Summary of Study ST000386

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 PR000302. The data can be accessed directly via it's Project DOI: 10.21228/M80W30 This work is supported by NIH grant, U2C- DK119886.

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Study IDST000386
Study TitleInvestigation of metabolomic blood biomarkers for detection of adenocarcinoma lung cancer (test/validation)
Study SummaryRecently, the National Lung Cancer Screen Trial (NLST) demonstrated that low-dose CT (LDCT) screening could reduce mortality due to lung cancer by 20%. However, LDCT screening is largely hindered by high false-positive rates (96%), particularly in high-risk populations (heavy smokers), due to the low prevalence rates (less than 2%) of malignant tumors and high incidence of benign lung nodules. Consequently, complementary biomarkers that can be used in conjunction with LDCT screening to improve diagnostic capacities and reduce false-positive rates are highly desirable. Preferably, such complementary tools should be noninvasive and exhibit high sensitivity and specificity. The application of “-omic” sciences (genomics, transcriptomics, proteomics, and metabolomics) represents valuable tools for the discovery and validation of potential biomarkers that can be used for detection of NSCLC. Of these omic sciences, metabolomics has received considerable attention for its application in cancer. Metabolomics is the assessment of small molecules and biochemical intermediates (metabolites) using analytic instrumentation. Metabolites in blood are the product of all cellular processes, which are highly responsive to conditions of disease and environment, and represent the final output products of all organs forming a detailed systemic representation of an individual's current physiologic state. In this study, we used an untargeted metabolomics approach using gas chromatography time-of-flight mass spectrometry (GCTOFMS) to analyze the metabolome of serum and plasma samples both collected from the same patients that were organized into two independent case–control studies (ADC1 and ADC2). In both studies, only NSCLC adenocarcinoma was investigated. The overall objectives were to (i) determine whether individual or combinations of metabolites could be used as a diagnostic test to distinguish NSCLC adenocarcinoma from controls and (ii) to determine which, plasma or serum, provides more accurate classifiers for the detection of lung cancer. We developed individual and multimetabolite classifiers using a training test from the ADC1 study and evaluated the performance of the constructed classifiers, individually or in combination, in an independent test/validation study (ADC2). This study shows the potential of metabolite-based diagnostic tests for detection of lung adenocarcinoma. Further validation in a larger pool of samples is warranted.
Institute
University of California, Davis
DepartmentGenome and Biomedical Sciences Facility
LaboratoryWCMC Metabolomics Core
Last NameFiehn
First NameOliver
Address1315 Genome and Biomedical Sciences Facility, 451 Health Sciences Drive, Davis, CA 95616
Emailofiehn@ucdavis.edu
Phone(530) 754-8258
Submit Date2016-10-04
Study CommentsSS = Sigma sample and is used as a quality control The first set (ADC1) used for biomarker development consisted of serum and plasma samples obtained from 52 stages I–IV NSCLC adenocarcinoma patients (52 plasma and 49 serum), and 31 healthy controls (31 pairs of serum and plasma) for a total of 163 samples. This set was regarded as the training set for biomarker discovery and classifier development. A second, independent case–control study (ADC2) consisting of serum and plasma samples collected from 43 stage I–IV NSCLC adenocarcinoma patients and 43 healthy controls (total 172 samples) was used as an independent test set for biomarker evaluation. A limitation of this study is the relatively small sample size for each cohort (52 cases, 31 controls for ADC1, and 43 cases and 43 controls for ADC2) because patient variability can be a big factor in smaller studies.
Raw Data AvailableYes
Raw Data File Type(s)peg
Analysis Type DetailGC-MS
Release Date2016-04-25
Release Version1
Oliver Fiehn Oliver Fiehn
https://dx.doi.org/10.21228/M80W30
ftp://www.metabolomicsworkbench.org/Studies/ application/zip

Select appropriate tab below to view additional metadata details:

Project:

Project ID:PR000302
Project DOI:doi: 10.21228/M80W30
Project Title:Study1 Investigation of metabolomic blood biomarkers for detection of adenocarcinoma lung cancer
Project Summary:Recently, the National Lung Cancer Screen Trial (NLST) demonstrated that low-dose CT (LDCT) screening could reduce mortality due to lung cancer by 20%. However, LDCT screening is largely hindered by high false-positive rates (96%), particularly in high-risk populations (heavy smokers), due to the low prevalence rates (less than 2%) of malignant tumors and high incidence of benign lung nodules. Consequently, complementary biomarkers that can be used in conjunction with LDCT screening to improve diagnostic capacities and reduce false-positive rates are highly desirable. Preferably, such complementary tools should be noninvasive and exhibit high sensitivity and specificity. The application of “-omic” sciences (genomics, transcriptomics, proteomics, and metabolomics) represents valuable tools for the discovery and validation of potential biomarkers that can be used for detection of NSCLC. Of these omic sciences, metabolomics has received considerable attention for its application in cancer. Metabolomics is the assessment of small molecules and biochemical intermediates (metabolites) using analytic instrumentation. Metabolites in blood are the product of all cellular processes, which are highly responsive to conditions of disease and environment, and represent the final output products of all organs forming a detailed systemic representation of an individual's current physiologic state. In this study, we used an untargeted metabolomics approach using gas chromatography time-of-flight mass spectrometry (GCTOFMS) to analyze the metabolome of serum and plasma samples both collected from the same patients that were organized into two independent case–control studies (ADC1 and ADC2). In both studies, only NSCLC adenocarcinoma was investigated. The overall objectives were to (i) determine whether individual or combinations of metabolites could be used as a diagnostic test to distinguish NSCLC adenocarcinoma from controls and (ii) to determine which, plasma or serum, provides more accurate classifiers for the detection of lung cancer. We developed individual and multimetabolite classifiers using a training test from the ADC1 study and evaluated the performance of the constructed classifiers, individually or in combination, in an independent test/validation study (ADC2). This study shows the potential of metabolite-based diagnostic tests for detection of lung adenocarcinoma. Further validation in a larger pool of samples is warranted.
Institute:University of California, Davis
Department:Genome and Biomedical Sciences Facility
Laboratory:WCMC Metabolomics Core
Last Name:Fiehn
First Name:Oliver
Address:1315 Genome and Biomedical Sciences Facility, 451 Health Sciences Drive, Davis, CA 95616
Email:ofiehn@ucdavis.edu
Phone:(530) 754-8258
Funding Source:NIH U24DK097154

Subject:

Subject ID:SU000407
Subject Type:Human
Subject Species:Homo sapiens
Taxonomy ID:9606
Species Group:Human

Factors:

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

mb_sample_id local_sample_id Organ Cancer status Smoker Gender
SA017673130729dlvsa48_2Plasma Adenocarcinoma Current F
SA017674130729dlvsa46_3Plasma Adenocarcinoma Current F
SA017675130730dlvsa28_1Plasma Adenocarcinoma Current F
SA017676130729dlvsa13_1Plasma Adenocarcinoma Current F
SA017677130729dlvsa17_1Plasma Adenocarcinoma Current F
SA017678130731dlvsa26_1Plasma Adenocarcinoma Current F
SA017679130731dlvsa44_1Plasma Adenocarcinoma Current F
SA017680130730dlvsa37_3Plasma Adenocarcinoma Current F
SA017681130729dlvsa28_1Plasma Adenocarcinoma Current F
SA017682130729dlvsa30_2Plasma Adenocarcinoma Current M
SA017683130729dlvsa36_2Plasma Adenocarcinoma Current M
SA017684130730dlvsa13_1Plasma Adenocarcinoma Current M
SA017685130731dlvsa28_1Plasma Adenocarcinoma Former F
SA017686130731dlvsa32_1Plasma Adenocarcinoma Former F
SA017687130730dlvsa16_1Plasma Adenocarcinoma Former F
SA017688130730dlvsa18_1Plasma Adenocarcinoma Former F
SA017689130729dlvsa07_1Plasma Adenocarcinoma Former F
SA017690130730dlvsa32_1Plasma Adenocarcinoma Former F
SA017691130731dlvsa02_1Plasma Adenocarcinoma Former F
SA017692130731dlvsa14_1Plasma Adenocarcinoma Former F
SA017693130730dlvsa46_1Plasma Adenocarcinoma Former F
SA017694130729dlvsa09_1Plasma Adenocarcinoma Former F
SA017695130730dlvsa26_1Plasma Adenocarcinoma Former F
SA017696130731dlvsa34_1Plasma Adenocarcinoma Former F
SA017697130729dlvsa50_2Plasma Adenocarcinoma Former F
SA017698130729dlvsa24_1Plasma Adenocarcinoma Former F
SA017699130729dlvsa42_3Plasma Adenocarcinoma Former F
SA017700130801dlvsa02_1Plasma Adenocarcinoma Former F
SA017701130730dlvsa03_2Plasma Adenocarcinoma Former F
SA017702130730dlvsa01_2Plasma Adenocarcinoma Former F
SA017703130730dlvsa07_2Plasma Adenocarcinoma Former F
SA017704130729dlvsa21_1Plasma Adenocarcinoma Former F
SA017705130731dlvsa36_1Plasma Adenocarcinoma Former F
SA017706130731dlvsa22_1Plasma Adenocarcinoma Former M
SA017707130731dlvsa18_1Plasma Adenocarcinoma Former M
SA017708130730dlvsa44_1Plasma Adenocarcinoma Former M
SA017709130729dlvsa11_1Plasma Adenocarcinoma Former M
SA017710130731dlvsa24_1Plasma Adenocarcinoma Former M
SA017711130730dlvsa33_1Plasma Adenocarcinoma Former M
SA017712130730dlvsa05_2Plasma Adenocarcinoma Former M
SA017713130730dlvsa20_1Plasma Adenocarcinoma Former M
SA017714130731dlvsa38_1Plasma Adenocarcinoma Former M
SA017715130731dlvsa10_2Plasma Adenocarcinoma Former M
SA017716130730dlvsa35_1Plasma Adenocarcinoma Former M
SA017717130729dlvsa15_1Plasma Adenocarcinoma Former M
SA017718130801dlvsa08_1Plasma Adenocarcnoma Former F
SA017719130801dlvsa04_1Plasma Adenocarcnoma Former F
SA017720130801dlvsa10_1Plasma Adenocarcnoma Former F
SA017721130729dlvsa38_2Plasma Adenosquamous Current F
SA017722130731dlvsa16_1Plasma Adenosquamous Current M
SA017723130729dlvsa22_1Plasma Adenosquamous Former M
SA017724130729dlvsa40_2Plasma Healthy Current F
SA017725130729dlvsa44_3Plasma Healthy Current F
SA017726130731dlvsa30_1Plasma Healthy Current F
SA017727130729dlvsa32_2Plasma Healthy Current F
SA017728130730dlvsa38_3Plasma Healthy Current F
SA017729130731dlvsa08_1Plasma Healthy Current F
SA017730130729dlvsa19_1Plasma Healthy Current M
SA017731130731dlvsa50_1Plasma Healthy Current M
SA017732130731dlvsa12_1Plasma Healthy Current M
SA017733130730dlvsa50_1Plasma Healthy Current M
SA017734130731dlvsa46_1Plasma Healthy Former F
SA017735130730dlvsa30_1Plasma Healthy Former F
SA017736130801dlvsa06_1Plasma Healthy Former F
SA017737130731dlvsa06_1Plasma Healthy Former F
SA017738130729dlvsa34_2Plasma Healthy Former F
SA017739130731dlvsa42_1Plasma Healthy Former F
SA017740130731dlvsa40_1Plasma Healthy Former F
SA017741130729dlvsa26_1Plasma Healthy Former F
SA017742130801dlvsa12_1Plasma Healthy Former F
SA017743130730dlvsa40_1Plasma Healthy Former F
SA017744130731dlvsa04_1Plasma Healthy Former F
SA017745130731dlvsa20_1Plasma Healthy Former F
SA017746130730dlvsa24_1Plasma Healthy Former M
SA017747130729dlvsa03_1Plasma Healthy Former M
SA017748130730dlvsa11_1Plasma Healthy Former M
SA017749130730dlvsa48_2Plasma Healthy Former M
SA017750130730dlvsa09_1Plasma Healthy Former M
SA017751130730dlvsa22_1Plasma Healthy Former M
SA017752130729dlvsa05_1Plasma Healthy Former M
SA017753130731dlvsa48_1Plasma Healthy Former M
SA017754130730dlvsa42_1Plasma Healthy Former M
SA017755130801dlvsa19_2Plasma NA NA NA
SA017756130801dlvsa20_1Plasma NA NA NA
SA017757130801dlvsa18_2Plasma NA NA NA
SA017758130801dlvsa15_1Plasma NA NA NA
SA017759130801dlvsa14_1Plasma NA NA NA
SA017760130801dlvsa16_1Plasma NA NA NA
SA017761130801dlvsa17_2Plasma NA NA NA
SA017762130801dlvsa28_1Plasma NA NA NA
SA017763130801dlvsa26_1Plasma NA NA NA
SA017764130801dlvsa27_1Plasma NA NA NA
SA017765130801dlvsa25_1Plasma NA NA NA
SA017766130801dlvsa24_1Plasma NA NA NA
SA017767130801dlvsa22_1Plasma NA NA NA
SA017768130801dlvsa23_1Plasma NA NA NA
SA017769130801dlvsa21_1Plasma NA NA NA
SA017770130801dlvsa29_1Plasma NA NA NA
SA017771130801dlvsa31_1Plasma NA NA NA
SA017772130801dlvsa30_2Plasma NA NA NA
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Collection:

Collection ID:CO000401
Collection Summary:Blood samples (serum and plasma) were collected from NSCLC adenocarcinoma and control subjects with patient consent using approved IRB protocols (LC001 for cancer cases and LC002 for control cases).
Collection Protocol Filename:Cancer_Epidemiol_Biomarkers_Prev-2015-Fahrmann-1716-23.pdf
Sample Type:Blood

Treatment:

Treatment ID:TR000421
Treatment Summary:Subjects were recruited over a 4-year period (2010–2014) from the UC Davis Medical Center and Cancer Center Clinics. All subjects were diagnosed with NSCLC adenocarcinoma before specimen collection. The control population was heavily recruited from spouses and family members accompanying a lung cancer patient to their clinic to maintain as much of a similar environment and life styles, especially diet and smoking history, as possible. Cases were frequency matched with controls for gender, age, and smoking history. Only cases diagnosed with NSCLC adenocarcinoma were used in these studies. Fasting status was not controlled for as individuals were recruited upon their arrival to the clinic. The first set (ADC1) used for biomarker development consisted of serum and plasma samples obtained from 52 stages I–IV NSCLC adenocarcinoma patients (52 plasma and 49 serum), and 31 healthy controls (31 pairs of serum and plasma) for a total of 163 samples. This set was regarded as the training set for biomarker discovery and classifier development. A second, independent case–control study (ADC2) consisting of serum and plasma samples collected from 43 stage I–IV NSCLC adenocarcinoma patients and 43 healthy controls (total 172 samples) was used as an independent test set for biomarker evaluation.
Treatment Protocol Filename:Cancer_Epidemiol_Biomarkers_Prev-2015-Fahrmann-1716-23.pdf

Sample Preparation:

Sampleprep ID:SP000414
Sampleprep Summary:1. Switch on bath to pre-cool at –20°C (±2°C validity temperature range) 2. Gently rotate or aspirate the blood samples for about 10s to obtain a homogenised sample. 3. Aliquot 30μl of plasma sample to a 1.0 mL extraction solution. The extraction solution has to be prechilled using the ThermoElectron Neslab RTE 740 cooling bath set to -20°C. 4. Vortex the sample for about 10s and shake for 5 min at 4°C using the Orbital Mixing Chilling/Heating Plate. If you are using more than one sample, keep the rest of the sample on ice (chilled at <0°C with sodium chloride). 5. Centrifuge samples for 2min at 14000 rcf using the centrifuge Eppendorf 5415 D. 6. Aliquot two 450μL portions of the supernatant. One for analysis and one for a backup sample. Store the backup aliquot in -20°C freezer. 7. Evaporate one 450μL aliquots of the sample in the Labconco Centrivap cold trap concentrator to complete dryness. 8. The dried aliquot is then re-suspended with 450 μL 50% acetonitrile (degassed as given above). 9. Centrifuged for 2 min at 14000 rcf using the centrifuge Eppendorf 5415. 10. Remove supernatant to a new Eppendorf tube. 11. Evaporate the supernatant to dryness in the Labconco Centrivap cold trap concentrator. 12. Submit to derivatization.
Sampleprep Protocol Filename:SOP_blood-GCTOF-11082012.pdf

Combined analysis:

Analysis ID AN000621
Analysis type MS
Chromatography type GC
Chromatography system Agilent 6890N
Column Restek Corporation Rtx-5Sil MS
MS Type EI
MS instrument type GC-TOF
MS instrument name Leco GC-TOF
Ion Mode POSITIVE
Units peak area

Chromatography:

Chromatography ID:CH000446
Methods Filename:Data_Dictionary_Fiehn_laboratory_GCTOF_MS_primary_metabolism_10-15-2013_general.pdf
Instrument Name:Agilent 6890N
Column Name:Restek Corporation Rtx-5Sil MS
Column Pressure:7.7 PSI (initial condition)
Column Temperature:50 - 330°C
Flow Rate:1 ml/min
Injection Temperature:50°C ramped to 250°C by 12°C/s
Sample Injection:0.5µl
Oven Temperature:50°C for 1 min, then ramped at 20°C/min to 330°C, held constant for 5 min
Transferline Temperature:230°C
Washing Buffer:Ethyl Acetate
Sample Loop Size:30 m length x 0.25 mm internal diameter
Randomization Order:Excel generated
Chromatography Type:GC

MS:

MS ID:MS000554
Analysis ID:AN000621
Instrument Name:Leco GC-TOF
Instrument Type:GC-TOF
MS Type:EI
Ion Mode:POSITIVE
Ion Source Temperature:250°C
Ionization Energy:70eV
Mass Accuracy:Nominal
Spray Voltage:250°C
Scan Range Moverz:85-500
Scanning Cycle:17 Hz
Skimmer Voltage:1850 V
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