Oral Virtual Presentation (Virtual only) ESA-SRB-ANZBMS 2021

Single-cell RNA analysis reveals heterogeneous sub-populations in neuroendocrine prostate cancer (#31)

Rosalia Quezada Urban 1 2 3 , Shivakumar Keerthikumar 1 3 4 , Ashlee K Clark 5 , Laura H Porter 5 , Mitchell G Lawrence 1 2 5 6 , Renea A Taylor 1 2 5 7 , Gail P Risbridger 1 2 5 6 , Roxanne Toivanen 1 5 , David L Goode 1 2 3
  1. Cancer Research Division, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
  2. Sir Peter MacCallum Department of Oncology, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
  3. Computational Cancer Biology Program, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
  4. Peter MacCallum Cancer Centre, Brunswick West, VICTORIA, Australia
  5. Prostate Cancer Research Group, Monash Biomedicine Discovery Institute, Cancer Program, Department of Anatomy and Developmental Biology, Monash Partners Comprehensive Cancer Consortium, Monash University, Clayton, Victoria, Australia
  6. Melbourne Urological Research Alliance (MURAL), Melbourne, Victoria, Australia
  7. Prostate Cancer Research Group, Monash Biomedicine Discovery Institute, Cancer Program, Department of Physiology, Monash Partners Comprehensive Cancer Consortium, Monash University, Clayton, Victoria, Australia

Background: Patients with neuroendocrine prostate cancer (NEPC) have aggressive tumours that result in poor patient outcomes. NEPC exhibits heterogeneity at the histological level, but the molecular drivers and therapeutic implications of this heterogeneity are poorly understood. Single-cell technology enables the resolution needed to unveil the complex heterogeneity of NEPC that bulk RNA analysis could not detect.

Objective: Characterise the molecular heterogeneity of NEPCs used in single cell RNA sequencing to detect common phenotypes across patients and identify new therapeutic targets.

Methods: We performed single-cell RNA sequencing on a novel cohort of eight patient-derived xenograft (PDX) models that recapitulate the pathological and clinical heterogeneity of NEPC. Downstream analysis of single-cell data was first completed on individual samples to identify distinct sub-populations of cells within each tumour. Then, integration analysis was performed to identify common and unique neuroendocrine populations across the different tumours. 

Results: Our pipeline allowed the single-cell RNA profiling of 17,760 cells captured from the eight NEPCs. We found that each tumour had between 3 to 8 different sub-populations, where each sup-population displayed distinct biological properties such as epithelial-mesenchymal transition, quiescence and stemness. Data integration of all samples revealed 18 sub-populations of tumour cells across all patients, of which 10 populations were primarily unique to one patient. Gene set enrichment analyses revealed heterogeneous expression of most cancer hallmarks and oncogenic pathways across sub-populations, although some pathways were common to several neuroendocrine sub-populations such as P53 and KRAS.

Conclusions: We demonstrate that NEPCs display intra- and inter- tumour heterogeneity at the single-cell level, but the molecular complexity of these tumours may make it challenging to identify a single target. Therefore, future work should continue investigating the heterogeneity of NEPC, and whether combination therapy or precision medicine may be more effective approaches for treating NEPCs.