Open AccessLinking cellular metabolism and metabolomics to risk-stratification of prostate cancer clinical aggressiveness and potential therapeutic pathways
Author(s) -
Eric Eidelman,
Hemantkumar Tripathi,
DeXue Fu,
Mohummad Minhaj Siddiqui
Publication year - 2018
Publication title -
translational andrology and urology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.721
H-Index - 27
eISSN - 2223-4691
pISSN - 2223-4683
DOI - 10.21037/tau.2018.04.08
Subject(s) - prostate cancer , risk stratification , disease , metabolomics , medicine , bioinformatics , stratification (seeds) , schema (genetic algorithms) , metabolic disease , computational biology , cancer , biology , computer science , seed dormancy , botany , germination , machine learning , dormancy
Prostate cancer treatment is based on the stratification of disease as low-, intermediate- or high-risk. This stratification has been largely based on anatomic pathology of the disease, as well as through the use of prostate specific antigen (PSA). However, despite this stratification, there remains heterogeneity within the current classification schema. Utilizing a metabolic approach may help to further establish novel biomolecular markers of disease aggressiveness. These markers may eventually be useful in not only the diagnosis of disease but in creating tumor specific targeted therapy for improved clinical outcomes.