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Quantitative Mass Spectrometric Profiling of Cancer-cell Proteomes Derived From Liquid and Solid Tumors
Published on: February 27, 2015
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LC-MS based metabolomic profiling for renal cell carcinoma histologic subtypes
Lun Jing1,2, Jean-Marie Guigonis1,2, Delphine Borchiellini3
1Laboratory Transporter in Imaging and Radiotherapy in Oncology (TIRO), Institut de biosciences et biotechnologies d'Aix-Marseille (BIAM), Commissariat à lEnergie Atomique, Nice, France.
Scientific Reports
|November 1, 2019
Summary
Metabolomic profiling accurately classifies renal cell carcinoma (RCC) subtypes, distinguishing clear cell, papillary, and chromophobe types. This approach reveals metabolic differences, aiding in understanding RCC behavior and developing targeted therapies.
Area of Science:
- Oncology
- Metabolomics
- Biochemistry
Background:
- Renal cell carcinoma (RCC) classification relies on histology, but understanding metabolic dysregulation is crucial.
- Accurate RCC subtype classification is vital for prognosis and treatment strategies.
Purpose of the Study:
- To utilize metabolomic analyses for classifying main RCC subtypes.
- To delineate metabolic variations within each RCC subtype.
- To explore the potential of metabolomics as a complementary diagnostic tool.
Main Methods:
- Metabolomic profiling of 65 RCC frozen samples (clear cell, papillary, chromophobe) using liquid chromatography-mass spectrometry.
- Orthogonal partial least squares-discriminant analysis (OPLS-DA) for multivariate data analysis.
- Pathway analysis of top metabolites to identify metabolic differences.
Main Results:
- Metabolomic data achieved clear discrimination of all three main RCC subtypes (R² = 75.0%, Q² = 59.7%).
- Prognostic evaluation demonstrated high accuracy (AUROC 0.924–1.0) for subtype classification.
- Significant differences in amino acid and fatty acid metabolism were observed between RCC subtypes.
Conclusions:
- Metabolomic profiling serves as a valuable tool complementary to histology for RCC subtype classification.
- This study provides insights into the metabolic dysregulation of RCC subtypes.
- Findings can inform the development of targeted therapeutic strategies for RCC.
