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A Novel Use of Biomarkers in the Modeling of Cancer Activity Based on the Theory of Endobiogeny
INTRODUCTION: Cancer is a complex disorder whose detection and monitoring remains challenging. A biological modeling system, the biology of functions (BoF), claims to be able to evaluate physiologic elements related to carcinogenic activity. A pilot study was undertaken to evaluate the accuracy of t...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Global Advances in Health and Medicine
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4104563/ https://www.ncbi.nlm.nih.gov/pubmed/25105079 http://dx.doi.org/10.7453/gahmj.2013.041 |
Sumario: | INTRODUCTION: Cancer is a complex disorder whose detection and monitoring remains challenging. A biological modeling system, the biology of functions (BoF), claims to be able to evaluate physiologic elements related to carcinogenic activity. A pilot study was undertaken to evaluate the accuracy of the BoF in detecting differences between cancer cases and matched controls. MATERIALS AND METHODS: A retrospective case control study was performed using the BoF analyses of 46 patients with all types of solid and hematgenous cancers, active and inactive (total cases), and 46 controls from a private practice. The standard BoF panel of 17 biomarkers was evaluated. Sixty-two of 150 BoF indices derived from these biomarkers were pre-selected for analysis based on their relationship to cancer physiology. The data was analyzed with the Wilcoxon Signed Ranks Test using SPSS software. RESULTS: Of the 62 indices, 7 were found to be statistically significant in comparing total cancer cases to controls: βMSH/αMSH, Estrogen Fraction #5, Comparative Genital Androgeny, Thyroid, Genito-thyroid, Catabolism/Anabolism and Pro-inflammatory. CONCLUSIONS: In a small retrospective case control study, statistically significant differences were found between cancer cases and controls in 7 BoF indices. These indices are indicators of physiological conditions consistent with cancer growth. These results warrant further study of this biological modeling system in cancer patients. |
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