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Genome-wide characterization of circulating tumor cells identifies novel prognostic genomic alterations in systemic melanoma metastasis.

Successful treatment of melanoma requires understanding of the metastatic process and identification of patients with tumors at risk for developing aggressive metastatic disease. Circulating tumor cells (CTC) (6) have been detected in the blood of patients with melanoma (1, 2) and other solid cancers (3-5). Previously, we have demonstrated that CTC biomarkers increase with metastasis and tumor burden in melanoma patients (6). We also have shown that CTC are associated with increased risk of tumor recurrence and poor survival in melanoma patients (1, 6). Measurement of CTC has also been used as an indicator of patient response to systemic therapy in melanoma (1). Thus, CTC may be an important predictor of patient outcome and may represent an approach for early detection of "subclinical systemic metastasis" (7).

A detailed genomic characterization of CTC in melanoma has not been reported to date. However, genomewide profiling studies have been carried out in melanoma tumor samples with identification of important genomic aberrations (8-10). Single-nucleotide polymorphism (SNP)-derived copy number aberrations (CNA) [copy number gains (CNG), copy number losses (CNL)], and loss of heterozygosity (LOH) are important genetic aberrations in cancer progression. High-density SNP microarrays have been applied to detailed genome-wide identification of CNA events in cancer and represent an informative platform for the discovery of functional tumor-related genes (11).

Melanomas are heterogeneous, with both variant and common genotypes and phenotypes (12). We postulated that genomic signatures could occur in CTC that may represent particularly aggressive stage IIIB/C metastases capable of evolving into clinical distant organ metastasis. Genomic profiling of CTC may allow improved understanding of their role in real-time cancer metastasis events and may represent a novel approach in identification of genomic aberrations associated with melanoma prognosis and treatment.

In this study, we performed an array-based genomewide CNA characterization of melanoma CTC. We successfully identified 251 CNAs in melanoma CTC from 13 patients and showed high genomic concordance in CTC-tumor metastasis pairs. There were notable recurring CNA in paired CTC and tumor metastases across patients. In subsequent exploratory studies, we verified the significance of CTC-associated CNA by their presence in 27 distant organ melanoma metastases [American Joint Committee on Cancer (AJCC) stage IV] and as biomarkers of poor prognosis in 35 patients with regional melanoma metastasis (stage IIIB/C).

Materials and Methods


Three nonoverlapping cohorts of patients with metastatic melanoma were included in this 2-phase study. In the CTC discovery phase, tumor-involved nodal tissue and peripheral blood mononuclear cell (PBMC) samples were obtained from 13 patients with stage IIIB/C regional melanoma metastasis. In the verification phase, the clinical relevance of CTC-associated CNA was verified in distant stage IV metastasis tumor tissue of 27 patients with stage IV melanoma involving systemic metastases to the brain (n = 15), lung(n = 4), and gastrointestinal tract (n = 8) and in cell lines derived from 35 melanoma patients with regional metastasis (stage IIIB/C melanoma). Ml and M14 metastatic melanoma cell lines were used to verify the sensitivity of the CTC immune-capture assay.

All operative tissue samples were collected and processed at the John Wayne Cancer Institute and cryopreserved in liquid nitrogen. All cell lines were from human tumor tissue obtained at the time of surgery. Early passaged melanoma lines (<12 passages) were used. This study was approved by the John Wayne Cancer Institute/Saint John's Health Center and Western Institutional Review Board. Informed consent was obtained from all patients.


Human IgM monoclonal antibodies (mAb) to ganglioside GM3 (L612) (13), ganglioside GM2 (L55) (14), and ganglioside GD2 (L72) (15) were developed by R.I. from an established Epstein-Barr virus-transformed human B-cell line, cloned, extensively purified, and verified and quality controlled under good laboratory practice (GLP) conditions. These 3 mAb were coupled to Dynabeads M-450 tosylactivated (Life Technologies), according to the manufacturer's instructions.


M1 and M14 melanoma cells were serially diluted in PBMC from healthy donors (100, 50, 10,1, and 0 melanoma cells in 107 PBMC). Previously assessed CTC mRNA melanoma reverse transcription-quantitative PCR (RT-qPCR) biomarkers by our group (6,16-18) were used for verification of capture of melanoma cells, including tyrosine-related protein 2 (TRP-2), melanoma antigen recognized by T cells 1 (MART-1), melanoma antigen gene-A3 family (MAGE-A3), and paired box homeotic gene transcription factor 3 (PAX-3). Additionally, immunocaptured cells were stained with anti-MART-1 mAb (GeneTex, Clone # GTX75965), followed by incubation with Alexa Fluor[R] 555 goat antimouse IgG2b (Invitrogen) and were mounted onto glass slides and stained with ProLong[R] Gold antifade reagent with DAPI (Invitrogen). The cells were analyzed by Leica microscopy to verify captured melanoma CTC.


PBMC were isolated by Ficoll-Hypaque, collected, and suspended in freezing medium and cryopreserved in liquid nitrogen. IgM Ab-coupled Dynabeads were added to each sample ([10.sup.7] cells/mL) followed by incubation at 4[degrees]C (1 h). For the immunocapture assay, samples were then placed in the Dynal[R] MPC-6 appliance (Invitrogen), allowing aspiration of unbound cells. Beads with bound cells were then washed using 0.1% BSA/PBS with 2 mmol/L EDTA. Immunocaptured cells were subjected to immunofluorescent staining with MART-1 mAb or to DNA or RNA extractions with DNAzol and Tri-Reagent (Molecular Research Center), respectively. The RT-qPCR assay was performed with the iCycler iQ Real-Time Thermocycler Detection System (Bio-Rad Laboratories) with a beta-2-microglobulin (B2M) [7] control housekeeping gene. The sequences of primers and fluorescence resonance energy transfer probe of B2M were as follows: primers, 5'-TGTCACAGCCCAAGATAG-3' and 5'CAAGCAAGCAGAATTTGGAA-3' and probe, 5'FAM-TCCATGATGCTGCTTACATGTCTCGA-BHQ- 1-3' (6).


DNA extraction from frozen tumor tissues and cell lines was carried out with the QIAamp DNA mini kit (QIAGEN). DNA extraction from CTC was carried out using DNAzol. DNA quantification was performed using Quant-iTTM PicoGreen[R] double-stranded DNA reagent and kits (Invitrogen). Extracted DNA from CTC and paired melanoma tissue in the discovery cohort was further subjected to whole-genome amplification (WGA) using a REPLI-g mini kit (QIAGEN). The reaction was performed at 30[degrees]C for 16 h, followed by heat inactivation at 65[degrees]C for 3 min. Amplified DNA was used for Affymetrix SNP 6.0 array analysis. DNA isolated for the CNA verification cohort (27 stage IV melanoma metastases, 35 stage IIIB/C regional melanoma metastases) was not subjected to WGA.


DNA obtained after WGA was assessed on the SNP array for genotyping analysis and the procedures were performed at the University of Southern California/ Children's Hospital of Los Angeles Genome Core Laboratory. Genotyping of samples was performed using Affymetrix Genotyping Console 4.0 with the Birdseed v2 algorithm under GLP conditions (19). Before genotyping, QC of arrays was conducted using the contrast QC algorithm with a minimal call rate of >95%. For copy number analysis QC, individual arrays must have a median of the absolute values of all pairwise differences below 0.35. CNA analyses were performed using Affymetrix Genotyping Console 4.0 with regional GC correction and default software settings. HapMap reference, release 30, was used as the reference model for CNA analyses. CNA segments were reported with a hidden Markov model algorithm using the default CNA map in Genotyping Console 4.0 (Toronto DGV map). LOH was defined by Genotyping Console 4.0 using the sliding window algorithm described in http:// loh_algorithm_gtc2_whitepaper.pdf, which demonstrated a true-positive call rate of well over 90% for most validation cases and a false-positive rate of <10%. The minimum LOH size was set to 100 kb, eliminating >70% of the copy number-neutral LOH found in HapMap samples, and a minimum of 10 SNP markers within the region that report LOH were used.

The methods we used have been characterized previously to be highly robust and accurate when identifying large (>100 kb) CNA and LOH (20-22). Data generated by Genotyping Console were used to identify frequent CNA regions among CTC-tumor metastasis pairs. CNA on the sex chromosomes were excluded from analysis, and autosomal CNA were kept in the final analysis. The CNA reported were all on the size order of a cytoband.


The biostatistical analysis methods are described in the Data Supplement that accompanies the online version of this report at vol60/issue6.



A CTC immunocapture was developed utilizing IgM human mAb against 3 melanoma-related gangliosides [GM3 (13), GM2 (14), and GD2 (15)] coupled to immunomagnetic beads. Tumor-associated gangliosides are sialyl glycosphingolipids present on the outer surface of the cell plasma membrane (23). Melanomaassociated ganglioside expression has been previously reported by our group using biochemical assays and patient Ab analysis (13, 23, 24), and gangliosides have been successfully used as targets for mAb-based therapy in melanoma (14, 25). Use of multiple cell-surface Ab for immunocapture of CTC in melanoma patients addresses CTC capture sensitivity, tumor heterogeneity, and identification of aggressive CTC phenotypes. IgM human mAbs were used because they provide stronger capture efficiency than IgG mAbs. To evaluate the detection limit of our immuno-CTC capture assay, we spiked serially diluted cultured melanoma cells (100, 50, 10, 1, and 0 cells) in 107 PBMCs from healthy donors and retrieved by our immunocapture technique (Fig. 1A). Total RNA was extracted from captured melanoma cells and subjected to RT-qPCR as previously described (26). Captured CTC were verified by detection of 4 known melanoma-associated RTq-PCR biomarkers (TRP-2, MAGE-A3, MART-1, and PAX-3) that we previously identified in tumors and CTC from metastatic melanoma patients. The immunocapture assay sensitivity of capturing melanoma CTC from PBMCs was approximately 1 to 5 melanoma cells in 107 PBMCs (Fig. 1A). The specificity of the assay for isolation of melanoma cells was verified by staining captured CTC with a melanoma-related antigen, MART-1 (Fig. 1B).


Whole-genome SNP-based analysis using the Affymetrix Human Genome-Wide SNP 6.0 microarray was carried out on captured CTC and paired metastatic tissue from 13 patients with melanoma regional palpable metastases (stage IIIB/C). CTC were evaluated for CNA using Genotyping Console 4.0 against the HapMap 270 reference. There were several notable recurring CNA across patient CTC. We identified 251 CNA present in >50% of CTC (Table 1). Of these, CNG at 20 loci were present in >90% of CTC, and CNG aberrations at 2 loci (2q35 and 16p13.3) were seen in 100% of CTC. Furthermore, 100% of CTC had CNL at 9 loci (4p16.3, 6q25.3, 9p34.3, 10p15.3, 10q26.3, 14q32.33, 16p13.3, 18q23, 19p13.3), and an additional 14 CNL were present in >90% of CTC. Additionally, >90% of CTC had LOH at 14q23.3, and an additional 23 LOHs were detected in >50% of CTC.


To examine the relevance of CTC-associated genomic aberrations, we compared the genomic profiles of CTC to those for paired tumor tissue samples from 13 melanoma patients with stage III B/C regional metastases. All 13 sample pairs showed SNP status concordance of >90%, and 10 pairs had SNP concordance of [greater than or equal to] 97% (see online Supplemental Table 1). Furthermore, in a genome-wide comparative analysis of CNA states defined by gene segment, the 13 CTC-tumor metastasis pairs showed 71% to 96% concordant CNA changes among 17 599 gene coding regions and 80% to 98% concordant CNA changes among 30 994 coding and noncoding 100-kb gene segments (see online Supplemental Table 1). By use of the Cohen k statistical analysis, all CTC and tumor pairs showed a k coefficient of >0.7, showing high agreement between CTC and tumor genotype and CNA.

Melanomas are heterogeneous, and we hypothesized that CTC harbor genomic CNA representative of particularly aggressive tumor clones. To this end, a detailed CNA analysis at SNP loci was carried out on each CTC-tumor metastasis pair to determine regions of common genomic change. Common loci CNA are presented in Fig. 2. Ten loci CNG and 14 loci CNL were identified in >80% of CTC-tumor metastasis pairs, and 13 loci LOH were identified in >50% of CTC-tumor metastasis pairs. Of note, CNG at 2q35 was detected in all CTC-tumor metastasis pairs, CNG in 1q25.1, 2p16.3, and 14q32.33 were present in 12 of 13 CTC-tumor metastasis pairs, and an additional 6 CNG were detected in 11 of 13 CTC-tumor pairs (Fig. 2A). Additionally, CNL in 6q25.3, 9p34.3, 14q32.33, and 19p13.3 were identified in all CTC-tumor metastasis pairs, and an additional 10 CNLs were found in 11 of 13 CTC-tumor metastasis pairs (Fig. 2B). Lastly, 13 CTC LOHs were also positively verified in their paired tumor metastases in >50% of CTC-tumor pairs, and LOH at 14q23.3 was identified in 12 of 13 CTC-tumor metastasis pairs (Fig. 2C).


Because distant organ metastases are CTC derived, we postulated that CTC-associated CNA may represent genomic regions of importance in melanoma metastasis. We sought to verify our hypothesis by evaluation of CTC-associated genomic changes in a subsequent exploratory study of 27 patients who had undergone surgical resection of distant organ tumor metastasis (stage IV patients). We evaluated the top CNA (n = 37) identified in paired CTC-tumor metastasis in the discovery cohort (Fig. 2), defined by CNG and CNL common in >80% of paired CTC-tumor metastasis and LOH common in >50% of paired CTC-tumor metastasis. Of these 37 loci, genomic aberrations at 15 loci were identified in >50% of distant-organ melanoma metastases in this verification study.

To further verify whether these CNA were indeed present in metastatic melanomas, we assessed the presence of CNA spanning the 37 putative CNA from melanoma lymph node metastases (n = 169) and distant metastases (n = 35) from TCGA. For the CNGs, 4 were present in over 24% of the TCGA cohort, and 6 were present in >40% of the cohort. All CNLs reported were present in >40% of the TCGA cohort. LOH data were not publicly available.

To further verify whether the CNA verified in the stage IV patient cohort were indeed linked to the systemic metastatic potential of CTC rather than overall melanoma metastasis, we assessed the presence of the CNA in regional metastasis (n = 6, stage IIIB/C melanoma patients) with 10-year disease-free survival (DFS) after surgical resection to render the patients disease free. Using a Pearson test to compare these verified CNA/LOH to those present in 6 patients with 10year DFS, we found that CNGs at 14q32.33 and 1q25.1 as well as LOH at 12q24.13, 16q11.2, and 1p34.3 were indeed present at a significantly higher frequency in stage IV metastases (see online Supplemental Table 2). These findings verified that certain CTC-associated CNA were also present in systemic metastases, and suggest that CTC may contain specific genomic aberrations important in development of systemic metastasis.


To determine the relevance of CTC-associated CNA in predicting progression of regional melanoma, CTC-associated genomic aberrations were verified in an exploratory biomarker study of cell lines derived from regional metastatic tissue of 35 patients with stage IIIB/ IIIC melanomas. The top CNA (n = 37) identified in CTC-tumor metastasis pairs in the discovery cohort (Fig. 2) were evaluated. Single-genomic site analyses and genomic panel analyses were carried out. Survival analyses of individual genomic sites did not reach statistical significance after correction for multiple testing in this pilot study analysis. Using stepwise Cox regression, we developed a 5-marker CNA panel with the greatest prognostic utility, consisting of CNG at 1p35.1, CNG at 2q14.3, CNG at 14q32.33, CNL at 14q32.11, and CNL at 21q22.3. To determine whether these events were common in metastatic melanomas, the presence of CNA in these cytobands was assessed in the TCGA cohort. Of the 5 CNA reported, a CNG at 2q14.3 was present in 26% of the cohort, with the CNA at the other markers present in 40%-51% of the cohort.

A risk score was generated that classified patients into high-risk and low-risk groups for melanoma recurrence and death. The high-risk group classification conferred a significantly worse cancer outcome compared to the low-risk group, with 5-year DFS rates of 13% vs 69% (P = 0.0006) and overall survival of 28% vs 94% (there were limited events in one group to report an accurate P value), respectively (Fig. 3, A and B).

The risk score generated from the 5-marker CNA panel was then placed in a multivariable Cox model with known melanoma prognostic factors (27). In a multivariable analysis of the CNA risk score and lymph node positivity, the CNA risk-score was an independent prognostic factor for 5-year melanoma recurrence (hazard ratio, 1.14; CI 1.00-1.44; P = 0.0471) and death (hazard ratio, 2.86; CI 1.23-14.42; P = 0.0014).


CTC are an attractive alternative to tumor tissues for genomic profiling and biomarker analysis (28). CTC can be readily extracted from PBMC obtained from a blood draw without the antecedent risks of and need for an invasive surgical resection or percutaneous tissue biopsy for tumor sampling. Furthermore, tumor tissue may not always be available for analysis, particularly when metastases are small or when biopsy or surgery is not technically feasible. CTC can provide a real-time evaluation of subclinical melanoma spread and a method for monitoring patient response to therapy (1, 6, 29). The study of genomic aberrations in CTC may provide insight into genomic characteristics and mechanisms by which tumor cells establish distant organ metastasis and lead to the development of strategies to target CTC to prevent or control systemic melanoma metastasis.

A comprehensive genomic profile and analysis of melanoma CTC have not been reported to date. Our genome-wide SNP-based characterization of CTC revealed 251 CNA, which may represent candidate genomic aberrations important in melanoma progression and metastasis. Herein, we independently report on several known melanoma-associated SNP loci.

SNP loci identified by CTC were used to generate an exploratory 5-marker CNA gene panel: CUB and Sushi multiple domains 2 (CSMD2), 1p35.1; contactin associated protein-like 5 (CNTNAP5), 2q14.3; NRDE-2, necessary for RNA interference, domain containing (NRDE2), 14q32.11; ADAM metallopeptidase domain 6, pseudogene (ADAM6), 14q32.33; and transient receptor potential cation channel, subfamily M, member 2 (TRPM2), 21q22.3, with the ability to differentiate melanoma patients with good and poor outcome. Four of these 5 genes have been reported in cancer or have been implicated in cell adhesion and metastasis. TRPM2 is a calcium channel activated by oxidative stress that regulates susceptibility to cell death (30-33) and has been implicated in prostate cancer (32) and melanoma (33). In a recent report by Orfanelli et al. on aberrant sense and antisense transcripts derived from global hypomethylation studies in melanoma, several transcripts within the TRPM2 locus were enriched in melanoma (33). qPCR confirmed upregulation of TRPM2-AS and TRPM2-TE transcripts within the TRPM2 region, with corresponding methylation status of a shared CpG island in melanoma. Overexpression of wild-type TRPM2 and functional knockout of TRPM2-TE by stable transfection increased cellular apoptosis and necrosis in melanoma cells. Further, CSMD2 has been reported to be hypermethylated in pancreatic cancer and is a putative tumor suppressor gene (34). Also, CNTNAP5 is a transmembrane protein involved in cell adhesion (35). Comparative CNA and gene-based analyses showed the association of CNTNAP1 (member of CNTNAP family) with breast cancer risk (36). Lastly, cancer metastasis requires the ability to dissociate from neighboring cells or the extracellular matrix. ADAM is a family of membrane proteins involved in cell- cell adhesion and cell-matrix adhesion (37, 38). It is characterized by a disintegrin and metalloprotease domain with an epidermal growth factor-like region and harbors both adhesion and proteolytic domains implicated in integrin function and matrix degradation (38, 39). Verification of the biomarker panel in a large independent patient cohort would be valuable and warrants further study. Additionally, there may be other genes relevant to melanoma progression spanning the regions identified in the 5-marker CNA panel. The genes mentioned are major reported genes that have potential importance in metastasis and/or melanoma.

Our study was limited in that the immunocapture approach targeted different gangliosides with several mAbs, so some melanoma CTC that expressed low amounts or none of the gangliosides on their surface may be missed. Additionally, the verification cohorts used were pathologically well-defined stage IIIB/C and IV melanomas. Given that melanoma tumors may be heterogeneous, these samples were representative of the tumor removed beyond tissue necessary for standard pathological assessment.

This study provides the first detailed genome-wide SNP- and CNA-based analysis of melanoma CTC. The results confirm the close genomic relation between CTC and tumor metastases. There were notable recurring CNA across patient groups, which were subsequently demonstrated to be highly represented in systemic metastatic melanomas and to be of prognostic utility. The genomic study of CTC may be an important and novel approach in the identification of prometastatic genes in melanoma patients with regional stage IIIB/C disease whose risk of distant metastasis development is high and time frame of recurrence is unknown.

Data Access

All array data are deposited in NCBI's Gene Expression Omnibus (GEO) databank and are accessible through GEO Series accession file GSE43934. In particular, the samples with 10-year DFS are O871, O870, O857, O844, O848, and O866.

Author Contributions: All authors confirmed they have contributed to the intellectual content of this paper and have met the following 3 requirements: (a) significant contributions to the conception and design, acquisition of data, oranalysis and interpretation of data; (b) drafting or revising the article for intellectual content; and (c) final approval of the published article.

Authors' Disclosures or Potential Conflicts of Interest: Upon manuscript submission, all authors completed the author disclosure form. Disclosures and/or potential conflicts of interest:

Employment or Leadership: D.S.B. Hoon, JWCI.

Consultant or Advisory Role: None declared.

Stock Ownership: None declared.

Honoraria: None declared.

Research Funding: D.L. Morton, award numbers P0 CA029605 and P0 CA012582 from the National Institutes of Health, National Cancer Institute; D.S.B. Hoon, the Dr. Miriam and Sheldon G. Adelson Medical Research Foundation, the Melanoma Research Alliance, and award numbers P0 CA029605 and P0 CA012582 from the National Institutes of Health, National Cancer Institute.

Expert Testimony: None declared.

Patents: D.S.B. Hoon, U.S. patent number 8,039,218.

Role of Sponsor: The funding organizations played no role in the design of study, choice of enrolled patients, review and interpretation of data, or preparation or approval of manuscript.


(1.) Koyanagi K, O'Day SJ, Boasberg P, Atkins MB, Wang HJ, Gonzalez R, et al. Serial monitoring of circulating tumor cells predicts outcome of induction biochemotherapy plus maintenance biotherapy for metastatic melanoma. Clin Cancer Res 2010; 16:2402-8.

(2.) Palmieri G, Strazzullo M, Ascierto PA, Satriano SM, Daponte A, Castello G. Polymerase chain reaction-based detection of circulating melanoma cells as an effective marker of tumor progression. Melanoma cooperative group. J Clin Oncol 1999; 17:304-11.

(3.) Fehm T, Muller V, Aktas B, Janni W, Schneeweiss A, Stickeler E, et al. Her2 status of circulating tumor cells in patients with metastatic breast cancer: a prospective, multicenter trial. Breast Cancer Res Treat 2010; 124:403-12.

(4.) Koyanagi K, Bilchik AJ, Saha S, Turner RR, Wiese D, McCarter M, et al. Prognostic relevance of occult nodal micrometastases and circulating tumor cells in colorectal cancer in a prospective multicenter trial. Clin Cancer Res 2008; 14: 7391-6.

(5.) Scher HI, Jia X, de Bono JS, Fleisher M, Pienta KJ, Raghavan D, Heller G. Circulating tumour cells as prognostic markers in progressive, castration-resistant prostate cancer: a reanalysis of IMMC38 trial data. Lancet Oncol 2009; 10:233-9.

(6.) Koyanagi K, O'Day SJ, Gonzalez R, Lewis K, Robinson WA, Amatruda TT, et al. Serial monitoring of circulating melanoma cells during neoadjuvant biochemotherapy for stage III melanoma: outcome prediction in a multicenter trial. J Clin Oncol 2005; 23:8057-64.

(7.) Pantel K, Brakenhoff RH, Brandt B. Detection, clinical relevance and specific biological properties of disseminating tumour cells. Nat Rev Cancer 2008; 8:329-40.

(8.) Bishop DT, Demenais F, Iles MM, Harland M, Taylor JC, Corda E, et al. Genome-wide association study identifies three loci associated with melanoma risk. Nat Genet 2009; 41:920-5.

(9.) Garraway LA, Widlund HR, Rubin MA, Getz G, Berger AJ, Ramaswamy S, et al. Integrative genomic analyses identify MITF as a lineage survival oncogene amplified in malignant melanoma. Nature 2005; 436:117-22.

(10.) Hodis E, Watson IR, Kryukov GV, Arold ST, Imielinski M, Theurillat JP, et al. A landscape of driver mutations in melanoma. Cell 2012; 150: 251-63.

(11.) Zhao X, Li C, Paez JG, Chin K, Janne PA, Chen TH, et al. An integrated view of copy number and allelic alterations in the cancer genome using single nucleotide polymorphism arrays. Cancer Res 2004; 64:3060-71.

(12.) Koh SS, Wei JP, Li X, Huang RR, Doan NB, Scolyer RA, et al. Differential gene expression profiling of primary cutaneous melanoma and sentinel lymph node metastases. Mod Pathol 2012; 25:828-37.

(13.) Hoon DS, Wang Y, Sze L, Kanda H, Watanabe T, Morrison SL, et al. Molecular cloning of a human monoclonal antibody reactive to ganglioside GM3 antigen on human cancers. Cancer Res 1993; 53:5244-50.

(14.) Irie RF, Matsuki T, Morton DL. Human monoclonal antibody to ganglioside GM2 for melanoma treatment. Lancet 1989; 1:786-7.

(15.) Irie RF, Sze LL, Saxton RE. Human antibodyto OFA-I, a tumor antigen, produced in vitro by Epstein-Barr virus-transformed human B-lymphoid cell lines. Proc Natl Acad SciUSA 1982; 79:5666-70.

(16.) Hoshimoto S, Faries MB, Morton DL, Shingai T, Kuo C, Wang HJ, et al. Assessment of prognostic circulating tumor cells in a phase III trial of adjuvant immunotherapy after complete resection of stage IV melanoma. Ann Surg 2012; 255: 357-62.

(17.) Nicholl MB, Elashoff D, Takeuchi H, Morton DL, Hoon DS. Molecular upstaging based on paraffinembedded sentinel lymph nodes: ten-year follow-up confirms prognostic utility in melanoma patients. Ann Surg 2011; 253:116-22.

(18.) Yamano T, Kaneda Y, Huang S, Hiramatsu SH, Hoon DS. Enhancement of immunity by a DNA melanoma vaccine against TRP2 with CCL21 as an adjuvant. Mol Ther 2006; 13:194-202.

(19.) Pinto D, Darvishi K, Shi X, Rajan D, Rigler D, Fitzgerald T, et al. Comprehensive assessment of array-based platforms and calling algorithms for detection of copy number variants. Nat Biotech nol 2011; 29:512-20.

(20.) Nannya Y, Sanada M, Nakazaki K, Hosoya N, Wang L, Hangaishi A, et al. A robust algorithm for copy number detection using high-density oligonucleotide single nucleotide polymorphism genotyping arrays. Cancer Res 2005; 65:6071-9.

(21.) Beroukhim R, Lin M, Park Y, Hao K, Zhao X, Garraway LA, et al. Inferring loss-ofheterozygosity from unpaired tumors using highdensity oligonucleotide SNP arrays. PLoS Comput Biol 2006; 2:e41.

(22.) Li X, Self SG, Galipeau PC, Paulson TG, Reid BJ. Direct inference of SNP heterozygosity rates and resolution of LOH detection. PLoS Comput Biol 2007; 3:e244.

(23.) Tsuchida T, Saxton RE, Morton DL, Irie RF. Gangliosides of human melanoma. J Natl Cancer Inst 1987; 78:45-54.

(24.) Tsuchida T, Saxton RE, Morton DL, Irie RF. Gangliosides of human melanoma. Cancer 1989; 63: 1166-74.

(25.) Irie RF, Ollila DW, O'Day S, Morton DL. Phase I pilot clinical trial of human IgM monoclonal antibody to ganglioside GM3 in patients with metastatic melanoma. Cancer Immunol Immunother 2004; 53:110-7.

(26.) Koyanagi K, Kuo C, Nakagawa T, Mori T, Ueno H, Lorico AR Jr, et al. Multimarker quantitative real-time PCR detection of circulating melanoma cells in peripheral blood: relation to disease stage in melanoma patients. Clin Chem 2005; 51:981-8.

(27.) Balch CM, Gershenwald JE, Soong SJ, Thompson JF. Update on the melanoma staging system: the importance of sentinel node staging and primary tumor mitotic rate. J Surg Oncol 2011; 104:37985.

(28.) van de Stolpe A, Pantel K, Sleijfer S, Terstappen LW, den Toonder JM. Circulating tumor cell isolation and diagnostics: toward routine clinical use. Cancer Res 2011; 71:5955-60.

(29.) Hoshimoto S, Shingai T, Morton D, Kuo C, Faries M, Chong KK, et al. Association between circulating tumor cells and prognosis in patients with stage III melanoma with sentinel lymph node metastasis in a phase III international multicenter trial. J Clin Oncol 2012; 30:3819-26.

(30.) Hara Y, Wakamori M, Ishii M, Maeno E, Nishida M, Yoshida T, et al. LTRPC2 Ca2+permeable channel activated by changes in redox status confers susceptibility to cell death. Mol Cell 2002; 9:163-73.

(31.) Zhang W, Chu X, Tong Q, Cheung JY, Conrad K, Masker K, Miller BA. A novel TRPM2 isoform inhibits calcium influx and susceptibility to cell death. J Biol Chem 2003; 278:16222-9.

(32.) Zeng X, Sikka SC, Huang L, Sun C, Xu C, Jia D, et al. Novel role for the transient receptor potential channel TRPM2 in prostate cancer cell proliferation. Prostate Cancer Prostatic Dis 2010; 13:195201.

(33.) Orfanelli U, Wenke AK, Doglioni C, Russo V, Bosserhoff AK, Lavorgna G. Identification of novel sense and antisense transcription at the TRPM2 locus in cancer. Cell Res 2008; 18:1128-40.

(34.) Shimizu H, Horii A, Sunamura M, Motoi F, Egawa S, Unno M, Fukushige S. Identification of epigenetically silenced genes in human pancreatic cancer by a novel method "microarray coupled with methyl-CpG targeted transcriptional activation" (MeTA-array). Biochem Biophys Res Commun 2011; 411:162-7.

(35.) Peles E, Nativ M, Lustig M, Grumet M, Schilling J, Martinez R, et al. Identification of a novel contactin-associated transmembrane receptor with multiple domains implicated in protein-protein interactions. EMBO J 1997; 16:978-88.

(36.) Lee JY, Park AK, Lee KM, Park SK, Han S, Han W, et al. Candidate gene approach evaluates association between innate immunity genes and breast cancer risk in Korean women. Carcinogenesis 2009; 30:1528-31.

(37.) Blobel CP, Wolfsberg TG, Turck CW, Myles DG, Primakoff P, White JM. A potential fusion peptide and an integrin ligand domain in a protein active in sperm-egg fusion. Nature 1992; 356:248-52.

(38.) Wolfsberg TG, Primakoff P, Myles DG, White JM. ADAM, a novel family of membrane proteins containing a disintegrin and metalloprotease domain: multipotential functions in cell-cell and cell-matrix interactions. J Cell Biol 1995; 131: 275-8.

(39.) Perry AC, Jones R, Hall L. Analysis of transcripts encoding novel members of the mammalian metalloprotease-like, disintegrin-like, cysteinerich (MDC) protein family and their expression in reproductive and non-reproductive monkey tissues. Biochem J 1995; 312(Pt 1):239-44.

Connie G. Chiu, [1,2] ([dagger]) Yoshitaka Nakamura, [1] ([dagger]) Kelly K. Chong, [1] Sharon K. Huang, [1] Neal P. Kawas, [1] Timothy Triche, [3] David Elashoff, [4] Eiji Kiyohara, [1] Reiko F. Irie, [5] Donald L. Morton, [2] and Dave S.B. Hoon [1] *

[1] Department of Molecular Oncology and [2] Division of Surgical Oncology, John Wayne Cancer Institute, Santa Monica, CA; [3] Center for Personalized Medicine, Children's Hospital Los Angeles and Keck School of Medicine, University of Southern California, LosAngeles, CA; [4] Department of Medicine Statistics Core, UCLA School of Medicine, Los Angeles, CA; [5] Department of Biotechnology, John Wayne Cancer Institute, Santa Monica, CA.

* Address correspondence to this author at: Department of Molecular Oncology, John Wayne Cancer Institute at Saint John's Health Centre, 2200 Santa Monica Blvd., Santa Monica, CA 90404. Fax 310-449-5282; e-mail

([dagger]) Connie G. Chiu and Yoshitaka Nakamura contributed equally to the work, and both should be considered as first authors.

Received July 24, 2013; accepted March 20, 2014.

Previously published online at DOI: 10.1373/clinchem.2013.213611

[6] Nonstandard abbreviations: CTC, circulating tumor cells; SNP, single-nucleotide polymorphism; CNA, copy number aberration; CNG, copy number gains; CNL, copy number losses; LOH, loss of heterozygosity; AJCC, American Joint Committee on Cancer; PBMC, peripheral blood mononuclear cells; mAb, monoclonal antibody; GLP, good laboratory practice; RT-qPCR, reverse transcriptionquantitative PCR; TRP-2, tyrosine-related protein 2; MART-1, melanoma antigen recognized by T cells 1; MAGE-A3, melanoma antigen gene-A3 family; PAX-3, paired box homeotic gene transcription factor 3; WGA, whole-genome amplification; DFS, disease-free survival.

[7] Human genes: B2M, beta-2-microglobulin; CSMD2, CUB and Sushi multiple domains 2; C14orf102, chromosome 14 open reading frame 102; CNTNAP5, contactin associated protein-like 5; NRDE2, NRDE-2, necessary for RNA interference, domain containing; ADAM6, ADAM metallopeptidase domain 6, pseudogene; TRPM2, transient receptor potential cation channel, subfamily M, member 2. See also the Fig. 2 legend for more gene information.

Table 1. Summary of loci with CNAs in melanoma CTC.

Percentage of        CNG loci                 CNL loci
patients with
genomic variation
in CTC at loci (a)

100%                 2q35, 16p13.3            4p16.3, 6q25.3,
                                              9q34.3, 10p15.3,
                                              10q26.3, 14q32.33,
                                              16p13.3, 18q23,

90%-99%              1p34.1, 1p35.1,          5p15.33, 5q11.2, 6q27,
                     1q25.1, 1q25.2,          7q36.2, 7q36.3,
                     1q32.2, 2p16.3,          9q22.2, 9q34.2,
                     2q14.3, 6p21.33,         11p15.5, 14q32.11,
                     7q22.1, 7q32.3,          14q32.12, 15q21.1,
                     12q13.13, 14q32.33,      16q24.3, 20q13.33,
                     15q24.1, 19p13.12,       21q22.3
                     19p13.13, 19p13.2,
                     19p13.3, 19q13.2

80%-89%              1p32.2, 1p33, 1p36.13,   1p36.32, 1q42.13,
                     1q21.3, 1q22, 1q23.1,    5q14.1, 7p22.3,
                     3q23, 3q27.1, 6p21.1,    9p24.3, 13q34,
                     6p21.2, 6p21.31,         15q26.3, 17p13.3,
                     7q11.23, 9q33.1,         17q25.3, 18p11.21
                     11q25, 15q14, 17p13.1,
                     17q12, 17q21.31,
                     17q25.1, 18q12.2,
                     19p13.11, 20q13.12,

70%-79%              1q23.2, 1q32.1,          1p36.33, 5p15.31,
                     2p23.1, 3p25.1,          8q24.3, 9p13.2,
                     3q21.3, 4p15.33,         22q13.33
                     4q28.2, 6p21.32, 7q33,
                     7q34, 8p21.2, 9q33.2,
                     10q22.1, 11q23.2,
                     14q11.2, 16p12.1,
                     16p13.2, 17p13.2,
                     17q11.2, 17q21.33,
                     18q12.3, 19q13.12,
                     19q13.32, 19q13.42,
                     21q22.11, 22q12.3

60%-69%              1p12, 1p13.2, 1p36.12,   1p31.1, 2p22.3,
                     2p23.2, 3p14.2,          2p25.3, 2q37.1,
                     3p22.2, 3p25.3,          2q37.3, 4p16.2,
                     3q22.3, 4q12, 4q31.22,   4q28.2, 4q35.1,
                     5q32, 5q33.3, 7p21.3,    4q35.2, 5q12.3,
                     7p22.2, 7q31.1,          5q23.2, 5q31.3,
                     8p21.3, 8q24.13,         6p25.2, 8p23.3,
                     8q24.22, 9p13.3,         9q33.2, 10q22.1,
                     9q31.2, 11p15.4,         10q22.2, 10q24.32,
                     11q24.1, 11q24.2,        11q11, 12q23.3,
                     12p13.31, 12q13.2,       12q24.33, 13q14.3,
                     12q23.3, 12q24.21,       13q31.1, 14q12,
                     14q24.3, 14q32.2,        14q22.1, 14q32.31,
                     15q24.3, 15q25.3,        17q12, 19p13.2,
                     16p11.2, 16p12.3,        19q13.12, 20p11.23,
                     16q12.1, 17q21.1,        22q13.31
                     17q21.2, 17q21.32,
                     17q22, 18q21.1,
                     19q13.33, 20p11.21,

50%-59%              1p34.2, 1p34.3,          1p13.2, 1q31.1, 1q44,
                     1p35.2, 1p36.11,         4q25, 4q28.1, 5q15,
                     1p36.32, 1q25.3, 2p21,   5q35.2, 6q16.3,
                     2q37.1, 3p14.1,          9p13.1, 10p11.21,
                     3p24.3, 4q13.2,          10p12.2, 10q25.2,
                     5q13.1, 5q23.3,          11p15.1, 14q11.2,
                     5q31.3, 6p22.1, 6q15,    15q22.31, 19p12,
                     7q36.1, 8p23.1,          21q22.11
                     9q33.3, 10q24.31,
                     10q25.2, 11p11.2,
                     12q12, 12q13.3,
                     12q24.13, 13q14.12,
                     13q32.1, 16p13.11,
                     20q12, 22q11.22

Percentage of        LOH loci
patients with
genomic variation
in CTC at loci (a)


90%-99%              14q23.3


70%-79%              12q24.12, 12q24.13

60%-69%              1p34.3, 1q21.1,
                     3p21.31, 16q11.2,
                     16q12.1, 16q22.1,
                     1q21.2, 3p21.2,
                     11p11.12, 16p11.2

50%-59%              1p33, 2q21.3, 3p11.2,
                     6q24.3, 8p11.21,
                     8q11.22, 8q13.1,
                     8q13.2, 11p11.2,
                     12q24.11, 15q15.3

(a) n = 13 patients; CNA loci in >50% of CTC are shown.
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Title Annotation:Molecular Diagnostics and Genetics
Author:Chiu, Connie G.; Nakamura, Yoshitaka; Chong, Kelly K.; Huang, Sharon K.; Kawas, Neal P.; Triche, Tim
Publication:Clinical Chemistry
Article Type:Report
Date:Jun 1, 2014
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