Summary of Study ST001269
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 PR000854. The data can be accessed directly via it's Project DOI: 10.21228/M8998T This work is supported by NIH grant, U2C- DK119886.
See: https://www.metabolomicsworkbench.org/about/howtocite.php
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.
| Study ID | ST001269 |
| Study Title | Exosomal lipids for classifying early and late stage non-small cell lung cancer |
| Study Type | Biomarker Discovery |
| Study Summary | Lung cancer is the leading cause of cancer deaths in the United States. Patients with early stage lung cancer have the best prognosis with surgical removal of the tumor, but the disease is often asymptomatic until advanced disease develops, and there are no effective blood-based screening methods for early detection of lung cancer in at-risk populations. We have explored the lipid profiles of blood plasma exosomes using ultra high-resolution Fourier transform mass spectrometry (UHR-FTMS) for early detection of the prevalent non-small cell lung cancers (NSCLC). Exosomes are nanovehicles released by various cells and tumor tissues to elicit important biofunctions such as immune modulation and tumor development. Plasma exosomal lipid profiles were acquired from 39 normal and 91 NSCLC subjects (44 early stage and 47 late stage). We have applied two multivariate statistical methods, Random Forest (RF) and Least Absolute Shrinkage and Selection Operator (LASSO) to classify the data. For the RF method, the Gini importance of the assigned lipids was calculated to select 16 lipids with top importance. Using the LASSO method, 7 features were selected based on a grouped LASSO penalty. The Area Under the Receiver Operating Characteristic curve for early and late stage cancer versus normal subjects using the selected lipid features was 0.85 and 0.88 for RF and 0.79 and 0.77 for LASSO, respectively. These results show the value of RF and LASSO for metabolomics data-based biomarker development, which provide robust an independent classifiers with sparse data sets. Application of LASSO and Random Forests identifies lipid features that successfully distinguish early stage lung cancer patient from healthy individuals. |
| Institute | University of Kentucky |
| Department | Center for Environmental and Systems Biochemistry |
| Last Name | Thompson |
| First Name | Patrick |
| Address | 789 South Limestone, Lexington, Kentucky, 40536, USA |
| ptth222@uky.edu, rick.higashi@uky.edu | |
| Phone | 8592181027 |
| Submit Date | 2019-10-17 |
| Total Subjects | 95 |
| Publications | https://doi.org/10.1016/j.aca.2018.02.051 |
| Raw Data Available | Yes |
| Raw Data File Type(s) | raw(Thermo) |
| Analysis Type Detail | MS(Dir. Inf.) |
| Release Date | 2019-10-11 |
| Release Version | 1 |
Select appropriate tab below to view additional metadata details:
Sample Preparation:
| Sampleprep ID: | SP001345 |
| Sampleprep Summary: | Exosomes were isolated from plasma by differential ultracentrifugation adapted from Refs. [47,48]. 0.7 mL cleared plasma (see above) were placed in 5 41 mm polyallomer ultraclear ultracentrifuge tubes on ice, and centrifuged for 1 h at 70,000 g at 4 C in a SWTi55 swing out rotor (Beckman). The supernatant was recentrifuged at 100,000 g for 1 h at 4 C, and the pellet was drained and resuspended in 0.7 mL cold PBS, and recentrifuged at 100,000 g for 1 h at 4 C. The washed exosomal pellets were resuspended in 100 mL nanopure water, vortexed for 30 s and transferred to a fresh microcentrifuge tube. The ultracentrifuge tube was washed with another 100 mL of nanopure water, vortexed for 30 s and the wash was transferred into same microcentrifuge tube, using the same pipet tip. The combined exosome suspensions were then lyophilized except for a small portion that was used for characterization by particle size distribution analysis (see below). These nanoparticles are operationally defined as exosomes. The lyophilized EXO preparations were extracted for lipidic metabolites using a solvent partitioning method with CH3CN:H2O:CHCl3 (2:1.5:1, v/v) as described previously [49]. The resulting lipid extracts were vacuum-dried in a vacuum centrifuge (Eppendorf), redissolved in 200 mL CHCl3:CH3OH (2:1) with 1 mM butylated hydroxytoluene, which was further diluted 1:20 in isopropanol/CH3OH/CHCl3 (4:2:1) with 20 mM ammonium formate for UHR-FTMS analysis. |
| Sampleprep Protocol Comments: | A small fraction (<1%) of each exosome preparation was characterized by size distribution analysis using a Nanosight 300 (Malvern Instruments), which provided the distribution of the Stokes' radius (mean 60e66 nm) and the number density of the particles. A typical analysis is shown in Fig. S1. The method eliminates very small particles, and provides a strongly peaked, narrow distribution at the expected size for exosomes (40e100nm, observed mode of 60e65 nm for the main peaks in Figs. S1A and B). |
