st000284: Colorectal Cancer Detection Using Targeted Serum Metabolic...
In POMA: User-friendly Workflow for Pre-processing and Statistical Analysis of Mass Spectrometry Data
Description
Usage
Format
Source
References
Description
Colorectal cancer (CRC) is one of the most prevalent and deadly cancers in the world. Despite an expanding knowledge of its molecular
pathogenesis during the past two decades, robust biomarkers to enable screening, surveillance, and therapy monitoring of CRC are still lacking.
In this study, we present a targeted liquid chromatography-tandem mass spectrometry-based metabolic profiling approach for identifying biomarker
candidates that could enable highly sensitive and specific CRC detection using human serum samples. In this targeted approach, 158 metabolites
from 25 metabolic pathways of potential significance were monitored in 234 serum samples from three groups of patients (66 CRC patients,
76 polyp patients, and 92 healthy controls). Partial least squares-discriminant analysis (PLS-DA) models were established, which proved to
be powerful for distinguishing CRC patients from both healthy controls and polyp patients. Receiver operating characteristic curves generated
based on these PLS-DA models showed high sensitivities (0.96 and 0.89, respectively, for differentiating CRC patients from healthy controls
or polyp patients); good specificities (0.80 and 0.88), and excellent areas under the curve (0.93 and 0.95) were also obtained. Monte Carlo
cross validation (MCCV) was also applied, demonstrating the robust diagnostic power of this metabolic profiling approach.
Usage
1
Format
A MSnSet object: 224 samples, 113 metabolites, 4 covariables and 3 groups (CRC, Healthy and Polyp).
- metabolites
113 serum metabolites.
- covariables
Age at consent, Gender, Smoking Condition and Alcohol Consumption.
Source
References
Colorectal Cancer Detection Using Targeted Serum Metabolic Profiling, J. Proteome. Res., 2014, 13, 4120-4130.
POMA documentation built on Nov. 8, 2020, 6:26 p.m.
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Description Usage Format Source References
Description
Colorectal cancer (CRC) is one of the most prevalent and deadly cancers in the world. Despite an expanding knowledge of its molecular pathogenesis during the past two decades, robust biomarkers to enable screening, surveillance, and therapy monitoring of CRC are still lacking. In this study, we present a targeted liquid chromatography-tandem mass spectrometry-based metabolic profiling approach for identifying biomarker candidates that could enable highly sensitive and specific CRC detection using human serum samples. In this targeted approach, 158 metabolites from 25 metabolic pathways of potential significance were monitored in 234 serum samples from three groups of patients (66 CRC patients, 76 polyp patients, and 92 healthy controls). Partial least squares-discriminant analysis (PLS-DA) models were established, which proved to be powerful for distinguishing CRC patients from both healthy controls and polyp patients. Receiver operating characteristic curves generated based on these PLS-DA models showed high sensitivities (0.96 and 0.89, respectively, for differentiating CRC patients from healthy controls or polyp patients); good specificities (0.80 and 0.88), and excellent areas under the curve (0.93 and 0.95) were also obtained. Monte Carlo cross validation (MCCV) was also applied, demonstrating the robust diagnostic power of this metabolic profiling approach.
Usage
1 |
Format
A MSnSet object: 224 samples, 113 metabolites, 4 covariables and 3 groups (CRC, Healthy and Polyp).
- metabolites
113 serum metabolites.
- covariables
Age at consent, Gender, Smoking Condition and Alcohol Consumption.
Source
References
Colorectal Cancer Detection Using Targeted Serum Metabolic Profiling, J. Proteome. Res., 2014, 13, 4120-4130.
R Package Documentation
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Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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