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A deep learning model that leverages interpretable cellular features to improve feature extraction from H&E-stained tissue sections (NEURAL-PC) and represents an extensively validated diagnostic and prognostic model for advanced prostate cancer.
It is shown that metastasis-to-metastasis seeding is the dominant pattern of cancer spread and that increased polyclonal migration predicts poor prognosis, and that post-mortem cell-free DNA captures genomic and transcriptional heterogeneity of the subtypes, which provides a potential strategy for noninvasive assessmen...
The next wave of AR-directed therapies being developed for advanced prostate cancer is summarized, with a focus on agents being evaluated in ongoing clinical trials.
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