DNA methylation profile of 28 potential marker loci in malignant mesothelioma

Abstract

Patients with malignant mesothelioma (MM), an aggressive cancer associated with asbestos exposure, usually present clinically with advanced disease and this greatly reduces the likelihood of curative treatment. MM is difficult to diagnose without invasive techniques; the development of non-invasively detectable molecular markers would therefore be highly beneficial. DNA methylation changes in cancer cells provide powerful markers that are potentially detectable non-invasively in DNA shed into bodily fluids. Here we examined the methylation status of 28 loci in 52 MM tumors to investigate their potential as molecular markers for MM. To exclude candidate MM markers that might be positive in biopsies/pleural fluid due to contaminating surrounding non-tumor lung tissue/DNA, we also examined the methylation of these markers in lung samples (age- or environmentally induced hypermethylation is frequently observed in non-cancerous lung). Statistically significantly increased methylation in MM versus non-tumor lung samples was found for estrogen receptor 1 (ESR1; p = 0.0002), solute carrier family 6 member 20 (SLC6A20; p = 0.0022) and spleen tyrosine kinase (SYK; p=0.0003). Examination of associations between methylation levels of the 28 loci and clinical parameters suggest associations of the methylation status of metallothionein genes with gender, histology, asbestos exposure, and lymph node involvement, and the methylation status of leucine zipper tumor suppressor 1 (LZTS1) and SLC6A20 with survival.

Figure 1

Graphical representation of methylation of 28 loci in MM cases. Percentage of MM (black) or non-tumor lung (light gray) samples showing methylation is indicated in (A). Median PMR value of the samples showing methylation in MM (black) or non-tumor lung (white) is indicated in (B). Because the spread in PMR values was large, log-transformed values were plotted in (B). Stars indicate statistically significant differences in methylation between MM and non-tumor lung samples, using PMR as a continuous variable and taking into account a multiple comparison correction threshold (see Table 2 for values).

Figure 2

Comparison of distribution of PMR values for ESR1, SLC6A20 and SYK in MM (triangles) and non-tumor lung (open circles). The median PMR of methylation positive samples is indicated by the dashed line. Two MM samples (indicated with an asterisk) showed very high PMR values for SLC6A20 as indicated by the discontinuous scale.

Figure 3

Two-dimensional hierarchical clustering analysis of methylation data for APC, SYK and SLC6A20. MM and non-tumor lung samples are indicated by closed black and open gray circles, respectively. Methylation levels range from undetectable (light gray) to most elevated (black).

Figure 4

Kaplan Meier analyses of survival vs. methylation for LZTS1 (left) and SLC6A20 (right) loci. LZTS1 PMR values were dichotomized at 130. P=0.046 without and 0.065 with age adjustment respectively, and the relative hazard ratio for PMR≥130 was 1.93 (0.94–3.97). SLC6A20 subjects were divided into with and without methylation; p=0.022 without and 0.023 with age adjustment respectively, and the relative hazard ratio for absence of methylation was 2.14 (1.05–4.37).