Abstract 1551: High-resolution parallel analysis of genome and transcriptome of single disseminated prostate cancer cells
Authors: Kirsch Stefan , Lahrmann Urs , Guzvic Miodrag , Czyz Zbigniew T. , Feliciello Giancarlo , Polzer Bernhard , Klein Christoph A. 
Published: July 2016

Abstract
Introduction: Manifestation of bone metastases is the most frequent cause of death among prostate cancer patients. Since the progression from non-metastatic (M0) to metastatic (M1) is highly unpredictable, molecular analysis of disseminated cancer cells (DCCs) detected before overt metastasis may provide an opportunity to dissect the early stages of systemic cancer and enable detection of critical therapy targets. However, we previously showed that early stage prostate DCCs acquire a bone marrow-associated transcriptomic phenotype (Guzvic et al. Cancer Res. 2014, 15;74(24):7383-94) impeding the definite identification of DCCs. To address this problem we developed a workflow of combined single-cell RNA-Seq and single-cell aCGH allowing high-resolution analysis of genomes and transcriptomes of individual cells. Here, we present a proof-of-concept study using DCCs isolated from bone marrow of prostate cancer patients.
Materials and methods: We isolated 24 EPCAM-positive DCCs from bone marrow of prostate cancer patients. In addition, we analyzed two VCaP prostate cancer cells and two peripheral blood lymphocytes of healthy individuals. All isolated cells were subjected to combined whole genome and whole transcriptome amplification using Ampli1TM WGA Kit and a WTA approach (Klein CA et al., Nat Biotechnol. 2002, 20(4):387-92), respectively. The suitability of WTA and WGA products for downstream analyses were assessed using PCR-based QC-assays. Subsequently, WGA products were hybridized on high-resolution SurePrint aCGH arrays and analyzed with Agilent Genomic Workbench Software. WTA products were sequenced using Roche 454 GS FLX+ or Illumina HiSeq 2000 systems. Single-cell RNA-Seq data were evaluated using a bioinformatic pipeline adjusted to the needs of the single cell WTA method.
Results: We provide two experimental protocols for single-cell RNA-Seq: (i) allowing detection of low-abundant transcripts and (ii) enabling comprehensive gene-expression analysis. The protocols were validated using VCaP cells, in which we could successfully detect low expression levels of TMPRSS2-ERG fusion transcripts. The established analysis allowed also detection of novel fusion transcripts in a M1-stage prostate cancer patient. Comprehensive gene expression analysis revealed presence of 4.000 to 13.000 transcripts expressed in bone marrow-derived cells. The comparison of RNA-Seq and aCGH data allowed to simultaneously detecting copy number alterations and corresponding changes in gene expression dosage. Thereby, the combined genome and transcriptome analysis of single cells enables to uncover the impact of genomic gains and losses on cellular transcriptomes.
Conclusions: Combined genome and transcriptome analysis of patient-derived single DCCs is feasible and enables unambiguous identification and genotypic and phenotypic characterization of DCCs.
Citation Format: Stefan Kirsch, Urs Lahrmann, Miodrag Guzvic, Zbigniew T. Czyz, Giancarlo Feliciello, Bernhard Polzer, Christoph A. Klein. High-resolution parallel analysis of genome and transcriptome of single disseminated prostate cancer cells. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 1551.