Cells Comprising the Prostate Cancer Microenvironment Lack Recurrent Clonal Somatic Genomic Aberrations

Abstract

Prostate cancer-associated stroma (CAS) plays an active role in malignant transformation, tumor progression, and metastasis. Molecular analyses of CAS have demonstrated significant changes in gene expression; however, conflicting evidence exists on whether genomic alterations in benign cells comprising the tumor microenvironment (TME) underlie gene expression changes and oncogenic phenotypes. This study evaluates the nuclear and mitochondrial DNA integrity of prostate carcinoma cells, CAS, matched benign epithelium and benign epithelium-associated stroma by whole-genome copy-number analyses, targeted sequencing of TP53, and FISH. Array comparative genomic hybridization (aCGH) of CAS revealed a copy-neutral diploid genome with only rare and small somatic copy-number aberrations (SCNA). In contrast, several expected recurrent SCNAs were evident in the adjacent prostate carcinoma cells, including gains at 3q, 7p, and 8q, and losses at 8p and 10q. No somatic TP53 mutations were observed in CAS. Mitochondrial DNA (mtDNA) extracted from carcinoma cells and stroma identified 23 somatic mtDNA mutations in neoplastic epithelial cells, but only one mutation in stroma. Finally, genomic analyses identified no SCNAs, LOH, or copy-neutral LOH in cultured cancer-associated fibroblasts, which are known to promote prostate cancer progression in vivo

Implications: The gene expression changes observed in prostate cancer-adjacent stroma and the attendant contribution of the stroma to the development and progression of prostate cancer are not due to frequent or recurrent genomic alterations in the TME.

Figure 1. Laser capture microdissection of epithelial and stromal cells from fresh frozen prostate tissue

(A) Image of 7 µM prostate tissue section on PEP membrane slide. (B) Image of tumor region of interest. (C–D). An area cancer adjacent stroma (*) before (C) and after (D) LCM. E–F, an epithelial area ( ) from the same tumor region before (E) and after (F) LCM. (G–H), Patient-matched benign epithelium (G) and stromal (H) areas microdissected from regions away from the tumor or from other tissue blocks (preferentially). Delineated areas in black and marked (+) are the benign epithelium and stromal adjacent to benign epithelium areas, immediately after LCM but before lifting the cap from the whole tissue section.

Figure 2. Genomic copy number aberrations in prostate cancer epithelium and cancer-associated stroma

(A) Number of somatic copy number aberrations (SCNAs) found within each case in both CPE and CAS. Red, SCNAs identified as unique to CPE. Blue, SCNAs identified as unique to CAS, green, SCNAs identified as overlapping between CAS and CPE. Note the low number of CAS unique SCNAs as compared to SCNAs unique to CPE. (B–C) Frequency plots of DNA copy number alterations in the genome of prostate cancer. The y-axis indicates the percentage of the population in the selected samples (B) CPE matched paired samples (n = 20) and (C) CAS-matched paired samples (n = 20) having a copy number aberration event at a specific point along the genome. Blue indicates copy number gain events (above the 0% baseline) and red, copy number loss events (below the 0% baseline). The X-axis represents the position of the genome on each chromosome. Each chromosome was designated by its corresponding number and the divisions between individual chromosomes are shown by vertical lines. Note the high number of genomic aberrations and high frequency of SCNAs found in the tumor epithelium, in great contrast to the tumor stromal which exhibits a very low number of genomic aberrations and a low frequency of SCNAs across the whole genome.

Figure 3. Comparison of genes found in aberrations unique to CPE or CAS using different copy number calling algorithms

Venn diagram comparing genes identified by Nexus and Agilent CytoGenomics algorithms for the unique CPE-SCNAs gains (A) and losses (B). Venn diagram comparing genes identified by Nexus and Agilent algorithms for the unique CAS-SCNAs gains (C) and losses (D). The majority of genes identified in the CPE samples by Nexus are also found in the Agilent analysis (84% gains and 86% losses). In contrast, only 8% of genes within copy number losses in the CAS samples overlapped between both analyses. (E) ddPCR measurements of HOXA5 and HOXA10 copy numbers from unamplified DNA from the 4 different cell compartments from two patients identified by aCGH to have copy number losses in the HOXA gene cluster (cases 10-011 and 00-081). No copy losses of HOXA5 or HOXA10 were identified in any cell compartment (BAS, BPE, CAS and CPE): each had 2 copies per diploid genome.

Figure 4. Absence of DNA copy number alterations in primary cancer-associated fibroblast (CAF) cell cultures

Whole genome plots are shown for CAF1/NAF1-matched pair (A) and CAF2/NAF2-matched pair (B), and a representative CGH plot from cancer epithelium (C). Several alterations are detected in the epithelial tumors (arrows) with the absence of SCNAs in the cancer-associated fibroblast (CAF1 and CAF2). (D) aCGH/SNP array platform and number of copy number aberrations (CNAs) and somatic CNAs (SCNAs, CAF-NAF) identified in each CAF sample. Note the absence of SCNAs in the CAF samples after subtracting the CNAs present in the matched (NAF) normal pair.