The laboratory of Dr. Thomas Graeber at UCLA developed a novel in vivo model that can characterize mechanisms of the trans-differentiation of prostate cancer into small cell neuroendocrine cancer.
BACKGROUND: Prostate cancer is one of the most common cancers among men worldwide, with an estimated 288,300 new cases in the U.S. last year. Among many reasons, cancer is difficult to treat because cancer cells are remarkably plastic, adaptive, and can evolve to form resistance over time to treatments, such as androgen deprivation therapy (ADT), a common treatment for prostate cancer. In some cases, prostate cancer cells can go through a process called trans-differentiation, where they can transform into and acquire characteristics of another differentiated cell in their resistance to therapies. Trans-differentiation from prostate cancer into small cell neuroendocrine (SCN) cancer is thought to occur as a way for prostate cancer cells to lose their dependence on androgen signaling and become resistant to ADT, allowing tumors to continue growing and spreading. Understanding the mechanisms of trans-differentiation in cancer research is critical to mitigate this adverse process, though it remains a challenge due to limitations of available research models.
INNOVATION: The laboratory of Dr. Thomas Graeber at UCLA has developed a novel in vivo mouse model that can characterize the trans-differentiation of prostate cancer cells into SCN cancer on a temporal scale. Their model, named pan-small cell neuroendocrine cancer model (PARCB), relies on a forward genetic transformation using human naive prostate basal epithelial cells. Researchers conducted a comprehensive analysis over time using multi-omics techniques to assess the PARCB model, revealing temporal and transcriptional trends in the development of SCN tumors. Additionally, they identified commonalities between prostate and lung cancers, as well as with normal neuroendocrine cells, shedding light on cross-tissue parallels. This tool allows users to explore both bulk RNA-sequencing and single-cell RNA-sequencing data of a clinically relevant prostate model across different time points.
POTENTIAL APPLICATIONS:
- Identification of SCN trans-differentiation pathways
- Sub-classification of SCN prostate cancer tumors by temporal transcriptomic profiles
- Identification of critical transcription factors at different disease stages of neuroendocrine prostate cancer
- Identifying temporal candidate proteins for therapeutic and diagnostic targets in treating SCN cancers
ADVANTAGES:
- The model is human cell-based with high translational value
- Accelerates mechanistic understanding of neuroendocrine prostate cancer
- Comprehensive profiling of the trans-differentiation process
- High temporal resolution with this technique
DEVELOPMENT-TO-DATE: in-vivo studies
Related paper (by the inventors only): Balanis, Sheu, et al., Cancer Cell, 2019;36(1):17-34.e7