Molecular profiling of cutaneous squamous cell carcinomas and actinic keratoses from organ transplant recipients

Abstract

Background: The risk of developing cutaneous squamous cell carcinoma (SCC) is markedly increased in organ transplant recipients (OTRs) compared to the normal population. Next to sun exposure, the immunosuppressive regimen is an important risk factor for the development of SCC in OTRs. Various gene mutations (e.g. TP53) and genetic alterations (e.g. loss of CDKN2A, amplification of RAS) have been found in SCCs. The aim of this genome-wide study was to identify pathways and genomic alterations that are consistently involved in the formation of SCCs and their precursor lesions, actinic keratoses (AKs).

Methods: To perform the analysis in an isogenic background, RNA and DNA were isolated from SCC, AK and normal (unexposed) epidermis (NS) from each of 13 OTRs. Samples were subjected to genome-wide expression analysis and genome SNP analysis using Illumina's HumanWG-6 BeadChips and Infinium II HumanHap550 Genotyping BeadChips, respectively. mRNA expression results were verified by quantitative PCR.

Results: Hierarchical cluster analysis of mRNA expression profiles showed SCC, AK and NS samples to separate into three distinct groups. Several thousand genes were differentially expressed between epidermis, AK and SCC; most upregulated in SCCs were hyperproliferation related genes and stress markers, such as keratin 6 (KRT6), KRT16 and KRT17. Matching to oncogenic pathways revealed activation of downstream targets of RAS and cMYC in SCCs and of NFκB and TNF already in AKs. In contrast to what has been reported previously, genome-wide SNP analysis showed very few copy number variations in AKs and SCCs, and these variations had no apparent relationship with observed changes in mRNA expression profiles.

Conclusion: Vast differences in gene expression profiles exist between SCC, AK and NS from immunosuppressed OTRs. Moreover, several pathways activated in SCCs were already activated in AKs, confirming the assumption that AKs are the precursor lesions of SCCs. Since the drastic changes in gene expression appeared unlinked to specific genomic gains or losses, the causal events driving SCC development require further investigation. Other molecular mechanisms, such as DNA methylation or miRNA alterations, may affect gene expression in SCCs of OTRs. Further study is required to identify the mechanisms of early activation of NFκB and TNF, and to establish whether these pathways offer a feasible target for preventive intervention among OTRs.

Figure 1

Graphical overview of chromosomal aberrations in SCCs and AKs. Idiograms summarizing chromosomal aberrations in SCCs (A) and AKs (B) compared to the patient matched normal control. LOH events are shown to the left of the chromosomes in either red (physical loss) or blue (copy-neutral LOH (cnLOH)). Gains are indicated on the right of the chromosomes in green. Dotted lines represent aberrations that were not present in all tumor cells of a sample.

Figure 2

Cluster analysis. (A) Dendogram of unsupervised hierarchical cluster analysis of all samples. Clustering was based on 10,100 probes for which the average expression among all samples showed a standard deviation ≥ 0.15. Samples are labeled by sample group (NS/AK/SCC) and patient number (P-#). (B) Scatter plot of the first two components from PCA based on 6,104 probes for which the average expression among all samples showed a standard deviation/mean ≥ 0.1. Labels indicate the position for each sample (NS/AK/SCC) of a certain patient (P-#).

Figure 3

Venn diagrams of differentially expressed probes (DEPs) from different comparisons within the three sample groups; NS, AK and SCC. The FDR was set at <1%. (A) Differentially expressed probes with FDR < 1%. (B) DEPs with log₂FC > 0.5 and FDR < 1%. (C) DEPs with log₂FC > 1.0 and FDR < 1%.

Figure 4

Results Parametric geneset enrichment analysis (PGSEA). Gene expression profiles derived from AK (n = 14) and SCC (n = 15) samples were compared with gene expression profiles derived from normal skin (NS, n = 13) samples and analyzed using PGSEA for the gene lists that contain genes responsive to oncogenes or for indicated pathways. The genes that show increased expression to NS for each pathway are indicated with ‘up’. List of genes that show decreased expression relative to control cells for each pathway are indicated with ‘down’ [28]. The resulting t-statistic for each gene list was plotted (−10 < t < 10), p < 0.005); red squares represent significant number of genes in the list with increased expression in tumor samples (AK or SCC) relative to NS; blue squares represent a significant number of genes in each list with decreased expression.

Figure 5

QPCR and genome-wide expression analysis (GWEA). (A) Histograms showing the expression level of CCL27 in NS, AK and SCC samples measured by QPCR (left) and GWEA (right). (B) Histograms showing the expression level of KRT17 in NS, AK and SCC samples measured by QPCR (left) and GWEA (right). For QPCR the normalized relative expression level represents the expression of the gene of interest normalized to those of four reference genes. For the GWEA the normalized expression level represents the RSN normalized, VST transformed expression of the gene of interest.