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Involvement of
ANXA5
and
ILKAP
in Susceptibility to
Malignant Melanoma
Yoana Arroyo-Berdugo
1
, Santos Alonso
2
, Glorı
´a Ribas
3
, Maider Ibarrola-Villava
3
,Marı
´a Pen
˜a-Chilet
3
,
Conrado Martı
´nez-Cadenas
4
, Jesu
´s Gardeazabal
5
, Juan Antonio Rato
´n-Nieto
5
, Ana Sa
´nchez-Dı
´ez
6
,
Jesu
´s Marı
´a Careaga
6
, Gorka Pe
´rez-Yarza
1
, Gregorio Carretero
7
, Manuel Martı
´n-Gonza
´lez
8
,
Cristina Go
´mez-Ferna
´ndez
9
, Eduardo Nagore
10
, Aintzane Asumendi
1
,Marı
´a Dolores Boyano
1
*
1Department of Cell Biology and Histology, School of Medicine and Dentistry, University of the Basque Country (UPV/EHU), Leioa, Bizkaia, Spain, 2Department of
Genetics, Physical Anthropology and Animal Physiology, Faculty of Science and Technology, University of the Basque Country (UPV/EHU), Leioa, Bizkaia, Spain,
3Department of Hematology and Medical Oncology, Instituto Investigacio
´n Sanitaria, INCLIVA, Valencia, Spain, 4Department of Medicine, University of Castellon Jaume I,
Castellon, Spain, 5Department of Dermatology, Ophthalmology and Otorhinolaryngology, UPV/EHU, Service of Dermatology, BioCruces Health Research Institute, Cruces
University Hospital, Barakaldo, Bizkaia, Spain, 6Department of Dermatology, Ophthalmology and Otorhinolaryngology, UPV/EHU, Service of Dermatology, BioCruces
Health Research Institute, Basurto University Hospital, Bilbao, Bizkaia, Spain, 7Department of Dermatology, Doctor Negrin Hospital, Las Palmas de Gran Canaria, Spain,
8Department of Dermatology, Ramo
´n y Cajal Hospital, Madrid, Spain, 9Deparment of Dermatology, La Paz University Hospital, Madrid, Spain, 10 Department of
Dermatology, Instituto Valenciano de Oncologı
´a, Valencia, Spain
Abstract
Single nucleotide-polymorphisms (SNPs) are a source of diversity among human population, which may be responsible for
the different individual susceptibility to diseases and/or response to drugs, among other phenotypic traits. Several low
penetrance susceptibility genes associated with malignant melanoma (MM) have been described, including genes related to
pigmentation, DNA damage repair and oxidative stress pathways. In the present work, we conducted a candidate gene
association study based on proteins and genes whose expression we had detected altered in melanoma cell lines as
compared to normal melanocytes. The result was the selection of 88 loci and 384 SNPs, of which 314 fulfilled our quality
criteria for a case-control association study. The SNP rs6854854 in ANXA5 was statistically significant after conservative
Bonferroni correction when 464 melanoma patients and 400 controls were analyzed in a discovery Phase I. However, this
finding could not be replicated in the validation phase, perhaps because the minor allele frequency of SNP rs6854854 varies
depending on the geographical region considered. Additionally, a second SNP (rs6431588) located on ILKAP was found to
be associated with melanoma after considering a combined set of 1,883 MM cases and 1,358 disease-free controls. The OR
was 1.29 (95% CI 1.12–1.48; p-value =4610
24
). Both SNPs, rs6854854 in ANXA5 and rs6431588 in ILKAP, show population
structure, which, assuming that the Spanish population is not significantly structured, suggests a role of these loci on a
specific genetic adaptation to different environmental conditions. Furthermore, the biological relevance of these genes in
MM is supported by in vitro experiments, which show a decrease in the transcription levels of ANXA5 and ILKAP in
melanoma cells compared to normal melanocytes.
Citation: Arroyo-Berdugo Y, Alonso S, Ribas G, Ibarrola-Villava M, Pen
˜a-Chilet M, et al. (2014) Involvement of ANXA5 and ILKAP in Susceptibility to Malignant
Melanoma. PLoS ONE 9(4): e95522. doi:10.1371/journal.pone.0095522
Editor: Masaru Katoh, National Cancer Center, Japan
Received January 20, 2014; Accepted March 27, 2014; Published April 17, 2014
Copyright: ß2014 Arroyo-Berdugo et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: This work was supported by the Dpt. Educacion, Universidades e Investigacio
´n of the Basque Government, project IT524-10; Diputacio
´n Foral de
Bizkaia, project DIPE 08/19, the University of the Basque Country program UFI11/44 and a predoctoral fellowship from the Dept. Educacio
´n, Universidades e
Investigacio
´n of the Basque Government to YA-B (BFI07.282). The funders had no role in study design, data collection and analysis, decision to publish, or
preparation of the manuscript.
Competing Interests: The author have declared that no competing interests exist.
* E-mail: lola.boyano@ehu.es
Introduction
Malignant melanoma (MM) is a stepwise tumor process in
which normal melanocytes in the basal layer of the epidermis
acquire genetic aberrations that drive progression to melanoma. In
recent years, there has been a constant increase in the incidence of
MM among the world population, which is a worrying fact
because MM is a highly aggressive, potentially lethal form of
cancer [1]. Summaries of national melanoma notifications
provided to the International Agency for Research on Cancer
(IARC) (2002) demonstrate that the highest reported national
incidence rates for melanoma occurred in the populations of
Australia (39:100,000 per year) and New Zealand (34:100,000 per
year). The next highest national melanoma rates were observed in
the USA (17:100,000 per year) followed by the countries in
northern (Denmark, Norway and Sweden) and western European
countries (the Netherlands and the United Kingdom), with
incidences of 9–15:100,000 per year [2,3]. According to data
published by the Spanish National Epidemiology Carlos III
Health Institute, the annual incidence of melanoma in Spain is
close to the adjusted annual incidence for the European
population of 6.14 per 100,000 population in men and 7.26 per
100,000 population in women [3]. The predominantly non-
Caucasian populations of Africa and Asia reported melanoma
rates less than 3:100,000 per year [2]. Likewise, MM tends to
PLOS ONE | www.plosone.org 1 April 2014 | Volume 9 | Issue 4 | e95522
occur more often in people with light skin, hair and eyes, who
seem to be more sensitive to the sun’s ultraviolet radiation,
although the development of this pathology may happen in any
geographical human group [4].
In this regard, epidemiological and genetic studies show that
both the development of the disease and its evolution are
determined by individual-specific genetic factors, genetic and
epigenetic aberrations acquired by the tumor, and by environ-
mental conditions [5,6,7]. Two high-risk melanoma susceptibility
genes with large effects but low frequency in the population have
been described. The best-established high-risk loci for melanoma
susceptibility are the genes CDKN2A, located on chromosome
9p21, and CDK4 on 12q14. The CDKN2A locus encodes for both
proteins p16
INK4a
and p14
ARF
and accounts for susceptibility in
25–40% of melanoma families [8,9]. Mutations in CDK4 are rare
and worldwide only three families have been reported to carry
mutations on this gene worldwide [10,11]. However, familial
melanoma only comprises approximately 10% of all MM cases, so
it seems likely that there are other low-penetrance polymorphisms
with small effects but very common in the population also
associated with the susceptibility to develop MM. The MC1R gene
is the candidate locus par excellence associated with the appearance
of different pigmentary phenotypes as well as to the ability to
modulate the susceptibility to develop sporadic MM [12,13].
However, other these low-penetrance alleles have been reported
which belong to biological processes such as pigmentation (ASIP,
OCA2,SLC45A2, TYR,TYRP1), immune response (IL-1b,IL-10,
INF-c,TNF-a), DNA repair (ERCC1,ERCC2,MGMT,TERT1,
TRF1,XRCC1,XRCC3), and metabolism (GSTM1,GSTP1,
GSTT1), including the vitamin D receptor [12,14–19].
Despite the fact that investigating the molecular alterations
involved in the pathogenesis of MM is a topic of active research,
the advances achieved so far are still insufficient to establish a set of
biomarkers and molecular targets which will facilitate an early
diagnosis, predicting the risk for metastasis in melanoma patients,
and developing more efficient therapies against this neoplasm. In
this context, we have conducted a case-control association study
based on 384 SNPs distributed in 88 candidate genes, of which
314 were successfully genotyped. These SNPs were selected by the
combination of the information obtained from proteomic analysis
by two-dimensional electrophoresis and mass spectrometry, and
mRNA expression arrays performed previously by our group. The
selected SNPs were genotyped in a case-control study using three
series of Spanish population samples (1,883 MM patients and
1,358 disease-free controls in total). Our results showed that the
SNPs rs6854854, located in ANXA5 and, rs6431588 in ILKAP are
associated with MM.
Results
The candidate genes to be genotyped in the present work were
selected based on proteins and genes differentially expressed
between melanoma cell lines and primary melanocytes. Therefore,
previous proteomic analyses were performed on six melanoma cell
lines (A375, Hs294T, HT-144, 1205Lu, WM793B, JSG) and four
primary melanocytes (HEMn-LP, HEMn-MP, HEMn-DP,
HEMa-LP) using two-dimensional electrophoresis (2D-PAGE),
while Affymetrix Human U133A GeneChip arrays were used to
analyze and compare mRNA expression profiles on four different
melanoma cell lines isolated from patients’ biopsies in our
laboratory (which were named JEM, JSG1, JSG2, MJOI) and
three benign nevi from patients’ skin lesions isolated also in our
laboratory (named FDR, JPA, RRR) (unpublished data). Finally,
we selected 88 genes involved in cell growth, cell cycle and
apoptosis, cell signaling, transcription and stress response (Table 1).
A total of 384 SNPs were selected on the basis of their Linkage
Disequilibrium (LD) profiles using Haploview [20].
In discovery Phase I, a total of 464 patients with MM and 400
volunteer cancer-free controls were genotyped. From the initial list
of 384 SNPs, 70 SNPs were discarded in Phase I for the following
reasons: 17 SNPs because they could be genotyped in less than
85% of the samples; 5 SNPs due to a low quality genotyping;
18 SNPs were found to be monomorphic in our control
population and patients; and 30 SNPs were out of Hardy-
Weinberg equilibrium (HWE) after a conservative Bonferroni
correction for multiple testing. The list of removed SNPs is
provided in Table S1 in File S1.
Comparison of Allele Frequencies
Therefore, the study continued with 314 SNPs (Table S2 in File
S1), whose allele frequencies were estimated based on our control
samples and compared to those of the HapMap CEU population
(people with Northern and Western European ancestry). Frequen-
cies were very similar and a high positive correlation can be
observed in Figure 1 (R
2
= 0.92), suggesting that our study
population is sufficiently homogeneous to conduct genetic
association studies with minor risk of population stratification.
However, one-sample t-test gave evidence that the corresponding
Spanish minor allele frequency (MAF) differed from that published
in HapMap (p-value ,0.05) for 8 of the 314 SNPs considered
(rs2069502 in CDK4, rs3731239 in CDKN1A, rs2303942 in FASTK,
rs2497 in GDI2, rs2088702 in PEBP1, rs228275 in PSMB3,
rs17800727 in RBL2, rs6586542 in RCC2) (shown as blue dots in
Figure 1).
Associations with MM Risk
After a Fisher’s exact test to compare allele counts between cases
and controls, 38 SNPs located in 31 genes were associated with
MM in the Spanish population considering a p-value threshold of
0.05. Representation of –log10 p-values for the comparison of
minor allele frequency (MAF) between the 464 MM cases and the
400 controls are detailed in Figure 2. Detailed information on
SNP, gene, chromosome location, MAF, odds ratio (OR), 95%
confidence interval (95% CI) and p-value for these 37 SNPs are
presented in Table 2. If a more restrictive p-value threshold of 0.01
is established, 9 SNPs remain as candidates associated with MM in
our Spanish population. And among them, only rs6854854,
located in the intron 2 of ANXA5, showed an association that was
statistically significant (p-value =4610
25
), after applying the
Bonferroni correction for multiple comparisons. This means that
individuals who possess at least one ANXA5 rs6854854 C allele are
protected against developing MM relative to those with the
reference genotype (OR = 0.541; 95% CI = 0.371–0.791; p-
value = 0.0013). The ANXA5 rs6854854 locus was significant under
the additive (p-value = 9.06610
25
) and recessive genetic models (p-
value = 5.97610
25
).
From these 38 SNPs with a p-value ,0.05, we selected 15 SNPs
with a MAF greater than 0.05 in our control samples for
validation in Phase II, which consisted on an independent set of
507 MM cases and 383 controls. None of the SNPs presented a
statistically significant association with MM at this stage (Table 3).
However, four of them had an overall p-value ,0.05 when phases I
and II were considered together (971 MM cases and 783 controls).
These four SNPs were: rs13167522 in APC (p-value = 0.0035);
rs4874163 in EEF1D (p-value = 0.0077); rs6431588 in ILKAP (p-
value = 0.0086); and rs7212835 in PSMD11 (p-value = 0.038). As
association studies require large numbers of samples to detect
weak association and increasing study size typically has a large
ANXA5 and ILKAP in Melanoma Susceptibility
PLOS ONE | www.plosone.org 2 April 2014 | Volume 9 | Issue 4 | e95522
effect on power, these four SNPs were genotyped in 912 new MM
cases and 581 controls in validation Phase III.
After genotyping 1,883 patients with melanoma and 1,358
control subjects, one SNP in intron 3 of ILKAP gene (rs6431588)
was associated with increased risk of developing MM in the
Spanish population (Fisher’s test p-value =5610
24
). The OR was
1.29 (95% CI 1.12–1.48; p-value =4610
24
) (Figure 3). Therefore,
the ILKAP rs6431588 locus was significant under the additive
genetic model (p-value = 5.8610
24
, using the Cochrane-Armitage
trend test). For the other three remaining SNPs p-values were not
statistically significant.
ANXA5 and ILKAP Expression in Human Melanoma Cell
Lines and Primary Melanocytes
In order to confirm an alteration in the expression levels of
ANXA5 and ILKAP in MM, quantitative measurement of these
genes’ expression was investigated in 10 melanoma cell lines and 3
primary melanocytes using quantitative real time PCR (Figure 4).
The results showed a weak reduction in the ANXA5 gene
expression and a significant decreased gene expression of ILKAP
(p-value ,0.05 after applying Student’s t-test) in the melanoma cell
lines studied in comparison with primary melanocytes. Although
some individual heterogeneity was also observed as not all the
melanoma cell lines showed a reduction in ANXA5 or ILKAP gene
expression, the trend observed coincided with that obtained
previously using expression microarrays, in which only ILKAP, but
not ANXA5, showed significant differences at mRNA transcrip-
tional levels between melanocytes and the tumor cell lines studied
(unpublished data). Additionally, the results obtained from
previous 2D-PAGE assays made in our laboratory suggested a
decrease of both proteins ILKAP and Annexin A5 in melanoma
cell lines compared to primary melanocytes. A Western blot
confirmed a significant decrease of Annexin A5 protein amount in
melanoma cell lines (Figure 5). These results suggest a deregulation
of ILKAP at the transcriptional level, whereas the deregulation
seems to be at posttranslational level for Annexin A5.
ILKAP Coding and Promoter Region Sequence Analysis
As a change in the nucleotide sequence within the gene coding
region can alter the expression and/or mRNA stability and thus
the final protein concentration, we sequenced a cDNA fragment of
1,259 bp covering the whole ILKAP exons (Chr 2:239,079,043–
239,112,324 according to UCSC Genome Browser, GRCh37/
hg19), in order to assess if there were nucleotide changes in the
melanoma cell lines. However, the chromatograms showed no
changes in the nucleotide sequence of the ILKAP.
In the absence of coding region mutations that could be
associated to the ILKAP expression deregulation observed in
melanoma cell lines, we hypothesized that there could exist
mutations in the promoter region that could be altering the
transcriptional activity of ILKAP. Therefore, the ILKAP gene
promoter region was amplified from genomic DNA using two
pairs of primers that resulted in one fragment of 1,443 bp and
another overlapping fragment of 1,110 bp. The sequences
obtained for each sample were aligned and assembled, enabling
the reading of a sequence of 2,069 bp (Chr 2:239,112,648–
239,114,717). Twelve single nucleotide variants were found, all of
them corresponding to already polymorphisms described. Table 4
shows the SNPs identified in the promoter region of ILKAP and the
genotypes that each cell line presents. The 12 polymorphisms
observed in the tested cell lines clustered into three different
haplotypes, which are sorted from the position Chr 2:239,114,642
to the position Chr 2:239,113,023. The melanoma lines A375,
HT-144 and JSG are homozygous for Haplotype 1 (TACCG-
GATCCGA). The cell lines 1205Lu, WM793B and HEMn-MP
Table 1. Eighty-eight candidate genes selected for SNPs genotyping.
Category Genes
Cell growth, cell
cycle and apoptosis
ANXA5, APC, AR, AURKB, AXL, BAX, BCL2L11, CDK2, CDK4, CDKN1A,
CTSD, ENO1, FASTK, GAS6, GSTP1, HDGF, IGFBP5, ILKAP, IMPDH2,
MAGED1, MAPRE1, NDN, NME2, NPM1, NRAS, PEA15, PIM1, PSMB3,
PSMD11, RAD50, RAP1B, RBL2, RCC2, RELA, SPRR2G, TGFB1, WEE1
Cell signaling AR, BAG2, CALM3, CCT7, CLIC1, CSNK1G2, FSCN1, GDI2, GRB2, ITGA5,
ITGAM, MAPKAPK3, MCL1, MYD88, PDPK1, PEBP1, PKM2, RAC1,
RCN1, RPSA, SIAH2, SNAI1, THBS1, TPM2, TTC1, UBE2L6, WARS, WNT5A, YWHAZ
Transcription ARID5A, CREBBP, CTBP1, CTNNB1, EEF1D, FOS, HDAC5,
HTATIP, JUN, PIR, RUVBL1, RUVBL2, SP1, TFDP1, PIAS3
Stress response DUSP1, GPX1, PARK7, PRDX1, PRDX3, SOD2, TXNL1
doi:10.1371/journal.pone.0095522.t001
Figure 1. Comparison of minor allele frequencies (MAF),
Spanish
vs.
HapMap European data. The small and big red circles
show the range within one and two standard deviation (SD) of the
mean, respectively. Blue dots represent values that significantly differ
from HapMap European data.
doi:10.1371/journal.pone.0095522.g001
ANXA5 and ILKAP in Melanoma Susceptibility
PLOS ONE | www.plosone.org 3 April 2014 | Volume 9 | Issue 4 | e95522
are homozygous for Haplotype 2 (CGTGGCGCCAAG). Finally,
the cell lines Hs294T, HEMn-LP and HEMn-DP are homozygous
for Haplotype 3 (CGTGACGCTAAG).
Tajima’s DTest Analysis to Identify Putative Signatures of
Positive Selection
Due to the high frequency of polymorphisms observed in the
promoter region of ILKAP, we decided to use the Tajima’s Dtest to
investigate if this locus was subjected to the effect of Natural
Selection in order to add evolutionary relevance to the function of
this locus. Thus, we used data from 1000 Genomes Project to
analyze a final region of 66 Kb (chr2:239066043-239132324
according to UCSC Genome Browser website, GRCh37/hg19),
which included the promoter and the coding region of ILKAP. The
African population (n = 246) did not show a statistically significant
value of Tajima’s D(D= 0.7; p-value = 0.16). However, the values
of Tajima’s Dobtained for Europeans (D= 2.54; p-value = 0.010;
n = 380) and for the Asian population (D= 2.50; p-value = 0.013;
n = 286) were statistically significant. These large and positive
Tajima’s Dtest in ILKAP suggests that balancing selection could be
playing a role on the evolutionary history of this locus.
Discussion
Instead of selecting among candidate genes already described in
the literature, the present work started by searching for genes
whose expression (both at the protein and mRNA levels) is altered
in melanoma cell lines as compared to normal melanocytes. After
identifying the candidate genes in this way, a set of SNPs was
selected for each corresponding gene. The result was the selection
of 88 loci and 384 SNPs, of which 314 fulfilled our quality criteria.
The allele frequencies observed in our control samples were
highly correlated to the HapMap CEU population (R
2
= 0.92).
Therefore, our experimental results are in good agreement with
the recent report by Gaya´n et al. showing that the Spanish
population is similar to Western and Northern Europeans and
sufficiently homogeneous to conduct genetic association studies
with minor risk of population stratification [21]. However, we also
saw that in our control population the MAF for 8 of the 314 SNPs
considered differed from that published in HapMap. This may be
due to a role of these SNPs (or of really linked SNPs) in adaptive
differences to environmental conditions because the frequency of
these 8 SNPs seems to differ across populations with different
geographic location (Table S3 in File S1).
From discovery Phase I, 38 SNPs showed p-values below 0.05
and, of these, only the ANXA5 rs6854854 SNP remained
statistically significant after Bonferroni correction. The annexins
are a super-family of closely related calcium and membrane
binding proteins which show cell type specific expression. Twelve
annexins, named as annexins A1–A11 and A13, have been
described common to vertebrates [22,23]. This protein family has
a wide variety of cellular functions including vesicle trafficking, cell
division, apoptosis, calcium signaling and growth regulation
[24,25]. Although Annexin A5 was the first annexin characterized
for three-dimensional structure in 1990 [26], its exact physiolog-
ical function has not been fully understood. Recent data suggest
that the invasion capacity, a main characteristic of tumors, is at
least in part regulated by Annexin A5 in different cancer types
[27,28,29]. Thus, Wehder et al. (2009) detected a decreased
migration activity and invasion capability of head and neck
squamous cell carcinoma after lacking ANXA5 [29]. Therefore, the
reduction of Annexin A5 protein amount observed in melanoma
cell lines may be changing motile capacity of the tumor cells.
However, it should be aware that ANXA5 seems to have specific
effects on distinct types of tumors [27], so experimentally
functional analysis are needed to determine the specific role of
Annexin A5 in MM.
Thereby, although the results obtained suggest that allele C in
rs6854854 has a protective role against melanoma (p-val-
ue =4610
25
), with an OR of 0.541 (95% CI 0.371–0.791; p-
value = 0.0013), after genotyping 464 MM patients and 400
disease-free controls, the ANXA5 rs6854854 SNP did not reach
statistical significance in validation Phase II. It is possible that the
difficulty in replication of results may be due to the existence of a
change in the minor C allele frequency in the control group of
Phase II. The C allele frequency in HapMap for European
population (CEU) is 0.110 which matches the frequency obtained
for the control group in Phase I of the study, however, the control
population tested in the Phase II showed a minor C allele
frequency of 0.075. An analysis of allele frequencies in different
Figure 2. SNP association results. The –log10 of the allelic p-values from 314 SNPs comparing 464 melanoma patients and 400 controls of
Spanish origin at Phase I are represented. The chromosomal SNP distribution is shown. The SNP rs6854854 in ANXA5 remained statistically significant
after Bonferroni correction (p-value ,0.00015).
doi:10.1371/journal.pone.0095522.g002
ANXA5 and ILKAP in Melanoma Susceptibility
PLOS ONE | www.plosone.org 4 April 2014 | Volume 9 | Issue 4 | e95522
Table 2. SNPs associated with Malignant Melanoma p,0.05 in Spanish population analyzed in Phase I.
Gene SNP Chrom Controls MA Controls MAF Cases MAF
Fisher
p-
value
OR (95% CI) p-
value
ANXA5 rs6854854 4 C 0.115 0.059 0.00004 0.541 (0.371–0.791) 0.0013
CTNNB1 rs4135385 3 G 0.273 0.202 0.0007 0.652 (0.494–0.862) 0.0025
APC rs13167522 5 C 0.125 0.083 0.0043 0.638 (0.451–0.969) 0.0040
TTC1 rs6556466 5 C 0.094 0.058 0.0054 0.645 (0.434–0.957) 0.0280
FASTK rs2288648 7 A 0.008 0 0.0061 0.061 (0.003–1.081) 0.0060
SIAH2 rs8072 3 T 0.013 0.002 0.0063 0.173 (0.037–0.806) 0.0110
NDN rs1722807 15 A 0.010 0 0.0074 0.060 (0.003–1.074) 0.0059
WEE1 rs11042431 11 G 0.211 0.160 0.0079 0.817 (0.611–1.092) 0.1710
ITGA5 rs12318746 12 A 0.010 0 0.0079 0.061 (0.003–1.095) 0.0064
RUVBL1 rs11719889 3 A 0.219 0.275 0.0102 1.425 (1.079–1.883) 0.0120
EEF1D rs4874163 8 G 0.155 0.113 0.0121 0.697 (0.525–0.926) 0.0120
PKM2 rs2959910 15 C 0.009 0 0.0172 0.072 (0.004–1.305) 0.0123
CCT7 rs2231427 2 G 0.009 0 0.0174 0.072 (0.004–1.312) 0.0125
ENO1 rs11544514 1 A 0.008 0 0.0179 0.073 (0.004–1.326) 0.0129
APC rs4987109 5 C 0.009 0 0.0180 0.073 (0.004–1.326) 0.0130
BAG2 rs9370567 6 C 0.093 0.062 0.0198 0.698 (0.472–1.033) 0.0710
RAD50 rs4526098 5 G 0.029 0.011 0.0205 0.453 (0.213–0.964) 0.0354
RAC1 rs6951997 7 G 0.040 0.019 0.0210 0.506 (0.270–0.948) 0.0305
ILKAP rs6431588 2 T 0.146 0.188 0.0214 1.358 (1.049–1.768) 0.0210
GAS6 rs7997328 13 C 0.268 0.320 0.0216 1.427 (1.084–1.877) 0.0110
PSMD11 rs7212835 17 G 0.165 0.127 0.0278 0.739 (0.561–0.968) 0.0270
PIR rs1996173 X T 0.016 0 0.0290 0.053 (0.003–0.933) 0.0032
TXNL1 rs655539 18 C 0.105 0.075 0.0294 0.730 (0.507–1.050) 0.0880
TGFB1 rs2241715 19 T 0.370 0.320 0.0317 0.792 (0.601–1.045) 0.0990
MAPRE1 rs2235760 20 T 0.148 0.113 0.0326 0.714 (0.520–0.982) 0.0370
APC rs1882619 5 C 0.083 0.057 0.0377 0.716 (0.478–1.074) 0.1050
GAS6 rs6602910 13 G 0.389 0.439 0.0399 1.360 (1.021–1.811) 0.0350
MCL1 rs12036617 1 T 0.006 0 0.0400 0.089 (0.005–1.665) 0.0261
MAPRE1 rs242553 20 T 0.497 0.547 0.0401 0.767 (0.566–1.040) 0.0870
MYD88 rs989298 3 A 0.006 0 0.0411 0.090 (0.005–1.684) 0.0270
RBL2 rs17800727 16 G 0.413 0.365 0.0445 0.980 (0.740–1.297) 0.8870
TTC1 rs3733868 5 T 0.068 0.045 0.0449 0.632 (0.407–0.980) 0.0390
TGFB1 rs8110090 19 G 0.068 0.046 0.0457 0.716 (0.461–1.111) 0.1350
GRB2 rs7219 17 G 0.270 0.228 0.0460 0.814 (0.617–1.073) 0.1430
BAG2 rs9885757 6 T 0.270 0.228 0.0465 0.782 (0.594–1.029) 0.0790
ANXA5 and ILKAP in Melanoma Susceptibility
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populations using data from 1000 Genomes Project supports a
possible population structure for rs6854854 (Table 5). These data
suggest the need for a new validation in a population where C
minor allele frequency remains similar to that described in
HapMap for European population. On the other hand, although
using HWE as a screening tool removed part of the SNPs selected
for analysis, SNP rs17718 (out of HW equilibrium and located in
the ANXA5 39UTR) turned out to be significantly associated with
MM. Fardo et al. (2009) found that true disease susceptibility loci
subjected to various patterns of genotype miscalls can be largely
out of HWE and, thus, be candidates for removal before
association testing [30].
After genotypig a total of 1,883 MM cases and 1,358 controls,
SNP rs6431588, located in ILKAP, was a new locus associated with
a higher susceptibility to MM. Therefore, our data suggest that
individuals who possess the T allele in the ILKAP rs6431588 locus
are more likely to develop MM, fitting to an additive model of
inheritance.
The 1000 Genomes database shows that the frequency of the T
allele in rs6431588 varies significantly depending on the
geographical region considered (Table 5). The minor allele of
rs6431588 appears more frequently in the European populations
than in the rest of geographic regions. In fact, it seems that
rs6431588 has a population structure where the frequency of the T
allele increases from Africa towards the North of Europe. Some
findings support the hypothesis that latitudinal genetic diversity
gradients are present in humans and reflect genetic adaptations to
different environmental pressures that have shaped the human
genome [31,32,33]. Latitude appears to provide a good proxy for
the selective pressures that shaped variation in our genome
because it is correlated with different variables like mean winter
and summer temperatures, rainfall or ultraviolet radiation
exposure, which appears to be the predominant environmental
risk factor for MM.
We also have experimentally observed that the levels of ILKAP
gene expression decrease in melanoma cells compared to normal
melanocytes. In this regard, the ILKAP (Integrin-linked kinase-
associated serine/threonine phosphatase 2C) plays a role in the
regulation of diverse processes such as cell cycle progression,
migration and cell death, and appears to have an important role in
oncogenic transformation [34,35,36]. Thus, it is possible that
decreasing ILKAP expression levels favor a constitutive activation
of ILK (Integrin-linked kinase). In its turn, this activation
inactivates instead GSK3bwhich favors the stabilization and
nuclear translocation of b-catenin, which results in the subsequent
activation of the TCF/LEF family of transcription factors that
promote cell survival and proliferation [35]. In fact, a high
activation of ILK is associated with poor outcome in patients with
melanoma [37]. Likewise, low levels of ILKAP may reduce
apoptosis induced by Tumor Necrosis Factor alpha (TNFa) and
the presence of reactive oxygen species (ROS), as well as reduce
the formation of complexes with RSK2 (Ribosomal protein S6
kinase-2) in the nucleus and consequently enhance the expression
of Cyclin D1 (a RSK2 downstream substrate), which ultimately
promotes tumor cell survival and proliferation [36]. Researchers
have thus far considered ILKAP a cytoplasmic protein, however,
its location also in the nucleus opens a window to unknown
functions of ILKAP. Anyway, ILKAP and Annexin A5 functions
are not the main focus of the present work and it would be
necessary to perform experimentally functional analysis to
determine whether the down-regulation of these genes has actually
a role in MM.
On the other hand, despite the emphasis put on functional
analyses of coding SNPs, many SNPs are located in non-coding
Table 2. Cont.
Gene SNP Chrom Controls MA Controls MAF Cases MAF
Fisher
p-
value
OR (95% CI) p-
value
MAPKAPK3 rs11130254 3 G 0.148 0.115 0.0480 0.769 (0.557–1.063) 0.1110
RCC2 rs1204897 1 A 0.207 0.170 0.0486 0.763 (0.573–1.016) 0.0630
Chrom. Chromosome; MA. Minor Allele; MAF. Minor Allele Frequency; OR (95% CI). Odds ratio (95% confidence interval).
doi:10.1371/journal.pone.0095522.t002
ANXA5 and ILKAP in Melanoma Susceptibility
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Table 3. Data of the SNPs analyzed in Phase II.
Gene SNP Chrom
Phase II
Fisher
p-
value
Phase II
OR
(95% CI)
Phase II
p-
value
Phase I
+
II
OR
(95% CI)
Phase I
+
II
p-
value
GAS6 rs7997328 13 0.217 1.253
(0.959–1.636)
0.097 1.336
(1.103–1.617)
0.003
ILKAP rs6431588 2 0.157 1.198
(0.935–1.535)
0.157 1.322
(1.076–1.623)
0.007
APC rs13167522 5 0.236 0.813
(0.583–1.145)
0.236 0.730
(0.569–0.937)
0.013
EEF1D rs4874163 8 0.201 0.831
(0.630–1.101)
0.201 0.757
(0.607–0.944)
0.013
CTNNB1 rs4135385 3 0.941 0.949
(0.721–1.250)
0.711 0.788
(0.648–0.958)
0.016
TTC1 rs3733868 5 0.315 0.744
(0.478–1.158)
0.189 0.685
(0.501–0.935)
0.016
ANXA5 rs6854854 4 0.579 1.122
(0.775–1.623)
0.542 0.787
(0.606–1.022)
0.071
PSMD11 rs7212835 17 0.501 0.907
(0.687–1.202)
0.501 0.823
(0.663–1.022)
0.077
RUVBL1 rs11719889 3 0.901 0.972
(0.743–1.272)
0.837 1.169
(0.964–1.418)
0.112
TTC1 rs6556466 5 0.881 1.078
(0.732–1.586)
0.704 0.839
(0.638–1.105)
0.211
TXNL1 rs655539 18 0.881 1.078
(0.732–1.586)
0.704 0.874
(0.672–1.137)
0.315
WEE1 rs11042431 11 0.914 1.011
(0.761–1.343)
0.941 0.911
(0.744–1.116)
0.367
TGFB1 rs2241715 19 0.724 1.082
(0.827–1.417)
0.565 0.929
(0.766–1.126)
0.452
RBL2 rs17800727 16 0.524 1.126
(0.851–1.490)
0.407 1.047
(0.859–1.277)
0.647
APC rs1882619 5 0.297 1.242
(0.820–1.881)
0.305 0.939
(0.704–1.252)
0.667
Chrom. Chromosome; OR (95% CI) Odds ratio (95% confidence interval).
doi:10.1371/journal.pone.0095522.t003
ANXA5 and ILKAP in Melanoma Susceptibility
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regulatory regions whose exact functions are not yet clear, but that
could be influencing the binding affinity of transcription factors,
and thus they could be exerting an important biological regulatory
role [38]. As we detected no variation within the coding region, we
decided to investigate the 59region of ILKAP, where we detected
12 SNPs. The minor allele frequencies for the 12 SNPs found in
the ILKAP gene promoter region are very similar for all the three
compared populations, except for rs11694064 and rs11695186
whose minor allele frequencies are similar in the European and
African populations but are almost zero in the Asian population,
according to the data collected from 1000 Genomes Project
(Table 5). Although we detected three different haplotypes in the
melanoma cell lines and primary melanocytes studied, a total of six
different haplotypes have been reported worldwide in the 1000
Genomes database, whose genealogical relationship suggests the
existence of two different main lineages (Figure 6). This fact
typically occurs under certain non-neutral conditions such as
under balancing selection. Tajima’s Dtest suggests that this could
actually be the case, which adds evolutionary relevance to the
diversity patterns of ILKAP. We ignore which functional mecha-
nism is shaping ILKAP diversity but it is likely relevant for the
survival of the species and adds meaning to the association of
rs6431588 to melanoma risk.
In summary, we have found that ANXA5 and ILKAP expression
are down-regulated at the transcriptional level in MM cells
compared to melanocytes, suggesting that these two genes could
have an important role in MM. Moreover, we have detected two
SNPs associated with MM in these genes for the first time:
rs6854854 on the ANXA5 gene and rs6431588 on the ILKAP gene.
Both SNPs show different allele frequencies among populations
that differ in geographical location and additionally ILKAP region
is under balancing selection, which suggest the role of the
environment in MM susceptibility.
Materials and Methods
SNPs Genotyping
Ethics statement. All subjects gave written informed consent
and the study was approved by the Ethics Committee of Cruces
and Basurto Universitary Hospitals (Bizkaia, Spain); Gregorio
Maran˜o´n Hospital (Madrid, Spain) and University Clinic Hospital
(Valencia,Spain).
Figure 3. Forest plot showing the odds ratios and 95% confident intervals for the four SNPs most associated with melanoma risk
predisposition. Dots represent odds ratios for each phase, discovery (Phase I) and validations (Phases II and III). The non-shown p-values are not
statistically significant.
doi:10.1371/journal.pone.0095522.g003
ANXA5 and ILKAP in Melanoma Susceptibility
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Genotyping study participants. A total number of 1,883
patients with melanoma and 1,358 cancer-free controls were
genotyped in three phases. Discovery Phase I:A total of 464
patients with malignant melanoma (MM) were recruited from
March 2004 to March 2010 at the Dermatology Services of two
hospitals from the Basque Country: 246 from Basurto University
Hospital (Bilbao, Spain) and 218 from Cruces University Hospital
(Barakaldo, Spain). Similarly, 400 cancer-free controls from the
Figure 4.
ANXA5
and
ILKAP
mRNA expression in human melanoma cell lines and primary melanocytes. A) ANXA5 relative expression
levels. B) ILKAP relative expression levels. Results are expressed as mean relative expression fold 6standard deviation (SD) in the histograms,
calculated on six replicates of each sample. The relative expression fold values are reported in boxes below histograms. The average expression of
primary melanocytes is shown with a dashed line. Statistically significant differences of each melanoma cell line with respect to primary melanocytes:
*p-value #0.05; ** p-value #0.01.
doi:10.1371/journal.pone.0095522.g004
ANXA5 and ILKAP in Melanoma Susceptibility
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Basque Country were recruited. The melanoma patients and
cancer-free controls in this study were of Caucasian origin based
on their self-declared ethnicity and the overall demographics of the
region. Written informed consents were obtained from all the
study participants and the study was approved by both Hospital
Ethics Committees. Validation Phase II:The second phase of
the study, consisting of an independent validation series, was
composed of 507 patients with melanoma recruited from the
Dermatology Services of three Spanish hospitals: 211 from
Gregorio Maran˜o´n General University Hospital (Madrid, Spain),
188 from La Paz University Hospital (Madrid, Spain) and
108 from Ramo´n y Cajal University Hospital (Madrid, Spain). A
total of 383 cancer-free controls were recruited from the same
geographical region (Madrid, Spain). Validation Phase III:The
third phase of the study was composed of 912 patients with
melanoma recruited from the Dermatology Services of five
different hospitals: 92 from Basurto University Hospital (Bilbao,
Spain), 122 from Castellon Province Hospital (Castello´n, Spain),
207 from Hospital Dr. Negrin from Las Palmas (Gran Canaria,
Spain), 166 from Gregorio Maran˜o´ n General University Hospital
(Madrid, Spain), and 373 from Instituto Valenciano de Oncologı
´a
(Valencia, Spain). Similarly, 581 cancer-free controls were
recruited from the geographical regions covered by the hospitals
involved in this third phase of the study.
SNP selection and genotyping. Proteomic analyses were
performed on six melanoma cell lines (A375, Hs294T, HT-144,
1205Lu, WM793B, JSG) and four primary melanocytes (HEMn-
LP, HEMn-MP, HEMn-DP, HEMa-LP). On the other hand,
Affymetrix Human U133A GeneChip arrays were used to analyze
and compare mRNA expression profiles on four melanoma cell
lines isolated from patients’ biopsies in our laboratory (which were
named JEM, JSG1, JSG2, MJOI) and three benign nevi from
patients’ skin lesions isolated also in our laboratory (named FDR,
JPA, RRR).
By combining the information obtained from the results of
protein analysis by two-dimensional gel electrophoresis (2-D
PAGE), Western blot and mRNA expression microarrays
performed previously by our group (data no shown), we produced
a list of candidate genes related to melanoma and selected the
potential SNPs using the program Haploview (www.broadinstitute.
org/haploview) and HapMap Phase 1 & 2 full dataset (http://
hapmap.ncbi.nlm.nih.gov/). Finally, a total of 384 SNPs located
in 88 different genes were chosen related with cancer for their
involvement in cell growth, cell cycle and apoptosis, cell signaling,
transcription and stress response.
In Phase I, SNPs were genotyped using the GoldenGate
Genotyping Assay system according to the manufacturer’s
protocol (Illumina, San Diego, CA, USA) using services from
Progenika Biopharma, Bizkaia, Spain. Genotyping was carried out
using 350 ng of DNA per reaction and genotypes were called
using the proprietary software supplied by Illumina (BeadStudio,
v3.1.3.). In validation phases, 15 SNPs (rs6854854, ANXA5;
rs13167522 and rs1882619, APC; rs4135385, CTNNB1;
rs4874163, EEF1D; rs7997328, GAS2; rs6431588, ILKAP;
rs7212835, PSMD11; rs17800727, RBL2; rs11719889, RUVBL1;
rs2241715, TGFB1; rs3733868 and rs6556466, TTC1; rs655539,
Figure 5. Western blot analysis for Annexin A5 in melanoma cell lines and primary melanocytes. (A) Western blotting shows a decrease
in Annexin A5 protein levels in melanoma cell lines with respect to primary melanocytes; c-tubulin was used as the internal control. (B) Histogram
showing the relative expression levels of Annexin A5 in melanoma cell lines and primary melanocytes.
doi:10.1371/journal.pone.0095522.g005
ANXA5 and ILKAP in Melanoma Susceptibility
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Table 4. Polymorphisms and alleles identified in the promoter region of ILKAP gene in each cell line studied.
Melanoma cell lines Primary melanocytes
Chr2 position A375 Hs294T HT-144 1205Lu WM793B JSG HEMn-LP HEMn-MP HEMn-DP
1
rs13007964 239,114,642 T/T C/C T/T C/C C/C T/T C/C C/C C/C
2
rs13006295 239,114,577 A/A G/G A/A G/G G/G A/A G/G G/G G/G
3
rs13033116 239,114,240 C/C T/T C/C T/T T/T C/C T/T T/T T/T
4
rs13000470 239,114,218 C/C G/G C/C G/G G/G C/C G/G G/G G/G
5
rs11694064 239,113,971 G/G A/A G/G G/G G/G G/G A/A G/G A/A
6
rs13001461 239,113,961 G/G C/C G/G C/C C/C G/G C/C C/C C/C
7
rs34795319 239,113,875 A/A G/G A/A G/G G/G A/A G/G G/G G/G
8
rs35519451 239,113,863 T/T C/C T/T C/C C/C T/T C/C C/C C/C
9
rs11695186 239,113,794 C/C T/T C/C C/C C/C C/C T/T C/C T/T
10
rs34272954 239,113,510 C/C A/A C/C A/A A/A C/C A/A A/A A/A
11
rs13020362 239,113,103 G/G A/A G/G A/A A/A G/G A/A A/A A/A
12
rs34193006 239,113,023 A/A G/G A/A G/G G/G A/A G/G G/G G/G
The SNPs are numbered according to their appearance in the promoter region of ILKAP from the position Chr 2:239,114,642 to the position Chr 2:239,113,023 according to NCBI dbSNP 138. The ancestral allele is in black and the
derived allele in bold.
doi:10.1371/journal.pone.0095522.t004
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Table 5. Minor allele frequency for the SNPs found in the promoter region of ILKAP in different populations (Data from 1000 Genomes Phase I May 2011).
Minor allele frequency
SNP
Gene
Europe (n = 380) Africa (n = 246) Asia (n = 286)
rs6854854 ANXA5 0.075 C 0.278 C 0 C
rs6431588 ILKAP 0.179 T 0.122 T 0.003 T
rs13007964 ILKAP 0.333 T 0.197 T 0.203 T
rs13006295 ILKAP 0.333 A 0.197 A 0.203 A
rs13033116 ILKAP 0.333 C 0.197 C 0.205 C
rs13000470 ILKAP 0.328 C 0.197 C 0.205 C
rs11694064 ILKAP 0.169 A 0.169 A 0.010 A
rs13001461 ILKAP 0.333 G 0.197 G 0.203 G
rs34795319 ILKAP 0.320 A 0.197 A 0.203 A
rs35519451 ILKAP 0.333 T 0.197 T 0.203 T
rs11695186 ILKAP 0.217 T 0.179 T 0.030 T
rs34272954 ILKAP 0.333 C 0.197 C 0.203 C
rs13020362 ILKAP 0.333 G 0.197 G 0.203 G
rs34193006 ILKAP 0.333 A 0.197 A 0.203 A
doi:10.1371/journal.pone.0095522.t005
ANXA5 and ILKAP in Melanoma Susceptibility
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TXNL1; and rs11042431, WEE1) were genotyped using the
KASPAR SNP Genotyping System (KBiosciences, Hoddesdon,
UK). The PCR was carried out according to the manufacturer’s
instructions. The genotype of each sample was determined by
measuring allele-specific final fluorescence in an ABI Prism
7900HT Detection System, using the SDS 2.3 software for allele
discrimination (Applied Biosystems, Foster City, CA, USA). As a
quality control measure, one sample duplicate and a non-template
sample per 96-well plate were included.
Genotyping statistical analysis. For all polymorphisms
studied in Phase I, Fisher’s exact test was used to account for
differences in allele frequencies between HapMap CEU data and
population data from the Basque Country, to test for deviations
from Hardy-Weinberg equilibrium (HWE) among controls, and to
compare allele counts between cases and controls. Correction for
multiple testing was carried out using the Bonferroni method
based on a final set of 314 accepted marker loci. Genotype-related
odds ratios, their corresponding 95% confidence intervals and
associated p-values were estimated via logistic regression using
SPSS v.17 and the online software ‘‘Hardy-Weinberg equilibri-
um’’ (http://ihg2.helmholtz-muenchen.de/cgi-bin/hw/hwa1.pl).
Statistical analysis of the SNPs located in chromosome X was
done with the genotypes of women only. Genotype frequencies
were also compared between MM cases and controls using the
Cochran-Armitage trend test.
ILKAP Expression and Sequencing in Melanomas and
Primary Melanocytes
Cell lines. In the present work, ten melanoma cell lines and
three primary melanocytes were used. The three primary human
melanocytes were purchased from Invitrogen (Cat. No. C-002-5C
for lightly pigmented neonatal foreskin, HEMn-LP; Cat. No. C-
102-5C for moderately pigmented neonatal foreskin, HEMn-MP;
and Cat. No. C-202-5C for darkly pigmented adult foreskin,
HEMn-DP). All primary human melanocytes were grown in
Cascade Medium 254 supplemented with Cascade Human
Melanocyte Growth Supplement (both from Invitrogen; Carlsbad,
CA, USA) in the absence of antibiotics.
Likewise, we cultivated ten different melanoma cell lines. Of
these, A375 (ATCC CRL-1619), Hs294T (ATCC HTB-140), HT-
144 (ATCC HTB-63), WM793B (ATCC CRL-2806), and 1205Lu
(ATCC CRL-2812) were purchased from American Type Culture
Collection (Rockville, MD, USA); RPMI7951 (ACC76), COLO-
800 (ACC193), MEL-HO (ACC62), and MEL-Juso (ACC74) were
obtained from Innoprot (Derio, Bizkaia, Spain); and JSG was
established and characterized in our laboratory from a surgical
primary melanoma as described previously [39]. The melanoma
cell lines were cultured in appropriate medium supplemented with
10% fetal bovine serum (FBS), 2 mM L-glutamin and antibiotics
according to the manufacturer’s instruction. All primary human
melanocytes and melanoma cell lines were cultured at 37uC with
5% CO
2
and 95% humidity.
Gene expression by quantitative real-time PCR (RT-
qPCR). Total RNA was isolated from ten melanoma cell lines
(A375, Hs294T, HT-144, 1205Lu, WM793B, JSG, MEL-HO,
MEL-Juso, COLO-800, RPMI7951) and three primary melano-
cytes (HEMn-LP, HEMn-MP, HEMn-DP) using the RNeasy Mini
kit (Qiagen Inc., Hilden, Germany). For each sample, cDNA was
synthesized from 1 mg total RNA using the iScript
TM
cDNA
Synthesis kit (Bio-Rad Laboratories, Hercules, CA, USA) accord-
ing to the manufacturer’s instructions. Real-time RT-PCR assays
were carried out using an iCycler PCR platform (Bio-Rad
Laboratories, Hercules, CA, USA). The reaction mixture
contained 0.1 ml cDNA from the reverse transcription reaction,
Figure 6. Haplotypes in the promoter region of
ILKAP
gene in different populations obtained from 1000 Genomes Project. Although
we detected three different haplotypes among the melanoma cell lines and the primary melanocytes studied (underlined haplotypes), a total of six
different haplotypes have been reported worldwide. Each haplotype is represented with a circle, whose size is proportional to their frequency in the
global population. The genealogic relationship suggests the existence of two different main lineages, showed in green and red circles.
doi:10.1371/journal.pone.0095522.g006
ANXA5 and ILKAP in Melanoma Susceptibility
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together with forward and reverse specific primers and iQ
TM
SYBRHGreen Supermix (Bio-Rad Laboratories, Hercules, CA,
USA) in a final reaction volume of 20 ml. The PCR reaction began
by heating at 95uC for 10min, followed by 45 cycles of
denaturation at 95uC for 30s, annealing at the corresponding
temperature for each gene (56–61uC) for 20s and extension at
72uC for 30s. Each assay included a negative control with no
template. Expression data were generated from 2 amplification
reactions with samples and controls run in triplicate. Optical data
obtained by real-time PCR were analyzed using the MyiQ Single-
Color Real-Time PCR Detection System Software, Version 1.0
(Bio-Rad Laboratories, Hercules, CA, USA). Melt Curve analysis
of each PCR assay and 1.5% agarose gel electrophoresis analysis
of randomly selected samples were performed to confirm the
specificity of the amplification products. To normalize expression
data obtained from the studied genes, we used the expression of
three different housekeeping genes (ACTB,GAPDH, and RPS15)
and the Gene Expression Macro Software v.1.1 (Bio-Rad
Laboratories, Hercules, CA, USA), where the relative expression
values were computed by the comparative Ct method [40,41].
The sequences of primers used were: ANXA5, forward 59-
CAGCGGATGTTGGTGGTTC-39and reverse 59-CAGCCT-
GAAATAAAGCCTGAG-39;ILKAP, forward 59-AAGTTTG-
TAAAGCCTCTTCGGTG-39and reverse 59-CTCGGTGAT-
GTCGTTCAGGAG-39;ACTB, forward 59-AGATGACCCA-
GATCATGTTTGAG-39and reverse 59-GTCACCGGAGTC-
CATCACG-39;GADPH, forward 59-CCTGTTCGACAGTCA-
GCCG-39and reverse 59-CGACCAAATCCGTTGACTCC-39;
RPS15, forward 59-TTCCGCAAGTTCACCTACC-39and re-
verse 59-CGGGCCGGCCATGCTTTACG-39.
ILKAP sequencing. ILKAP was sequenced in ten melanoma
cell lines (A375, Hs294T, HT-144, 1205Lu, WM793B, JSG,
MEL-HO, MEL-Juso, COLO-800, RPMI7951) and three
primary melanocytes (HEMn-LP, HEMn-MP, HEMn-DP).
DNA was amplified by PCR with specific primers and using the
reaction mix ImmoMix
TM
Red (Gentaur, Kampenhout, Belgium)
according to the following protocol: a 10min denaturation at
95uC, 35 three-step cycles (95uC for 30s, 56–60uC for 30s, and
72uC for 1min), and 10min at 72uC in an iCycler PCR platform
(Bio-Rad Laboratories, Hercules, CA, USA). The removal of the
unincorporated deoxynucleotide triphosphates and primers was
performed using High Pure PCR Product Purification kit (Roche
Molecular Biochemicals, Madrid, Spain). The purified DNA and
3.2 pmol of either the forward or reverse primer were used in
standard cycle sequencing reactions with an ABI PRISM BigDye
Terminator kit and run on an ABI PRISM 310 genetic analyzer
(both PE Applied Biosystems, Foster City, CA). The analysis and
alignment of sequences were performed using Chromas software
and the BioEdit Sequence alignment Editor and the reference
sequence from UCSC Genome Browser website, GRCh37/hg19
(http://www.genome.ucsc.edu/) and NCBI dbSNP 138 (http://
www.ncbi.nlm.nih.gov/snp/). The sequences of primers used for
ILKAP promoter region sequencing were: first pair, forward 59-
TCTTTGTCTCCCCATCAACC-39and reverse 59-
ATTCTGGCCAATTTCGATCA-39; second pair, forward 59-
TTCCAACCCTGCAATAAACG-39and reverse 59-
TTCTGGAGCTCTTGCCATCT-39. The sequences of primers
used for the sequencing of ILKAP exons were: forward 59-
TGAGTGTCTGTCGCTGCTG-39and reverse 59-AAGTCAA-
TACCATGCGTGC-39. Genomic DNA was used for ILKAP
promoter region sequencing, while cDNA was used for the
sequencing of ILKAP exons.
Tajima’s Dtest. The variation of nucleotide patterns from
the neutral expectation was tested by the Tajima’s Dtest using
DnaSP v.5.10.1. Gene diversity is controlled by the parameter
theta (h=4 N
e
m, where N
e
is the effective population size and m
the per generation mutation rate). Several sample- based
estimators of theta (h) exist, all based on the site-frequency
spectrum of the mutations (SFS), that is, the distribution of the
proportion of sites where the mutant is at frequency x. Tajima’s D
test compares h
k
and h
p
asking about the occurrence of rare and
common variants [42]. This test takes into account the number of
nucleotide positions at which a polymorphism is found or,
equivalently, the number of segregating sites, k, and the average
per nucleotide diversity, p. Using some mathematical expressions,
if the nucleotide sequence variation among our haplotypes is
neutral and the population from which we sampled is in
equilibrium with respect to drift and mutation, then Tajima’s D
test should be indistinguishable from zero. If it is either negative or
positive, we can infer that there’s some departure from the
assumptions of neutrality and/or equilibrium.
A region of 66 Kb (chr2:239,066,043–239,132,324 according to
UCSC Genome Browser website, GRCh37/hg19), including the
promoter and coding region of ILKAP gene, was analyzed and
compared among European, Asian and African populations from
1000 Genomes Project. Standard coalescent simulations, as
implemented in DnaSP, were used to estimate the statistical
significance of the Dvalues.
Western blot. Melanoma cells (A375, Hs294T, HT-144,
1205Lu, WM793B, JSG, MEL-HO, MEL-Juso, COLO-800,
RPMI7951) and primary melanocytes (HEMn-LP, HEMn-MP,
HEMn-DP) were harvested by trypsinization, washed with PBS
and lysed in RIPA lysis buffer (80 mM Tris-HCl pH 8, 150 mM
NaCl, 1% NP 40, 0.5% sodium deoxycholate, 0.1% SDS)
containing Protease Inhibitor Cocktail (Sigma-Aldrich Quimica,
S.A., Madrid, Spain) for 15 minutes on ice. Lysates were then
cleared by centrifugation at 10,000 g for 5 minutes and total
protein concentration was determined. Fifty micrograms of total
proteins from each sample were resolved by electrophoresis on an
SDS-polyacrylamide gel and then transferred onto a nitrocellulose
membrane (Whatman GmbH, Dassel, Germany). The blots were
incubated with PBS containing 5% non-fat milk and 0.1% Tween-
20 for 1 hour to block nonspecific binding, and then incubated
with an appropriate dilution of primary antibody at 4uC for
overnight. The primary antibodies used were anti-human Annexin
A5 (ab54775) and c-tubulin (ab11320) antibodies (Abcam, Inc,
Cambridge, CA). After washing, membranes were incubated for
1 hour with horseradish peroxidase-linked secondary antibody.
Finally, proteins were visualized by enhanced chemiluminescence
using the SuperSignalHWest Pico Chemiluminescent Substrate
(Thermo Scientific, Rockford, IL, USA) and the intensity of each
band was measured using ImageJ software.
Supporting Information
File S1 Table S1. SNPs removed in the discovery Phase I of the
genotyping study. Table S2. List of 314 successfully genotyped
SNPs, HapMap_CEU MAF, Spanish MAF, and HWE p-value.
Table S3. Minor allele frequency in different populations for the
8 SNPs appearing as outliers in Figure 1 (Data from 1000
Genomes Phase I May 2011).
(DOC)
Acknowledgments
We thank SGIker, General Service of Genomic and Proteomic of the
University of the Basque Country for assistance with DNA sequencing.
ANXA5 and ILKAP in Melanoma Susceptibility
PLOS ONE | www.plosone.org 14 April 2014 | Volume 9 | Issue 4 | e95522
Author Contributions
Conceived and designed the experiments: MDB SA. Performed the
experiments: YA-B. Analyzed the data: YA-B SA GR. Contributed
reagents/materials/analysis tools: YA-B MI-V MP-C. Wrote the paper:
YA-B. Conceived of and are responsible for the selection and examination
of the patients and obtained tumor information of all participants: JG JAR-
N AS-D JMC GC MM-G CG-F EN. Critical revision of the manuscript:
SA MDB GR CM-C AA GP-Y.
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