Summary of Study ST000385
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.
See: https://www.metabolomicsworkbench.org/about/howtocite.php
Study ID | ST000385 |
Study Title | Investigation of metabolomic blood biomarkers for detection of adenocarcinoma lung cancer (training set) |
Study 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 |
ofiehn@ucdavis.edu | |
Phone | (530) 754-8258 |
Submit Date | 2016-10-04 |
Study Comments | SS = 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 Available | Yes |
Analysis Type Detail | GC-MS |
Release Date | 2016-04-30 |
Release Version | 1 |
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: | SU000406 |
Subject Type: | Human |
Subject Species: | Homo sapiens |
Taxonomy ID: | 9606 |
Species Group: | Mammals |
Factors:
Subject type: Human; Subject species: Homo sapiens (Factor headings shown in green)
mb_sample_id | local_sample_id | Organ | Health State | Smoking Status | Gender |
---|---|---|---|---|---|
SA017481 | 140227dlvsa36_1 | Plasma | Adenocarcinoma | Current | F |
SA017482 | 140226dlvsa30_1 | Plasma | Adenocarcinoma | Current | F |
SA017483 | 140226dlvsa36_1 | Plasma | Adenocarcinoma | Current | F |
SA017484 | 140227dlvsa47_1 | Plasma | Adenocarcinoma | Current | F |
SA017485 | 140228dlvsa08_1 | Plasma | Adenocarcinoma | Current | F |
SA017486 | 140228dlvsa30_1 | Plasma | Adenocarcinoma | Current | F |
SA017487 | 140228dlvsa17_1 | Plasma | Adenocarcinoma | Current | F |
SA017488 | 140225dlvsa44_1 | Plasma | Adenocarcinoma | Current | F |
SA017489 | 140228dlvsa39_1 | Plasma | Adenocarcinoma | Current | F |
SA017490 | 140225dlvsa14_1 | Plasma | Adenocarcinoma | Current | M |
SA017491 | 140226dlvsa21_1 | Plasma | Adenocarcinoma | Current | M |
SA017492 | 140226dlvsa41_1 | Plasma | Adenocarcinoma | Current | M |
SA017493 | 140225dlvsa31_1 | Plasma | Adenocarcinoma | Current | M |
SA017494 | 140228dlvsa28_1 | Plasma | Adenocarcinoma | Current | M |
SA017495 | 140227dlvsa14_1 | Plasma | Adenocarcinoma | Current | M |
SA017496 | 140225dlvsa05_1 | Plasma | Adenocarcinoma | Former | F |
SA017497 | 140225dlvsa09_1 | Plasma | Adenocarcinoma | Former | F |
SA017498 | 140225dlvsa07_1 | Plasma | Adenocarcinoma | Former | F |
SA017499 | 140225dlvsa22_1 | Plasma | Adenocarcinoma | Former | F |
SA017500 | 140226dlvsa03_1 | Plasma | Adenocarcinoma | Former | F |
SA017501 | 140227dlvsa40_1 | Plasma | Adenocarcinoma | Former | F |
SA017502 | 140226dlvsa23_1 | Plasma | Adenocarcinoma | Former | F |
SA017503 | 140226dlvsa43_1 | Plasma | Adenocarcinoma | Former | F |
SA017504 | 140228dlvsa26_1 | Plasma | Adenocarcinoma | Former | F |
SA017505 | 140225dlvsa18_1 | Plasma | Adenocarcinoma | Former | F |
SA017506 | 140228dlvsa19_1 | Plasma | Adenocarcinoma | Former | F |
SA017507 | 140227dlvsa03_1 | Plasma | Adenocarcinoma | Former | F |
SA017508 | 140228dlvsa06_1 | Plasma | Adenocarcinoma | Former | F |
SA017509 | 140225dlvsa16_1 | Plasma | Adenocarcinoma | Former | F |
SA017510 | 140228dlvsa12_1 | Plasma | Adenocarcinoma | Former | F |
SA017511 | 140227dlvsa18_1 | Plasma | Adenocarcinoma | Former | M |
SA017512 | 140227dlvsa21_1 | Plasma | Adenocarcinoma | Former | M |
SA017513 | 140228dlvsa34_1 | Plasma | Adenocarcinoma | Former | M |
SA017514 | 140226dlvsa27_1 | Plasma | Adenocarcinoma | Former | M |
SA017515 | 140228dlvsa37_1 | Plasma | Adenocarcinoma | Former | M |
SA017516 | 140225dlvsa36_1 | Plasma | Adenocarcinoma | Former | M |
SA017517 | 140228dlvsa23_1 | Plasma | Adenocarcinoma | Former | M |
SA017518 | 140227dlvsa01_1 | Plasma | Adenocarcinoma | Former | M |
SA017519 | 140227dlvsa45_1 | Plasma | Adenocarcinoma | Former | M |
SA017520 | 140228dlvsa21_1 | Plasma | Adenocarcinoma | Former | M |
SA017521 | 140227dlvsa49_1 | Plasma | Adenocarcinoma | Former | M |
SA017522 | 140226dlvsa16_1 | Plasma | Adenocarcinoma | Former | M |
SA017523 | 140226dlvsa49_1 | Plasma | Adenocarcinoma | Former | M |
SA017524 | 140225dlvsa33_1 | Plasma | Healthy | Current | F |
SA017525 | 140227dlvsa16_1 | Plasma | Healthy | Current | F |
SA017526 | 140227dlvsa25_1 | Plasma | Healthy | Current | F |
SA017527 | 140225dlvsa49_1 | Plasma | Healthy | Current | F |
SA017528 | 140226dlvsa12_1 | Plasma | Healthy | Current | F |
SA017529 | 140225dlvsa25_1 | Plasma | Healthy | Current | F |
SA017530 | 140226dlvsa14_1 | Plasma | Healthy | Current | F |
SA017531 | 140227dlvsa10_1 | Plasma | Healthy | Current | F |
SA017532 | 140227dlvsa07_1 | Plasma | Healthy | Current | F |
SA017533 | 140225dlvsa40_1 | Plasma | Healthy | Current | M |
SA017534 | 140226dlvsa08_1 | Plasma | Healthy | Current | M |
SA017535 | 140228dlvsa15_1 | Plasma | Healthy | Current | M |
SA017536 | 140225dlvsa27_1 | Plasma | Healthy | Current | M |
SA017537 | 140227dlvsa43_1 | Plasma | Healthy | Current | M |
SA017538 | 140227dlvsa34_1 | Plasma | Healthy | Current | M |
SA017539 | 140227dlvsa32_1 | Plasma | Healthy | Current | M |
SA017540 | 140227dlvsa29_1 | Plasma | Healthy | Former | F |
SA017541 | 140228dlvsa01_1 | Plasma | Healthy | Former | F |
SA017542 | 140225dlvsa42_1 | Plasma | Healthy | Former | F |
SA017543 | 140225dlvsa20_1 | Plasma | Healthy | Former | F |
SA017544 | 140226dlvsa34_1 | Plasma | Healthy | Former | F |
SA017545 | 140226dlvsa45_1 | Plasma | Healthy | Former | F |
SA017546 | 140226dlvsa05_1 | Plasma | Healthy | Former | F |
SA017547 | 140228dlvsa04_1 | Plasma | Healthy | Former | F |
SA017548 | 140225dlvsa03_1 | Plasma | Healthy | Former | F |
SA017549 | 140227dlvsa23_1 | Plasma | Healthy | Former | F |
SA017550 | 140228dlvsa10_1 | Plasma | Healthy | Former | F |
SA017551 | 140226dlvsa19_1 | Plasma | Healthy | Former | F |
SA017552 | 140226dlvsa10_1 | Plasma | Healthy | Former | F |
SA017553 | 140226dlvsa25_1 | Plasma | Healthy | Former | M |
SA017554 | 140228dlvsa32_1 | Plasma | Healthy | Former | M |
SA017555 | 140226dlvsa32_1 | Plasma | Healthy | Former | M |
SA017556 | 140225dlvsa38_1 | Plasma | Healthy | Former | M |
SA017557 | 140227dlvsa27_1 | Plasma | Healthy | Former | M |
SA017558 | 140227dlvsa05_1 | Plasma | Healthy | Former | M |
SA017559 | 140227dlvsa38_1 | Plasma | Healthy | Former | M |
SA017560 | 140225dlvsa11_1 | Plasma | Healthy | Former | M |
SA017561 | 140225dlvsa29_1 | Plasma | Healthy | Former | M |
SA017562 | 140226dlvsa38_1 | Plasma | Healthy | Former | M |
SA017563 | 140225dlvsa47_1 | Plasma | Healthy | Former | M |
SA017564 | 140228dlvsa41_1 | Plasma | Healthy | Former | M |
SA017565 | 140227dlvsa12_1 | Plasma | Healthy | Former | M |
SA017566 | 140226dlvsa01_1 | Plasma | Healthy | Former | M |
SA017587 | 140225dlvsa43_1 | Serum | Adenocarcinoma | Current | F |
SA017588 | 140228dlvsa07_1 | Serum | Adenocarcinoma | Current | F |
SA017589 | 140227dlvsa46_1 | Serum | Adenocarcinoma | Current | F |
SA017590 | 140228dlvsa38_1 | Serum | Adenocarcinoma | Current | F |
SA017591 | 140226dlvsa35_1 | Serum | Adenocarcinoma | Current | F |
SA017592 | 140228dlvsa29_1 | Serum | Adenocarcinoma | Current | F |
SA017593 | 140226dlvsa29_1 | Serum | Adenocarcinoma | Current | F |
SA017594 | 140228dlvsa16_1 | Serum | Adenocarcinoma | Current | F |
SA017595 | 140227dlvsa35_1 | Serum | Adenocarcinoma | Current | F |
SA017596 | 140226dlvsa40_1 | Serum | Adenocarcinoma | Current | M |
SA017597 | 140227dlvsa13_1 | Serum | Adenocarcinoma | Current | M |
SA017598 | 140228dlvsa27_1 | Serum | Adenocarcinoma | Current | M |
SA017599 | 140225dlvsa13_1 | Serum | Adenocarcinoma | Current | M |
SA017600 | 140226dlvsa20_1 | Serum | Adenocarcinoma | Current | M |
Collection:
Collection ID: | CO000400 |
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: | TR000420 |
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: | SP000413 |
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 | AN000620 |
---|---|
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: | CH000445 |
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: | MS000553 |
Analysis ID: | AN000620 |
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 |