ArticleCell cycle (Georgetown, Tex.)
Identification of progression markers for prostate cancer.
Article in Cell cycle (Georgetown, Tex.). The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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5 authors.
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Abstract
TGFβ functions as a tumor suppressor or promoter, depending on the context, making TGFβ a useful predictive biomarker. Genes related to TGFβ signaling and Aurora kinase were tested for their ability to predict the progression risk of primary prostate tumors. Using data from The Cancer Genome Atlas (TCGA), we trained an elastic-net regularized Cox regression model including a minimal set of gene expression, copy number (CN), and clinical data. A multi-step feature selection and regularization scheme was applied to minimize the number of features while maintaining predictive power. An independent hold-out cohort was used to validate the model. Expanding from prostate cancer, predictive models were similarly trained on all other eligible cancer types in TCGA.
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