The appearance of vitiligo and spontaneous regression of the primary lesion in melanoma patients illustrate a relationship between tumor immunity and autoimmunity. T lymphocytes play a major role both in tumor immunity and autoimmunity. CD28, Cytotoxic T lymphocyte antigen 4 (CTLA4) and inducible costimulator (ICOS) molecules are important secondary signal molecules in the T lymphocyte activation. Single nucleotide polymorphisms (SNPs) in the CD28/CTLA4/ICOS gene region were reported to be associated with several autoimmune diseases including, type-1 diabetes, SLE, autoimmune thyroid diseases and celiac disease. In this study, we investigated the association of SNPs in the CD28, CTLA4 and ICOS genes with the risk of melanoma. We also assessed the prognostic effect of the different polymorphisms in melanoma patients. Twenty-four tagging SNPs across the three genes and four additional SNPs were genotyped in a cohort of 763 German melanoma patients and 734 healthy German controls. Influence on prognosis was determined in 587 melanoma cases belonging to stage I or II of the disease. In general, no differences in genotype or allele frequencies were detected between melanoma patients and controls. However, the variant alleles for two polymorphisms in the CD28 gene were differentially distributed in cases and controls. Similarly no association of any polymorphism with prognosis, except for the rs3181098 polymorphism in the CD28 gene, was observed. In addition, individuals with AA genotype for rs11571323 polymorphism in the ICOS gene showed reduced overall survival. However, keeping in view the correction for multiple hypothesis testing our results suggest that the polymorphisms in the CD28, CTLA4 and ICOS genes at least do not modulate risk of melanoma and nor do those influence the disease prognosis in the investigated population.
The online version of this article (doi:10.1007/s00262-009-0751-2) contains supplementary material, which is available to authorized users.
Introduction
The association between tumor immunity and autoimmunity is complex [1]. Spontaneous regression is believed to be more common in melanoma than any other cancer types. However, the effect of the phenomenon on prognosis is rather unclear; however, the vitiligo is considered a favorable prognostic factor. Autoimmune conditions like thyroiditis and vitiligo, induced by interleukin 2 and/or Interferon α (IFN) therapy, have been associated with an improved prognosis in melanoma patients [2, 3]. The appearance of autoantibodies or autoimmune manifestations in IFN-treated patients has been reported to be associated with significantly improved recurrence free and overall survival [4]. However, the findings could not be replicated when serum samples were analyzed of patients that were randomized to IFN treatment or observation in the EORTC 18952 and the Nordic Melanoma Group phase III trials [5].
T lymphocytes play an important role both in tumor immunity as well as in autoimmunity. The CD28, cytotoxic T lymphocyte antigen 4 (CTLA4) and inducible co-stimulator (ICOS) molecules are important secondary signaling molecules involved in the T lymphocyte activation. The genes encoding CD28, CTL4 and ICOS are located within a stretch of 300 kb region on chromosome 2q33. Ligation of CD28 molecules with the B7-1 (CD80) or B7-2 (CD86) on antigen presenting cells (APCs), stimulate T cell activation and proliferation. CTLA4 counterbalances this effect by competing with CD28 for B7-1/B7-2 binding and is therefore an important inhibitor of T cell activation [6, 7]. CTLA-4 is also an established negative regulator of T-cell function and proliferation through multiple mechanisms such as reducing interleukin (IL)-2 and IL-2 receptor productions and arresting T-cell at the G1-phase of cell cycle [8]. ICOS is another co-stimulatory molecule which is expressed on activated T cells. It binds to a unique ligand, ICOSL, and does not bind to other ligands such as B7-1/B7-2. Polymorphisms in the CD28/CTLA4/ICOS gene region have been associated with several autoimmune diseases including, type 1 diabetes, SLE, autoimmune thyroid diseases and celiac disease [9, 10]. However, a majority of the studies focused on the known CTLA4 polymorphisms. A high prevalence of AA genotype for the CT60 polymorphism in the gene was observed in patients with renal cell cancer and a positive correlation between the polymorphism and tumor grade was also established [11]. The association between the variants in the promoter region of the CTLA4 gene and breast cancer progression has also been reported [12].
Anzeige
In this study, in order to find an association between polymorphisms in the CD28, CTLA-4 and ICOS genes and risk of cutaneous melanoma we screened patients from Germany and ethnically matched healthy controls. The single nucleotide polymorphisms (SNPs) in the three CD28/CTLA4/ICOS genes were selected by tagging approach in order to cover the entire gene regions. Additionally four SNPs reported to be of interest in literature in the CTLA-4 gene were also included in the study. The association of variants alleles with prognostic outcome was also determined.
Methods
Patients and controls
The study population consisted of 763 melanoma patients from Germany (418 male and 345 female), recruited by the Skin Cancer Unit Mannheim, from 2001 to 2008. Patients with primary cutaneous melanoma with different disease stages that included, 10 cases with in situ melanoma, 615 with stage I/II, 111 stage III and 12 cases with stage IV of the disease. For 15 patients stage was unknown. Disease staging was performed according to the current AJCC criteria from 2001 [13]. Median and mean age of the melanoma cases at diagnosis was 55 and 54 years, respectively. Blood samples from case subjects were taken at their first presentation at the skin cancer unit. DNA was isolated from blood samples using Qiagen mini-preparation kits. Informed consent was obtained from the patients and the study was approved by the institutional ethical review board. Control subjects included 734 healthy German individuals (367 male and 367 female) recruited from blood bank Mannheim, with mean and median age of 60 and 61 years, respectively. They were born in southwest Germany and were matched for ethnicity with cases. The inclusion criteria for controls in the study included cancer free status. The age difference between the cases and controls was statistically significant (T-test; P-value <0.01), whereas, the gender difference was not statistically significant (χ2-test; P-value >0.05).
Genes and SNPs selection
The selection of polymorphisms in the CD28, CTLA4 and ICOS genes was based on inclusion of known non-synonymous SNPs and those located in regulatory regions as reported in the dbSNP database of the National Center for Biotechnology Information, NCBI (http://www.ncbi.nlm.nih.gov/SNP/) or reported in published papers. Additionally, tagging SNPs from each gene region were selected from HapMap data using Haploview software 3.32, with pair-wise r2 > 0.8 for each SNP pair and minor allele frequencies >5% (Fig. 1). Ten tagging SNPs in the CD28 gene, five in the CTLA4 gene and 10 in the ICOS gene were selected from HapMap database that covered three genes completely. Four polymorphisms, rs11571319 (CT61), rs11571302 (JO31), rs7665213 (JO30) and rs11571297 (JO27) in the CTLA4 gene, which have been described to correlate with autoimmune disease(s) were also selected. The investigated polymorphisms span a region of 31.0 kb for the CD28 gene region, 6.1 kb for the CTLA4 gene region and 24.7 kb for the ICOS gene region. In total, 29 polymorphisms in three genes (CD28, CTLA4 and ICOS) were identified.
Fig. 1
Haplotype blocks in the genomic region with CTLA-4, CD28 and ICOS genes based on HapMap data
×
Validation of the SNPs by DNA sequencing
The validation of the 29 selected polymorphisms was carried out by sequencing a set of 32 DNA samples from control subjects. Sequencing reactions were performed using Big Dye Terminator Cycle Sequencing Kit (Applied Biosystems, Foster City, Ca, USA) and the following conditions were used; initial 94°C for 1 min followed by 27 cycles at 96°C for 16 s, 56°C for 5 s and 60°C for 4 min. Reaction products were run on ABI prism 3100 Genetic analyzer (Applied Biosystems). Primers used in PCR amplification and sequencing reaction are listed in Supplementary Table.
Anzeige
Genotyping
Genotyping of the validated SNPs was performed by allelic discrimination technique (TaqMan assays, ‘by demand or design’ Applied Biosystems, Supplementary Table). Genotyping for one polymorphism in the ICOS gene (rs4355090) failed and was, thus, excluded from the study. Genotype failure rate was 0.14%, calculated from samples that could not be genotyped after two repeated assays and by direct DNA sequencing. Genotyping data were confirmed by random direct DNA sequencing of 5% of all samples, which showed 100% concordance.
Statistical analysis
The association between malignant melanoma and different genotypes was estimated as odds ratios (OR), 95% confidence intervals (CI) and P-values using SAS version 9.1. Estimates were adjusted for gender and age. Haplotype procedure of SAS/Genetics Software was used to calculate haplotype frequencies in cases and controls. Linkage disequilibrium (LD) was calculated with Haploview software (www.broad.mit.edu/mpg/haploview/documentation.php). The association between genotypes and different survival parameters, adjusted for age, gender and Breslow thickness, was carried out using proportional hazard regression (Cox) model. Metastases free survival (MFS) was the time from date of diagnosis until the first metastasis (either lymph node or distant metastasis) and overall survival (OS) was time from diagnosis to death. The follow-up of patients without metastases or who did not decease has been censored at the latest visit/last contact.
Results
Case-control study
The allelic distribution of polymorphisms in the CD28, CTLA4 and ICOS genes was assessed in 763 German melanoma patients and compared with 734 healthy German controls. A total of 28 SNPs were studied and genotype and allele distributions of all the polymorphisms are summarized in Table 1. Genotype frequency in controls for all the polymorphisms was in accordance with the Hardy–Weinberg equilibrium. Minor allele frequency (MAF) for the rs3181098 polymorphism was higher in cases than in controls (OR: 1.18, 95% CI: 1.00–1.38; P = 0.05). And for the rs3181100 (C > G) polymorphisms the MAF was lower in cases than controls (OR: 0.83, 95% CI: 0.71–0.97; P = 0.02). None of the inferred haplotypes in three genes showed differential distribution between cases and controls (data not shown).
Table 1
Case control
SNP
Genotype
Cases N = 763
(%)
Controls N = 734
(%)
OR
95% CI
P-value
CD28
rs3181098
GG
315
41
331
45
AG
331
43
325
44
1.05
0.84–1.31
AA
117
15
78
11
1.50
1.07–2.11
0.06
G-allele
961
63
987
67
A-allele
565
37
481
33
1.18
1.00–1.38
0.05
rs3181100
CC
279
37
229
31
CG
368
48
357
49
0.87
0.69–1.10
GG
116
15
145
20
0.68
0.50–0.93
0.05
C-allele
926
61
815
56
G-allele
600
39
647
44
0.83
0.71–0.97
0.02
rs3181101
CC
570
75
559
77
CG
175
23
165
23
0.98
0.76–1.26
GG
17
2
7
10
1.97
0.78–4.96
0.35
C-allele
1,315
86
1,283
88
G-allele
209
14
179
12
1.06
0.85–1.33
0.61
rs1181390
GG
474
62
467
64
GT
257
34
233
32
1.14
0.91–1.43
TT
32
4
33
5
0.92
0.55–1.55
0.47
G-allele
1,205
79
1,167
80
T-allele
321
21
299
20
1.06
0.88–1.28
0.53
rs1181388
GG
575
76
545
74
AG
169
22
170
23
0.98
0.76–1.26
AA
17
2
18
3
0.90
0.45–1.81
0.95
G-allele
1,319
87
1,260
86
A-allele
203
13
206
14
0.97
0.78–1.20
0.76
rs17533594
AA
483
63
474
65
AG
257
34
232
32
1.11
0.89–1.40
GG
23
3
24
3
0.94
0.52–1.73
0.63
A-allele
1,223
80
1,180
81
G-allele
303
20
280
19
1.06
0.88–1.28
0.55
rs3116494
AA
414
54
393
54
AG
307
40
299
41
1.01
0.81–1.26
GG
42
6
39
5
1.09
0.67–1.75
0.94
A-allele
1,135
74
1,085
74
G-allele
391
26
377
26
1.02
0.86–1.21
0.79
rs3181107
AA
659
86
620
85
AG
100
13
106
15
0.92
0.67–1.25
GG
4
1
6
1
0.74
0.20–2.79
0.78
A-allele
1,418
93
1,346
92
G-allele
108
7
118
8
0.91
0.68–1.20
0.49
rs3116496 (IVS3 + 17)
TT
487
64
475
65
CT
254
33
231
32
1.10
0.88–1.38
CC
22
3
24
3
0.89
0.48–1.64
0.63
T-allele
1,228
81
1,181
81
C-allele
298
20
279
20
1.04
0.86–1.26
0.66
CTLA4
rs16840252
CC
521
68
489
67
1.00
CT
218
29
222
30
0.91
0.72–1.15
TT
23
3
21
3
1.02
0.54–1.91
0.74
C-allele
1,260
83
1,200
82
T-allele
264
17
264
18
0.95
0.78–1.15
0.57
rs5742909 (CT44)
CC
619
81
596
81
1.00
CT
136
18
130
18
0.96
0.73–1.27
TT
8
1
8
1
0.89
0.32–2.49
0.95
C-allele
1,374
90
1,322
90
T-allele
152
10
146
10
0.96
0.75–1.23
0.74
rs231775 (CT42)
AA
289
38
283
39
1.00
AG
369
48
345
47
1.08
0.86–1.36
GG
104
14
106
14
0.97
0.70–1.36
0.71
A-allele
947
62
911
62
G-allele
577
38
557
38
1.01
0.87–1.18
0.90
rs231777
CC
539
71
514
70
1.00
CT
208
27
203
28
0.97
0.76–1.23
TT
15
2
16
2
0.83
0.39–1.77
0.87
C-allele
1,286
84
1,231
84
T-allele
238
16
235
16
0.95
0.78–1.17
0.64
rs3087243 (CT60)
GG
246
32
223
30
1.00
AG
355
47
388
53
0.81
0.63–1.03
AA
162
21
122
17
1.22
0.89–1.65
0.01
G-allele
847
56
834
57
A-allele
679
45
632
43
1.06
0.91–1.23
0.45
rs11571319 (CT61)
GG
518
68
488
67
1.00
AG
222
29
223
31
0.93
0.73–1.17
AA
23
3
21
3
1.02
0.54–1.92
0.81
G-allele
1,258
82
1,199
82
A-allele
268
18
265
18
0.96
0.79–1.16
0.64
rs11571302 (JO31)
GG
225
30
210
29
1.00
GT
370
49
383
52
0.87
0.68–1.12
TT
168
22
140
19
1.14
0.84–1.55
0.15
G-allele
820
54
803
55
T-allele
706
46
663
45
1.05
0.90–1.22
0.53
rs7665213 (JO30)
GG
228
30
211
29
1.00
AG
370
49
383
52
0.87
0.68–1.12
AA
165
22
137
19
1.13
0.83–1.53
0.17
G-allele
826
54
805
55
A-allele
700
46
657
45
1.04
0.90–1.21
0.59
rs11571297 (JO27)
TT
214
28
193
26
1.00
CT
376
49
393
54
0.84
0.65–1.08
CC
173
23
148
20
1.07
0.79–1.45
0.15
T-allele
804
53
779
53
C-allele
722
47
689
47
1.02
0.88–1.18
0.81
ICOS
rs10932029 (+173)
TT
538
71
488
67
1.00
CT
204
27
228
31
0.82
0.65–1.03
CC
21
3
15
2
1.14
0.57–2.27
0.20
T-allele
1,280
84
1,204
82
C-allele
246
16
258
18
0.89
0.73–1.08
0.23
rs4335928
TT
579
76
559
76
1.00
CT
170
22
162
22
0.99
0.77–1.28
CC
14
2
12
2
1.11
0.50–2.47
0.96
T-allele
1,328
87
1,280
87
C-allele
198
13
186
13
1.01
0.80–1.26
0.96
rs4675374
CC
457
60
436
60
1.00
CT
272
36
258
35
0.98
0.78–1.23
TT
34
5
38
5
0.85
0.52–1.40
0.82
C-allele
1,186
78
1,130
77
T-allele
340
22
334
23
0.96
0.80–1.14
0.62
rs7602383
AA
550
72
533
73
1.00
AG
197
26
183
25
1.01
0.79–1.29
GG
16
2
17
2
0.93
0.46–1.90
0.98
A-allele
1,297
85
1,249
85
G-allele
229
15
217
15
0.99
0.81–1.23
0.95
rs4521021
TT
450
59
451
61
1.00
CT
276
36
260
35
1.00
0.80–1.25
CC
37
5
23
3
1.47
0.83–2.60
0.41
T-allele
1,176
77
1,162
80
C-allele
350
23
306
21
1.07
0.89–1.28
0.45
rs11571323
GG
587
77
534
73
1.00
AG
161
21
184
25
0.81
0.63–1.04
AA
15
2
13
2
1.30
0.60–2.84
0.18
G-allele
1,335
88
1,252
86
A-allele
191
13
210
14
0.89
0.71–1.10
0.29
rs12466129
TT
448
59
451
62
1.00
AT
273
36
239
33
1.14
0.91–1.43
AA
42
6
42
6
0,94
0.59–1.51
0.47
T-allele
1,169
77
1,141
78
A-allele
357
23
323
22
1.06
0.89–1.27
0.54
rs10172036
GG
301
40
283
39
1.00
GT
353
46
352
48
0.92
0.73–1.15
TT
109
14
97
13
1.04
0.75–1.45
0.63
G-allele
955
63
918
63
T-allele
571
37
546
37
0.99
0.85–1.16
0.93
rs10183087
AA
461
61
418
57
1.00
AC
263
35
277
38
0.85
0.68–1.06
CC
38
5
37
5
1.04
0.63–1.70
0.32
A-allele
1,185
78
1,113
76
C-allele
339
22
351
24
0.92
0.77–1.10
0.36
rs10932036
AA
611
80
594
81
1.00
AT
144
19
129
18
1.09
0.83–1.44
TT
7
1
7
1
1.12
0.37–3.35
0.81
A-allele
1,366
90
1,317
90
T-allele
158
10
143
10
1.08
0.85–1.39
0.53
Association between polymorphisms and prognosis
The association between polymorphisms and survival parameters was evaluated for melanoma patients in stage I and II. Information regarding metastases free survival (MFS), overall survival (OS) and Breslow thickness was available for 587 patients (321 male and 266 female). Mean age was 54 years (median 55 years), the mean and median Breslow thickness was 1.84 and 1.50 mm, respectively. Ulceration status of the primary tumor was not systematically recorded in the past and is therefore lacking. Age, gender and Breslow thickness were included as covariates in the Cox regression analysis. Overall, on comparing carriers versus non-carriers, no significant differences in OS were observed (Tables 2, 3, 4). A single SNP in the CD28 gene (rs3181098) showed an association with reduced metastases free survival (HR 1.34 95% CI: 1.02–1.77). In addition to the carrier versus non-carrier approach, effect of the different genotypes on prognosis was analyzed. According to this analysis, one SNP (AA) in the ICOS gene (rs11571323) was associated with reduced overall survival, P = 0.04, HR 3.60; 95% CI, 1.31–9.91, however, only 13 (2.2%) melanoma patients carried AA genotype.
Table 2
CD28
SNP
Genotype
Cases (%) N = 587
Metastases free survival
Overall survival
OR
95% CI
P-value
OR
95% CI
P-value
rs3181098
GG
247 (42)
AG/AA
340 (58)
1.34
1.02–1.77
0.04
1.18
0.81–1.72
0.38
rs3181100
CC
212 (36)
CG/GG
375 (64)
0.82
0.62–1.08
0.16
0.82
0.56–1.20
0.31
rs3181101
CC
440 (75)
CG/GG
146 (25)
1.28
0.94–1.74
0.12
1.21
0.80–1.83
0.38
rs1181390
GG
360 (61)
GT/TT
227 (39)
0.92
0.70–1.21
0.56
1.16
0.80–1.67
0.45
rs1181388
GG
440 (75)
AG/AA
146 (25)
0.86
0.63–1.17
0.32
0.82
0.53–1.25
0.35
rs17533594
AA
372 (63)
AG/GG
215 (37)
1.03
0.78–1.35
0.84
1.23
0.85–1.79
0.28
rs3116494
AA
319 (54)
AG/GG
268 (46)
0.99
0.76–1.30
0.96
1.13
0.79–1.62
0.52
rs3181107
AA
506 (86)
AG/GG
81 (14)
0.81
0.54–1.21
0.30
0.73
0.41–1.29
0.28
rs3116496 (IVS3 +17)
TT
378 (64)
CT/CC
209 (36)
1.16
0.88–1.53
0.29
1.39
0.96–2.02
0.08
Table 3
CTLA4
SNP
Genotype
Cases (%) N = 587
Metastases free survival
Overall survival
OR
95% CI
P-value
OR
95% CI
P-value
rs16840252
CC
399 (68)
CT/TT
187 (32)
1.11
0.84–1.48
0.46
1.25
0.85–1.82
0.26
rs5742909 (CT44)
CC
476 (81)
CT/TT
111 (19)
1.24
0.88–1.72
0.22
1.40
0.90–2.18
0.14
rs231775 (CT42)
AA
219 (37)
AG/GG
367 (63)
0.99
0.75–1.30
0.93
0.92
0.63–1.33
0.64
rs231777
CC
414 (71)
CT/TT
172 (29)
1.04
0.78–1.39
0.79
1.23
0.83–1.80
0.30
rs3087243 (CT60)
GG
195 (33)
AG/AA
392 (67)
0.99
0.74–1.31
0.92
0.93
0.63–1.36
0.69
rs11571319 (CT61)
GG
397 (68)
AG/AA
190 (32)
1.10
0.83–1.45
0.51
1.19
0.81–1.73
0.38
rs11571302 (JO31)
GG
173 (30)
GT/TT
414 (71)
0.95
0.71–1.27
0.72
0.80
0.55–1.17
0.26
rs7665213 (JO30)
GG
176 (30)
AG/AA
411 (70)
0.95
0.72–1.27
0.74
0.83
0.57–1.21
0.32
rs11571297 (JO27)
TT
163 (28)
CT/CC
424 (72)
0.87
0.65–1.16
0.33
0.76
0.52–1.11
0.16
Table 4
ICOS
SNP
Genotype
Cases (%) N = 587
Metastases free survival
Overall survival
OR
95% CI
P-value
OR
95% CI
P-value
rs10932029 (+173)
TT
412 (70)
CT/CC
175 (30)
0.87
0.65–1.17
0.36
0.79
0.53–1.18
0.25
rs4335928
TT
446 (76)
CT/CC
141 (24)
1.17
0.86–1.60
0.32
1.26
0.82–1.92
0.29
rs4675374
CC
352 (60)
CT/TT
235 (40)
1.08
0.82–1.42
0.58
1.31
0.91–1.88
0.15
rs7602383
AA
421 (72)
AG/GG
166 (28)
1.02
0.76–1.37
0.88
1.12
0.75–1.66
0.59
rs4521021
TT
345 (59)
CT/CC
242 (41)
0.96
0.73–1.26
0.77
1.19
0.83–1.71
0.35
rs11571323
GG
452 (77)
AG/AA
135 (23)
1.07
0.78–1.46
0.70
1.27
0.83–1.94
0.28
rs12466129
TT
340 (58)
AT/AA
247 (42)
0.86
0.66–1.13
0.28
1.03
0.72–1.48
0.88
rs10172036
GG
232 (40)
GT/TT
355 (61)
1.12
0.85–1.50
0.42
0.86
0.58–1.26
0.43
rs10183087
AA
352 (60)
AC/CC
234 (40)
0.87
0.66–1.15
0.33
0.93
0.64–1.35
0.70
rs10932036
AA
467 (80)
AT/TT
119 (20)
0.76
0.54–1.06
0.11
0.76
0.48–1.19
0.23
Discussion
The immunogenic nature of malignant melanoma is clinically manifested by spontaneous regression and appearance of vitiligo. The phenomenon of autoimmunity observed during various forms of immunotherapy, IL-2, IFN and anti-CTLA4 therapy, have been linked to the treatment response [2‐4]. To understand the link between tumor immunity and autoimmunity in melanoma and to explore its implication on disease susceptibility and prognosis remains a challenge [14]. The results from studies evaluating polymorphisms in various autoimmune diseases suggest the existence of a common autoimmune disease locus in the CTLA4 gene [9].
We genotyped 28 polymorphisms located in the CD28, CTLA4 and ICOS genes in melanoma patients and healthy controls. Use of tagging approach covered the entire loci for all three genes. To the best of our knowledge, the screen for SNPS in the CTLA4 gene was the largest ever performed in melanoma patients (and controls) and the first one for the ICOS and CD28 genes. Our results showed that the variant alleles for two polymorphisms in the CD28 gene (rs3181098 and rs3181100) were differentially distributed in cases and controls. No differences in genotype or allele frequencies were detected between melanoma patients and controls for any other polymorphism. Similarly, carriers of the variant allele for the polymorphism rs3181098 in the CD28 gene showed reduced metastasis free survival and for the polymorphism rs11571323 the individuals with variant allele homozygous genotype were associated with reduced overall survival. However, keeping in view the number of tests carried out in the present study, the observed significant associations would be lost upon multiple hypothesis correction. Moreover, the detected association would also require confirmatory testing in an independent population.
One of the limitations of the present study included lack of pigmentation data, history of sunburns and the existence of statistical significant difference in mean age between cases and controls. Keeping in view the fact that ethnicity and not the age is major determinant of variant allele frequency, in our study design we ensured complete match between cases and controls for the latter parameter.
Our results are in accordance with a previous study that reported no difference in frequencies of six polymorphisms in the CTLA4 gene in 203 melanoma patients (stage IIb, IIc and III), compared to 288 healthy controls. Also no polymorphism correlated with improved recurrence free or overall survival [15]. However, several studies have reported association of the CTLA4 polymorphisms with other malignancies [16]. In humans cell CTLA4 exists in two isoforms, a full-length and a soluble isoform that lacks exon 3 due to alternative splicing [17]. The CT60 (A/G) polymorphism in the CTLA4 gene is a key susceptibility locus for autoimmune diseases, and the G-allele was shown to be correlated with decreased levels of the soluble isoform [9]. The frequency of the AA genotype for CT60 polymorphism was reported to be higher in renal cell carcinoma (RCC) patients than in controls. In addition, a positive correlation between the AA genotype and tumor grade was also observed, suggesting a role in tumor development [11]. The CT42 polymorphism (49A/G) in exon 1 is the only amino acid (Thr > Ala) altering polymorphism in the CTLA4 gene; and the individuals homozygous for the Ala allele were associated with decreased CTLA4 expression on the T cell surfaces [18]. The AA genotype was correlated with increased frequencies in RCC patients and the A allele, in association with the 3′-untranslated region (AT)82 alleles, correlated with non-Hodgkin’s lymphoma (NHL) [11, 19]. Interestingly, the GG variant was linked to an increased risk of gastric mucosa-associated lymphoid tissue (MALT) lymphoma [20]. In a study on multiple cancer types, 49A/G polymorphism has been risk of lung, breast and esophageal cancers as well as gastric cardia [16]. CTLA-4 with variant Thr allele has been shown to be associated with stronger inhibitory effect on T-cell activation than that with common allele. Polymorphisms in the promoter region of the CTLA4 gene were described to modulate expression of the gene [21]. This region contains the CT44 polymorphism (−318 C/T) variant. The CC genotype of the CT44 polymorphism was shown to be correlated with significantly reduced lymph node involvement in breast cancer patients [12]. The T allele was linked to an increased risk of B-CLL but to a decreased risk of MALT lymphoma [20, 22]. No correlation was found between the CT44 polymorphism and the risk of colon cancer [23]. The chromosomal region 2q33 containing the CTLA-4 and CD28 genes has been linked with asthma, however, the association with polymorphisms in the genes was not detected [24].
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Melanoma patients with thick primary tumors and/or nodal involvement are at high risk for relapse or death [13]. However, adjuvant treatment is only beneficial in a small group of these patients. Genetic variability possibly predicts treatment outcome and could be a predictive marker to select the group benefiting from a certain treatment. In this study, only stage I and II melanoma patients were evaluated for a possible association between SNPs and prognosis. Since these patients do not frequently receive systemic treatment, we could not assess the predictive value of any of the polymorphisms. Nevertheless, recently it was shown that polymorphisms in the CTLA4 gene were correlated with response in melanoma patients (stage IV) receiving anti-CTLA4 treatment [25].
In conclusion, from the results of this large study we did not find convincing evidence for association between polymorphisms in the CD28, CTLA4 and ICOS genes and the risk of melanoma, nor with an effect on prognosis. Even two individual polymorphisms showed differential distribution of variant alleles between cases and controls, the effect nevertheless was marginal and a chance factor could no be ruled. The study was confined to German population, therefore, a strong association of polymorphisms investigated with melanoma susceptibility or disease outcome, in other populations cannot be entirely precluded.
Acknowledgments
We acknowledge technical assistance by Sigrid Claus. This work was supported by the Initiative and Networking Fund of the Helmholtz Association within the Helmholtz Alliance on Immunotherapy of Cancer and an EORTC Translational Grant STrF/2008-1.
Open Access
This article is distributed under the terms of the Creative Commons Attribution Noncommercial License which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited.
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Open AccessThis is an open access article distributed under the terms of the Creative Commons Attribution Noncommercial License (https://creativecommons.org/licenses/by-nc/2.0), which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited.
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