Lineage plasticity underlies therapeutic resistance in cancer1,2, yet the translational mechanisms that enable this phenotypic flexibility remain largely unknown. Here using prostate cancer as a model of lineage dependence, we performed unbiased small RNA sequencing and identified tRNA1Arg(UCU) as a regulator of lineag...
Y. Kim, Sonali Arora, D. Young et al.· Nature· 0 citations
Background: Biochemical recurrence (BCR) occurs in 20-40% of men after radical prostatectomy. Existing postoperative recurrence risk tools based on PSA and pathology are clinically useful but show only moderate and variable discrimination, highlighting the need for biomarkers that improve risk stratification and conseq...
B. Wang, S. Mukherjee, A. Baj et al.· medRxiv· 0 citations
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.
Zhi-Jun Chen, Erolcan Sayar, D. Guevara et al.· JCI Insight· 0 citations
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...
P. Itagi, Samantha L. Schuster, Sonali Arora et al.· Nature· 0 citations
Combined BET bromodomain and DNA methyltransferase (DNMT) inhibition was more effective than single-agent treatment in suppressing growth of TP53/RB1-loss models exhibiting a stem-like or NEPC program.
W. Storck, Diana Flores, A. Kumaraswamy et al.· JCI Insight· 0 citations
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