Genetic epidemiology of glioblastoma multiforme: confirmatory and new findings from analyses of human leukocyte antigen alleles and motifs.
ABSTRACT Human leukocyte antigen (HLA) class I genes mediate cytotoxic T-lymphocyte responses and natural killer cell function. In a previous study, several HLA-B and HLA-C alleles and haplotypes were positively or negatively associated with the occurrence and prognosis of glioblastoma multiforme (GBM).
As an extension of the Upper Midwest Health Study, we have performed HLA genotyping for 149 GBM patients and 149 healthy control subjects from a non-metropolitan population consisting almost exclusively of European Americans. Conditional logistic regression models did not reproduce the association of HLA-B*07 or the B*07-Cw*07 haplotype with GBM. Nonetheless, HLA-A*32, which has previously been shown to predispose GBM patients to a favorable prognosis, was negatively associated with occurrence of GBM (odds ratio=0.41, p=0.04 by univariate analysis). Other alleles (A*29, A*30, A*31 and A*33) within the A19 serology group to which A*32 belongs showed inconsistent trends. Sequencing-based HLA-A genotyping established that A*3201 was the single A*32 allele underlying the observed association. Additional evaluation of HLA-A promoter and exon 1 sequences did not detect any unexpected single nucleotide polymorphisms that could suggest differential allelic expression. Further analyses restricted to female GBM cases and controls revealed a second association with a specific HLA-B sequence motif corresponding to Bw4-80Ile (odds ratio=2.71, p=0.02).
HLA-A allelic product encoded by A*3201 is likely to be functionally important to GBM. The novel, sex-specific association will require further confirmation in other representative study populations.
- SourceAvailable from: James Tang[Show abstract] [Hide abstract]
ABSTRACT: Research in the past two decades has generated unequivocal evidence that host genetic variations substantially account for the heterogeneous outcomes following human immunodeficiency virus type 1 (HIV-1) infection. In particular, genes encoding human leukocyte antigens (HLA) have various alleles, haplotypes, or specific motifs that can dictate the set-point (a relatively steady state) of plasma viral load (VL), although rapid viral evolution driven by innate and acquired immune responses can obscure the long-term relationships between HLA genotypes and HIV-1-related outcomes. In our analyses of VL data from 521 recent HIV-1 seroconverters enrolled from eastern and southern Africa, HLA-A*03:01 was strongly and persistently associated with low VL in women (frequency = 11.3 %, P < 0.0001) but not in men (frequency = 7.7 %, P = 0.66). This novel sex by HLA interaction (P = 0.003, q = 0.090) did not extend to other frequent HLA class I alleles (n = 34), although HLA-C*18:01 also showed a weak association with low VL in women only (frequency = 9.3 %, P = 0.042, q > 0.50). In a reduced multivariable model, age, sex, geography (clinical sites), previously identified HLA factors (HLA-B*18, B*45, B*53, and B*57), and the interaction term for female sex and HLA-A*03:01 collectively explained 17.0 % of the overall variance in geometric mean VL over a 3-year follow-up period (P < 0.0001). Multiple sensitivity analyses of longitudinal and cross-sectional VL data yielded consistent results. These findings can serve as a proof of principle that the gap of "missing heritability" in quantitative genetics can be partially bridged by a systematic evaluation of sex-specific associations.Human genetics. 06/2014;
- [Show abstract] [Hide abstract]
ABSTRACT: The majority of killer cell immunoglobin-like receptor (KIR) genes are detected as either present or absent using locus-specific genotyping technology. Ambiguity arises from the presence of a specific KIR gene since the exact copy number (one or two) of that gene is unknown. Therefore, haplotype inference for these genes is becoming more challenging due to such large portion of missing information. Meantime, many haplotypes and partial haplotype patterns have been previously identified due to tight linkage disequilibrium (LD) among these clustered genes thus can be incorporated to facilitate haplotype inference. In this paper, we developed a hidden Markov model (HMM) based method that can incorporate identified haplotypes or partial haplotype patterns for haplotype inference from present-absent data of clustered genes (e.g., KIR genes). We compared its performance with an expectation maximization (EM) based method previously developed in terms of haplotype assignments and haplotype frequency estimation through extensive simulations for KIR genes. The simulation results showed that the new HMM based method outperformed the previous method when some incorrect haplotypes were included as identified haplotypes and/or the standard deviation of haplotype frequencies were small. We also compared the performance of our method with two methods that do not use previously identified haplotypes and haplotype patterns, including an EM based method, HPALORE, and a HMM based method, MaCH. Our simulation results showed that the incorporation of identified haplotypes and partial haplotype patterns can improve accuracy for haplotype inference. The new software package HaploHMM is available and can be downloaded at http://www.soph.uab.edu/ssg/files/People/KZhang/HaploHMM/haplohmm-index.html.Frontiers in Genetics 01/2014; 5:267.
- [Show abstract] [Hide abstract]
ABSTRACT: Both genetic and environmental factors are thought to be causal in gliomagenesis. Several genes have been implicated in glioma development, but the putative role of a major immunity-related gene complex member, immunoglobulin heavy chain γ (IGHG) has not been evaluated. Prior observations that IGHG-encoded γ marker (GM) allotypes exhibit differential sensitivity to an immunoevasion strategy of cytomegalovirus, a pathogen implicated as a promoter of gliomagenesis, has lead us to hypothesize that these determinants are risk factors for glioma. To test this hypothesis, we genotyped the IGHG locus comprising the GM alleles, specifically GM alleles 3 and 17, of 120 glioma patients and 133 controls via TaqMan® genotyping assay. To assess the associations between GM genotypes and the risk of glioma, we applied an unconditional multivariate logistic regression analysis adjusted for potential confounding variables. In comparison to subjects who were homozygous for the GM 17 allele, the GM 3 homozygotes were over twice as likely, and the GM 3/17 heterozygotes were over three times as likely, to develop glioma. Similar results were achieved when analyzed by combining the data corresponding to alleles GM 3 and GM 3/17 in a dominant model. The GM 3/17 genotype and the combination of GM 3 and GM 3/17 were found to be further associated with over 3 times increased risk for high-grade astrocytoma (grades III-IV). Allele frequency analyses also showed an increased risk for gliomas and high-grade astrocytoma in association with GM 3. Our findings support the premise that the GM 3 allele may present risk for the development of glioma, possibly by modulating immunity to cytomegalovirus.Oncoimmunology. 01/2014; 3:e28609.
Genetic Epidemiology of Glioblastoma Multiforme:
Confirmatory and New Findings from Analyses of Human
Leukocyte Antigen Alleles and Motifs
Wei Song1, Avima M. Ruder2, Liangyuan Hu1, Yufeng Li3, Rong Ni3, Wenshuo Shao1, Richard A.
Kaslow1,3, MaryAnn Butler2, Jianming Tang3*
1Department of Epidemiology, University of Alabama at Birmingham, Birmingham, Alabama, United States of America, 2National Institute for Occupational Safety and
Health, Centers for Disease Control and Prevention, Cincinnati, Ohio, United States of America, 3Department of Medicine, University of Alabama at Birmingham,
Birmingham, Alabama, United States of America
Background: Human leukocyte antigen (HLA) class I genes mediate cytotoxic T-lymphocyte responses and natural killer cell
function. In a previous study, several HLA-B and HLA-C alleles and haplotypes were positively or negatively associated with
the occurrence and prognosis of glioblastoma multiforme (GBM).
Methodology/Principal Findings: As an extension of the Upper Midwest Health Study, we have performed HLA genotyping
for 149 GBM patients and 149 healthy control subjects from a non-metropolitan population consisting almost exclusively of
European Americans. Conditional logistic regression models did not reproduce the association of HLA-B*07 or the B*07-Cw*07
haplotype with GBM. Nonetheless, HLA-A*32, which has previously been shown to predispose GBM patients to a favorable
prognosis, was negatively associated with occurrence of GBM (odds ratio=0.41, p=0.04 by univariate analysis). Other alleles
(A*29, A*30, A*31 and A*33) within the A19 serology group to which A*32 belongs showed inconsistent trends. Sequencing-
based HLA-A genotyping established that A*3201 was the single A*32 allele underlying the observed association. Additional
evaluation of HLA-A promoter and exon 1 sequences did not detect any unexpected single nucleotide polymorphisms that
could suggest differential allelic expression. Further analyses restricted to female GBM cases and controls revealed a second
association with a specific HLA-B sequence motif corresponding to Bw4-80Ile (odds ratio=2.71, p=0.02).
Conclusions/Significance: HLA-A allelic product encoded by A*3201 is likely to be functionally important to GBM. The
novel, sex-specific association will require further confirmation in other representative study populations.
Citation: Song W, Ruder AM, Hu L, Li Y, Ni R, et al. (2009) Genetic Epidemiology of Glioblastoma Multiforme: Confirmatory and New Findings from Analyses of
Human Leukocyte Antigen Alleles and Motifs. PLoS ONE 4(9): e7157. doi:10.1371/journal.pone.0007157
Editor: Pedro R. Lowenstein, Cedars-Sinai Medical Center and University of California Los Angeles, United States of America
Received April 7, 2009; Accepted September 1, 2009; Published September 23, 2009
This is an open-access article distributed under the terms of the Creative Commons Public Domain declaration which stipulates that, once placed in the public
domain, this work may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose.
Funding: This work was supported by grants CA128059, CA097257 and CA097247 from the National Cancer Institute. JT is the recipient of an independent
scientist award (K02 AI076123) from National Institute of Allergy and Infectious Diseases. The funders had no role in study design, data collection, data analyses,
decision to publish, or preparation of this manuscript.
Competing Interests: The authors have declared that no competing interests exist.
* E-mail: email@example.com
the most common and most severe form of primarybrain cancer, with
[1–7]. In the United States, age-adjusted GBM rates are 2.5 times
higher in European Americans than in African Americans and 60%
higher in men than in women [1,2,8,9]. With varying degrees of
certainty, additional factors associated with GBM range from
agents, and variations in genes that regulate DNA repair, carcinogen
metabolism, cell cycle, or inflammatory and immune responses .
Overall, genetic, developmental and environmental factors are all
likely contributors to the etiology and pathogenesis of GBM.
Genes encoding the highly polymorphic human leukocyte
antigens (HLA) are known to mediate inflammatory diseases,
immune disorders, infectious diseases, and human malignancies
[11,12]. These and other clustered genes form the major
histocompatibility complex (MHC) on the short arm of chromo-
some 6 (6p21.3) and most have dual roles in innate and adaptive
immune responses. Multiple HLA alleles and haplotypes have
been associated with GBM [13–16] as well as other malignancies,
including nasopharyngeal carcinoma [17–19] and cervical cancer
[20–22]. Some of these reported associations have been partially
replicated and/or validated in studies of immune function
[23–25], while most appear to be population- or study-specific
findings with largely dubious pathogenetic implications.
In previous work based on 155 GBM patients and 157 healthy
control subjects recruited from the San Francisco Bay area, several
HLA factors have been associated with GBM occurrence and its
prognosis . Our follow-up study in a different population now
provides further evidence that at least one HLA-A allele known as
A*3201 may well be a favorable allele that deserves further
PLoS ONE | www.plosone.org1September 2009 | Volume 4 | Issue 9 | e7157
Overall characteristics of the study population
Nested within the Upper Midwest Health Study (UMHS) [26,27],
149 GBM patients and 149 healthy control subjects (Table 1) were
selected based on 1:1 matching for four criteria, i.e., ethnicity, sex,
age and county of residence. As a result, patients and controls were
highly comparable in ethnic background, age and sex ratio, although
four African American (AA) patients had to be paired with European
Americans (EA) controls. Body mass index, which was not used as a
selection criterion, was also quite similar between GBM patients and
healthy control subjects (p=0.469). These characteristics formed the
basis for conditional logistic regression analyses of HLA genotypes in
the paired GBM patients and controls.
Analyses of HLA alleles and haplotypes
PCR-based genotyping for three HLA class I genes (HLA-A, -B
and –C) and one class II locus (HLA-DRB1) was successful for all
149 case-control pairs. Within each locus, the global distribution of
common alleles (frequency $0.01 in any given population) was
similar (p.0.50) between the UMHS population and another
population studied earlier (Table 2), as were the patterns of
pairwise linkage disequilibrium (LD) among alleles from different
loci (data not shown). Minor differences were noted for a few
individual alleles, including A*32, B*14, B*55, and Cw*08
(p#0.025 by univariate Chi-square or Fisher exact tests).
GBM patients and healthy controls were compared for 11 HLA-
A, 14 HLA-B, 10 HLA-C and 11 HLA-DRB1 alleles in a total of 46
univariate models. Three variants, i.e., A*32 (n=29), B*14
(n=11), and B*40 (n=46), were found to be over-represented
among the healthy control group (p=0.030 to 0.054) (Table 3),
while Cw*05 (n=50) was more common in GBM patients (22.2%)
than in controls (11.4%) (odds ratio=2.21, 95% confidence
interval=1.17–4.17). In contrast, no other alleles highlighted in
earlier studies [13–16] showed any appreciable trend for positive
or negative associations with the occurrence of GBM. Further
analyses of local and extended haplotypes in this study population
also failed to detect any notable relationships.
Multivariable analyses dismissed B*14 and B*40 as independent
factors (adjusted p=0.070 and 0.118, respectively). In the reduced
multivariable model, A*32 retained its negative association with
GBM (adjusted OR=0.39, 95% CI=0.16–0.91, and p=0.024),
with Cw*05 being the only variant showing positive association
(adjusted OR=2.48, 95% CI=1.24–4.97, and p=0.011). Sequenc-
ing of HLA-A exons 2 to 4 revealed that A*3201 was the only A*32
allele in the study population. Similar sequencing strategy confirmed
that Cw*0501 was the only allele representing Cw*05.
Insights gained from HLA-A promoter and exon 1
SNPs at frequency $0.02 (Figure1a); five had no known reference
sequence (rs) number in the dbSNP database (version 126). Strong
pairwise LD among some SNPs produced four apparent haplotype
blocks, each having 3–23 SNPs (Figure S1). Regardless of DNA
source (GBM patients or control subjects), A*3201 had six unique
SNPs (Figure 1b), one of which (rs2230954) is nonsynonymous
(Ser to Leu substitution) in the first exon. The other five (rs9260090,
rs9260100, rs9260102, rs9260105 and rs2735113) are around the
core promoter sequences, without any known or predictable
functional attributes. DNA sequencing also allowed the assembly
of homozygous sequences for 10 common HLA-A alleles
(Figure 1b). A neighbor-joining tree (Figure S2) revealed
topologies that were identical to known taxonomic hierarchy for
their entire open reading frames .
Analyses of HLA class I sequence motifs
HLA-A, -B, and –C sequence motifs were defined by 43, 66, and
28 specific probes in the respective SSO assays. Most (81% to 89%)
of them had enough inter-individual variations to be suitable for
comparative analyses. The presence of the HLA-A motif defined by
SSO probe 34 was negatively associated with GBM (OR=0.50,
95% CI=0.27–0.91, and p=0.024) (Table 4). Common allele
groups known to carry this motif include A*23, A*29, A*31, A*32
and A*33 (A*74 was not detected). With the exception of A*23,
these allele groups all belong to the A19 serology group .
However, individuals whose DNA bound to SSO probe 34 in the
absence of A*32 (A*3201) were no less likely to be cases than
controls (OR=0.59, 95% CI=0.27–1.29, and p=0.183), because
modest trends seen with A*23 (8 patients versus 4 controls), A*31 (6
versus 4) and A*33 (3 versus 0) was reversed by A*29 (6 versus 9).
Likewise, a common HLA-B motif defined by SSO probe 62 had a
p=0.015). Multiple HLA-B alleles (e.g., B*14, B*15, B*35, B*44,
B*45, B*49, B*50, B*51, B*53, and B*57) are known to have this
motif, but none of these alleles were individually associated with
GBM (p.0.15 in all tests).
Despite reduced statistical power, separate analyses of males
and females revealed three more sequence motifs that appeared to
be associated with GBM in females only (Table 4). The HLA-A
sequence motif defined by SSO probe 42 showed a negative
association (OR=0.35, 95% CI=0.15–0.83, and p=0.017).
Relatively common alleles with this motif include A*01, A*11,
A*25, and A*26. HLA-B probes 30 and 34 had identical positive
association (OR=2.71, 95% CI=1.14–6.46, and p=0.024)
because they were in exclusive (100%) LD (r2=1.0). Probe 34
corresponds to a subset of alleles having the Bw4 serological
specificity, including B*15 (B*1510 and B*1517), B*39, B*49,
B*51, B*53, and B*57. Multivariable analyses supported the
independent associations of HLA-A and HLA-B motifs captured by
probes 42 and 34, respectively (adjusted p#0.017) (Table 4).
Among the specific sequence motifs of interest, HLA-A probes
34 and 42 corresponds to four codons, 149-GCG, 151-CGT, 152-
GTG and 153-GCG, and three codons, 161-SAG (where S is
either G or C), 163-CGG and 165-GTG, respectively. HLA-B
probe 30 detects four codons (75-CGA, 77-AAC, 78-CTG and 80-
Table 1. Characteristics of glioblastoma multiforme (GBM)
patients and healthy control subjects selected from the Upper
Midwest Health Study.
GBM patientsHealthy controlsp
Number of subjects149 149_
Sex ratio: F/M 61/88 (0.69)61/88 (0.69)_
Body mass index (kg/m2)
P values$0.75 are omitted (–); EA=European American, F=female, M=male,
SD=standard deviation, SE=standard error of the mean.
HLA and Glioblastoma
PLoS ONE | www.plosone.org2 September 2009 | Volume 4 | Issue 9 | e7157
ATC), which have partial overlap with three codons (80-ATC, 81-
GCG and 83-CGC) detected by HLA-B probe 34. Thus, HLA-B
probes 30 and 34 share specificity for HLA-B codon 80-ATC
(AUC in RNA, for Ile). Four more codons defined by the HLA-B
probe 62 are 161-GAG (for Glu), 162-GGC (Gly), 163-CTG (Leu)
and 164-TGC (Cys).
Genotypes of two SNPs with broad implications for
Consistent with results from the CEPH DNA samples analyzed
by the International HapMap Project, SNPs rs401681 and
rs2736098 in our study population had the minor allele as T
and A, respectively. The frequency of rs401681[T] was 0.409 in
healthy controls versus 0.440 in GBM cases (p.0.65). The
rs401681[C] allele has been positively associated with multiple
cancers (OR ,1.2) but negatively associated with melanoma
(OR=0.88) . Here, rs401681[C] was slightly less frequent in
GBM cases than healthy controls (OR=0.88 in test of allele
frequency). For SNP rs2736098, the frequency of its minor allele A
was 0.338 in healthy controls versus 0.288 in GBM cases (p.0.35),
in contrast with its positive association with other cancers .
Overall, none of the differences in SNP alleles and genotypes
(diplotypes) was close to statistical significance.
In several ways, our study of GBM patients and healthy controls
from the Upper Midwest Health Study (UMHS) refined and
extended findings based on another cohort from the San Francisco
Bay area . First, most HLA factors (e.g., B*07, B*13, and
Cw*01) revealed by the previous study could not be confirmed here,
so their role in the origins of GBM, if any, is unlikely to be
generalizable. Second, HLA-A*32 (A*3201) was the only allele that
was favorable in both the San Francisco population (prolonged
survival) and the Midwest population (protection from disease).
Third, specificmotifs in the HLA-A and HLA-B open readingframes
appeared to be prominent factors in the Midwest cohort, especially
in females. Statistically, age was the most significant difference
(p,0.0001) between the San Francisco population (mean6standard
deviation=58612) and the Midwest population (52613), which
might have contributed to inconsistent findings from these cohorts.
Environmental factors, including those related to farming [26,31],
could further distinguish the Midwest cohort from the San
Table 2. Distribution of relatively common HLA-A, -B, -C, and -DRB1 variants in similar case-control populations studied here (this
study, N=298) and elsewhere (N=312).
HLA-A allele frequency HLA-B allele frequency HLA-C allele frequency HLA-DRB1 allele frequency
AllelesElsewhere This studyAlleles Elsewhere This studyAllelesElsewhere This studyAllelesElsewhere This study
A*010.172 0.171B*07 0.1300.128 Cw*010.032 0.022*010.104 0.106
A*02 0.2890.310B*08 0.0960.111Cw*02 0.045 0.052 *030.1310.114
A*030.111 0.141B*130.0190.032Cw*030.1310.153 *040.1490.161
A*11 0.0690.057B*140.0420.018Cw*040.1120.111 *070.117 0.134
A*240.0830.079B*18 0.0550.052 Cw*060.0880.109 *090.0100.008
A*250.0220.025B*270.0370.042 Cw*070.293 0.310*100.013 0.012
A*26 0.034 0.022B*350.093 0.087 Cw*080.050 0.017 *110.103 0.092
A*290.039 0.025B*370.018 0.027Cw*120.0660.070 *120.018 0.018
A*300.0300.022 B*38 0.018 0.013Cw*140.016 0.008 *130.1410.121
A*31 0.0180.017 B*40 0.0670.082 Cw*150.040 0.022*14 0.026 0.027
A*32 0.026 0.050B*44 0.130 0.153Cw*16 0.034 0.030*15 0.1350.149
A*33 0.0180.005B*49 0.0210.008 Cw*17 0.0110.010 *16 0.0190.017
A*68 0.0500.045 B*510.0580.042 Others 0.0020
Others 0.008 0.011B*52 0.0160.020
Previously studied population consists of European Americans from the San Francisco Bay area . Rare alleles at each locus are grouped together (others), with
number of chromosomes (2N) used as the denominator in all tabulations. Between study populations, statistically significant differences (p#0.025) are seen with A*32,
B*14, B*55, and Cw*08.
Table 3. Univariate analyses of HLA variants showing clear
trend for association with occurrence of glioblastoma
multiforme (GBM) in the Upper Midwest Health Study.
p OR95% CI
A*32 9 (6.0)20 (13.4)0.0400.410.18–0.94
B*14 2 (1.3)9 (6.0)0.0540.210.05–0.99
B*4016 (10.7)30 (20.1)0.0300.480.25–0.92
Cw*0533 (22.2)17 (11.4)0.0142.211.17–4.17
Numbers below each group correspond to n (%) and p values are based on
maximum likelihood Chi-square test or Fisher exact test (for B*14 only) for 149
GBM patients and 149 healthy controls. OR=odds ratio, CI=confidence
HLA and Glioblastoma
PLoS ONE | www.plosone.org3 September 2009 | Volume 4 | Issue 9 | e7157
Figure 1. DNA polymorphisms within HLA-A promoter and exon 1 sequences. A 1000-bp region (Panel a) has been sequenced for select
population samples. Upper case letters are cDNA sequences (part of the open reading frame); the translation start codon (ATG) is indicated by a
horizontal arrow. STR denotes a short tandem repeat sequence that has either three or four AAC repeats. Five transcription factor-bindings sites
(TFBS) are also indicated. Within this fragment, 69 single nucleotide polymorphisms (SNPs) (bold and underlined) have already been reported in the
literature. Those (n=19) not confirmed in this work are shaded grey. The five novel SNPs are designated as ‘‘New’’ (underlined nucleotides below
vertical lines). The SNPs unique to A*3201 are marked by vertical arrows before their respective reference sequence (rs) numbers (from dbSNP
database, version 126). In panel b, 53 informative SNPs (minor allele frequency $0.02) are linked to 11 HLA alleles found in homozygous state.
HLA and Glioblastoma
PLoS ONE | www.plosone.org4September 2009 | Volume 4 | Issue 9 | e7157
Francisco cohort. Minor genetic heterogeneity can also offer some
alternative explanations, because the frequencies of several HLA-B
and HLA-C alleles differed between the two study populations
(Table 2). Overall, discordant observations were apparent between
the two cohorts despite their close similarity in ethnic background
and sample size (statistical power), suggesting that other aspects of
study design and population characteristics can be critical to
Aside from the question about relative impact of specific HLA
alleles or motifs on GBM in European Americans, our study here
and previous work  both indicated that the association signals
primarily came from the HLA class I region, which, if real, would
imply the involvement of cytotoxic T-lymphocyte (CTL) and/or
natural killer (NK) cell responses. In that regard, the Bw4 sequence
motif (Bw4-80Ile, defined by HLA-B probe 34) associated with
increased risk for GBM in females is of particular interest, due to
its direct role in NK cell activities. Evaluation of two killer
KIR3DL1, could shed further light on the Bw4 association because
these receptors directly or indirectly interact with the Bw4 motif to
activate or inhibit NK cell function [32–34]. Meanwhile, analyses
presented here and elsewhere  did not provide any corrobo-
ration of positive findings on HLA-DRB1 genotypes reported in
small cohorts [15,35]. Therefore, HLA class II alleles that dictate T-
helper cell function lacked appreciable impact on GBM.
The importance of HLA class I molecules to cancer immunol-
ogy has been well recognized in experimental studies . In brain
cancer, low expression of classical HLA class I genes (HLA-A, -B,
and –C)  coupled with up-regulation of nonclassical genes (e.g.,
HLA-E and HLA-G) likely contributes to immune escape by tumor
cells with various somatic mutations [37–39]. On the other hand, a
study of long-term survivors of anaplastic astrocytoma, which is
closely related to GBM , has suggested that protective CTLs
can effectively respond to glioma-associated antigens . CTLs
have indeed been detected in the peripheral blood of GBM
patients  and antigenic epitopes derived from the alpha 2
chain of interleukin-13 receptor can be presented by HLA-A*02
(A*0201) and A*24 [42–44]. It remains to be seen if HLA-A*3201
is advantageous in presenting oncogenic antigens commonly seen
in glioma cells [45–49]. Patients of African ancestry can be
particularly informative as HLA-A alleles in the A19 serology
group are most common in African Americans [50,51]. Epidemi-
ological study of patients with other major forms of brain cancer
(e.g., anaplastic astrocytoma) should also help identify favorable
HLA factors, which can lead to critical information about the
underlying protective mechanisms.
HLA allelic diversity is earmarked by the dominance of
nonsynonymous SNPs in the open reading frames, often as a
consequence of balancing selection by a variety of human
infectious diseases . Such allelic diversity may be equally
advantageous in the battle with cancerous cells that frequently
switch antigenic repertoire . Thus, in addition to examining
the A*3201 open reading frame using routine HLA typing
methods, we also partially surveyed regulatory sequences because
allele-specific immune surveillance can further depend on allelic
expression profile. Our work did reveal five SNP variants in the
HLA-A promoter region that are likely specific to the A*3201
allele, but none of these is within known transcription factor-
binding sites. Expanded analyses of other non-coding sequences
around the HLA-A locus may help determine whether regulatory
sequences beyond the promoter region can separate favorable
from unfavorable or neutral alleles, especially when closely related
alleles (e.g., A*3201 and others in the A19 serology group) differ in
their impact on disease.
In other brain tumor studies that have dealt with candidate
genes outside the HLA system (reviewed in ref. 10), the
magnitudes of genetic associations (usually with SNP genotypes)
have generally been modest. Further evidence from SNP-based
genome-wide association studies has been equally unremarkable
(less than 2-fold difference), including the recent implication of two
SNPs (rs401681 and rs2736098) consistently but weakly associated
with a variety of human malignancies , as well as other SNP
genotypes detected in genome-wide association studies of glioma
[54,55]. Indeed, our analyses of rs401681 and rs2736098
produced only minimal evidence that allele C of the intronic
SNP rs401681 (at the CLPTM1L locus) is probably unfavorable in
In summary, case-control studies described here and earlier 
have yielded clues to potential involvement of HLA class I alleles
and motifs in GBM. The findings are still difficult to interpret
because none of them can be immediately related to other reports
on solid tumors. Of note, HLA-A*3201 (A19 or A32 by serology) is
a relatively infrequent allele, with an overall carriage (‘‘pheno-
type’’) frequency less than 10% (allele frequency ,0.05) in most
populations [29,50,56]. Lack of information about this allele is not
surprising, because even studies of adequate sample size (i.e.,
hundreds to thousands of cases and controls) can have limited
statistical power if the association is weak or obscured by other
factors. Bw4-80Ile, on the other hand, is a common variant;
hypothesis about Bw4-80Ile can be readily tested. Large
collaborative efforts, as promoted by the Brain Tumor Epidemi-
ology Consortium , are expected to expedite confirmatory
studies of HLA alleles and motifs in other well-defined cohorts,
especially those of diverse ethnic backgrounds as well as wide
geographic coverage. Recognition of GBM as a molecularly
heterogeneous cancer [4,7] also calls for the separate analyses of
primary and secondary glioblastoma, as the latter is closely related
to anaplastic astrocytoma (Grade III glioma) .
Materials and Methods
We studied unrelated subjects in the Upper Midwest Health
Study [26,27], which enrolled cancer patients and frequency-
Table 4. Individual HLA class I sequence motifs associated
with the occurrence of glioblasotma multiforme (GBM) in the
Upper Midwest Health Study population (N=298 subjects) or
in the female subset (61 GBM patients and 61 healthy
In all subjects
HLA-A, probe 3426 (17.5)42 (28.2)0.0240.50 0.27–0.91
HLA-B, probe 62114 (76.5) 94 (63.1)0.0151.87 1.13–3.10
In females only
HLA-A, probe 4224 (39.3)37 (60.7)0.017 0.350.15–0.83
HLA-B, probe 30 21 (34.4)9 (14.8)0.0242.711.14–6.46
HLA-B, probe 34 21 (34.4)9 (14.8)0.0242.711.14–6.46
As described in the text, HLA motifs are defined by individual sequence-specific
oligonucleotide (SSO) probes, including HLA-B probes 30 and 34 that are in
exclusive linkage disequilibrium (r2=1.0). The p values correspond to maximum
likelihood estimates. OR=odds ratio, CI=confidence interval.
HLA and Glioblastoma
PLoS ONE | www.plosone.org5 September 2009 | Volume 4 | Issue 9 | e7157
matched, population-based controls from non-metropolitan areas
in four Midwest states (Iowa, Michigan, Minnesota and Wiscon-
sin). All patients with glioblastoma multiforme (GBM=Grade IV
glioma, as classified by the World Health Organization) were
included if they were 18 years or older at time of GBM diagnosis
and blood sampling. Healthy control subjects drawn from this
study had no self-reported cancer of any type and were matched to
GBM patients at a 1:1 ratio by sex, state of residence and at least
two of three additional criteria, i.e., age (63 yr), race/ethnicity
(self-identified), and county of residence (or adjacent county). The
final study population consisted of 149 pairs of GBM patients and
healthy controls (Table 1). The original research and this
substudy conformed to the US Department of Health and Human
Services guidelines for protection of human subjects. All patients
and healthy controls provided written informed consent. The
procedures for obtaining written informed consent, blood sample,
clinical information, data management and data analysis were
approved by institutional review board (IRB) at the National
Institute for Occupational Safety and Health (NIOSH, Protocol
HSRB 94-DSHEFS-08). Work related to this substudy was further
approved by IRBs at NIOSH and University of Alabama at
Birmingham (Protocol X071005007).
Genomic DNA samples, prepared from whole blood either using
the QIAamp blood kit (QIAGEN Inc., Chatsworth, Calif., USA) or
by sodium-perchlorate chloroform extraction , were used for
molecular typing of three HLA class I genes (HLA-A, HLA-B, and
HLA-C), along with the most polymorphic HLA class II gene, HLA-
DRB1. Genotyping relied on a combination of PCR-based
techniques commonly used in population-based studies [57,58].
Briefly, alleles (4-digit designations) and allele groups (2-digit
designations) from the three HLA class I genes were first amplified
by locus-specific primer mixes and then classified after automated
hybridization to sequence-specific oligonucleotide (SSO) probes
(Innogenetics, Alpharetta, Georgia, USA). Ambiguous HLA class I
genotypes were resolved by sequencing-based typing (SBT), which
covered three exons (2–4) in six sequencing reactions (three forward
and three reverse) (Abbott Molecular, Inc., Des Plaines, Illinois,
USA). Capillary electrophoresis and allele assignments in SBT were
done using the ABI 3130xl DNA Analyzer (Applied Biosystems,
Foster City, Calif., USA). HLA-DRB1 alleles in the HLA class II
region were directly resolved by sequencing exon 2 in three
reactions (forward, reverse, and codon 86) (Abbott Molecular, Inc.).
For quality control purposes, randomly selected samples (n=39, or
13% of the total) were genotyped in duplicate.
Confirmatory sequencing of HLA-A promoter and exon 1
To enhance the interpretation of findings on HLA-A alleles, a
1000-bp region (Figure 1a) not targeted in routine genotyping was
sequenced using a commercial, high-throughput platform (Poly-
morphic DNA Technologies, Alameda, Calif., USA). The fragment
has the core promoter [59–61] and exon 1 sequences, with .60
single nucleotide polymorphisms (SNPs). Eight PCR primers and
eight internal sequencing primers (sequences available from JT
upon request) were used for bidirectional sequencing in subjects
who carried homozygous genotypes or common alleles of interest.
Individual SNP genotypes were analyzed for pairwise linkage
disequilibrium (LD) using the HaploView program (http://www.
broad.mit.edu/haploview/haploview-downloads). Homozygous se-
quences were also tested for phylogenetic relationships (Figure S2)
that could be directly compared with known taxonomic hierarchy
for protein-coding sequences (open reading frames) .
Selective genoyping of two SNPs with broad implications
for human malignancies
For exploratory analyses, two SNPs (rs401681 and rs2736098)
recently associated withmultiplehuman cancers  weretyped for
all GBM cases and healthy controls using pre-designed TaqMan (59
nuclease) assays (assay-on demand IDs C_1150767_20 and
C_26414916_20, respectively) (Applied Biosystems, Foster City,
CA). Based on procedures recommended by the manufacturer, the
SNP assays were run in 6-mL PCR reactions in 96-well plates, with
each reaction having 10 ng total genomic DNA mixed with 26
TaqMan Universal PCR Master Mix (Applied Biosystems). Allelic
discrimination relied on end-point fluorescence intensity after 35
cycles of PCR (denaturing at 95uC for 15 sec and annealing/
extendingat60uC for60 sec)inanABI7500FAST system(Applied
Biosystems). Each plate had four wells for negative controls (no
template DNA added) and 3% of all DNA samples were tested in
random duplicates for quality control.
Statistical Analysis Software (SAS), version 9.2 (SAS Institute,
Cary, North Carolina, USA) was used for all descriptive statistics
and comparative analyses. Serial analytical strategies were similar
to those reported in prior work , with a starting focus on 2-digit
allele groups (often equivalent to serological specificities) and
linkage disequilibrium (LD) between HLA factors. Only common
variants found in at least 10 individuals (,3.4% of the study
population) were formally tested. In all hypothesis testing, a
nominal P value #0.05 was considered statistically significant.
Multivariable and conditional logistic regression models with
backward or step-wise selection procedure were used to generate
the parsimonious models with all independent factors (adjusted
multivariable P value #0.05). Novel associations were reported as
such if the univariate P value was ,0.05 in conditional logistic
regression models. As homozygosity with any given HLA allele or
motif (defined by individual SSO probes) was rare, statistical
models only tested dominant effects. Analyses of individual SNP
genotypes were modeled for recessive effects (homozygosity or two
copies of the minor allele), dominant effects (homo- and
heterozygosity combined), and additive effects (0, 1 and 2 copies
of the minor allele). Estimates of odds ratio (OR) and 95%
confidence interval (CI) were the main summary statistics from
informative SNPs within HLA-A promoter and exon 1 sequences.
Novel SNPs without the official reference sequence (rs) numbers
are designated as ‘‘New.’’ Among the 51 SNPs with minor allele
frequencies $0.02 (Figure 1), one (rs9260109) is excluded from
this analysis because of three different alleles (i.e., not dimorphic)
at this site. Strong pairwise LD (shown in red) leads to the
identification of four haplotype blocks (framed), which consist of
13, 23, 6 and 3 SNPs, respectively.
Found at: doi:10.1371/journal.pone.0007157.s001 (0.27 MB
Patterns of linkage disequilibrium (LD) among
relationships of HLA-A promoter and exon 1 sequences repre-
senting 11 alleles found in homozygous state. Two alleles
(A*260101 and A*320101) have the full, 6-digit designations.
Scale of genetic distance is shown at the bottom.
Found at: doi:10.1371/journal.pone.0007157.s002 (0.05 MB
Neighbor-joining tree illustrating the phylogenetic
HLA and Glioblastoma
PLoS ONE | www.plosone.org6September 2009 | Volume 4 | Issue 9 | e7157
This study benefited from the Brain SPORE (Specialized Programs of
Research Excellence) project at UAB. We are indebted to Dr. G. Yancey
Gillespie for scientific advice, to Mary Shirley and Dale Isabelle for
administrative assistance, and to Drs. Koen De Clercq and Angela
Alexander for custom software that facilitates the analyses of individual
HLA class I sequences motifs (SSO probes). The findings and conclusions
from this study are those of the authors and do not necessarily represent the
views of the National Institute for Occupational Safety and Health.
Conceived and designed the experiments: AMR YL RK MB JT.
Performed the experiments: WS LH RN WS. Analyzed the data: WS
AMR LH YL WS MB JT. Contributed reagents/materials/analysis tools:
AMR RN RK MB JT. Wrote the paper: WS AMR LH YL RK JT.
Reviewed the literature: JT AMR.
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