Inherited Variants in Regulatory T Cell Genes and
Outcome of Ovarian Cancer
Ellen L. Goode1*, Melissa DeRycke1, Kimberly R. Kalli2, Ann L. Oberg1, Julie M. Cunningham3,
Matthew J. Maurer1, Brooke L. Fridley1, Sebastian M. Armasu1, Daniel J. Serie1, Priya Ramar1,
Krista Goergen1, Robert A. Vierkant1, David N. Rider1, Hugues Sicotte1, Chen Wang1, Boris Winterhoff7,
Catherine M. Phelan18, Joellen M. Schildkraut8, Rachel P. Weber9, Ed Iversen10, Andrew Berchuck8,
Rebecca Sutphen11, Michael J. Birrer12, Shalaka Hampras5, Leah Preus5, Simon A. Gayther13,
Susan J. Ramus13, Nicolas Wentzensen14, Hannah P. Yang14, Montserrat Garcia-Closas15, Honglin Song16,
Jonathan Tyrer16, Paul P. D. Pharoah16, Gottfried Konecny17, Thomas A. Sellers18, Roberta B. Ness6,
Lara E. Sucheston5, Kunle Odunsi4, Lynn C. Hartmann2, Kirsten B. Moysich5, Keith L. Knutson19
1Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, United States of America, 2Department of Medical Oncology, Mayo Clinic, Rochester,
Minnesota, United States of America, 3Department of Experimental Pathology, Mayo Clinic, Rochester, Minnesota, United States of America, 4Department of Gynecologic
Oncology, Roswell Park Cancer Institute, Buffalo, New York, United States of America, 5Department of Cancer Prevention and Control, Roswell Park Cancer Institute,
Buffalo, New York, United States of America, 6School of Public Health, University of Texas, Houston, Texas, United States of America, 7Department of Gynecologic
Oncology, Mayo Clinic, Rochester, Minnesota, United States of America, 8Duke Comprehensive Cancer Center, Duke University, Durham, North Carolina, United States of
America, 9Department of Community and Family Medicine, Duke University Medical Center, Durham, North Carolina, United States of America, 10Department of
Statistical Science, Duke University, Durham, North Carolina, United States of America, 11University of South Florida College of Medicine, Tampa, Florida, United States of
America, 12Brigham and Women’s Hospital, Boston, Massachusetts, United States of America, 13University of Southern California, Los Angeles, California, United States
of America, 14National Cancer Institute, Bethesda, Maryland, United States of America, 15Institute of Cancer Research, Sutton, United Kingdom, 16University of
Cambridge, Cambridge, United Kingdom, 17Department of Gynecologic Oncology, University of California Los Angeles, Los Angeles, California, United States of America,
18H. Lee Moffitt Cancer Center & Research Institute, Tampa, Florida, United States of America, 19Department of Immunology, Mayo Clinic, Rochester, Minnesota, United
States of America
Although ovarian cancer is the most lethal of gynecologic malignancies, wide variation in outcome following conventional
therapy continues to exist. The presence of tumor-infiltrating regulatory T cells (Tregs) has a role in outcome of this disease,
and a growing body of data supports the existence of inherited prognostic factors. However, the role of inherited variants in
genes encoding Treg-related immune molecules has not been fully explored. We analyzed expression quantitative trait loci
(eQTL) and sequence-based tagging single nucleotide polymorphisms (tagSNPs) for 54 genes associated with Tregs in 3,662
invasive ovarian cancer cases. With adjustment for known prognostic factors, suggestive results were observed among rarer
histological subtypes; poorer survival was associated with minor alleles at SNPs in RGS1 (clear cell, rs10921202,
p=2.761025), LRRC32 and TNFRSF18/TNFRSF4 (mucinous, rs3781699, p=4.561024, and rs3753348, p=9.061024,
respectively), and CD80 (endometrioid, rs13071247, p=8.061024). Fo0r the latter, correlative data support a CD80
rs13071247 genotype association with CD80 tumor RNA expression (p=0.006). An additional eQTL SNP in CD80 was
associated with shorter survival (rs7804190, p=8.161024) among all cases combined. As the products of these genes are
known to affect induction, trafficking, or immunosuppressive function of Tregs, these results suggest the need for follow-up
Citation: Goode EL, DeRycke M, Kalli KR, Oberg AL, Cunningham JM, et al. (2013) Inherited Variants in Regulatory T Cell Genes and Outcome of Ovarian
Cancer. PLoS ONE 8(1): e53903. doi:10.1371/journal.pone.0053903
Editor: Michael Scheurer, Baylor College of Medicine, United States of America
Received July 6, 2012; Accepted December 4, 2012; Published January 30, 2013
Copyright: ? 2013 Goode 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: The scientific development and funding for this project were supported in part by the Mayo Clinic Ovarian Cancer SPORE (P50-CA136393) to ELG, LCH,
and KLK, the National Cancer Institute GAME-ON Post-GWAS Initiative (U19-CA148112), National Cancer Institute Research project grants (R01-CA086888, R01-
CA122443, R01-CA106414, R01-CA76016, R01-CA114343), Cancer Research United Kingdom (A10119, A10124, A8339, A6187, A11306, A7058), the Medical
Research Council (G0801875–89310), the Ovarian Cancer Research Fund, the Mayo Foundation, the Minnesota Ovarian Cancer Alliance, the Mayo Foundation, the
Roswell Park Cancer Institute Alliance Foundation, and the Fred C. and Katherine B. Andersen Foundation. The funders had no role in study design, data collection
and analysis, decision to publish, or preparation of the manuscript.
Competing Interests: The authors have declared that no competing interests exist.
* E-mail: email@example.com
Ovarian cancer is the fifth leading cause of cancer death among
women in the United States . Five-year overall survival is
approximately 45%, and, even with modern surgical and
chemotherapeutic strategies, most cases with advanced disease
relapse and succumb to the disease [2,3]. Rare germline BRCA1
or BRCA2 mutations confer improved survival . Common
inherited variants could also influence outcome; genome-wide
association studies (GWAS) are underway, but have yet to find
PLOS ONE | www.plosone.org1January 2013 | Volume 8 | Issue 1 | e53903
survival-associated loci . Consideration of novel biological
pathways using in-depth analysis of variation in candidate genes
holds promise for the identification of prognostic genetic factors.
Several studies demonstrate the importance of the immune
system in ovarian cancer outcome. For example, in one report,
cases with evidence of CD3 T cell tumor infiltration (approxi-
mately one-half of the cases studied) showed improved progres-
sion-free and overall survival . Subsequent studies have refined
our understanding of tumor-infiltrating T cells, including one
showing that CD8+T lymphocytes are the primary sub-population
of T cells associated with better survival . Along with the finding
that tumor antigen-specific T cell responses can be detected in
cases, these results suggest that anti-tumor immunity is elicited
against ovarian cancers and impacts the clinical course of the
disease . Despite this generation of an immune response,
however, anti-tumor immunity is counterbalanced by an immune
suppressive microenvironment . Of immune suppressive
mechanisms, CD4+regulatory T cells (Tregs) are a primary
means of immune evasion in ovarian cancers; these are CD4+T
lineage cells whose primary function is immune regulation . In
collaboration with others, we first suggested a role of tumor-
infiltrating Tregs in ovarian cancer pathogenesis, reporting higher
levels of CD4+Tregs, measured with immunofluorescence, among
cases with poorer survival . Subsequent work supports the
importance of CD4+Tregs in ovarian cancer pathogenesis and
outcome [7,12]. For example, the presence of CD4+Tregs appears
to influence the anti-tumor activity of tumor-infiltrating cytotoxic
CD8+T cells . CD4+Tregs block both adaptive and innate
immune effectors by cell contact mechanisms as well as by soluble
mediators [13,14]. Soluble mediators of suppression commonly
associated with CD4+Tregs include IL-10 and TGF-b, both of
which block T cell proliferation and cell-mediated immunity
[15,16,17]. Other cell surface molecules implicated in suppressing
the immuneresponse include
(TNFRSF18), LAG-3, CTLA-4, and surface-bound TGF-b
Because of the importance of CD4+Tregs and a role for
inherited factors in outcome, we assessed whether common
inherited variation related to CD4+Treg-related genes was
associated with ovarian cancer outcome following standard of
care therapy. Specifically, we assessed 54 genes key to the
induction, trafficking, or immunosuppressive functions of CD4+
Tregs. Utilizing data from a novel candidate gene study combined
with existing data, we studied polymorphisms that have been
shown to affect the expression of or to tag inherited variation in
these genes. Variants associated with outcome in multiple study
populations could shed light on immunosuppressive mechanisms
in ovarian cancer.
Materials and Methods
Protocols were approved by the appropriate institutional review
boards (Mayo Clinic Institutional Review Board, Roswell Park
Cancer Institute Institutional Review Boards, Duke University
Institutional Review Boards, National Cancer Institute Institu-
tional Review Boards, Moffitt Cancer Center Institutional Review
Boards) or ethics panel (Royal Marsden Hospital ethics panel,
University of Cambridge ethics panel, University College London
ethics panel). All participants gave written informed consent.
Candidate Gene SNP Array
Fifty-four genes of key relevance to the biology of Tregs
(ACVR2B, AGTR1, CCL11, CCL17, CCL19, CCL2, CCL20,
CCL22, CCL3, CCL4, CCL5, CCR4, CCR6, CCR7, CCR8,
CD274, CD46, CD80, CD86, CXCL10, CXCL13, CXCR5,
DUSP4, EGR2, GPR83, IDO1, IKZF2, IKZF4, IL10RB,
IL15RA, IL2RB, IL6ST, IL9, INHBA, INHBB, IRF4, ITGAE,
KLF10, LAG3, LRRC32, MDFIC, NRP1, PDCD1, PLAG1,
PRNP, RGS1, RGS16, SH3BGRL2, SLC22A2, SMAD3,
SOCS2, TNFRSF18, TNFRSF4, and TNFRSF9) were chosen
for study (Table S1). The relevance of these genes was established
from a PubMed  database search which revealed published
information that either directly showed or suggested a role for the
respective gene products in the induction, immune suppressive
function, or trafficking of Tregs. Eighty-five SNPs associated
(p,1026) with lymphocyte mRNA expression of one or more
candidate genes (eQTL SNPs) were included . In addition,
within five kb of each gene, SNPs tagging other SNPs with minor
allele frequency (MAF) $0.05 at r2$0.9 were identified from 60
European-American participants in the Low-Coverage Pilot of the
1000 Genomes Project (for 53 genes)  or the SeattleSNPs
Variation Discovery Resource (for CCL2) , whichever was
most informative. Selected tagSNPs (N=1,451) were optimized to
include SNPs with appropriate design scores for an Illumina
Goldengate BeadArray Assay, predicted functionality, and to
include more than one tagSNP for large groups of correlated SNPs
. Additional SNP information is in Table S2.
Candidate Gene Study Participants and Genotyping
Cases genotyped on the Treg custom SNP array included
women with pathologically-confirmed invasive primary epithelial
ovarian, peritoneal, or fallopian tube cancer enrolled at the Mayo
Clinic and Roswell Park Cancer Institute (RPCI). Mayo Clinic
cases (N=905) were ascertained between December 1999 and
November 2010 into the Mayo Clinic Ovarian Cancer Case-
Control Study (MAY) or the Mayo Clinic Case-Only Ovarian
Cancer Study (MAC) and included women aged 20 years or above
enrolled through Mayo Clinic’s Divisions of Gynecologic Surgery
and Medical Oncology. Sixty eight percent of these cases were
enrolled within a week of diagnosis (median time from diagnosis to
recruitment was zero days). RPCI cases (N=167) were residents of
Western Pennsylvania, Eastern Ohio, or Western New York, aged
25 years or above and ascertained between January 2004 and May
2009 within six months of diagnosis through Roswell Park Cancer
Institute’s Divisions of Gynecological Surgery and Oncology.
These cases were enrolled with a median time from diagnosis to
recruitment of 80 days. At both sites, DNA was extracted from 10
to 15 mL fresh peripheral blood (using Gentra AutoPure LS
Purgene salting out methodology at Mayo Clinic and FlexiGene
DNA Kit methodology at RPCI), stored at 280uC, and bar-coded
to ensure accurate processing. A total of 1,072 participants were
genotyped using a custom Illumina Goldengate BeadArray Assay
along with 24 duplicates and 24 HapMap CEU replicates (8 trios).
Concordance among study duplicates was 99.998%, no SNPs had
unresolved replicate or Mendelian errors, and the mean genotype
call rate was 99.88%. Samples with genotyping failure (N=22) or
call rate ,97% (N=11) were excluded as well as samples found to
be incorrectly plated (N=1) or from cases deemed ineligible due to
non-epithelial disease (N=5), borderline tumor behavior (N=34),
or enrollment more than one year prior to diagnosis (N=5). SNPs
with genotyping failure (N=162), call rate ,95% (N=19), or
HWE ,0.0001 and poor clustering (N=15) were excluded. Thus,
analyses were based on 994 cases and 1,340 SNPs.
Genome-Wide Association Study
We also analyzed data from the Follow-up of Ovarian Cancer
Genetic Association and Interaction Studies (FOCI) collaboration
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which is part of the National Cancer Institute GAME-ON Post-
GWAS initiative and is described elsewhere [26,27]. In brief,
participants were 2,167 self-reported white invasive ovarian cancer
cases enrolled in the North Carolina Ovarian Cancer Study
(NCO), the NCI Ovarian Case-Control Study in Poland (POL),
the Royal Marsden Cancer Study (RMH), the UK Studies of
Epidemiology and Risk Factors in Cancer Heredity Ovarian
Cancer Study (SEA), the Tampa Bay Ovarian Cancer Study
(TBO), and the UK Familial Ovarian Cancer Registry and the
UK Ovarian Cancer Population Study (UKR+UKO). Genotyp-
ing used Illumina 317 k or 610-Quad Infinium Arrays with
imputation to HapMap v 26 using dosage values obtained from
the MACH software package . Data on 820 SNPs were
available on all cases.
We used Cox proportional hazards regression accounting for
left truncation to estimate hazard ratios (HRs) and 95%
confidence intervals (CIs) for association with overall survival.
Survival time was defined as time from diagnosis of ovarian cancer
until death from any cause or last follow-up. For each SNP, HRs
with 95% CIs were estimated per-allele (i.e., 0, 1, or 2 copies of
minor allele), analogous to the Armitage test for trend for binary
endpoints. Log-additive Cox proportional hazards regression
models were adjusted for study site (MAY+MAC, RPCI, POL,
NCO, RMH, SEA, TBO, UKO+UKR), age at diagnosis (,50
years, 50–69 years, .70 years), tumor stage (I or II, III or IV,
unknown), tumor grade (low, high, unknown), and race (white,
non-white, unknown), modeling direct genotype calls for MAY+-
MAC and RPCI and imputed allele dosage values where
appropriate for FOCI participants. Heterogeneity of HRs across
study site was formally examined using study-by-SNP interaction
terms and performing likelihood ratio tests; no correction for
multiple testing was performed.
Tumor Expression Quantitative Trait Locus (eQTL)
For 54 genotyped Mayo Clinic cases (33 serous, nine clear cell,
eight endometrioid, four mucinous), expression analyses were also
performed. Tumor RNA was isolated from fresh frozen samples,
using the Qiagen RNEasy protocol and quantitated using a
Nanodrop Spectrophotomer (Agilent Technologies, Santa Clara,
CA). Total RNA (750 ng) of high quality (RNA integrated number
.8.0) was labeled with cyanine 5-CTP or cyanine 3-CTP, using
the Low RNA Input Fluorescent Linear Amplification Kit (Agilent
Technologies), purified on RNeasy Mini columns (Qiagen), and
hybridized to Agilent whole human genome 4644 K expression
arrays (using a mixed reference containing 106 tumor samples).
Slides were scanned using the Agilent 2565BA Scanner, and data
were normalized using Agilent’s error model and exported by the
Agilent Feature Extraction Software (version 7.5.1). Data in the
form of the log ratios of signals from individual tumors to signals
from the reference mix were used for analysis. For genes with
SNPs that were associated with survival at p,0.001, association
between genotype and expression probes was assessed using
Wilcoxon rank-sum tests.
The nearly 1,000 invasive ovarian cancer cases genotyped in a
Treg custom SNP array and approximately 2,600 cases in the
FOCI collaboration demonstrated the expected distributions of
mortality, age, and clinical features (Table 1). 1,529 deaths were
observed during a median follow-up of 5.4 years. In combined
analyses of all cases and case groups defined by histology, eight
SNPs yielded p,0.001 including six independent at r2,0.95
(Table 2). Results were similar when restricted to 2,518 cases with
complete data on stage, grade, and histology. At each SNP, minor
alleles were associated with poorer ovarian cancer survival. The
most statistically significant association was between survival
following clear cell ovarian cancer (N=217) and minor alleles at
an uncommon intronic SNP in the regulator of G-protein
signaling 1 (RGS1), suggesting an almost three-fold increased risk
of death (p=2.761025).
Among 272 mucinous ovarian cancers, minor alleles at four
SNPs in leucine rich repeat containing 32 (LRRC32) were
associated with greater than two-fold poorer survival. Three of
these SNPs (rs3781699, rs3197153, rs3781701) were highly
correlated (r2$0.97), thus only one of these is presented in
Table 2 (rs3781669 p=4.561024). A fourth SNP, LRRC32 SNP
rs7944357, was only modestly correlated with this three-SNP
cluster (r2#0.26), yet was also associated with survival among cases
with mucinous ovarian cancer (p=8.361024). One other SNP
rs3753348 showed association with a more than three-fold risk
with survival in mucinous ovarian cancer (Table 2); this SNP
resides in the 5 kb region between tumor necrosis factor receptor
superfamily members 4 and 18 (TNFRSF4 and TNFRSF18) on
Among 570 endometrioid ovarian cancer cases, minor alleles at
an intronic CD80 tagSNP rs13071247 were associated with a 73%
increased risk of mortality (p=8.061024, Table 2). In addition,
analysis of all cases regardless of histology suggested that an eQTL
SNP for CD80 (rs7804190) was associated with 14% shorter
survival time (p=8.061024). The rs7804190 eQTL, which resides
intronic to MAD1 mitotic arrest deficient-like 1 (yeast) (MAD1L1),
is of interest because genotype has been found to correlate with
expression of CD80 (p=6.061027), as well as polymerase (DNA
directed), beta (POLB), proline-serine-threonine phosphatase
interacting protein 2 (PSTPIP2), and KIAA1128 (p,1026) in
lymphoblastoid cell lines . Of note, no SNPs were associated
with survival following serous ovarian cancer (p,0.001), the most
common and most lethal histologic subtype. Tests for interaction
revealed no site-specific heterogeneity of association for any of the
SNPs in Table 2 (p.0.05 for each).
To explore potential mechanisms of the observed SNPs
associated with ovarian cancer survival, we examined tumor
RNA expression data on 54 Mayo Clinic cases and correlated
expression with genotype at the most suggestive survival-associated
SNPs described above. At CD80 rs13071247, an association was
observed such that heterozygotes and minor allele homozygotes
(AC and CC genotypes) had slightly increased tumor expression
(median fold change =1.04 on the raw scale, 0.06 on the log2
scale) than cases with AA genotype (p=0.006; Figure 1). No other
associations between genotype and tumor RNA expression were
observed at p,0.05.
Previous studies support an important role for Tregs in ovarian
cancer which appear to foster an immune suppressive microen-
vironment. Here, we analyzed ovarian cancer survival in relation
to inherited Treg genotypes using a combination of customized
genotyping and integration of existing genotypes from a collab-
orating GWAS. While no SNPs yielded suggestive results among
the more common serous cases, poorer survival was associated
with minor alleles at SNPs in RGS1 (clear cell), LRRC32 and
TNFRSF18/TNFRSF4 (mucinous), and CD80 (endometrioid).
For the latter, additional data support a CD80 genotype
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association with CD80 tumor RNA expression. Combined analysis
of multiple independent datasets provides greater statistical power
than separate discovery and replication analyses ; thus, we
used this study design and examined the possibility of heteroge-
neity of results across studies. As no statistically significant
heterogeneity across studies was observed, our inference is based
on this combined, most powerful approach. It is worth noting that
we examined a relatively large number of SNPs across 54 Treg-
associated genes and across different histologic subtypes, and
therefore we acknowledge that multiple testing issues may exist;
some of our highlighted results could indeed be false positive
associations. The fact that the genes examined were chosen based
on an a priori role in ovarian cancer and that we concentrated
only on SNP associations with p-values less than 0.001 lessens, but
does not entirely eliminate, this possibility. Nonetheless, this work
highlights particular Treg-related genes of interest.
CD80 has been extensively studied for its role in immune
responses, yet no focused analysis of SNPs and ovarian cancer
outcome has been reported, to our knowledge. It acts as a ligand
for both CD28 and CTLA4, leading to proliferation and anergy in
Table 1. Distributions of Ovarian Cancer Clinical Characteristics by Study.
Vital status at last follow up
Alive 450 (52%) 74 (61%)264 (54%)95 (45%) 57 (40%)719 (66%)118 (56%) 359 (68%) 2,136 (58%)
Deceased 423 (48%)47 (39%) 228 (46%)115 (55%)86 (60%) 368 (34%)94 (44%) 168 (32%) 1,529 (42%)
Age at diagnosis
,50 years 126 (14%) 19 (16%)119 (24%)66 (31%) 45 (31%) 260 (24%) 35 (17%)94 (18%) 764 (21%)
50–69 years484 (55%)71 (59%) 299 (61%)117 (56%)97 (68%)780 (72%) 134 (63%)332 (63%)2,314 (63%)
70+ years 263 (30%) 31 (26%) 74 (15%)27 (13%)1 (1%)47 (4%) 43 (20%)101 (19%) 587 (16%)
Serous 638 (79%)89 (82%) 294 (65%)93 (65%) 55 (48%)502 (53%)139 (74%) 282 (60%)2,092 (65%)
Endometrioid106 (13%) 11 (10%)80 (18%) 28 (20%)26 (23%) 201 (21%)27 (14%)91 (19%) 570 (18%)
Clear cell 46 (6%)1 (1%) 58 (13%)9 (6%) 17 (15%) 109 (12%)11 (6%) 46 (10%)297 (9%)
Mucinous 22 (3%)7 (6%) 20 (4%)13 (9%) 16 (14%)129 (14%)12 (6%) 53 (11%)272 (8%)
Other/unknown 61134067 29 1462355 434
Stage I/II 176 (20%) 25 (23%)160 (33%)56 (39%)0 512 (61%)50 (24%)216 (47%) 1,195 (38%)
Stage III/IV692 (80%) 84 (77%)330 (67%)86 (61%)0 326 (39%) 155 (76%)247 (53%)1,920 (62%)
Unknown5 122 68 1432497 64 550
Low grade116 (14%) 37 (33%) 202 (42%) 61 (47%) 43 (54%) 442 (55%)51 (24%) 168 (43%)1,120 (37%)
High grade724 (86%) 76 (67%) 278 (58%)69 (53%) 36 (46%)365 (45%)156 (75%)225 (57%)1,929 (63%)
Unknown3381280 642805 134 616
White767 (98%) 112 (93%)492 (100%) 210 (100%) 143 (100%)1,087 (100%) 212 (100%) 527 (100%)3,550 (99%)
Non-white13 (2%) 8 (7%)000000 21 (1%)
Table 2. Regulatory T Cell SNPs Associated with Overall Survival (p,0.001).
Case GroupGeneSNPMAFLocation HR (95% CI)p-value
Clear Cell (N=217)RGS1rs10921202 0.07Intron2.93 (1.77–4.84)2.761025
Mucinous (N=272)LRRC32rs37816990.35 39 UTR 2.32 (1.45–3.71)4.561024
rs79443570.44Intron2.04 (1.34–3.10) 8.361024
TNFRSF4/TNFRSF18rs3753348 0.05Intergenic3.41 (1.65–7.05) 9.061024
Endometrioid (N=570)CD80 rs130712470.14 Intron 1.73 (1.26–2.39) 8.061024
All Cases (N=3,655)CD80 rs78041900.37 MAD1L1 1.14 (1.06–1.23)8.161024
Adjusted for study site (MAY+MAC, RPCI, POL, UKO+UKR, TBO, NCO, RMH, SEA), age at diagnosis (,50 years, 50–69 years, .70 years), tumor stage (I or II, III or IV,
unknown), race (white, non-white, unknown), and tumor grade (low, high, unknown); linkage disequilibrium reduced to r2,0.95; MAF, minor allele frequency.
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naı ¨ve T cells, respectively [30,31,32]. CTLA4 is constitutively
expressed in Tregs, where it is important in suppressing immune
responses through a variety of proposed mechanisms, including
activation of the indoleamine-2,3-dioxygenase pathway in den-
dritic cells (DCs) and inhibition of interactions between activated
T cells and DCs [33,34,35]. We observed that an intronic tagging
CD80 SNP was associated with poorer survival of endometrioid
cases and with increased tumor CD80 expression, and, among all
cases, we observed that an eQTL SNP on another chromosome
which associated with CD80 lymphocyte expression was also
associated with poorer survival. Altogether, these data suggest that
CD80 expression may be in part driven by inherited factors and
may lead to increased immune suppression and poorer outcome.
Of interest to clear cell ovarian cancer, the gene product of
RGS1, RGS1 or BL34, is a member of the RGS protein family
whose members are involved in regulation of G-protein signaling.
Specifically, they are GTPase-activating proteins that limit the
duration of G-protein signaling [36,37]. Lymphocyte migration to
chemotactic signals are mediated by G-protein signals and
previous studies have found that Tregs do not respond as well to
chemokine signaling as naı ¨ve T cells ). Furthermore, RGS1 is
more highly expressed in Tregs and expression is inversely
correlated with migration . Interestingly, RGS1 gene expres-
sion is increased in activated Tregs, and this is mediated by
binding of the Treg transcription factor FOXP3 to the RGS1 gene
. Associations of RGS1 SNPs have also been observed in
numerous T cell-mediated autoimmune diseases, including type 1
diabetes, celiac disease, and multiple sclerosis [40,41,42,43]. Based
on these prior studies, it is tempting to speculate that genetically
determined RGS1 levels may regulate Treg infiltration into clear
cell ovarian cancers and thus contribute to outcome.
A SNP of possible relevance to mucinous disease is in LRRC32
which encodes GARP, a transmembrane protein expressed
specifically on naturally occurring activated Tregs, but not resting
Tregs [44,45]. GARP has been shown to be a receptor for
inactive, latency-associated peptide (LAP) bound TGF-b [46,47].
GARP does not induce activation of latent TGF-b; however, it
may function in infectious tolerance, converting FOXP32cells to
suppressive FOXP3+cells [46,48]. Additionally, GARP is part of a
positive feedback loop with FOXP3 in Tregs, which are known to
maintain a suppressive tumor microenvironment and prevent an
effective immunological response . Our finding of poorer
survival among mucinous cases with minor alleles at an LRRC32
SNP suggests that these cases may have increased immune
We report an association between risk of death due to mucinous
ovarian cancer and a SNP in a gene cluster containing
TNFRSF18 and TNFRSF4. TNFRSF18 encodes GITR, a co-
stimulatory molecule present constitutively on Treg cells and
upregulated on naı ¨ve T cells after stimulation. Reports are
conflicting as to the role of GITR, as it has been reported both to
increase [49,50] and to abolish the suppressive function of Tregs
[51,52]. While the specific mechanism of GITR action remains
controversial, it is clear that it modulates Tregs. TNFRSF4
encodes OX40 (CD134), and signaling through OX40 reduces the
ability of Tregs to act as suppressor cells by decreasing expression
of FOXP3 [53,54]. Reduced FOXP3 results in decreased miR155
and a subsequent increase in SOCS1 (suppressor of cytokine
signaling 1). SOCS1 is a component of a negative feedback loop
Figure 1. CD80 rs13071247 Genotype and Tumor Expression. Among N=54 MAY+MAC invasive ovarian cancer cases, Agilent whole human
genome 4644 K expression array probe A_24_P155632; CD80 log2ratios of tumor versus reference RNA expression (y-axis) versus genotype (x-axis);
dashes indicate median; each symbol represents a unique patient; data points are jittered so all data are visible.
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for IL-2 signaling cascade; increased expression of SOCS1 results
in a need for increased IL-2 levels for survival of Tregs . Thus,
OX40 signaling in Tregs can modulate suppressor functions both
by decreasing their effector function and by requiring higher
amounts of IL-2 for continued survival and activation. The
intergenic SNP associated with overall survival in cases with
mucinous ovarian cancer may act through either a GITR or
OX40 mechanism. Dissecting the role of the germline variants
may help to identify mechanisms that could explain why the
immune system is not able to mount an effective response to
In conclusion, our analysis of 3,662 invasive ovarian cancer
cases suggests that inherited variants related to Tregs are
associated with ovarian cancer outcome in a subtype-specific
manner, even after adjustment for known prognostic features. Our
findings underscore the importance of subtype-specific analyses in
clinical and epidemiological studies of ovarian cancer, given the
established disease heterogeneity, with each histologic subtype
expressing different patterns of genetic, epidemiologic and clinical
characteristics (reviewed by Karst and Drapkin ). Future work
should include examination of additional study populations,
immunological studies, and correlation of inherited variants with
other tumor features, such as levels of Treg infiltration.
We are grateful to the family and friends of Kathryn Sladek Smith for their
generous support of Ovarian Cancer Association Consortium through their
donations to the Ovarian Cancer Research Fund.
Conceived and designed the experiments: ELG KRK ALO LCH KBM
KLK. Performed the experiments: JMC BW GK. Analyzed the data: MJM
BLF SMA DJS PR KG RAV DNR H Sicotte CW. Contributed reagents/
materials/analysis tools: CMP JMS RPW EI AB RS MJB SH LP SAG SJR
NW HPY MG H Sicotte H Song JT PPDP TAS RBN LES KO. Wrote the
paper: ELG MD KLK.
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