical significance (p-value) of the fold change, and the comparative research designs of all the studies that identify this metabolite.

The LCMD provides two browse modes (“Browse Metabolites” and “Browse Studies”).

Using the “Browse Metabolites” mode, users can browse metabolites in LCMD by applying 11 kinds of filters (metabolite name, chemical taxonomy, participants, specimen, marker function, chromatography, ion source, p-value, FDR, fold change, and VIP).

Users then can access to a list of lung cancer-related metabolites that satisfy the filter specifications and receive the summary information of each metabolite. By clicking on the “HMDB ID” (e.g. HMDB0003403), users will be directed to the HMDB site.

By clicking on the “Reference” (e.g. Wen et al. 2013), users will be directed to a page containing the detailed information of the selected mass spectrometry-based lung cancer metabolomics studies. The details of this page will be introduced later. By clicking on the metabolite name (e.g. oleic acid), users will be directed to a page containing the detailed information of this metabolite. This page can be divided into three parts.

1.  The first part is the metabolite’s basic information including HMDB ID, synonyms, chemical formula, monoisotopic molecular weight, chemical taxonomy, and pathways.

2.  The second part refers to the studies that particularly mentioned that this metabolite could serve as a lung cancer biomarker.

3.  The third part refers to all the mass spectrometry-based lung cancer metabolomics studies that have identified this metabolite. Users can know the detailed (cancer vs. normal) comparative design of each study including (i) sample information, (ii) analytical methods, (iii) data processing, and (iv) statistical analysis.

It should be noted that the identification of a metabolite does not necessarily mean that this metabolite is a useful biomarker. However, users can still judge whether this metabolite may be a potential biomarker based on the detailed comparative research designs and differential analysis results provided by the LCMD.

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The second way for exploring the LCMD is using “Browse Studies” mode. Users can browse studies in the LCMD by applying 5 kinds of filters (participants, specimen, chromatography, ion source, and year of publication).

Users then can obtain a list of mass spectrometry-based metabolomics studies that satisfy the filter specifications.

By clicking on the “Reference” (e.g. Wen et al. 2013), users will be directed to a page containing the detailed information of the selected study. This page can be divided into 7 parts.

1.  “Citation information” provides the authors’ names, paper titles, journal names, and links to the PubMed.

2.  “Analytical methods” provides the details of the mass spectrometry being used.

3.  “Sample information” provides the details of the specimen and participants

4.  “Data processing and metabolite identification” provides the details of the software and database search engines being used to identify the metabolites from the mass spectrometry data.

5.  “Statistical analysis” provides the details of the differential analysis, classification, and survival analysis methods being used.

6.  Sixth, “Lung cancer-related metabolites identified in the paper” provides the details of all the metabolites identified in the paper derived from the differential analysis and classification analysis.

7.  Seventh, “Paper graphical summary” provides a summary of the study design of the paper.