Summary of Study ST004073

This data is available at the NIH Common Fund's National Metabolomics Data Repository (NMDR) website, the Metabolomics Workbench, https://www.metabolomicsworkbench.org, where it has been assigned Project ID PR002553. The data can be accessed directly via it's Project DOI: 10.21228/M8NC2B This work is supported by NIH grant, U2C- DK119886.

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This study contains a large results data set and is not available in the mwTab file. It is only available for download via FTP as data file(s) here.

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Study IDST004073
Study TitleDevelopment of Novel Pancreatic Cancer Diagnostic Biomarkers via Lipidomic Profiling - targeted metabolomics of human plasma
Study SummaryPancreatic ductal adenocarcinoma (PDAC) remains a lethal malignancy due to late diagnosis and the lack of sensitive screening tools. We recently discovered that tumors depend on circulating fatty acids as a major energy source. Accordingly, we conducted a study to identify screening-diagnostic biomarkers for PDAC in the lipid fraction of patient plasma. In this study, we performed non-targeted lipidomics on human and mouse plasma samples and identified eight concordant lipid metabolites. We then established four targeted-lipidomics platforms—acylcarnitines, phospholipids, fatty acid amides, and sphingolipids—and carried out quantitative analysis in two independent patient cohorts. A combined tertiary analysis of both cohorts revealed 20 lipid species (1 acylcarnitine, 1 sphingolipid, and 18 phospholipids) that achieved an AUC ≥ 0.75 for discriminating PDAC patients from healthy controls. A logistic regression model incorporating 11 or more phospholipids yielded an AUC of 0.9207, which further increased to 0.9427 in the validation cohort upon addition of CA19-9. While extensive validation in larger, multicenter cohorts is necessary, these findings highlight the promise of a lipid biomarker panel and multivariate algorithms as novel metabolic indicators for early PDAC diagnosis. This study aims to find plasma metabolite biomarkers of pancreatic cancer from human plasma of control vs cancer patients. Targeted metabolomics approaches were used: acyl-carnitines, fatty acid amides, phospholipids, and sphingolipids. In-house targeted metabolomics platforms were established using commercially available authentic chemicals.
Institute
National Cancer Center Graduate School of Cancer Science and Policy
Last NameKang
First NameJoon Hee
Address323 Ilsan-ro, Ilsandong-gu, Goyang-si, Gyeonggi-do, 10408, South Korea
Emailwnsl2820@gmail.com
Phone82-031-920-2227
Submit Date2025-07-17
Raw Data AvailableYes
Raw Data File Type(s)rdb
Analysis Type DetailLC-MS
Release Date2025-10-22
Release Version1
Joon Hee Kang Joon Hee Kang
https://dx.doi.org/10.21228/M8NC2B
ftp://www.metabolomicsworkbench.org/Studies/ application/zip

Select appropriate tab below to view additional metadata details:

Project:

Project ID:PR002553
Project DOI:doi: 10.21228/M8NC2B
Project Title:Development of Novel Pancreatic Cancer Diagnostic Biomarkers via Lipidomic Profiling
Project Summary:Pancreatic ductal adenocarcinoma (PDAC) remains a lethal malignancy due to late diagnosis and the lack of sensitive screening tools. We recently discovered that tumors depend on circulating fatty acids as a major energy source. Accordingly, we conducted a study to identify screening-diagnostic biomarkers for PDAC in the lipid fraction of patient plasma. In this study, we performed non-targeted lipidomics on human and mouse plasma samples and identified eight concordant lipid metabolites. We then established four targeted-lipidomics platforms—acylcarnitines, phospholipids, fatty acid amides, and sphingolipids—and carried out quantitative analysis in two independent patient cohorts. A combined tertiary analysis of both cohorts revealed 20 lipid species (1 acylcarnitine, 1 sphingolipid, and 18 phospholipids) that achieved an AUC ≥ 0.75 for discriminating PDAC patients from healthy controls. A logistic regression model incorporating 11 or more phospholipids yielded an AUC of 0.9207, which further increased to 0.9427 in the validation cohort upon addition of CA19-9. While extensive validation in larger, multicenter cohorts is necessary, these findings highlight the promise of a lipid biomarker panel and multivariate algorithms as novel metabolic indicators for early PDAC diagnosis.
Institute:National Cancer Center Graduate School of Cancer Science and Policy
Last Name:Kang
First Name:Joon Hee
Address:323 Ilsan-ro, Ilsandong-gu, Goyang-si, Gyeonggi-do, 10408, South Korea
Email:wnsl2820@gmail.com
Phone:82-031-920-2227

Subject:

Subject ID:SU004219
Subject Type:Human
Subject Species:Homo sapiens
Taxonomy ID:9606
Gender:Male and female
Human Ethnicity:Easn Asian

Factors:

Subject type: Human; Subject species: Homo sapiens (Factor headings shown in green)

mb_sample_id local_sample_id Disease Sample source
SA472716Cancer_18Cancer human_plasma
SA472717Cancer_No_99Cancer human_plasma
SA472718Cancer_1Cancer human_plasma
SA472719Cancer_10Cancer human_plasma
SA472720Cancer_No_10Cancer human_plasma
SA472721Cancer_12Cancer human_plasma
SA472722Cancer_13Cancer human_plasma
SA472723Cancer_14Cancer human_plasma
SA472724Cancer_15Cancer human_plasma
SA472725Cancer_16Cancer human_plasma
SA472726Cancer_17Cancer human_plasma
SA472727Cancer_19Cancer human_plasma
SA472728Cancer_No_97Cancer human_plasma
SA472729Cancer_2Cancer human_plasma
SA472730Cancer_20Cancer human_plasma
SA472731Cancer_3Cancer human_plasma
SA472732Cancer_4Cancer human_plasma
SA472733Cancer_5Cancer human_plasma
SA472734Cancer_6Cancer human_plasma
SA472735Cancer_7Cancer human_plasma
SA472736Cancer_8Cancer human_plasma
SA472737Cancer_9Cancer human_plasma
SA472738Cancer_21Cancer human_plasma
SA472739Cancer_22Cancer human_plasma
SA472740Cancer_No_98Cancer human_plasma
SA472741Cancer_No_95Cancer human_plasma
SA472742Cancer_24Cancer human_plasma
SA472743Cancer_No_102Cancer human_plasma
SA472744Cancer_No_78Cancer human_plasma
SA472745Cancer_No_79Cancer human_plasma
SA472746Cancer_No_80Cancer human_plasma
SA472747Cancer_No_81Cancer human_plasma
SA472748Cancer_No_83Cancer human_plasma
SA472749Cancer_No_84Cancer human_plasma
SA472750Cancer_No_85Cancer human_plasma
SA472751Cancer_No_86Cancer human_plasma
SA472752Cancer_No_87Cancer human_plasma
SA472753Cancer_No_100Cancer human_plasma
SA472754Cancer_No_101Cancer human_plasma
SA472755Cancer_No_103Cancer human_plasma
SA472756Cancer_No_94Cancer human_plasma
SA472757Cancer_No_104Cancer human_plasma
SA472758Cancer_No_105Cancer human_plasma
SA472759Cancer_No_106Cancer human_plasma
SA472760Cancer_No_107Cancer human_plasma
SA472761Cancer_No_108Cancer human_plasma
SA472762Cancer_No_88Cancer human_plasma
SA472763Cancer_No_89Cancer human_plasma
SA472764Cancer_No_90Cancer human_plasma
SA472765Cancer_No_91Cancer human_plasma
SA472766Cancer_No_92Cancer human_plasma
SA472767Cancer_No_93Cancer human_plasma
SA472768Cancer_23Cancer human_plasma
SA472769Cancer_25Cancer human_plasma
SA472770Cancer_No_76Cancer human_plasma
SA472771Cancer_68Cancer human_plasma
SA472772Cancer_56Cancer human_plasma
SA472773Cancer_57Cancer human_plasma
SA472774Cancer_59Cancer human_plasma
SA472775Cancer_60Cancer human_plasma
SA472776Cancer_61Cancer human_plasma
SA472777Cancer_62Cancer human_plasma
SA472778Cancer_63Cancer human_plasma
SA472779Cancer_64Cancer human_plasma
SA472780Cancer_65Cancer human_plasma
SA472781Cancer_66Cancer human_plasma
SA472782Cancer_67Cancer human_plasma
SA472783Cancer_69Cancer human_plasma
SA472784Cancer_54Cancer human_plasma
SA472785Cancer_70Cancer human_plasma
SA472786Cancer_71Cancer human_plasma
SA472787Cancer_72Cancer human_plasma
SA472788Cancer_73Cancer human_plasma
SA472789Cancer_74Cancer human_plasma
SA472790Cancer_75Cancer human_plasma
SA472791Cancer_76Cancer human_plasma
SA472792Cancer_77Cancer human_plasma
SA472793Cancer_78Cancer human_plasma
SA472794Cancer_79Cancer human_plasma
SA472795Cancer_80Cancer human_plasma
SA472796Cancer_55Cancer human_plasma
SA472797Cancer_53Cancer human_plasma
SA472798Cancer_26Cancer human_plasma
SA472799Cancer_38Cancer human_plasma
SA472800Cancer_27Cancer human_plasma
SA472801Cancer_28Cancer human_plasma
SA472802Cancer_29Cancer human_plasma
SA472803Cancer_30Cancer human_plasma
SA472804Cancer_31Cancer human_plasma
SA472805Cancer_32Cancer human_plasma
SA472806Cancer_33Cancer human_plasma
SA472807Cancer_34Cancer human_plasma
SA472808Cancer_35Cancer human_plasma
SA472809Cancer_36Cancer human_plasma
SA472810Cancer_37Cancer human_plasma
SA472811Cancer_39Cancer human_plasma
SA472812Cancer_52Cancer human_plasma
SA472813Cancer_40Cancer human_plasma
SA472814Cancer_41Cancer human_plasma
SA472815Cancer_42Cancer human_plasma
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Collection:

Collection ID:CO004212
Collection Summary:human plasma was collected using EDTA tube.
Sample Type:Blood (plasma)
Collection Location:vein
Collection Frequency:1
Collection Duration:2017-2023
Volumeoramount Collected:2 mL
Storage Conditions:-80℃
Collection Vials:EDTA tube
Storage Vials:1.8 mL micro-tube
Collection Tube Temp:RT

Treatment:

Treatment ID:TR004228
Treatment Summary:Human plasma was stored at deep freezer until analysis. Blood samples for the control group were obtained from subjects undergoing routine health examinations at our institution, while samples for the pancreatic cancer group were those collected for preoperative blood testing. No pharmacological treatments were administered to the pancreatic cancer patients.
Treatment:none
Treatment Compound:none
Treatment Route:none
Treatment Dose:none
Treatment Dosevolume:none
Treatment Doseduration:none
Treatment Vehicle:none
Human Fasting:none
Human Endp Clinical Signs:none

Sample Preparation:

Sampleprep ID:SP004225
Sampleprep Summary:50 μL human plasma was mixed well after adding 50 μL of internal standard solutions (C18 Ceramide d7 for ceramides, 18:1 SM-d9 for Sphingomyelins; 1 μM 18:0 D70 PC and 1 μM 16:0 D31-18:1 PE for phosphatidylcholines, and phosphatidylethanolamines, respectively; 500 nM arachidonoylethanolamide-d4 for fatty acid amides, 10 nM C16-L-carnitine-d3-HCL(N-methyl-d3) for acylcarnitines). Metabolites were collected from the lower organic phase and upper aqueous phase by liquid-liquid extraction after the addition of chloroform and H2O. The organic and aqueous phases were dried under vacuum and stored at -20℃ until further analysis. The dried matter from the organic solutions was reconstituted with 50 μL of MeOH for lipids and the aqueous solutions was reconstituted with 50 μL of 50% MeOH for acylcarnitines. prior to LC-MS/MS analysis.
Processing Storage Conditions:4℃
Extraction Method:liquid-liquid extraction
Extract Enrichment:Resuspension after vaccum dry
Extract Cleanup:none
Extract Storage:-20℃
Sample Resuspension:50uL methanol/H2O (50/50,v/v) for acyl-carnitines, 50uL methanol for others
Sample Derivatization:none
Sample Spiking:none

Chromatography:

Chromatography ID:CH005121
Chromatography Summary:SL (sphingolipids)
Methods Filename:Method_Targeted_metabolomics.pdf
Chromatography Comments:total run time: 20min
Instrument Name:Agilent 1290
Column Name:Agilent ZORBAX Eclipse Plus C18 (50 x 2.1mm,1.8um)
Column Temperature:23 ℃
Flow Gradient:isocratic condition of 60% B for 20min
Flow Rate:400 μl/min for 20 min
Sample Injection:3uL
Solvent A:90% methanol/5% isopropanol/5% water; 10 mM ammonium acetate
Solvent B:94% Methanol/5% isopropanol/1% water; 10 mM ammonium acetate
Chromatography Type:Reversed phase
  
Chromatography ID:CH005122
Chromatography Summary:PL (phospholipid: PC, PE, PLS, PAF)
Methods Filename:Method_Targeted_metabolomics.pdf
Chromatography Comments:total run time: 25min
Instrument Name:Agilent 1290
Column Name:Agilent ZORBAX Eclipse Plus C18 (50 x 2.1mm,1.8um)
Column Temperature:23 ℃
Flow Gradient:60% B for 0 min, 60% B for 10 min, 60 to 90% B for 0.1min, 90% B for 7.9 min, 90 to 60% B for 0.1 min, 60% A for 6.9 min
Flow Rate:300-400 μl/min
Sample Injection:3uL
Solvent A:90% methanol/5% isopropanol/5% water; 10 mM ammonium acetate
Solvent B:94% methanol/5% isopropanol/1% water; 10 mM ammonium acetate
Chromatography Type:Reversed phase
  
Chromatography ID:CH005123
Chromatography Summary:AC (Acylcarnitine): Solvent A - 50% ACN; 45% H2O; 5% 100 mM pH 3.2 ammonium formate in H2O; Solvent B - 90% ACN; 5% H2O; 5% 100 mM pH 3.2 ammonium formate in H2O
Methods Filename:Method_Targeted_metabolomics.pdf
Chromatography Comments:total run time: 15min
Instrument Name:Agilent 1290
Column Name:Agilent Zorbax RR HILIC plus (150 x 2.1mm, 3.5um)
Column Temperature:35 ℃
Flow Gradient:95% B for 0 min, 95 to 0% B for 7 min, 0% B for 3 min, 0 to 95% B for 2 min, then 95% B for 3 min
Flow Rate:300 μl/min
Sample Injection:3uL
Solvent A:50% acetonitrile/50% water; 5mM ammonium formate pH3.2
Solvent B:90% acetonitrile/10% water; 5mM ammonium formate pH3.2
Chromatography Type:HILIC
  
Chromatography ID:CH005124
Chromatography Summary:FAA (Fatty acid amide)
Methods Filename:Method_Targeted_metabolomics.pdf
Chromatography Comments:total run time: 20min
Instrument Name:Agilent 1290
Column Name:Agilent Pursuit 5 C18 (150 x 2.1mm, 5um)
Column Temperature:25 ℃
Flow Gradient:isocratic 90% B for 20 min
Flow Rate:200 ul/min
Sample Injection:3uL
Solvent A:100% water; 0.1% formic acid
Solvent B:100% methanol; 0.1% formic acid
Chromatography Type:Reversed phase

Analysis:

Analysis ID:AN006739
Analysis Type:MS
Chromatography ID:CH005121
Num Factors:2
Num Metabolites:12
Units:pmol/uL
  
Analysis ID:AN006740
Analysis Type:MS
Chromatography ID:CH005122
Num Factors:2
Num Metabolites:64
Units:pmol/uL
  
Analysis ID:AN006741
Analysis Type:MS
Chromatography ID:CH005123
Num Factors:2
Num Metabolites:13
Units:pmol/uL
  
Analysis ID:AN006742
Analysis Type:MS
Chromatography ID:CH005124
Num Factors:2
Num Metabolites:13
Units:pmol/uL
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