Abstract
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Objectives To determine which amino acid transporter has the best capacity to distinguish prostate cancer.
Methods We analyzed a U133A array dataset published by YP Wang et al. (GSE8218) that includes 136 prostate samples with documenting percentages of tumor, stroma, hypertrophy, and atrophy. 17 transcripts of amino acid transporters were investigated by ROC, an excel program developed by Charles Zaiontz (www.real-statistacs.com)
Results eight over 17 transcripts of amino acid transcripts have an AUC > 0.5 (p < 0.05) in logistic regression modeling. From high to low calculated AUC of 8 transcripts were SLC7A11 (0.79), SLC7A1 (0.78), SLC7A (0.68), SLC1A4 (0.68), SLC36A1 (0.65), SLC1A5 (0.64), SLC7A8 (0.64), and SLC6A14 (0.61). The AUC of the combination of SLC7A11 and SLC7A1 was 0.8.
Conclusions Based on traditional academic point system (0.9-1=excellent; 0.8-0.9=good; 0.7-.08=fair; 0.6-0.7= poor; 0.5-0.6= fail), SLC7A11 and SLC7A1 are classified as fair. Other amino acid transporters are poor or fail. Our analysis suggests SLC7A11 and SLC7A1 might be the biological foundation for Anti-1-Amino-3-18F-Fluorocyclobutane-1-Carboxylic Acid (FACBC) uptake in prostate cancer.
Research Support T32EB006351