Genomic deregulation during metastasis of renal cell carcinoma implements a myofibroblast-like program of gene expression

Abstract

Clear cell renal cell carcinoma (RCC) is the most common and invasive adult kidney cancer. The genetic and biological mechanisms that drive metastatic spread of RCC remain largely unknown. We have investigated the molecular signatures and underlying genomic aberrations associated with RCC metastasis, using an approach that combines a human xenograft model; expression profiling of RNA, DNA, and microRNA (miRNA); functional verification; and clinical validation. We show that increased metastatic activity is associated with acquisition of a myofibroblast-like signature in both tumor cell lines and in metastatic tumor biopsies. Our results also show that the mesenchymal trait did not provide an invasive advantage to the metastatic tumor cells. We further show that some of the constituents of the mesenchymal signature, including the expression of the well-characterized myofibroblastic marker S100A4, are functionally relevant. Epigenetic silencing and miRNA-induced expression changes accounted for the change in expression of a significant number of genes, including S100A4, in the myofibroblastic signature; however, DNA copy number variation did not affect the same set of genes. These findings provide evidence that widespread genetic and epigenetic alterations can lead directly to global deregulation of gene expression and contribute to the development or progression of RCC metastasis culminating in a highly malignant myofibroblast-like cell.

Figure 1. A xenograft mouse model for RCC metastasis

NOD/SCID mice were injected with 10⁶ tumor cells as indicated in the kidney subcapsule. (A Primary tumor (B) Lung metastasis (C) H&E staining. Black arrow indicates thrombi inside the blood vessels. Blue arrow indicates vascular thrombus invading the vessel wall.

Figure 2. S100A4 controls metastatic activity

(A) LM2 cells were infected with lentiviruses encoding the indicated shRNAs. Equal amounts of total proteins were subjected to immunoblotting with antibodies to the indicated antigens. shSC, non-targeting shRNA; shS100A4, shRNAs targeting S100A4. (B) SN12C cells were infected with retroviruses bearing a vector encoding S100A4 or an empty vector. Total cellular lysis was subjected to immunoblotting using antibodies against the specified proteins. (A, B graphs) Groups of 5 mice were injected in the kidney subcapsule with the indicated cell populations and numbers of lung metastatic nodules were scored after 2 months.

Figure 3. DNA copy variation

(A) Segmented copy numbers for each cell line were inferred with the GLAD (gain and loss analysis of DNA) algorithm and normalized to a median of two copies. Vertical dashed red lines represent the breakpoints detected with GLAD and the assigned statuses are indicated by a color code: green for loss, yellow for normal and red for gain. (B) Chromosomal mapping of regions of copy number alteration. Regions appearing increased in copy number are shown in red, and those decreased in copy number are shown in blue.

Figure 4. Promoter methylation related gene expression changes

(A) Venn diagram of genes predicted to be hypermethylated in SN12C and spontaneously demethylated in LM2 cells. (B) Venn analysis of genes predicted to be hypomethylated in SN12C and spontaneously hypermethylated in LM2 cells. (C) Genes predicted to be hypermethylated in LM2 cells and showing loss of copy number. (D) Quantitation of DNA methylation in CpG dinucleotides of 4 genes from panel A by EpiTYPER analysis. CpG specific methylation is showed in a heat map.

Figure 5

Identification of miRNAs altered in RCC cell derivatives. Clustering of normalized miRNA expression levels in SN12C and LM cell lines.