Single Nucleotide Polymorphism Array Analysis of Uveal Melanomas Reveals That Amplification of CNKSR3 Is Correlated With Improved Patient Survival
2013; Elsevier BV; Volume: 182; Issue: 3 Linguagem: Inglês
10.1016/j.ajpath.2012.11.036
ISSN1525-2191
AutoresSarah L. Lake, Bertil Damato, Helen Kalirai, Andrew Dodson, Azzam Taktak, Bryony H. Lloyd, Sarah E. Coupland,
Tópico(s)Ocular Disorders and Treatments
ResumoMetastatic death from uveal melanoma occurs almost exclusively with tumors showing monosomy of chromosome 3. However, approximately 5% of patients with a disomy 3 uveal melanoma develop metastases, and a further 5% of monosomy 3 uveal melanoma patients exhibit disease-free survival for >5 years. In the present study, whole-genome microarrays were used to interrogate four clinically well-defined subgroups of uveal melanoma: i) disomy 3 uveal melanoma with long-term survival; ii) metastasizing monosomy 3 uveal melanoma; iii) metastasizing disomy 3 uveal melanoma; and iv) monosomy 3 uveal melanoma with long-term survival. Cox regression and Kaplan–Meier survival analysis identified that amplification of the CNKSR3 gene (log-rank, P = 0.022) with an associated increase in its protein expression (log-rank, P = 0.011) correlated with longer patient survival. Although little is known about CNKSR3, the correlation of protein expression with increased survival suggests a biological function in uveal melanoma, possibly working to limit metastatic progression of monosomy 3 uveal melanoma cells. Metastatic death from uveal melanoma occurs almost exclusively with tumors showing monosomy of chromosome 3. However, approximately 5% of patients with a disomy 3 uveal melanoma develop metastases, and a further 5% of monosomy 3 uveal melanoma patients exhibit disease-free survival for >5 years. In the present study, whole-genome microarrays were used to interrogate four clinically well-defined subgroups of uveal melanoma: i) disomy 3 uveal melanoma with long-term survival; ii) metastasizing monosomy 3 uveal melanoma; iii) metastasizing disomy 3 uveal melanoma; and iv) monosomy 3 uveal melanoma with long-term survival. Cox regression and Kaplan–Meier survival analysis identified that amplification of the CNKSR3 gene (log-rank, P = 0.022) with an associated increase in its protein expression (log-rank, P = 0.011) correlated with longer patient survival. Although little is known about CNKSR3, the correlation of protein expression with increased survival suggests a biological function in uveal melanoma, possibly working to limit metastatic progression of monosomy 3 uveal melanoma cells. Almost 50% of patients with uveal melanoma develop fatal metastases, despite successful ablation of the primary, ocular tumor.1Damato B. Does ocular treatment of uveal melanoma influence survival?.Br J Cancer. 2010; 103: 285-290Crossref PubMed Scopus (88) Google Scholar Metastatic disease usually involves the liver, with mortality of 92% at 2 years.2Rietschel P. Panageas K.S. Hanlon C. Patel A. Abramson D.H. Chapman P.B. 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Mutations in GNA11 in uveal melanoma.N Engl J Med. 2010; 363: 2191-2199Crossref PubMed Scopus (1111) Google Scholar It has been proposed that aberrations of LZTS1, ASAP1 (previously known as DDEF1), and NOTCH signaling play a role in uveal melanoma metastasis; however, to date, the most convincing metastasis-regulatory gene in uveal melanoma is BAP1.18Asnaghi L. Ebrahimi K.B. Schreck K.C. Bar E.E. Coonfield M.L. Bell W.R. Handa J. Merbs S.L. Harbour J.W. Eberhart C.G. Notch signaling promotes growth and invasion in uveal melanoma.Clin Cancer Res. 2012; 18: 654-665Crossref PubMed Scopus (58) Google Scholar, 19Ehlers J.P. Worley L. Onken M.D. Harbour J.W. DDEF1 is located in an amplified region of chromosome 8q and is overexpressed in uveal melanoma.Clin Cancer Res. 2005; 11: 3609-3613Crossref PubMed Scopus (113) Google Scholar, 20Harbour J.W. Onken M.D. Roberson E.D. Duan S. Cao L. Worley L.A. Council M.L. Matatall K.A. Helms C. Bowcock A.M. 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Genetic and structural variation in the gastric cancer kinome revealed through targeted deep sequencing.Cancer Res. 2011; 71: 29-39Crossref PubMed Scopus (73) Google Scholar Such data suggest that mutations other than those identified in uveal melanoma to date may play a key role in development of the disease and in the metastatic process. In the present study, we analyzed 58 primary uveal melanoma specimens with well-defined clinical, histomorphological, and chromosomal features, using whole-genome single-nucleotide polymorphism microarrays (aSNP). Our cohort consisted of four distinct genetic subgroups: i) disomy 3 uveal melanoma with long-term survival and no metastasis (DS); ii) monosomy 3 uveal melanoma that had metastasized (MM); iii) atypical disomy 3 uveal melanoma that had unexpectedly metastasized within a short follow-up period (DM); and iv) atypical monosomy 3 uveal melanoma from patients with an exceptionally long disease-free survival (MS). Based on our previous research, we hypothesized that the underlying pathological alterations of metastatic disomy 3 uveal melanoma are similar to those of monosomy 3 uveal melanoma. That is, instead of complete loss of chromosome 3, deletion of key metastasis-regulatory genes are proposed to occur in these particular uveal melanomas.27Lake S.L. Coupland S.E. Taktak A.F. Damato B.E. Whole-genome microarray detects deletions and loss of heterozygosity of chromosome 3 occurring exclusively in metastasizing uveal melanoma.Invest Ophthalmol Vis Sci. 2010; 51: 4884-4891Crossref PubMed Scopus (48) Google Scholar Conversely, in the monosomy 3 uveal melanoma from patients with long-term disease-free survival, we hypothesize that additional genetic changes are present that result in a slowing down or deceleration of the metastatic process. In analyzing the genomes of these four subgroups of patients, we aimed to identify deletion or amplification of genes that may be influencing uveal melanoma metastasis. The effect of genetic changes on protein expression was also determined by immunohistochemistry in both primary uveal melanoma samples and liver metastases. We recruited 58 patients who were diagnosed both clinically and histologically with primary uveal melanoma between 1999 and 2007. As part of routine clinical practice at the Royal Liverpool University Hospital, the copy numbers of chromosomes 3 and 8q were determined. Between 1999 and 2007, this was done by fluorescence in situ hybridization (FISH), as described by Damato et al.5Damato B. Duke C. Coupland S.E. Hiscott P. Smith P.A. Campbell I. Douglas A. Howard P. Cytogenetics of uveal melanoma: a 7-year clinical experience.Ophthalmology. 2007; 114: 1925-1931Abstract Full Text Full Text PDF PubMed Scopus (254) Google Scholar A related study, published in 2010, used multiplex ligation-dependent probe amplification to reassess the chromosome 3 copy number of fatal disomy 3 uveal melanomas.27Lake S.L. Coupland S.E. Taktak A.F. Damato B.E. Whole-genome microarray detects deletions and loss of heterozygosity of chromosome 3 occurring exclusively in metastasizing uveal melanoma.Invest Ophthalmol Vis Sci. 2010; 51: 4884-4891Crossref PubMed Scopus (48) Google Scholar All DM uveal melanomas analyzed in the present study were found to have disomy of chromosome 3 by multiplex ligation-dependent probe amplification and by aSNP. (Disomy is the normal copy number; monosomy indicates complete loss of one chromosome copy.) The study received ethical approval from the North West Research Ethics Committee (North West REC number: 10/H1015/56). All patients gave informed consent to participate in the study. Of the 58 patients, 31 were known to have developed clinically detectable metastases within 7 years of diagnosis: of these, 15 patients had disomy 3 tumors (subgroup DM), and 16 had monosomy 3 tumors (subgroup MM). The remaining 27 patients were not known to have developed metastases at the close of the study in January 2012, amounting to a minimum of 6.5 years (median, 9.3 years) since the diagnosis of uveal melanoma. Of these patients without clinically evident metastases, 10 had disomy 3 tumors (subgroup DS) and 17 had monosomy 3 tumors (subgroup MS). Samples of uveal melanoma hepatic metastases (confirmed by histology) from 15 patients were donated by Ian Cree (University of Warwick). All these patients had consented to participate in a previous research study. Tissue samples were taken at autopsy, as described by Borthwick et al.28Borthwick N.J. Thombs J. Polak M. Gabriel F.G. Hungerford J.L. Damato B. Rennie I.G. Jager M.J. Cree I.A. The biology of micrometastases from uveal melanoma.J Clin Pathol. 2011; 64: 666-671Crossref PubMed Scopus (21) Google Scholar Detailed patient information, such as age and sex, was not available for this group of patients, and paired primary and metastatic lesions were not available for this analysis. H&E-stained slides of uveal melanoma were inspected, and areas with >90% tumor cells were microdissected from sections (20 μm thick) of formalin-fixed, paraffin-embedded tissues. DNA was extracted after tissue digestion and cell lysis, using silica-membrane columns (DNeasy blood and tissue kit; Qiagen, Valencia, CA; Crawley, UK) according to the manufacturer’s protocol for use with formalin-fixed, paraffin-embedded samples. The protocol was modified to include tissue digestion for 36 hours, undertaken at 37°C, with a further 100 ng (∼32 mAU) of proteinase K (Qiagen) being added after 12 and 24 hours, and with two AW1 buffer washes. DNA was further purified using GenElute linear polyacrylamide neutral carrier (Sigma-Aldrich, St. Louis, MO), according to the manufacturer’s guidelines, with elution in 30 μL nuclease-free water (Qiagen). DNA concentration was quantified by fluorometry (Invitrogen Qubit fluorometer and broad-range DNA quantification assay; Life Technologies, Carlsbad, CA; Glasgow, UK). DNA (500 ng) was analyzed using an SNP version 6.0 whole-genome microarray with a GeneChip system (Affymetrix, Santa Clara, CA) at the Molecular Biology Core Facility, Paterson Institute for Cancer Research, Manchester, UK. Prehybridization PCR was performed according to the manufacturer’s standard protocols. SNP genotypes and confidence scores were generated by fitting two-dimensional Gaussian functions to the SNP data using a customized expectation-maximization algorithm (Birdseed algorithm version 2.0; Affymetrix). Subsequent data analysis was performed using Partek Genomics Suite software version 6.5 (Partek, St. Louis, MI). In the absence of DNA from matched normal tissues, the 794-sample HapMap baseline was used (Partek). The Partek Copy Number Workflow was used to determine CNAs. Cross-platform normalizations were performed to adjust for local GC content and to remove GC waves (based on the regression model approach of Diskin et al29Diskin S.J. Li M. Hou C. Yang S. Glessner J. Hakonarson H. Bucan M. Maris J.M. Wang K. Adjustment of genomic waves in signal intensities from whole-genome SNP genotyping platforms.Nucleic Acids Res. 2008; 36: e126Crossref PubMed Scopus (252) Google Scholar). The binary logarithm was generated for all data and used in genomic segmentation (P = 0.00001). The association of CNAs with monosomy 3 and the presence of metastases was explored using χ2 analyses. Regions of CNA detected were overlaid with data from the National Center for Biotechnology Information Reference Sequence (RefSeq) collection of genomic DNA, transcript, and protein sequence information (http://www.ncbi.nlm.nih.gov/RefSeq) and data from miRBase release 18 (http://www.mirbase.org). Gene CNAs were analyzed to determine the differences and similarities among all four patient subgroups (DM, DS, MM, and MS) and the differences and similarities between the two most common subgroups (DS and MM). The methodologies used in SNP data analysis are summarized in Figure 1. The GeneGo (St. Joseph, MI) MetaCore Compare Experiments Workflow tool was used to compare data from the patient subgroups by mapping gene CNAs to the ontologies available from the Metacore proprietary, manually curated database, and by determining the intersections of the data generated from each group (P value threshold, ≤0.05). This approach was used to determine common (present in all groups analyzed), similar (present in more than one group analyzed), and unique (present in only one group) genes with CNAs, and to explore the cell signaling networks that aberrant genes are involved in. Protein expression was examined in sections (4 μm thick) cut from tissue microarrays constructed with a Beecher tissue microarrayer (Beecher Instruments, Sun Prairie, WI). Arrays contained triplicate 0.6-mm cores from formalin-fixed, paraffin-embedded tissues of each of the uveal melanoma samples tested by SNP array, or metastatic liver lesions from 15 additional uveal melanoma patients. Using a PT Link (Dako, Carpinteria, CA; Ely, UK) pretreatment module, high-pH (pH 7.0) antigen retrieval was performed at 96°C for 20 minutes. The FLEX reagent system and Autostainer Plus (both from Dako) were used to perform the following steps: endogenous peroxidase blocking, 5 minutes; primary antibody incubation, 30 minutes; addition of either mouse or rabbit linker, 15 minutes; incubation with horseradish peroxidase, 20 minutes; and, last, AEC peroxidase substrate (3-amino-9-ethylcarbazole), 30 minutes. Slides were washed with 1× FLEX wash buffer between each incubation. All reagents were from Dako, with the exception of AEC (Vector Laboratories, Burlingame, CA; Peterborough, UK) and the primary antibodies. Anti-CNKSR3 antibody (mouse polyclonal; Abcam, Cambridge, UK) was used at a concentration of 10 μg/mL; anti-RIPK1 antibody (rabbit polyclonal; Abcam) was used at a concentration of 2.5 μg/mL; anti-proenkephalin antibody (rabbit polyclonal; Novus Biologicals, Littleton, CA; Cambridge, UK) was used at a concentration of 0.5 μg/mL. Counterstaining was performed with Mayer’s hematoxylin and slides were mounted with Aquatex aqueous mounting medium (EMD Millipore, Billerica, MA; Merck Millipore, Nottingham, UK). Tissues known to express the three proteins were included in each run as positive controls; primary antibody was omitted as a negative control. Scoring of tissue microarrays was independently performed by four investigators (S.L.L., H.K., A.R.D., and S.E.C.), using the thresholds described by Jmor et al,30Jmor F. Kalirai H. Taktak A. Damato B. Coupland S.E. HSP-27 protein expression in uveal melanoma: correlation with predicted survival.Acta Ophthalmol. 2010; 90: 534-539Crossref PubMed Scopus (21) Google Scholar to classify both percentage of tumor cells staining positively and (for cytoplasmic staining) intensity of staining. For proenkephalin (PENK), staining was seen in both the nucleus and the cytoplasm of cells, but at differing intensities. Consequently, individual scores for nuclear and cytoplasmic staining were generated. Cases with less than two scorable uveal melanoma cores were excluded from further analysis. Scoring between observers was consistent in the majority of cases; when discrepancies arose, cores were re-evaluated by the panel to obtain consensus. In formalin-fixed, paraffin-embedded sections (4 μm thick) of five uveal melanomas, dual immunofluorescence analysis was performed with 2.5 μg/mL anti-RIPK1 and either 6 mg/L anti-MITF (Dako) or 1 mg/L anti-MelA (Dako) antibodies. Methods were as described by Kalirai et al.31Kalirai H. Damato B.E. Coupland S.E. Uveal melanoma cell lines contain stem-like cells that self-renew, produce differentiated progeny, and survive chemotherapy.Invest Ophthalmol Vis Sci. 2011; 52: 8458-8466Crossref PubMed Scopus (45) Google Scholar For statistical analysis, Cox backward logistic regression, Kaplan–Meier survival curves, and χ2 testing were performed using IBM SPSS Statistics software version 19 (IBM, Chicago, IL), with the advice of A.F.G.T. The primary uveal melanoma patients (20 male, 38 female) included in the study were treated for their primary uveal melanoma by enucleation (n = 52) or local resection (n = 6). None of the patients had received any other therapy before surgery. By the close of the study (January 2012), three patients had died of causes other than metastatic uveal melanoma: one patient in the DS subgroup and two patients in the MS subgroup. Three other patients from the MS subgroup had died of metastatic uveal melanoma (after 8.8 years, 9.87 years, and 10.58 years). Clinical and histological features in each patient subgroup are summarized in Table 1. Importantly, the largest basal diameter of the uveal melanoma, as detected with ultrasonography by a single observer (B.E.D.), was not statistically significantly different between the MS and MM subgroups (χ2, P = 0.375 and P = 0.340, respectively).Table 1Summary of Clinical and Histomorphological Data for Uveal Melanoma Patients in Four SubgroupsPatient subgroup (sample size)Median age (years)∗Values in parenthesis indicate the range.Sex, M/F (no.)LUD (mm)∗Values in parenthesis indicate the range.LUH (mm)∗Values in parenthesis indicate the range.Epithelioid cells present (no.)Closed loops present (no.)Mitoses (no./HPF)Ciliary body involvement (no.)Extraocular extension (no.)Metastasis, (no.)Survival time (years)∗Values in parenthesis indicate the range.DS (n = 10)50.84 (35.30–79.22)2/814.6 (13.0–19.5)9.0 (6.0–13.0)4 no/6 yes4 no/6 yes210 no/0 yes10 no/0 yes10 no/0 yes11.19 (6.51–12.42)DM (n = 15)63.09 (31.00–76.64)6/917.2 (16.1–20.5)9.0 (5.0–15.7)2 no/13 yes7 no/8 yes8 (2–18)9 no/6 yes12 no/2 yes†One unknown.0 no/15 yes2.69 (0.52–5.87)MM (n = 16)67.59 (41.8–88.56)5/1118.1 (10.8–21.1)9.5 (4.0–14.0)3 no/13 yes1 no/15 yes6.5 (2–15)6 no/10 yes15 no/1 yes0 no/16 yes3.17 (1.50–6.94)MS (n = 17)65.42 (41.83–83.69)7/1015.7 (13.0–20.9)10.0 (4.0–15.0)7 no/10 yes11 no/6 yes5 (1–16)3 no/14 yes17 no/0 yes14 no/3 yes8.84 (6.61–11.74)F, female; M, male; DM, atypical disomy 3 UM with metastasis; DS, disomy 3 UM with long-term survival; HPF, high-power field; LUD, largest ultrasound tumor diameter; LUH, largest ultrasound tumor height; MM, monosomy 3 UM with metastasis; MS, atypical monosomy 3 UM with long-term survival.∗ Values in parenthesis indicate the range.† One unknown. Open table in a new tab F, female; M, male; DM, atypical disomy 3 UM with metastasis; DS, disomy 3 UM with long-term survival; HPF, high-power field; LUD, largest ultrasound tumor diameter; LUH, largest ultrasound tumor height; MM, monosomy 3 UM with metastasis; MS, atypical monosomy 3 UM with long-term survival. Agarose gel electrophoresis indicated DNA fragment sizes ranging from 100 to 1500 bp (data not shown). Quality control call rates from the SNP version 6.0 whole-genome microarray, after analysis using the Birdseed algorithm, ranged from 84.89 to 91.77 (median, 90.13). No association was found between the age of the specimen and any CNA detected (P = 0.533, χ2 analysis). Three hundred twelve genes and miRNAs showed significant differences (χ2 test, P < 0.050) in the frequency of aberrations among the four patient subgroups (DS, DM, MM, and MS). The 312 genes and miRNAs, along with the CNAs detected and the average copy number, are listed in Supplemental Table S1. Gene ontology analysis and comparison of the data intersections for each of the four subgroups with MetaCore (http://www.ncbi.nlm.nih.gov/geo; accession number GSE37259) identified those genes that were present in i) all groups analyzed (common genes), ii) more than one group analyzed (similar genes), or iii) in only one group (unique genes). Nine genes were identified as having a common CNA in all patients who developed, or were likely to develop, metastatic disease [ie, the monosomy 3 patients (MM and MS) and the disomy 3 metastasizing patients (DM)]. An additional 15 genes were also aberrant with high frequency in at least one of these three subgroups (DM, MM, and MS). The genes from both analyses are listed in Table 2.Table 2Genes With Copy Number Alterations in the Metastasizing UM Identified from a Comparison of All Four Patient SubgroupsGeneCytobandProtein description∗Protein characterization is according to GeneCards, Weizmann Institute of Science, Rehovot, Israel (http://www.genecards.org).AberrationP value†Log-rank P value for Cox regression.Common to MM, MS and DM ERC23p14.3Regulation of neurotransmitter releaseDelNA PLXND13q22.1Plexin D1DelNA ZBTB383q23Transcriptional activatorDel0.006 MB21D23q29UnknownAmpNA ETS111q23.3transcription factorAmp0.045 MID1IP1Xp11.4Regulation of lipogenesis in the liver, by homology, microtubule stabilizationAmpNA DMDXp21.2Part of the dystrophin-glycoprotein complexDelNA AMMECR1Xq22.3UnknownDelNA STAG2Xq25Component of the cohesin complexDelNAFrequent in MM, MS or DM CNKSR36q25.2CNKSR family member 3, possible sodium transporterAmp0.020 CSMD18p23.3Function in non-tumor cells unknown, potential role in suppression of squamous cell carcinomaAmp0.037 ARHGEF108p23.3Rho guanine nucleotide exchange factorAmpNA CLN88p23.3TLC-domain family transmembrane proteinAmp0.004 KBTBD118p23.3Kelch repeat and BTB domain-containing protein 11, function unknownAmpNA MIR5968p23.3miRNA 596AmpNA MYOM28p23.3Vertebrate myofibrillar M band componentAmpNA B4GALNT312p13.33β-1,4-N-acetyl-galactosaminyl transferaseAmp0.066 CCDC7712p13.33Coiled-coil domain-containing protein 77, function unknownAmpNA IQSEC312p13.33Guanine nucleotide exchange factor for ARF1AmpNA KDM5A12p13.33Demethylase for ‘Lys 4’ of histome H3AmpNA LOC57453812p13.33Uncategorized RNAAmpNA NINJ212p13.33Homophilic cell adhesion molecule that promotes axonal growthAmpNA SLC6A1212p13.33Sodium- and chloride-dependent betaine and gamma-aminobutyric acid transporterAmpNA WNK112p13.33Serine/threonine kinaseAmpNAAmp, amplification; Del, deletion; NA, not applicable.∗ Protein characterization is according to GeneCards, Weizmann Institute of Science, Rehovot, Israel (http://www.genecards.org).† Log-rank P value for Cox regression. Open table in a new tab Amp, amplification; Del, deletion; NA, not applicable. Cox regression (backward log-rank) analysis was performed to determine whether any of the 24 commonly aberrant genes (Table 2) were associated with a difference in patient survival. ETS1, ZBTB38, B4GALNT3, CSDM1, CLNN8, and CNKSR3 all remained in the model. However, B4GALNT3 failed to reach statistical significance (P = 0.066). (The log-rank P values for each gene are listed in Table 2.) The association of these CNAs with patient survival was further explored for ETS1, ZBTB38, CSDM1, CLNN8, and CNKSR3 by Kaplan–Meier analysis. A statistically significant difference in survival was seen only for CNKSR3 (log-rank, P = 0.022). Patients with amplification of CNKSR3 had longer survival times than those having either a deletion or no copy number change (Figure 2). By combining CNA calls and detection of loss of heterozygosity, isodisomy was investigated using the SNP 6.0 microarray data; no tumors sho
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