Global gene expression analysis of reactive stroma in prostate cancer

Abstract

Purpose: Marked reactive stroma formation, designated as grade 3 reactive stroma, is associated with poor outcome in clinically localized prostate cancer. To understand the biological processes and signaling mechanisms underlying the formation of such reactive stroma, we carried out microarray gene expression analysis of laser-captured reactive stroma and matched normal stroma.

Experimental design: Seventeen cases of reactive stroma grade 3 cancer were used to laser-capture tumor and normal stroma. Expression analysis was carried out using Agilent 44K arrays. Up-regulation of selected genes was confirmed by quantitative reverse transcription-PCR. Expression data was analyzed to identify significantly up- and down-regulated genes, and gene ontology analysis was used to define pathways altered in reactive stroma.

Results: A total of 544 unique genes were significantly higher in the reactive stroma and 606 unique genes were lower. Gene ontology analysis revealed significant alterations in a number of novel processes in prostate cancer reactive stroma, including neurogenesis, axonogenesis, and the DNA damage/repair pathways, as well as evidence of increases in stem cells in prostate cancer reactive stroma.

Conclusions: Formation of reactive stroma in prostate cancer is a dynamic process characterized by significant alterations in growth factor and signal transduction pathways and formation of new structures, including nerves and axons.

Figure 1. Validation of RNA amplification and laser capture

(A) Genes with no greater than 1.5-fold variation between amplified and unamplified RNA; 88.7% of genes met this criteria (left); genes with greater than 2-fold variation between amplified and unamplified RNAs (right), which constitute only 3% of the total. (B) Quantitative RT-PCR of PSA expression in laser captured normal and tumor stroma and prostate cancer tissue. PSA content of normal and tumor stroma was not significantly different and both were 1600-fold less than undissected prostate cancer tissue. Mean +/− of triplicate determinations is shown. PSA copy number was normalized to HPRT copy number relative to the Universal Reference RNA.

Figure 2. A gene transcription signature of Grade 3 reactive stroma in prostate cancer

(A) Heat map representation of 1675 gene probes (representing 1141 unique named genes) differentially expressed (P<0.01) in reactive prostate stroma compared to normal stroma (rows: genes, columns: profiled samples, yellow: high expression). (B) Quantitative RT-PCR validation of selected genes from the list of 1141 (P<0.05 for each, t-test). Mean +/− standard deviation of triplicate determinations is shown. HPRT was used for copy number normalization.

Figure 3. Interaction network analysis of reactive stroma genes

(A) Number of known human protein-protein interactions (from HPRD) involving the 1141 unique genes differentially expressed in reactive prostate stroma, as compared to that expected from a random gene set of 1141 (with +/− 1 SD, based on 1000 simulations). (B) Network representation of the entire set of 292 HPRD protein-protein interactions involving the 1141 named genes differentially expressed in reactive prostate stroma. (C) Subnetwork of HPRD protein-protein interactions from part (B). Nodes represent genes: yellow nodes, genes over-expressed in reactive stroma; blue nodes, genes under-expressed in reactive stroma. A line between two nodes signifies that the corresponding protein products of the genes can physically interact (according to the literature). Colored edges (other than gray) represent a common GO term annotation shared by both of the connected genes. Active hubs, or genes connected to a significant number (P < 0.01, one-sided Fisher’s exact test) of the other genes in the network, appear enlarged over the other nodes.

Figure 4. Expression patterns in breast cancer reactive stroma for genes over-expressed in prostate cancer reactive stroma

Referring to the profiling dataset from Finak et al.(15) of normal breast stroma (n=6) and breast cancer reactive stroma (n=52), the 776 transcript probes represented in that dataset and showing over-expression in Grade 3 prostate cancer reactive stroma (Figure 2A) were examined. Top panel, gene expression heat map (genes ordered from high to low expression in reactive stroma). Bottom panel, average expression of the (mean centroid-centered) genes for the corresponding sample profiles. Unique genes (those with a common name) showing over-expression in both prostate and breast reactive stroma in indicated region (P<0.01 each dataset) are listed.