Summary of study ST000368

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 PR000293. The data can be accessed directly via it's Project DOI: 10.21228/M85P57 This work is supported by NIH grant, U2C- DK119886.

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Study IDST000368
Study TitleInvestigation of metabolomic blood biomarkers for detection of adenocarcinoma lung cancer
Study TypeLung cancer case control biomarker discovery
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 Date2016-04-08
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 Date2016-04-08
Release Version1
Oliver Fiehn Oliver Fiehn
https://dx.doi.org/10.21228/M85P57
ftp://www.metabolomicsworkbench.org/Studies/ application/zip

Select appropriate tab below to view additional metadata details:


Project:

Project ID:PR000293
Project DOI:doi: 10.21228/M85P57
Project Title: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:SU000389
Subject Type:Human
Subject Species:Homo sapiens
Gender:M/F
Human Smoking Status:Former/Current
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
SA016520140228dlvsa30_1Plasma Adenocarcinoma Current F
SA016521140228dlvsa08_1Plasma Adenocarcinoma Current F
SA016522140225dlvsa44_1Plasma Adenocarcinoma Current F
SA016523140226dlvsa36_1Plasma Adenocarcinoma Current F
SA016524140226dlvsa30_1Plasma Adenocarcinoma Current F
SA016525140228dlvsa17_1Plasma Adenocarcinoma Current F
SA016526140227dlvsa36_1Plasma Adenocarcinoma Current F
SA016527140227dlvsa47_1Plasma Adenocarcinoma Current F
SA016528140228dlvsa39_1Plasma Adenocarcinoma Current F
SA016529140225dlvsa31_1Plasma Adenocarcinoma Current M
SA016530140227dlvsa14_1Plasma Adenocarcinoma Current M
SA016531140228dlvsa28_1Plasma Adenocarcinoma Current M
SA016532140226dlvsa41_1Plasma Adenocarcinoma Current M
SA016533140225dlvsa14_1Plasma Adenocarcinoma Current M
SA016534140226dlvsa21_1Plasma Adenocarcinoma Current M
SA016535140225dlvsa16_1Plasma Adenocarcinoma Former F
SA016536140226dlvsa23_1Plasma Adenocarcinoma Former F
SA016537140226dlvsa43_1Plasma Adenocarcinoma Former F
SA016538140225dlvsa18_1Plasma Adenocarcinoma Former F
SA016539140225dlvsa09_1Plasma Adenocarcinoma Former F
SA016540140227dlvsa40_1Plasma Adenocarcinoma Former F
SA016541140228dlvsa19_1Plasma Adenocarcinoma Former F
SA016542140225dlvsa07_1Plasma Adenocarcinoma Former F
SA016543140226dlvsa03_1Plasma Adenocarcinoma Former F
SA016544140225dlvsa05_1Plasma Adenocarcinoma Former F
SA016545140225dlvsa22_1Plasma Adenocarcinoma Former F
SA016546140228dlvsa06_1Plasma Adenocarcinoma Former F
SA016547140228dlvsa26_1Plasma Adenocarcinoma Former F
SA016548140227dlvsa03_1Plasma Adenocarcinoma Former F
SA016549140228dlvsa12_1Plasma Adenocarcinoma Former F
SA016550140228dlvsa37_1Plasma Adenocarcinoma Former M
SA016551140225dlvsa36_1Plasma Adenocarcinoma Former M
SA016552140227dlvsa18_1Plasma Adenocarcinoma Former M
SA016553140227dlvsa21_1Plasma Adenocarcinoma Former M
SA016554140226dlvsa27_1Plasma Adenocarcinoma Former M
SA016555140226dlvsa16_1Plasma Adenocarcinoma Former M
SA016556140227dlvsa01_1Plasma Adenocarcinoma Former M
SA016557140228dlvsa34_1Plasma Adenocarcinoma Former M
SA016558140228dlvsa23_1Plasma Adenocarcinoma Former M
SA016559140228dlvsa21_1Plasma Adenocarcinoma Former M
SA016560140227dlvsa49_1Plasma Adenocarcinoma Former M
SA016561140226dlvsa49_1Plasma Adenocarcinoma Former M
SA016562140227dlvsa45_1Plasma Adenocarcinoma Former M
SA016563140227dlvsa07_1Plasma Healthy Current F
SA016564140225dlvsa33_1Plasma Healthy Current F
SA016565140226dlvsa14_1Plasma Healthy Current F
SA016566140227dlvsa25_1Plasma Healthy Current F
SA016567140225dlvsa49_1Plasma Healthy Current F
SA016568140227dlvsa10_1Plasma Healthy Current F
SA016569140226dlvsa12_1Plasma Healthy Current F
SA016570140225dlvsa25_1Plasma Healthy Current F
SA016571140227dlvsa16_1Plasma Healthy Current F
SA016572140228dlvsa15_1Plasma Healthy Current M
SA016573140227dlvsa34_1Plasma Healthy Current M
SA016574140227dlvsa43_1Plasma Healthy Current M
SA016575140225dlvsa27_1Plasma Healthy Current M
SA016576140227dlvsa32_1Plasma Healthy Current M
SA016577140226dlvsa08_1Plasma Healthy Current M
SA016578140225dlvsa40_1Plasma Healthy Current M
SA016579140226dlvsa34_1Plasma Healthy Former F
SA016580140225dlvsa42_1Plasma Healthy Former F
SA016581140226dlvsa05_1Plasma Healthy Former F
SA016582140225dlvsa03_1Plasma Healthy Former F
SA016583140227dlvsa23_1Plasma Healthy Former F
SA016584140228dlvsa01_1Plasma Healthy Former F
SA016585140225dlvsa20_1Plasma Healthy Former F
SA016586140226dlvsa45_1Plasma Healthy Former F
SA016587140226dlvsa10_1Plasma Healthy Former F
SA016588140227dlvsa29_1Plasma Healthy Former F
SA016589140228dlvsa10_1Plasma Healthy Former F
SA016590140228dlvsa04_1Plasma Healthy Former F
SA016591140226dlvsa19_1Plasma Healthy Former F
SA016592140225dlvsa38_1Plasma Healthy Former M
SA016593140228dlvsa32_1Plasma Healthy Former M
SA016594140225dlvsa11_1Plasma Healthy Former M
SA016595140226dlvsa32_1Plasma Healthy Former M
SA016596140226dlvsa25_1Plasma Healthy Former M
SA016597140228dlvsa41_1Plasma Healthy Former M
SA016598140225dlvsa29_1Plasma Healthy Former M
SA016599140227dlvsa12_1Plasma Healthy Former M
SA016600140226dlvsa01_1Plasma Healthy Former M
SA016601140226dlvsa38_1Plasma Healthy Former M
SA016602140225dlvsa47_1Plasma Healthy Former M
SA016603140227dlvsa05_1Plasma Healthy Former M
SA016604140227dlvsa27_1Plasma Healthy Former M
SA016605140227dlvsa38_1Plasma Healthy Former M
SA016626140227dlvsa35_1Serum Adenocarcinoma Current F
SA016627140225dlvsa43_1Serum Adenocarcinoma Current F
SA016628140227dlvsa46_1Serum Adenocarcinoma Current F
SA016629140226dlvsa35_1Serum Adenocarcinoma Current F
SA016630140226dlvsa29_1Serum Adenocarcinoma Current F
SA016631140228dlvsa07_1Serum Adenocarcinoma Current F
SA016632140228dlvsa16_1Serum Adenocarcinoma Current F
SA016633140228dlvsa38_1Serum Adenocarcinoma Current F
SA016634140228dlvsa29_1Serum Adenocarcinoma Current F
SA016635140225dlvsa13_1Serum Adenocarcinoma Current M
SA016636140227dlvsa13_1Serum Adenocarcinoma Current M
SA016637140225dlvsa30_1Serum Adenocarcinoma Current M
SA016638140226dlvsa20_1Serum Adenocarcinoma Current M
SA016639140228dlvsa27_1Serum Adenocarcinoma Current M
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Collection:

Collection ID:CO000383
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:TR000403
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
Human Fasting:None

Sample Preparation:

Sampleprep ID:SP000396
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 AN000602
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 Pegasus IV TOF
Ion Mode POSITIVE
Units counts

Chromatography:

Chromatography ID:CH000428
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 Temperature:50-330C
Flow Rate:1 ml/min
Oven Temperature:50°C for 1 min, then ramped at 20°C/min to 330°C, held constant for 5 min
Transferline Temperature:230C
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:MS000535
Analysis ID:AN000602
Instrument Name:Leco Pegasus IV TOF
Instrument Type:GC-TOF
MS Type:EI
Ion Mode:POSITIVE
Ion Source Temperature:250 C
Ionization Energy:70 eV
Mass Accuracy:Nominal
Source Temperature:250 C
Scan Range Moverz:85-500 Da
Scanning Cycle:17 Hz
Scanning Range:85-500 Da
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