Applying random forests to identify biomarker panels in serum 2D-DIGE data for the detection and staging of prostate cancer
Abstract
In recent years, Prostate Specific Antigen (PSA) testing is widespread and has been associated with deceased mortality rates; however, this testing has raised concerns of overdiagnosis and overtreatment. It is clear that additional biomarkers are required. To identify these biomarkers, we have undertaken proteomics and metabolomics expression profiles of serum samples from BPH, Gleason score 5 and 7 using two-dimensional difference in gel electrophoresis (2D-DIGE) and nuclear magnetic resonance spectroscopy (NMR). Panels of serum protein biomarkers were identified by applying Random Forests to the 2D-DIGE data. The evaluation of selected biomarker panels has shown that they can provide higher prediction accuracy than the current diagnostic standard. With careful validation of these serum biomarker panels, these panels may potentially help to reduce unnecessary invasive diagnostic procedures and more accurately direct the urologist to curative surgery.
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Metabolomics and proteomics have been integrated using RF for prostate cancer and thyroid functioning.
“Metabolomics and proteomics have been integrated using RF for analysis of prostate cancer (Fan et al., 2011) and thyroid functioning (Pietzner et al., 2017).”
From Using machine learning approaches for multi-omics data analysis: A review (2021) · cites this paper as Fan et al., 2011
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Machine Learning Analysis of Immune Cells for Diagnosis and Prognosis of Cutaneous Melanoma
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Metabolomics-Based Liquid Biopsy for Predicting Clinically Significant Prostate Cancer
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Supplementary Figure 1 from Metabolomics of Prostate Cancer Gleason Score in Tumor Tissue and Serum
Penney, K. L., Tyekucheva, S., Rosenthal, J., Fandy, H. E., Carelli, R., Borgstein, S., Zadra, G., Fanelli, G. N., Stefanizzi, L., Giunchi, F., et al. (2023) · doi:10.1158/1541-7786.22526778
Supplementary Figure 2 from Metabolomics of Prostate Cancer Gleason Score in Tumor Tissue and Serum
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- Authors
- Fan, Y., Murphy, T. B., Byrne, J. C., Brennan, L., Fitzpatrick, J. M., & Watson, R. W. G.
- Affiliations
- University College Dublin (IE)
- Mater Misericordiae University Hospital (IE)
- Corresponding author
- Watson, R. William G.
- Venue
- Journal of Proteome Research
- Publisher
- American Chemical Society (ACS)
- Published
- 2011-01-27
- Volume
- 10
- Issue
- 3
- Pages
- 1361-1373
- ISSN
- 1535-3893 (ISSN-L)
- 1535-3907
- OpenAlex
- W2325347090
- Cited by
- 77
- References
- 37
- Citations by year
- 2025: 3 · 2024: 3 · 2023: 4 · 2022: 3 · 2021: 5 · 2020: 6 · 2019: 7 · 2018: 3 · 2017: 7 · 2016: 4 · 2015: 6 · 2014: 6 · 2013: 6 · 2012: 8
- FWCI
- 2.94
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Proteome Research (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Physical Sciences › Chemistry › Spectroscopy › Advanced Proteomics Techniques and Applications
- Health Sciences › Medicine › Pulmonary and Respiratory Medicine › Prostate Cancer Diagnosis and Treatment
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene expression and cancer classification
- Keywords
- prostate cancer, serum biomarker panel, random forest, 2D-DIGE, prostate-specific antigen, benign prostatic hyperplasia, Gleason score, tumor staging, cancer detection, overdiagnosis, serum proteomics, NMR metabolomics
- MeSH terms
- Humans, Male, Neoplasm Staging, Prostatic Neoplasms, Mass Spectrometry, Biomarkers, Tumor, Reproducibility of Results, Cluster Analysis, Area Under Curve, Two-Dimensional Difference Gel Electrophoresis
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