Chromatin profiles classify castration-resistant prostate cancers suggesting therapeutic targets
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ABSTRACT:
PROVIDER: PRJNA818767 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR15335220_1.fastq.gz | Fastqsanger.gz | |||
| SRR15335220_2.fastq.gz | Fastqsanger.gz | |||
| SRR15335221_1.fastq.gz | Fastqsanger.gz | |||
| SRR15335221_2.fastq.gz | Fastqsanger.gz | |||
| SRR15335222_1.fastq.gz | Fastqsanger.gz |
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Project description:In castration-resistant prostate cancer (CRPC), the loss of androgen receptor (AR) dependence leads to clinically aggressive tumors with few therapeutic options. We used ATAC-seq (assay for transposase-accessible chromatin sequencing), RNA-seq, and DNA sequencing to investigate 22 organoids, six patient-derived xenografts, and 12 cell lines. We identified the well-characterized AR-dependent and neuroendocrine subtypes, as well as two AR-negative/low groups: a Wnt-dependent subtype, and a stem cell-like (SCL) subtype driven by activator protein-1 (AP-1) transcription factors. We used transcriptomic signatures to classify 366 patients, which showed that SCL is the second most common subtype of CRPC after AR-dependent. Our data suggest that AP-1 interacts with the YAP/TAZ and TEAD proteins to maintain subtype-specific chromatin accessibility and transcriptomic landscapes in this group. Together, this molecular classification reveals drug targets and can potentially guide therapeutic decisions.
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Project description:Untreated prostate cancers rely on androgen receptor (AR) signaling for growth and survival, forming the basis for the initial efficacy of androgen deprivation therapy (ADT). Yet, the disease can relapse and progress to a lethal stage termed castration-resistant prostate cancer (CRPC). Reactivation of AR signaling represents the most common driver of CRPC growth and next generation AR signaling inhibitors (ARSIs) are now used in combination with ADT as a first line therapy. However, ARSIs can result in selective pressure generating AR-independent tumors. The transition from AR-dependence frequently accompanies a change in phenotype resembling developmental trans-differentiation or ‘lineage plasticity’. Neuroendocrine prostate cancer, which lacks a defined pathologic classification, is the most studied type of lineage plasticity. However, most AR-null tumors do not exhibit neuroendocrine features and are classified as ‘double-negative prostate cancer’, the drivers of which are poorly defined. Lineage plasticity studies in CRPC are limited by the lack of genetically defined patient-derived models that recapitulate the disease spectrum.
To address this, we developed a biobank of organoids generated from patient biopsies to study the landscape of metastatic CRPC and allow for functional validation assays. Proteins called transcription factors (TFs) are drivers of tumor lineage plasticity. To identify the key TFs that drive the growth of AR-independent tumors, we integrated epigenetic and transcriptomic data generated from CRPC models.
By presenting a map of the chromatin accessibility and transcriptomic landscape of CRPC using a diverse biobank of organoids, PDXs and cell lines that recapitulate the heterogeneity of metastatic prostate cancer, we validate CRPC-AR and CRPC-NE subtypes and reveal two subtypes of AR-negative/low samples as well as their respective masterTFs. Additional analysis revealed a model in which YAP, TAZ, TEAD and AP-1 function together and drive oncogenic growth in CRPC-SCL samples. Overall, we show here how an approach to stratify CRPC patients into four subtypes using their transcriptomic signatures can potentially inform upon appropriate clinical decisions.
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