Distinct gene expression profiles in ovarian cancer linked to Lynch syndrome

We collected paraffin-embedded tumor tissue from Swedish and Danish Lynch syndrome mutation carriers and matched these tumors to sporadic ovarian cancers to correct for differences related to histopathology [15]. Histopathologic subtype and grade were determined according to Silverberg and to the WHO guidelines [16‐18]. Hematoxylin & Eosin stained slides were reviewed by a gynecologic pathologist (AM) to verify histopathologic subtype and tumor grade. In total, 24 Lynch syndrome tumors from individuals with germline mutations in MLH1 (n = 1), MSH2 (n = 13) or MSH6 (n = 10) and an associated loss of immunohistochemical MMR protein expression were included along with 24 sporadic ovarian cancers in which heredity had been excluded based on family history, normal MMR protein staining and normal results from BRCA1 and BRCA2 mutation analysis [1, 3, 19]. Clinical characteristics are outlined in Table 1 and detailed data are provided in online resource 1. Tumor tissue for immunohistochemical assessment of target genes was available from 46 tumors. Ethical approval for the study was granted from the ethics committee in Region Hovedstaden, Denmark and from the Lund University ethics committee, Sweden.

3–5 Tissue 10-μm sections were selected from non-necrotic tumor areas with >70 % tumor cell content. RNA was extracted using the High Pure RNA Paraffin Kit (Roche, Castle Hill, Australia) and RNA concentrations were determined using a NanoDrop Spectrophotometer (NanoDrop Technologies, Wilmington, DE) requiring 300 ng of RNA with 260/280 ratios >1.8. Gene expression analyses were performed at the SCIBLU Genomics Centre, Lund University, Sweden. The cDNA mediated Annealing, Selection, extension and Ligation (WG-DASL) assay (Illumina Inc, San Diego, CA) containing 24,526 probes, which represent 18,626 unique genes, was used for whole genome expression analysis. The samples were randomized on the chips and were profiled following the manufacturer’s instructions. BeadChips were then scanned on a BeadArray™ Reader using BeadScan software (v4.2), during which fluorescence intensities were read and images extracted.

A raw average signal intensity >250 and >8,000 detected genes was required for further analysis of the samples. All 48 matched tumors met these criteria. The expression data were uploaded in the GenomeStudio software (Illumina Inc), quantile normalized and a presence filter of 80 % was applied to the probes across all samples with a detection p value of <0.01, leaving 12,897 probes for further analysis. The data were imported into MeV 4.6.02 software [20] and were log2 transformed and mean centered across assays. Unsupervised clustering using complete linkage hierarchical cluster analysis and Pearson correlation as similarity metric was performed. Two-class unpaired significance analysis of microarrays (SAM), including a permutation test using 100 permutations, was used to identify differentially expressed genes between the Lynch syndrome-associated and sporadic tumors at a false discovery rate (FDR) <0.01 [21]. Gene ontology analyses were generated through the use of Ingenuity Pathway Analysis (IPA; www.​ingenuity.​com). The data are available in NCBI’s Gene Expression Omnibus [22] through GEO Series accession number GSE37394. Technical reproducibility was granted through inclusion of duplicate samples, which demonstrated a mean correlation of 0.98 (range 0.90–0.99) and a mean r² value of 0.96 (range 0.81–0.99). In order to ensure data robustness, data analysis was independently performed using alternative parameters and stricter criteria, i.e. cubic spline normalization and RefSeq features present in 70 % of the samples (p = 0.01). This approach left 3,380 probes that were further analyzed as described above (including cluster analyses, permutation test and leave-one-out test, followed by gene ontology analyses).

The Lynch syndrome gene signature was validated using an independent, publically available data set consisting of 2,844 genes, mainly based on high-grade serous and endometrioid ovarian cancers [14]. The data were imported into MeV v4, log2 transformed and the probes were mean centred across assays. Unsupervised hierarchical clustering was performed as described above.

Immunohistochemical staining for key target genes was performed on fresh 3-µm sections from formalin-fixed, paraffin-embedded tumor tissue and the slides were mounted on ChemMate Capillary Gap Microscope Slides (DAKO A/S, Glostrup, Denmark). The sections were pretreated in PT Link (mTOR, PTEN) and Proteinase K (EGFR) according to the manufacturer’s instructions and stained in an automated immunostainer (TechMate 500 Plus, DAKO) with application of the DAKO EnVision™ Systems (DAKO) for visualization. The antibodies used included phosphorylated mTOR (p-mTOR, clone 49F, diluted 1:80, Cell Signaling Technology, Danvers, MA), PTEN (clone 6H2.1, diluted 1:100, DAKO) and EGFR (clone E30, diluted 1:25, DAKO). Evaluations were blinded to the hereditary status as well as to gene expression data and were performed independently by KB and JMJ. The p-mTOR stains were dichotomized as positive/negative, with any cytoplasmic p-mTOR staining considered positive. PTEN was evaluated as negative (no staining or weaker staining in the tumor cells compared to the surrounding tissues) or positive (equal or stronger cytoplasmic staining in tumor cells compared to surrounding tissues). EGFR staining was evaluated according to staining intensity (no, weak, moderate, or strong staining) and the percentage of stained tumor cells; tumors with >25 % of the cells moderately or intensely stained for EGFR were classified as positive [23‐25]. MMR protein staining is outlined in Ketabi et al. [19].