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Original Articles
Possible Genetic Predisposition to Lymphedemaafter Breast Cancer
Beth Newman, Ph.D.,1 Felicity Lose, Ph.D.,2 Mary-Anne Kedda, Ph.D.,1
Mathias Francois, Ph.D.,3 Kaltin Ferguson,2 Monika Janda, Ph.D.,1 Patsy Yates, Ph.D.,4
Amanda B. Spurdle, Ph.D.,2,* and Sandra C. Hayes, PhD1,*
Abstract
Background: Known risk factors for secondary lymphedema only partially explain who develops lymphedemafollowing cancer, suggesting that inherited genetic susceptibility may influence risk. Moreover, identification ofmolecular signatures could facilitate lymphedema risk prediction prior to surgery or lead to effective drugtherapies for prevention or treatment. Recent advances in the molecular biology underlying development of thelymphatic system and related congenital disorders implicate a number of potential candidate genes to explore inrelation to secondary lymphedema.Methods and Results: We undertook a nested case-control study, with participants who had developed lym-phedema after surgical intervention within the first 18 months of their breast cancer diagnosis serving as cases(n = 22) and those without lymphedema serving as controls (n = 98), identified from a prospective, population-based, cohort study in Queensland, Australia. TagSNPs that covered all known genetic variation in the genesSOX18, VEGFC, VEGFD, VEGFR2, VEGFR3, RORC, FOXC2, LYVE1, ADM, and PROX1 were selected forgenotyping. Multiple SNPs within three receptor genes, VEGFR2, VEGFR3, and RORC, were associated withlymphedema defined by statistical significance ( p < 0.05) or extreme risk estimates (OR < 0.5 or > 2.0).Conclusions: These provocative, albeit preliminary, findings regarding possible genetic predisposition to sec-ondary lymphedema following breast cancer treatment warrant further attention for potential replication usinglarger datasets.
Introduction
Lymphedema is one of the most problematic complica-tions following breast cancer treatment, experienced by
approximately 30% of breast cancer survivors.1–3 It representsfailure of the lymphatic system to adequately drain fluid andproteins from the interstitial tissue and to circulate lympho-cytes. Removal or damage to the lymph nodes or lymphaticvasculature during cancer treatment may impede properphysiological function of this network. Although lymphede-ma can occur in any part of the body, it generally refers to anaccumulation of fluid and subsequent distortion of a limb.4
Little is known about its prevention, and it is regarded as an
incurable, progressive, disfiguring, and disabling disorderthat is difficult to manage, compromising function5 andquality of life.6
Lymphedema may present immediately or years afterbreast cancer treatment,7 although the majority of cases seemto appear within the first 12-18 months post-surgery.3,8–9 Thepublished literature on risk factors is characterized by in-consistent relationships, but evidence is mounting for a few,including extent of surgery, extent of lymph node resection,radiation therapy, obesity, and surgical wound infection.10
Nevertheless, it is clear that these characteristics only partiallyexplain who develops lymphedema, and lymphedema canand does occur in women lacking these risk factors. It is
1Institute of Health and Biomedical Innovation and School of Public Health, and 4Institute of Health and Biomedical Innovation and Schoolof Nursing, Queensland University of Technology, Brisbane, Australia.
2Molecular Cancer Epidemiology Laboratory, Genetics and Population Health Division, Queensland Institute of Medical Research, Bris-bane, Australia.
3Institute of Molecular Bioscience, University of Queensland, Brisbane, Australia.*ABS led laboratory-related activities, while SCH led field-related activities.
LYMPHATIC RESEARCH AND BIOLOGYVolume 10, Number 1, 2012ª Mary Ann Liebert, Inc.DOI: 10.1089/lrb.2011.0024
2
therefore possible that inherited genetic susceptibility mayplay a role in the pathogenesis of secondary lymphedema.
There has been substantial progress in identifying genesthat contribute to development of the lymphatic vascularsystem during embryogenesis and its subsequent regula-tion.11–14 Some genes are now known to underlie primarylymphedema,15–18 a congenital or later-onset condition thatoccurs in the absence of any known injury or medical inter-vention, and findings from genetic studies of inherited lym-phedema assist with the molecular dissection of lymphaticdiseases.19 We hypothesized that genes involved in familiallymphedema (VEGFR3 (flt4), FOXC2,20 and SOX1815) and/orlymphangiogenesis in the embryo, such as VEGFC, VEGFD(also known as FIGF), VEGFR2 (KDR), RORC, LYVE1, ADM(Adrenomedullin), and PROX1,20–22 may also predispose tosecondary lymphedema. We therefore undertook a compre-hensive investigation of genetic variation in these 10 plausiblecandidate genes in a cohort of breast cancer survivors, to as-sess the role of inherited genetic susceptibility in the devel-opment of secondary lymphedema after breast cancer.
Materials and Methods
The study was a nested case-control design involvingparticipants who had developed lymphedema within the first18 months of their breast cancer diagnosis serving as casesand those without lymphedema serving as controls, identifiedfrom a prospective, population-based, cohort study called the‘Pulling Through Study’ (PTS) conducted in Queensland,Australia.
Study design and sample recruitment of the original‘Pulling Through Study’
Recruitment and study design for the PTS have been de-scribed in detail elsewhere.9 In brief, 417 women with pri-mary, unilateral, invasive breast cancer, diagnosed in 2002,were randomly selected from the Queensland Cancer Registryand invited to participate in the PTS. Of these, informedconsent was obtained for 68% (n = 287). Starting at 6 monthspost-diagnosis, women were prospectively followed for 12months, with data collection procedures involving comple-tion of a clinical assessment and/or self-administered ques-tionnaire every 3 months. Lymphedema status was evaluatedusing the sum of arm circumferences (SOAC) method.23 Awoman who scored a difference of > 5 cm between the treatedand untreated sides, during any of the five data collectionsessions between 6 and 18 months post-diagnosis, was con-sidered a lymphedema case. The remaining women wereconsidered controls. Some of the women (26%) participatedon a questionnaire-only basis; hence they lack objective as-sessments of lymphedema and therefore were not availablefor inclusion in these analyses.
Design and sample recruitment of the nestedcase-control study
The follow-up, nested case-control study reported herecommenced approximately 6 years following the date ofbreast cancer diagnosis for those in the PTS. Of the 287 orig-inal participants, 11 withdrew from the study and 16 had died(identified through the Queensland Cancer Registry mortalitydatabase), leaving 260 women to be re-contacted. Address
details were checked with the electronic White Pages, and achange of address search was carried out through AustraliaPost. When an address could not be confirmed from thesesources, the last postal address recorded in our files was used.The 260 potential participants were mailed an introductoryletter (reminding them of their involvement in the prior studyand inviting their participation in the current project), anewsletter (detailing findings from the original study), and aproject information sheet.
Following consent, collection of blood samples was ar-ranged using the phlebotomist at the Queensland Universityof Technology (QUT) or from a local commercial pathologycollection center, as preferred by the participant. Approxi-mately 8 mL of blood was drawn from the unaffected arm intoyellow-top, ACD tubes, and was transferred to QUT’s labo-ratory for processing. Upon receipt, samples were centri-fuged, and the buffy coat (white cells) removed, aliquoted,labeled with a unique code, and stored at - 80�C. Once sam-ples were collected and processed from all participants,samples were transferred to the Queensland Institute ofMedical Research, where genomic DNA was extracted fromfrozen buffy coat cells using the salting-out extraction meth-od, quantified (Nanodrop Spectrophotometer ND-1000, Na-nodrop Technologies, Wilmington, DE), diluted to astandardized concentration, and 12 ng of each sample platedonto 384-well plates for genotype analysis.
Genetic analyses
Tag single nucleotide polymorphisms (tagSNPs) that cov-ered all known genetic variation in SOX18, VEGFC, VEGFD,VEGFR2, VEGFR3, RORC, FOXC2, LYVE1, ADM and PROX1were selected for genotyping from HapMap data release 24/phase II, November 2008, NCBI build 36, dbSNP b126(www.hapmap.org), using the Tagger program within Hap-loview version 4.124 on CEU samples only. To minimize thenumber of genotypes tested while optimizing the number ofpolymorphisms evaluated, tagSNPs were chosen with an r2
‡ 0.8 using the pair-wise tagging approach. Several additionalpolymorphisms previously shown to have functional signifi-cance in primary lymphedema were also genotyped. To en-hance coverage of each locus, we included SNPs within 5kilobases (kb) of the 5’ and 3’ ends of each gene, based on thelong splice variant where relevant.
SNPs were genotyped using iPLEX Gold assays on theSequenom MassARRAY platform (Sequenom, San Diego,CA), as described previously.25 There were four negative(H2O) controls per 384-well plate, and quality control pa-rameters included genotype call rates > 95%, inclusion of 20duplicate samples per 384-well plate ( > 5% of samples) with‡ 98% concordance between duplicates, and Hardy-WeinbergEquilibrium p values ‡ 0.05. For assays not found to bepolymorphic, rare-allele frequencies were confirmed usingSPSmart (http://spsmart.cesga.es/).26 Across the 10 genesinvestigated, 152 SNPs were attempted, but 16 SNPs failedassay design or quality control standards and hence wereexcluded from further analysis. After genotyping, the BroadInstitute SNAP (SNP Annotation and Proxy Search) proxysearch tool was used to determine SNPs tagged by genotypedtagSNPs for bioinformatics analyses, using the 1000 genomesSNP data set (http://www.broadinstitute.org/mpg/snap/ldsearch.php).27
GENETIC PREDISPOSITION TO SECONDARY LYMPHEDEMA 3
Statistical analyses
All statistical analyses were conducted by SPSS, version 18.The genotype frequency distributions among cases and con-trols were compared using unadjusted logistic regressionanalysis. Results are reported using odds ratios (ORs) with 95%confidence intervals (CI). Co-dominant mode of inheritance(i.e., rare-allele homozygote, heterozygote, and reference cate-gory of common-allele homozygote) was assumed in statisticalanalyses, using a trend test with 1 degree of freedom. Resultswere interpreted initially by means of p value ( < 0.05). How-ever, because of the limited statistical power available, it wasdetermined a priori that ORs > 2.0 (or equivalently, < 0.5)would be acknowledged, irrespective of statistical significance,as long as results conformed to a pattern consistent withstraightforward Mendelian inheritance. This approach wasconsidered appropriate for generation of hypotheses prior toseeking validation in larger studies, as is now common practicewith breast cancer susceptibility genes.28
Results
Characteristics of the study participants
Of the 260 women invited to participate, a further 7 werefound to be deceased, 22 did not respond to the invitationletter and could not be contacted, and 36 declined participa-tion (primary reason: did not want to revisit illness). The re-maining 195 women provided consent, 161 women provideda blood sample, and DNA was successfully extracted from156 samples. Of these, 120 women had available data on theSOAC outcome measure used to define lymphedema status.Twenty-two women had evidence of lymphedema between6–18 months post-diagnosis, while 98 had no evidence oflymphedema. Demographic and disease characteristics ofparticipants in this case-control study were comparable to theinitial research sample (Table 1). Of note, the original cohortwas shown to be representative of the wider Queenslandbreast cancer population.9
Results of genetic analyses
Table 2 provides an overview of the 10 genes under in-vestigation. Not surprisingly, the more tagSNPs testedwithin a particular genetic locus and its flanking regions, themore likely we were to find a statistically significant trendtest and/or genotype-specific ORs of a magnitude greaterthan 2.0 or less than 0.5. Only three loci revealed trend testswith p < 0.05, and these same genes contained larger num-bers of genotype-specific ORs with extreme magnitudes thatconformed with Mendelian expectations: VEGFR3, VEGFR2,and RORC (Table 2).
Table 3 presents detailed results for VEGFR3, VEGFR2, andRORC. Multiple elevated (or reduced) genotype-specific ORsoccurred for adjacent tagSNPs in the 5’ flanking region andexon/intron 1 of the three genes, where four of the five sta-tistically significant results were found. VEGFR3 tagSNPsrs10464063, rs307814, and rs307811 (ptrend = 0.039 and 0.040,respectively; in high linkage disequilibrium in our sampleset), and rs11960332, as well as the polymorphisms coveredby these SNPs, are all located in the 5’ flanking region orintron 1 of the gene. Likewise, tagSNPs rs4284267, rs12128071,and rs11801866 (ptrend = 0.037) are situated in these regionsof the RORC gene, and VEGFR2 tagSNPs rs2239702 (ptrend =
0.010) and rs7667298 tag many SNPs located in that gene’s 5’flanking region, exon 1 and intron 1. Similar clustering wasobserved, but to a lesser extent, in the 3’ flanking region ofVEGFR3 (rs10055319 and rs11739214, ptrend = 0.020) as well astagSNPs rs6879285, rs1565818, and rs11747066 in intron 29(long splice variant)/3’ flanking region (short splice variant).Other regions of possible interest due to clustering of resultsoccurred in VEGFR2 at intron 2 (rs1531290 and rs4576072)and intron 7 (rs10020464, rs17711073, rs2034965, andrs17085326) (Table 3).
Three additional genes showed minimal evidence of clus-tering based on the presence of two adjacent tagSNPs,sometimes close to an additional tagSNP, with genotype-specific ORs > 2.0 or < 0.5. These include rs11947611 andrs1485766, near rs6828869, all located deep in intron 4 ofVEGFC; rs12089523 and rs10494972 in intron 4 of PROX1; andrs17318858 and rs17403620, near rs17403795, in the 3’ regionof LYVE1. The remaining tagSNPs with ORs beyond the apriori thresholds of interest are individually scattered acrossthe length of the tested genes.
Conclusions
The Pulling Through Study was designed to investigate thedevelopment of lymphedema through prospective follow-up
Table 1. Demographic and Disease Characteristics of
Women from the Pulling Through Study and Its
Genetic Follow-up Study
Original PullingThrough Studycohort (n = 287)
Participantsin the genetics
studya (n = 120)n (%)b n (%)b
Age (years)< 50 105 (31.4) 38 (27.2)‡ 50 182 (68.6) 82 (72.8)
Most extensive surgeryCLEc 185 (64.9) 83 (69.6)Mastectomy 102 (35.1) 37 (30.4)
Largest tumor size< 16 mm 171 (60.3) 78 (65.8)16 + mm 116 (39.7) 42 (34.2)
Number of nodes positiveNone removed 38 (13.1) 17 (14.1)None positive 158 (55.9) 66 (56.6)1–3 59 (20.1) 28 (22.2)4 + 29 (9.8) 9 (7.2)Unavailable 3 (1.1) 0 (0.0)
Overall histologic gradeOne 76 (26.7) 35 (29.4)Two 90 (31.7) 33 (27.5)Three 91 (30.7) 41 (33.5)Unavailable 30 (10.8) 11 (9.6)
Histologic typeInfiltrating ductal 210 (72.6) 88 (73.0)Infiltrating lobular 44 (15.6) 14 (12.0)Other 33 (11.7) 18 (15.0)
aThose from the original cohort with sufficient data to calculatecumulative burden of lymphedema between 6–18 months post-diagnosis and who provided a blood sample; bResults have beenappropriately weighted ( < 50 years, 1.0; ‡ 50 years, 1.3) foroversampling of younger women; cCLE, complete local excision.
4 NEWMAN ET AL.
of a cohort of Australian women recently treated for breastcancer. Among the women in our original cohort who pre-sented with lymphedema according to objective assessment(n = 67), around 40% were not in any of the high-risk cate-gories, which included receiving mastectomy, 20 + nodesexcised, or treated on the nondominant side,9,29 suggestingthat these factors were partial causes at best. This follow-upstudy now provides suggestive evidence for the involvementof the genes VEGFR2, VEGFR3, and RORC in the develop-ment of secondary lymphedema following breast cancertreatment. One or more tagSNPs in each of these genesshowed a statistically significant association with lymphede-ma, and these individual results appeared within clusters oftagSNPs exhibiting odds ratios suggestive of altered lym-phedema risk. All three genes code for receptor proteins, twoof which come from the same gene family, and the clusters ofnoteworthy findings occur in analogous gene regions withpotential biological function predicted on the basis of bioin-formatic analysis.
Vascular endothelial growth factor (VEGF) is a key playerin angiogenesis and lymphangiogenesis, and interacts withnumerous proteins, including VEGFC and VEGFD and thereceptors VEGFR2 and VEGFR3.30 The VEGFC and VEGFDligands stimulate lymphatic vessel growth31,32 and can ame-liorate secondary lymphedema in mice.33 VEGFC/D-inducedlymphangiogenesis is mediated by VEGFR3, and VEGFR3inhibition correlates with inhibition of lymphatic develop-ment and lymphedema;34 their increased expression is asso-ciated with metastatic disease.35 VEGFR3 has also been shownto cooperate with VEGFR2 in lymphatic vessel sprouting.32 Inaddition, a hereditary form of lymphedema called Milroydisease (also known as familial primary congenital lymphe-dema (PCL)) has been attributed to nonfunctional forms ofVEGFR3.36,37 It is therefore reasonable to hypothesize thatmore modest functional variations in these genes may pre-dispose to secondary lymphedema.
Bioinformatic analysis of tagSNPs located in the 5’ flankingregion and exon/intron 1 of VEGFR2 and VEGFR3 that areassociated with risk of lymphedema in our study revealedthat these SNPs, or SNPs that are tagged by them, are pre-dicted to have an effect on transcription factor binding sites.38
An example is the common SNP rs10464063, located up-stream of VEGFR3, which displayed substantially elevatedORs up to 8.29 (ptrend = 0.053) for the rare-allele homozygotegenotype. Of the nine SNPs tagged by this SNP (rs10464063included), eight are predicted to alter transcription factorbinding sites,38 and hence may affect expression of VEGFR3.VEGFR2 tagSNP rs2239702 displayed the most significantptrend value (0.010) of all SNPs tested in this study, with anincreased risk of secondary lymphedema up to 6.72 for therare-allele homozygote genotype. Rs2239702 tags over 15SNPs and four of these are predicted to alter transcriptionfactor binding sites.38 To our knowledge, the functional effectsof these SNPs have not been investigated experimentally.
The other interesting region of the VEGFR3 gene involvesthree tagSNPs in intron 29 of the long splice variant or the 3’flanking region in the short version. TagSNPs rs6879285 andrs11747066 (which are highly correlated with each other,r2 = 0.83) both tag rs1049095, located in the 3’ untranslatedregion of the short splice variant of VEGFR3. This SNP ispredicted to occur within two potential miRNA bindingsites,39 alteration of which could affect protein production.
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GENETIC PREDISPOSITION TO SECONDARY LYMPHEDEMA 5
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.98
0.4
7C
T50
2.54
0.65
,9.9
70.
18C
T11
1.05
0.21
,5.2
80.
96T
T18
4.63
1.12
,19.
190
.04
TT
302.
250.
51,9
.99
0.29
TT
24.
710.
28,7
9.01
0.28
MA
F=
0.39
14M
AF
=0.
50M
AF
=0.
07T
ren
dte
st0
.04
Tre
nd
test
0.3
2T
ren
dte
st0
.43
rs11
9603
32C
>T
rs45
7607
2A
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rs38
1141
7A
>G
CC
871.
00—
AA
831.
00—
AA
871.
00—
CT
250.
3100
.07,
1.44
0.1
4A
G32
0.37
0.10
,1.3
70.
14A
G29
0.66
0.20
,2.1
50.
49T
T5
cc
0.9
9G
G3
cc
0.99
GG
2c
c0.
99M
AF
=0.
15M
AF
=0.
16M
AF
=0.
14T
ren
dte
st0
.08
Tre
nd
test
0.0
9T
ren
dte
st0
.36
rs10
4794
76C
>A
rs68
3773
5G
>A
rs11
8018
66A
>T
CC
107
1.00
—G
G81
1.00
—A
A94
1.00
—C
A2
cc
0.99
GA
321.
020.
36,2
.90
0.98
AT
163.
431.
07,1
0.94
0.04
AA
1c
c1.
00A
A3
cc
0.99
TT
0—
MA
F=
0.02
MA
F=
0.16
MA
F=
0.07
Tre
nd
test
0.9
9T
ren
dte
st0
.68
Tre
nd
test
0.0
4
(con
tin
ued
)
6
Ta
bl
e3.
(Co
nt
in
ue
d)
VE
GF
R3
VE
GF
R2
RO
RC
Gen
oty
pe
Nb
OR
95
%C
IP
val
ue
Gen
oty
pe
Nb
OR
95
%C
IP
val
ue
Gen
oty
pe
Nb
OR
95
%C
IP
val
ue
rs11
7484
31C
>T
rs23
0594
9G
>A
rs66
8581
1G
>A
CC
591.
00—
GG
671.
00—
GG
118
1.00
—C
T46
1.06
0.40
,2.8
30.
90G
A43
0.67
0.24
,1.9
30.
46G
A1
cc
1.00
TT
110.
440.
05,3
.77
0.45
AA
81.
390.
25,7
.66
0.71
AA
0—
—M
AF
=0.
29M
AF
=0.
25M
AF
=0.
004
Tre
nd
test
0.6
3T
ren
dte
st0
.85
Tre
nd
test
1.0
0
rs30
7806
C>
Trs
7692
791
A>
Grs
4845
604
C>
TC
C92
1.00
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A31
1.00
—C
C89
1.00
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T24
0.88
0.27
,2.9
20.
84A
G56
0.35
0.12
,1.0
60.
06C
T29
1.71
0.61
,4.7
50.
31T
T1
cc
1.00
GG
230.
520.
14,1
.94
0.33
TT
0—
—M
AF
=0.
11M
AF
=0.
46M
AF
=0.
12T
ren
dte
st0
.71
Tre
nd
test
0.2
1T
ren
dte
st0
.31
rs47
0096
6A
>G
rs23
0594
8G
>A
rs12
0309
74C
>T
AA
961.
00—
GG
901.
00—
CC
791.
00—
AG
221.
030.
31,3
.44
0.96
GA
231.
290.
42,3
.97
0.66
CT
331.
030.
36,2
.97
0.95
GG
0—
—A
A3
cc
0.99
TT
60.
930.
10,8
.58
0.95
MA
F=
0.09
MA
F=
0.13
MA
F=
0.19
Tre
nd
test
0.9
6T
ren
dte
st0
.90
Tre
nd
test
1.0
0
rs22
9098
3T
>C
rs10
0204
64G
>A
rs11
2048
94T
>C
TT
391.
00—
GG
521.
00—
TT
701.
00—
TC
430.
540.
17,1
.69
0.29
GA
480.
570.
20,1
.59
0.28
TC
361.
790.
66,4
.82
0.25
CC
170.
440.
09,2
.32
0.34
AA
100.
370.
04,3
.23
0.37
CC
4c
c0.
99M
AF
=0.
39M
AF
=0.
31M
AF
=0.
20T
ren
dte
st0
.24
Tre
nd
test
0.2
0T
ren
dte
st0
.66
rs37
9710
2T
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9414
92G
>A
rs11
5784
18C
>T
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331.
00—
GG
671.
00—
CC
941.
00—
TC
601.
630.
47,5
.59
0.44
GA
411.
110.
41,3
.00
0.84
CT
162.
390.
73,7
.89
0.15
CC
252.
290.
57,9
.20
0.24
AA
100.
510.
06,4
.41
0.45
TT
0—
—M
AF
=0.
47M
AF
=0.
26M
AF
=0.
07T
ren
dte
st0
.24
Tre
nd
test
0.7
5T
ren
dte
st0
.15
rs30
7823
A>
Grs
1771
1073
A>
Grs
6693
413
T>
CA
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1.00
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1.00
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1.00
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0.56
0.17
,1.8
20.
34A
G20
0.45
0.10
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10.
31T
C57
0.96
0.33
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60.
93G
G4
1.35
0.13
,13.
900.
80G
G1
cc
1.00
CC
220.
630.
15,2
.75
0.54
MA
F=
0.17
MA
F=
0.09
MA
F=
0.44
Tre
nd
test
0.5
7T
ren
dte
st0
.27
Tre
nd
test
0.8
2
(con
tin
ued
)
7
Ta
bl
e3.
(Co
nt
in
ue
d)
VE
GF
R3
VE
GF
R2
RO
RC
Gen
oty
pe
Nb
OR
95
%C
IP
val
ue
Gen
oty
pe
Nb
OR
95
%C
IP
val
ue
Gen
oty
pe
Nb
OR
95
%C
IP
val
ue
rs37
9710
4A
>G
rs20
3496
5C
>T
rs37
9051
5G
>A
AA
911.
00—
CC
661.
00—
GG
941.
00—
AG
250.
350.
08,1
.64
0.18
CT
382.
620.
89,7
.73
0.08
GA
220.
400.
09,1
.84
0.24
GG
1c
c1.
00T
T9
2.41
0.42
,13.
940.
33A
A2
cc
0.99
MA
F=
0.12
MA
F=
0.25
MA
F=
0.11
Tre
nd
test
0.6
4T
ren
dte
st0
.11
Tre
nd
test
0.1
8
rs30
7826
A>
Grs
1708
5326
G>
Ars
1521
186
C>
TA
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1.00
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1.00
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1.00
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0.99
0.33
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00.
99G
A13
2.22
0.61
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10.
23C
T50
1.06
0.28
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70.
93G
G1
cc
1.00
AA
0T
T25
1.63
0.39
,6.8
50.
51M
AF
=0.
13M
AF
=0.
06M
AF
=0.
48T
ren
dte
st0
.86
Tre
nd
test
0.2
3T
ren
dte
st0
.51
rs30
7827
G>
Ars
7654
599
A>
Grs
9395
95G
>T
GG
881.
00—
AA
461.
00—
GG
511.
00—
GA
271.
020.
34,3
.11
0.97
AG
491.
220.
43,3
.42
0.71
GT
520.
590.
20,1
.79
0.35
AA
2c
c0.
99G
G21
0.76
0.19
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40.
75T
T14
0.48
0.06
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00.
50M
AF
=0.
13M
AF
=0.
39M
AF
=0.
34T
ren
dte
st0
.78
Tre
nd
test
0.8
8T
ren
dte
st0
.29
rs22
4220
8C
>T
rs13
1355
62G
>C
rs10
4942
69G
>C
CC
103
1.00
—G
G10
71.
00—
GG
511.
00—
CT
71.
890.
34,1
0.52
0.47
GC
80.
620.
07,5
.34
0.66
GC
521.
110.
20,1
.79
0.35
TT
0—
CC
0—
—C
C14
0.78
0.06
,4.1
00.
50M
AF
=0.
03M
AF
=0.
03M
AF
=0.
23T
ren
dte
st0
.47
Tre
nd
test
0.6
6T
ren
dte
st0
.29
rs13
1723
46C
>T
rs12
5057
58A
>G
rs15
2117
7A
>C
CC
691.
00—
AA
881.
00—
AA
321.
00—
CT
430.
570.
19,1
.72
0.32
AG
190.
460.
10,2
.16
0.32
AC
550.
520.
16,1
.65
0.27
TT
56.
460.
98,4
2,70
0.05
GG
3c
c0.
99C
C19
0.67
0.15
,2.9
70.
60M
AF
=0.
23M
AF
=0.
11M
AF
=0.
44T
ren
dte
st0
.54
Tre
nd
test
0.2
1T
ren
dte
st0
.46
rs68
7928
5T
>C
^rs
6838
752
A>
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1204
5886
A>
GT
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1.00
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1.00
—A
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1.00
—T
C57
1.19
0.39
,3.6
30.
76A
G50
1.42
0.53
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20.
49A
G49
0.47
0.17
,1.3
30.
15C
C6
3.17
0.47
,21.
240.
24G
G8
1.89
0.33
,10.
870.
48G
G4
cc
0.99
MA
F=
0.32
MA
F=
0.28
MA
F=
0.25
Tre
nd
test
0.3
6T
ren
dte
st0
.38
Tre
nd
test
0.0
9
(con
tin
ued
)
8
Ta
bl
e3.
(Co
nt
in
ue
d)
VE
GF
R3
VE
GF
R2
RO
RC
Gen
oty
pe
Nb
OR
95
%C
IP
val
ue
Gen
oty
pe
Nb
OR
95
%C
IP
val
ue
Gen
oty
pe
Nb
OR
95
%C
IP
val
ue
rs17
0804
12G
>C
rs14
5883
1A
>G
rs38
2805
7G
>A
GG
104
1.00
—A
A89
1.00
—G
G35
1.00
—G
C6
cc
0.99
AG
250.
320.
07,1
.48
0.14
GA
563.
560.
94,1
3.43
0.06
CC
0—
—G
G3
cc
0.99
AA
252.
030.
41,1
0.01
0.38
MA
F=
0.03
MA
F=
0.13
MA
F=
0.46
Tre
nd
test
0.9
9T
ren
dte
st0
.10
Tre
nd
test
0.3
4
rs15
6581
8C
>G
rs76
7174
5C
>T
rs98
26A
>G
CC
891.
00—
CC
441.
00—
AA
551.
00—
CG
140.
380.
05,3
.13
0.37
CT
501.
670.
59,4
.71
0.33
AG
480.
460.
16,1
.33
0.15
GG
1c
c1.
00T
T22
0.53
0.10
,2.7
90.
45G
G16
0.46
0.09
,2.3
00.
35M
AF
=0.
08M
AF
=0.
41M
AF
=0.
34T
ren
dte
st0
.32
Tre
nd
test
0.7
4T
ren
dte
st0
.16
rs11
7470
66C
>T
^rs
1531
289
G>
AC
C56
1.00
—G
G63
1.00
—C
T56
1.30
0.47
,3.6
00.
61G
A37
1.70
0.62
,4.6
80.
30T
T6
6.00
1.03
,35.
110.
05A
A8
0.76
0.08
,6.8
40.
80M
AF
=0.
29M
AF
=0.
25T
ren
dte
st0
.12
Tre
nd
test
0.6
4
rs68
7701
1G
>C
rs10
0083
60C
>T
GG
971.
00—
CC
115
1.00
—G
C12
1.69
0.41
,6.9
30.
47C
T3
2.38
0.21
,27.
480.
49C
C1
cc
1.00
TT
0—
—M
AF
=0.
06M
AF
=0.
01T
ren
dte
st0
.11
Tre
nd
test
0.4
9
rs22
7962
2G
>A
rs12
6423
07A
>G
GG
991.
00—
AA
481.
00—
GA
180.
970.
25,3
.70
0.96
AG
531.
020.
36,2
.91
0.97
AA
1c
c1.
00G
G16
1.67
0.43
,6.5
10.
46M
AF
=0.
08M
AF
=0.
36T
ren
dte
st0
.39
Tre
nd
test
0.5
4
(con
tin
ued
)
9
Ta
bl
e3.
(Co
nt
in
ue
d)
VE
GF
R3
VE
GF
R2
RO
RC
Gen
oty
pe
Nb
OR
95
%C
IP
val
ue
Gen
oty
pe
Nb
OR
95
%C
IP
val
ue
Gen
oty
pe
Nb
OR
95
%C
IP
val
ue
rs30
7822
G>
Ars
1000
6115
C>
AG
G81
1.00
—C
C11
11.
00—
GA
200.
920.
24,3
.61
0.91
CA
51.
140.
12,1
0.73
0.91
AA
41.
740.
17,1
8.09
0.64
AA
0—
—M
AF
=0.
13M
AF
=0.
02T
ren
dte
st0
.81
Tre
nd
test
0.9
1rs
1005
5319
G>
CG
G80
1.00
—G
C35
1.29
0.47
,3.5
70.
63C
C3
2.58
0.22
,30.
550.
45M
AF
=0.
17T
ren
dte
st0
.44
rs11
7392
14G
>C
GG
571.
00—
GC
512.
340.
80,6
.87
0.12
CC
105.
671.
24,2
5.96
0.03
MA
F=
0.30
Tre
nd
test
0.0
2
aR
esu
lts
for
tag
SN
Ps
wit
hn
ov
aria
tio
nin
ou
rsa
mp
lear
en
ot
sho
wn
,in
clu
din
grs
4324
75fo
rV
EG
FR
3,
and
for
RO
RC
:rs
1758
2155
,rs
7546
811;
bS
amp
lesi
zes
var
ysl
igh
tly
acro
ssta
gS
NP
sd
ue
tom
issi
ng
val
ues
fro
mra
nd
om
tech
nic
aler
rors
;c In
suffi
cien
td
ata
for
mea
nin
gfu
lan
aly
sis;
dM
AF
refe
rsto
min
or
alle
lefr
equ
ency
.*a
cco
rdin
gto
Hap
Map
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3078
14an
drs
3078
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ein
hig
hL
Db
ut
bel
ow
the
r2=
0.80
thre
sho
ld(r
2=
0.79
).O
ur
anal
yse
sre
vea
lth
etw
oS
NP
sto
be
inh
igh
LD
(r2
=0.
90);
^ac
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ing
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apM
ap,
rs68
7928
5an
drs
1174
7066
are
inL
D(r
2=
0.83
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had
edb
ox
esh
igh
lig
ht
clu
ster
so
fre
sult
s(i
nte
rms
of
ph
ysi
cal
loca
tio
nw
ith
inth
eg
ene)
that
mee
ta
pri
ori
crit
eria
of
inte
rest
,n
amel
yp
tren
d<
0.05
or
extr
eme
od
ds
rati
o(<
0.5
or
>2.
0);
see
resu
lts
for
furt
her
des
crip
tio
n.
10
The third tagSNP, rs1565818, also tags the nonsynonymousSNP p.R1146H (rs1130379), a common polymorphism re-ported not to be associated with PCL.18 However, the aminoacid substitution is located in the cytoplasmic tyrosine kinasedomain of VEGFR3,40 where various mutations have beenfound in PCL families.18,36,37 The functional effects ofp.R1146H have not been reported, although bioinformaticanalysis implies that this residue is not highly evolutionarilyconserved and therefore is most likely a benign alteration;41
nevertheless, the results from our study support furtherevaluation of this tagSNP and the polymorphisms it tags.
The only other statistically significant association we ob-served between a tagSNP and lymphedema occurred in theRORC gene. The functional significance of this member of theretinoid-related orphan receptor family remains unexploredin human secondary lymphedema;42 however, in mice, thisgene is essential for lymphoid organogenesis.21 Also, one of itsligands, retinoic acid, recently has been shown to modulatelymphangiogenesis in vivo in the mouse embryo.43 Similar tothe two VEGF receptor genes, RORC tagSNP rs11801866 islocated at the 5’ end of RORC (in intron 1 of the commonlyexpressed splice variant44). Both rs11801866 and another in-teresting tagSNP in this region, rs12128071, are predicted toaffect transcription factor binding sites.38
Two other genes had more limited evidence from this studyfor involvement in secondary lymphedema. PROX1 is a hu-man homologue of the Drosophila homeobox gene prospero,expressed in lymphatic vessels of adults, and essential tomaintain lymphatic endothelial cell identity.45 However, thetwo tagSNPs with provocative findings located in intron 4 ofPROX1 are now recognized to be in high linkage dysequili-brium with each other, and although they tag a large block ofmany SNPs, none are predicted to have any functional ef-fect.38 LYVE1 is a marker for commencement of lymphaticdevelopment, but the cluster of tagSNPS in the LYVE1 3’ re-gion (rs17318858 and rs17403620, near rs17403795) also hadno predicted functional effects based on current knowledge.38
To our knowledge, this is the first report evaluating po-tential genetic predisposition to secondary lymphedema fol-lowing breast cancer diagnosis and treatment. It is based onrigorous follow-up of a population-based cohort of womenwith breast cancer to detect lymphedema based on objectivemeasurements, followed by a systematic and thorough ex-ploration of polymorphisms in 10 genes of potential interest tothe etiology of secondary lymphedema. Bonferroni correctionwas not applied, as this is considered overly conservative for ahypothesis-generating study. The most significant limitationof the study relates to its small sample size. Although 67 caseshad been identified via clinical assessment in the PullingThrough Study at the time of funding, attrition was muchhigher than anticipated between the 18-month examinationand the 6-year follow-up, in part due to more difficulty ob-taining blood samples from all previous participants and ahigher mortality rate than expected among the women withlymphedema.46 Also, it is plausible that some of the womanclassified as controls had developed lymphedema betweenthe 18-month post-diagnosis assessment and 6-year blooddraw, making it more difficult to find clinically and statisti-cally significant differences between our cases and controls.Nevertheless, despite the limited statistical power, we iden-tified two genetic loci from the same biological family,VEGFR2 and VEGFR3, and a third gene, RORC, to have
clusters of interesting results for SNPs located in analogousparts of the genes. Moreover, a number of these SNPs couldpotentially influence transcription factor binding sites andprotein production. Many of these polymorphisms are suffi-ciently common to be of potential public health importance ifthese associations are genuine, for example, minor allele fre-quencies between 20%–40% for SNPs in the two VEGFRgenes.
In summary, this research extends findings from primarycongenital lymphedema and animal models to secondarylymphedema following cancer diagnosis. The possibility thatthe three receptor genes identified confer genetic predisposi-tion to secondary lymphedema following breast cancertreatment warrants further attention for potential replicationusing larger datasets. If confirmed, understanding the role ofinherited genetic variation in lymphedema pathogenesiscould lead to improvements in clinical management of breastcancer patients. First, with constant improvements in ge-nome-wide sequencing technology and lowering of geno-typing costs for clinical use, it is possible to envisionidentification of lymphedema molecular signature/s thatcould aid in the prediction and modified management ofwomen at risk. This information could be used to target wo-men for monitoring of lymphedema status and rapid referralto specialized care. It has been suggested that early detectionof lymphedema may facilitate more effective management,resulting in reduced severity and associated disability.47 Theemergence of new technologies in drug design and develop-ment, combined with the identification of novel moleculartargets specific to the onset of lymphedema, also may enablefurther development of tailored therapies, both for treatmentand prevention of the condition. Finally, although the find-ings in this study are specifically relevant to breast cancer, ifconfirmed, there are implications for other patients at risk ofsecondary lymphedema following injury, melanoma, or gy-necological, prostate, or head and neck cancers.
Acknowledgments
The original Pulling Through Study was funded by theNational Breast Cancer Foundation (NBCF), while the 6-yearfollow-up was supported by funds from the Australian Na-tional Health and Medical Research Council (NHMRC) andCancer Australia (Grant #497235). ABS was supported by aNHMRC Senior Research Fellowship, SCH was supported bya NBCF Early Career Development Fellowship, and MJ wassupported by a NHMRC Career Development Award. Thiswork was made possible by the women who generously gavetheir time to participate, the clinical support provided by Drs.Chris Pyke, John Bashford, and Christobel Saunders, and theresearch contributions of Dr. Tracey DiSipio, Sheree Rye, andTracy O’Mara.
Author Disclosure Statement
No competing financial interests exist.
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Address correspondence to:Sandra C. Hayes, Ph.D.School of Public Health
Queensland University of TechnologyVictoria Park Road
Kelvin GroveBrisbane, Queensland, 4059
Australia
E-mail: [email protected]
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