Back

Chromatin accessibility profiles of castration-resistant prostate cancers reveal novel subtypes and therapeutic vulnerabilities

Tang, F.; Wang, S.; Wong, C. K.; Lee, C. J.; Cohen, S.; Park, J.; Hill, C. E.; Eng, K.; Bareja, R.; Han, T.; Liu, E. M.; Palladino, A.; Di, W.; Gao, D.; Abida, W.; Beg, S.; Puca, L.; Berger, M. F.; Gopalan, A.; Dow, L. E.; Mosquera, J. M.; Beltran, H.; Sternberg, C. N.; Chi, P.; Scher, H. I.; Sboner, A.; Chen, Y.; Khurana, E.

2020-10-26 cancer biology
10.1101/2020.10.26.355925 bioRxiv
Show abstract

In castration-resistant prostate cancer (CRPC), the loss of androgen receptor (AR)-dependence due to lineage plasticity, which has become more prevalent, leads to clinically highly aggressive tumors with few therapeutic options and is mechanistically poorly defined. To identify the master transcription factors (TFs) of CRPC in a subtype-specific manner, we derived and collected 29 metastatic human prostate cancer organoids and cell lines, and generated ATAC-seq, RNA-seq and DNA sequencing data. We identified four subtypes and their master TFs using novel computational algorithms: AR-dependent; Wnt-dependent, driven by TCF; neuroendocrine, driven by ASCL1 and NEUROD1 and stem cell-like (SCL), driven by the AP-1 family. The transcriptomic signatures of these four subtypes enabled the classification of 370 patients. We find that AP-1 co-operates with the inhibitable YAP/TAZ/TEAD pathway in the SCL subtype, the second most common group of CRPC tumors after AR-dependent. Together, this molecular classification reveals new drug targets and can potentially guide therapeutic decisions.

Matching journals

The top 6 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.