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Abida, W.

Publications and source records attributed to Abida, W..

2 recordsLinked to original sources

Genomic characterization of metastatic patterns from prospective clinical sequencing of 25,000 patients

Progression to metastatic disease remains the main cause of cancer death. Yet, the underlying genomic mechanisms driving metastasis remain largely unknown. Here, we present MSK-MET, an integrated pan-cancer cohort of tumor genomic and clinical outcome data from more than 25,000 patients. We analyzed this dataset to identify associations between tumor genomic alterations and patterns of metastatic dissemination across 50 tumor types. We found that chromosomal instability is strongly correlated with metastatic burden in some tumor types, including prostate adenocarcinoma, lung adenocarcinoma and HR-positive breast ductal carcinoma, but not in others, such as colorectal adenocarcinoma, pancreatic adenocarcinoma and high-grade serous ovarian cancer. We also identified specific somatic alterations associated with increased metastatic burden and specific routes of metastatic spread. Our data offer a unique resource for the investigation of the biological basis for metastatic spread and highlight the crucial role of chromosomal instability in cancer progression.

cancer biology

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

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.

cancer biology