Prostate cancer (PCa) is a highly common cancer among men but lacks robust diagnostics
that can predict disease recurrence after initial treatment, for example, with radical …

Background Unsupervised learning methods, such as Hierarchical Cluster Analysis, are
commonly used for the analysis of genomic platform data. Unfortunately, such approaches …

BACKGROUND The derivation of molecular signatures indicative of disease status and
predictive of subsequent behavior could facilitate the optimal choice of treatment for prostate …

Prostate cancer, a complex disease, can be relatively harmless or extremely aggressive. To
identify candidate genes involved in causal pathways of aggressive prostate cancer, we …

Background Prostate cancer cells in primary tumors have been typed CD10-/CD13-/CD24
hi/CD26+/CD38 lo/CD44-/CD104-. This CD phenotype suggests a lineage relationship …

BACKGROUND Prostate cancer (PCa) is clinically and biologically heterogeneous, making
it difficult to predict at detection whether it will take an indolent or aggressive disease course …

Prostate cancer is the most common form of non-dermatological cancer among US men,
with an increasing incidence due to the aging population. Patients diagnosed with clinically …

The recurrence of prostate cancer (PCa) is intrinsically linked to increased mortality. The
goal of this study was to develop an efficient and reliable prognosis prediction signature for …

Background Molecular signatures in prostate cancer (PCa) tissue can provide useful
prognostic information to improve the understanding of a patient's risk of harbouring …

Prostate cancer is a highly heterogeneous disease and the second more common tumor in
males. Molecular and genetic profiles are currently used to identify subtypes and to guide …