IGF2R has been proposed to be a tumor suppressor gene given its antagonist role on cellular growth and evidence of loss of heterozygosity in several cancers, including breast cancer. To investigate whether inherited differences in potentially functional IGF2R variants influence the risk of breast cancer, we sequenced 46 exons of IGF2R to identify novel missense single-nucleotide polymorphisms (SNP) and tested 12 missense SNPs for their associations with breast cancer risk among 1,614 breast cancer cases and 1,960 controls from the Multiethnic Cohort. None of these missense SNPs were significantly associated with breast cancer risk. Our findings provide no evidence that missense SNPs in IGF2R influence breast cancer susceptibility.(Cancer Epidemiol Biomarkers Prev 2009;18(6):1922–4)

The insulin-like growth factor-II receptor (IGF2R) is a transmembrane receptor that primarily binds IGF-II, resulting in the degradation of IGF-II by internalization and transport to the lysosomes. By removing IGF-II from the extracellular environment and precluding its activation of the insulin-like growth factor-I receptor (IGF1R), IGF2R is believed to reduce the mitogenic effects of IGF-II (1). Loss of heterozygosity at the IGF2R locus has been reported in breast carcinomas, and somatic missense mutations of the remaining allele have shown alteration in ligand binding (2-4). IGF2R has been proposed to be a tumor suppressor gene given its antagonist role on cellular growth and evidence of loss-of-heterozygosity and loss-of-function mutations in several cancers (5-10), including breast cancer (2-4). To investigate whether inherited differences in potentially functional IGF2R variants influence the risk of breast cancer, we sequenced 46 exons of IGF2R to identify novel missense single-nucleotide polymorphisms (SNP) and tested 12 missense SNPs for their associations with breast cancer risk among 1,614 breast cancer cases and 1,960 controls from the Multiethnic Cohort.

Study Subjects

The Multiethnic Cohort study is a large population-based cohort study of more than 215,000 individuals from Hawaii and California. The cohort is composed of predominantly African Americans, Native Hawaiians, Japanese Americans, Latinos, and Whites, who were between the ages of 45 and 75 y when recruited from 1993 to 1996. Further methodologic details of this study are provided elsewhere (11).

The present case-control study was nested in the Multiethnic Cohort, as previously described (12). It includes 1,614 breast cancer cases and 1,960 controls that were frequency matched on age (within 5 y) and race/ethnicity. The majority of these women were postmenopausal at baseline (87% of cases and 82% of controls). This study was approved by the Institutional Review Boards at the University of Hawaii and the University of Southern California.

Sequencing and Validation Genotyping

To identify novel missense SNPs, we successfully sequenced 46 of the 48 exons of IGF2R in 95 advanced breast cancer cases (n = 19 per racial/ethnic group). Two exons (exon 1 and exon 30) did not meet our sequencing criteria of >80% of samples with Phred (base-calling) scores >20 for >80% of the target bases; thus, for these we relied on publicly available SNP information. Further details on sequencing methods are described elsewhere (13). Nineteen IGF2R missense SNPs were identified by sequencing. For validation, these 19 SNPs and 2 additional common missense SNPs (minor allele frequency >0.05) in dbSNP (rs8191754 and rs629849) were genotyped in an independent multiethnic panel of 349 control subjects (n = 69-70 per racial/ethnic group).

Genotyping of Breast Cancer Cases and Controls

Table 1 lists the 12 IGF2R missense SNPs that were genotyped in the breast case-control study. Ten SNPs were genotyped using the Sequenom genotyping platform; two SNPs (rs8191754 and rs629849) that failed Sequenom assay design or genotyping were genotyped by the TaqMan platform. The average concordance rate for ∼5% quality control repeats was 99.7% and the average genotyping success was 97.1%. There were no deviations from Hardy-Weinberg equilibrium (P > 0.01 > 1 racial/ethnic group).

Table 1.

Twelve IGF2R missense SNPs used for association testing

SNPExon no.Position*Nucleotide changeAmino acid changePolyPhen predictionMinor allele frequency (%)
African AmericansNative HawaiiansJapanese AmericansLatinosWhites
rs8191746 160365688 C>T Pro203Leu Probably damaging 2.1 
rs8191754 160368314 C>G Leu252Val Benign 12.1 18.4 31.6 6.4 14.5 
rs6413491 16 160388299 G>A Ala724Thr Benign 3.9 0.8 0.8 
IGF2R_C722T§ 17 160388898 C>T Pro772Leu Probably damaging 2.9 0.70 
rs8191808 18 160389500 G>C Val817Leu Benign 0.7 0.7 0.7 
rs8191844 25 160402919 C>G Thr1184Ser Possibly damaging 3.6 
IGF2R_C1194T§ 25 160402949 C>T Ser1194Leu Benign 2.2 
rs8191859 28 160405480 G>A Gly1315Glu Possibly damaging 8.0 
rs629849 34 160414399 G>A Gly1619Arg Benign 2.9 11.0 9.4 6.5 10.7 
IGF2R_C1822T§ 37 160419371 C>T Thr1822Met — 3.6 1.43 
rs8191904 38 160420618 G>A Arg1832His Benign 4.8 0.91 
rs8191955 48 160446006 C>T Ala2459Val Benign 2.9 0.7 0.7 
SNPExon no.Position*Nucleotide changeAmino acid changePolyPhen predictionMinor allele frequency (%)
African AmericansNative HawaiiansJapanese AmericansLatinosWhites
rs8191746 160365688 C>T Pro203Leu Probably damaging 2.1 
rs8191754 160368314 C>G Leu252Val Benign 12.1 18.4 31.6 6.4 14.5 
rs6413491 16 160388299 G>A Ala724Thr Benign 3.9 0.8 0.8 
IGF2R_C722T§ 17 160388898 C>T Pro772Leu Probably damaging 2.9 0.70 
rs8191808 18 160389500 G>C Val817Leu Benign 0.7 0.7 0.7 
rs8191844 25 160402919 C>G Thr1184Ser Possibly damaging 3.6 
IGF2R_C1194T§ 25 160402949 C>T Ser1194Leu Benign 2.2 
rs8191859 28 160405480 G>A Gly1315Glu Possibly damaging 8.0 
rs629849 34 160414399 G>A Gly1619Arg Benign 2.9 11.0 9.4 6.5 10.7 
IGF2R_C1822T§ 37 160419371 C>T Thr1822Met — 3.6 1.43 
rs8191904 38 160420618 G>A Arg1832His Benign 4.8 0.91 
rs8191955 48 160446006 C>T Ala2459Val Benign 2.9 0.7 0.7 
*

SNP position based on dbSNP reference assembly (Build 36.3).

Minor allele based on all groups combined.

§

Novel missense SNP identified by sequencing.

In silico Analysis

The Polymorphism Phenotype (PolyPhen)4

algorithm (14) was used to predict the potential effect of each missense SNP on IGF2R protein structure and function (Table 1). Predictions are based on sequence, phylogenetic, and structural information to evaluate the degree of damage a variant may have on the structural properties of the protein. A score is assigned to each SNP indicating either “probably damaging,” “possibly damaging,” or “benign” effects on protein function and/or structure.

Statistical Analysis

Odds ratios (OR) and 95% confidence intervals (95% CI) were estimated by unconditional logistic regression to estimate genotype-specific risks, adjusting for age and ethnicity in any analysis that combined racial/ethnic groups. All results were similar when adjusted for established breast cancer risk factors (15). In addition, given that missense SNPs generally have low minor allele frequencies, we examined the association between the aggregate number of variant missense alleles and breast cancer risk to assess whether there was an overrepresentation of variant alleles among cases versus controls. The aggregate number of variant alleles was determined by counting the total number of minor alleles across all 12 missense SNPs (38.5% of controls had >1 variant allele). All reported P values are two-sided.

Nineteen IGF2R missense SNPs were identified by sequencing 46 exons. With genotyping of these 19 SNPs in a multiethnic panel for validation, 3 SNPs were identified to be novel (Supplementary Table S1) because they are not present in the dbSNP database5

; 7 SNPs were already present in dbSNP; and 9 SNPs were monomorphic (minor allele frequency <0.01 in all of the five racial/ethnic groups).

Ten validated missense SNPs identified by sequencing and two additional missense SNPs from dbSNP (rs8191746 and rs8191808) were tested in our breast cancer case-control study. There were no associations between these missense SNPs and breast cancer risk (P > 0.06; Table 2). In addition, no association with breast cancer risk was observed for the aggregate number of variant missense alleles in comparison with no variant alleles (OR, 1.07; 95% CI, 0.93-1.25). Similarly, no association was observed for an increment of one variant allele (OR, 1.03; 95% CI, 0.95-1.12). For the aggregate number of variant alleles of the four missense SNPs (rs8191746, IGF2R_C722T, rs8191844, and rs8191859) predicted to have “probably/possibly damaging effects,” no association was observed (OR, 0.97; 95% CI, 0.66-1.42).

Table 2.

Associations between IGF2R missense variants and breast cancer risk

SNPGenotypeAll
Cases, n (%)Controls, n (%)OR (95% CI)*
rs8191746 CC 1584 (99.5) 1862 (99.4) 1.00 
 CT 8 (0.5) 11 (0.6) 0.76 (0.30-1.91) 
rs8191754 CC 1096 (71.1) 1354 (71.2) 1.00 
 CG/GG 445 (28.9) 547 (28.8) 1.14 (0.95-1.30) 
rs6413491 GG 1568 (98.6) 1833 (98.4) 1.00 
 GA/AA 23 (1.4) 29 (1.6) 0.85 (0.48-1.48) 
IGF2R_C722T CC 1572 (99.9) 1923 (100.0) 1.00 
 CT 1 (0.06) 1 (0.1) 1.18 (0.07-18.97) 
rs8191808 CC 1572 (99.1) 1846 (99.3) 1.00 
 CG 14 (0.9) 14 (0.8) 1.28 (0.60-2.73) 
rs8191844 CC 1562 (98.3) 1839 (98.6) 1.00 
 CG/GG 27 (1.7) 26 (1.4) 1.12 (0.64-1.96) 
IGF2R_C1194T CC 1574 (97.9) 1851 (98.7) 1.00 
 CT/TT 34 (2.1) 25 (1.3) 1.40 (0.82-2.39) 
rs8191859 GG 1557 (98.9) 1877 (97.4) 1.00 
 GA/AA 17 (1.1) 50 (2.6) 0.87 (0.48-1.59) 
rs629849 AA 1283 (82.8) 1589 (83.7) 1.00 
 AG/GG 267 (17.2) 309 (16.3) 1.06 (0.88-1.28) 
IGF2R_C1822T CC 1572 (98.7) 1839 (98.7) 1.00 
 CT 21 (1.3) 24 (1.3) 0.92 (0.50-1.68) 
rs8191904 GG 1551 (99.1) 1893 (98.4) 1.00 
 GA/AA 14 (0.9) 31 (1.6) 0.54 (0.28-1.03) 
rs8191955 CC 1550 (99.5) 1910 (99.5) 1.00 
 CT 8 (0.5) 9 (0.5) 1.50 (0.55-4.14) 
SNPGenotypeAll
Cases, n (%)Controls, n (%)OR (95% CI)*
rs8191746 CC 1584 (99.5) 1862 (99.4) 1.00 
 CT 8 (0.5) 11 (0.6) 0.76 (0.30-1.91) 
rs8191754 CC 1096 (71.1) 1354 (71.2) 1.00 
 CG/GG 445 (28.9) 547 (28.8) 1.14 (0.95-1.30) 
rs6413491 GG 1568 (98.6) 1833 (98.4) 1.00 
 GA/AA 23 (1.4) 29 (1.6) 0.85 (0.48-1.48) 
IGF2R_C722T CC 1572 (99.9) 1923 (100.0) 1.00 
 CT 1 (0.06) 1 (0.1) 1.18 (0.07-18.97) 
rs8191808 CC 1572 (99.1) 1846 (99.3) 1.00 
 CG 14 (0.9) 14 (0.8) 1.28 (0.60-2.73) 
rs8191844 CC 1562 (98.3) 1839 (98.6) 1.00 
 CG/GG 27 (1.7) 26 (1.4) 1.12 (0.64-1.96) 
IGF2R_C1194T CC 1574 (97.9) 1851 (98.7) 1.00 
 CT/TT 34 (2.1) 25 (1.3) 1.40 (0.82-2.39) 
rs8191859 GG 1557 (98.9) 1877 (97.4) 1.00 
 GA/AA 17 (1.1) 50 (2.6) 0.87 (0.48-1.59) 
rs629849 AA 1283 (82.8) 1589 (83.7) 1.00 
 AG/GG 267 (17.2) 309 (16.3) 1.06 (0.88-1.28) 
IGF2R_C1822T CC 1572 (98.7) 1839 (98.7) 1.00 
 CT 21 (1.3) 24 (1.3) 0.92 (0.50-1.68) 
rs8191904 GG 1551 (99.1) 1893 (98.4) 1.00 
 GA/AA 14 (0.9) 31 (1.6) 0.54 (0.28-1.03) 
rs8191955 CC 1550 (99.5) 1910 (99.5) 1.00 
 CT 8 (0.5) 9 (0.5) 1.50 (0.55-4.14) 
*

Adjusted for age and racial/ethnic group.

In summary, our multiethnic study does not support the influence of IGF2R missense SNPs on breast cancer risk. Our study had 80% power to detect a minimum OR of 1.35 and 1.57 for SNPs at 5% and 2% allele frequencies, respectively (α = 0.05, two-sided hypothesis test, log-linear model; ref. 16). In addition, we had 80% power to detect a minimum OR of 1.16 for missense SNPs in aggregate (38.5% of controls had >1 variant allele) under similar parameters. Our study cannot exclude the possibility that common genetic variation in IGF2R may have weak effects on breast cancer risk. Moreover, larger studies, such as in the National Cancer Institute Breast and Prostate Cancer Consortium (17), are indicated to evaluate whether the combined effects of several genes in the IGF pathway are more likely to affect breast cancer susceptibility.

No potential conflicts of interest were disclosed.

Grant support: Susan G. Komen Foundation grant BCTR0504392 and National Cancer Institute grants CA 63464 and CA 54281.

Note: Supplementary data for this article are available at Cancer Epidemiology Biomakers and Prevention Online (http://cebp.aacrjournals.org/).

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

We thank the participants of this study, who have contributed to a better understanding of the genetic contributions to breast cancer susceptibility.

1
Oates AJ, Schumaker LM, Jenkins SB, et al. The mannose 6-phosphate/insulin-like growth factor 2 receptor (M6P/IGF2R), a putative breast tumor suppressor gene.
Breast Cancer Res Treat
1998
;
47
:
269
–81.
2
Byrd JC, Devi GR, de Souza AT, Jirtle RL, MacDonald RG. Disruption of ligand binding to the insulin-like growth factor II/mannose 6-phosphate receptor by cancer-associated missense mutations.
J Biol Chem
1999
;
274
:
24408
–16.
3
Chappell SA, Walsh T, Walker RA, Shaw JA. Loss of heterozygosity at the mannose 6-phosphate insulin-like growth factor 2 receptor gene correlates with poor differentiation in early breast carcinomas.
Br J Cancer
1997
;
76
:
1558
–61.
4
Hankins GR, De Souza AT, Bentley RC, et al. M6P/IGF2 receptor: a candidate breast tumor suppressor gene.
Oncogene
1996
;
12
:
2003
–9.
5
Hu CK, McCall S, Madden J, et al. Loss of heterozygosity of M6P/IGF2R gene is an early event in the development of prostate cancer.
Prostate Cancer Prostatic Dis
2006
;
9
:
62
–7.
6
Huang Z, Wen Y, Shandilya R, Marks JR, Berchuck A, Murphy SK. High throughput detection of M6P/IGF2R intronic hypermethylation and LOH in ovarian cancer.
Nucleic Acids Res
2006
;
34
:
555
–63.
7
Kong FM, Anscher MS, Washington MK, Killian JK, Jirtle RL. M6P/IGF2R is mutated in squamous cell carcinoma of the lung.
Oncogene
2000
;
19
:
1572
–8.
8
Savage SA, Woodson K, Walk E, et al. Analysis of genes critical for growth regulation identifies insulin-like growth factor 2 receptor variations with possible functional significance as risk factors for osteosarcoma.
Cancer Epidemiol Biomarkers Prev
2007
;
16
:
1667
–74.
9
Yamada T, De Souza AT, Finkelstein S, Jirtle RL. Loss of the gene encoding mannose 6-phosphate/insulin-like growth factor II receptor is an early event in liver carcinogenesis.
Proc Natl Acad Sci U S A
1997
;
94
:
10351
–5.
10
Lee HY, Jung H, Jang IH, Suh PG, Ryu SH. Cdk5 phosphorylates PLD2 to mediate EGF-dependent insulin secretion.
Cell Signal
2008
;
20
:
1787
–94.
11
Kolonel LN, Henderson BE, Hankin JH, et al. A multiethnic cohort in Hawaii and Los Angeles: baseline characteristics.
Am J Epidemiol
2000
;
151
:
346
–57.
12
Haiman CA, Stram DO, Pike MC, et al. A comprehensive haplotype analysis of CYP19 and breast cancer risk: the Multiethnic Cohort.
Hum Mol Genet
2003
;
12
:
2679
–92.
13
Freedman ML, Pearce CL, Penney KL, et al. Systematic evaluation of genetic variation at the androgen receptor locus and risk of prostate cancer in a multiethnic cohort study.
Am J Hum Genet
2005
;
76
:
82
–90.
14
Ramensky V, Bork P, Sunyaev S. Human non-synonymous SNPs: server and survey.
Nucleic Acids Res
2002
;
30
:
3894
–900.
15
Pike MC, Kolonel LN, Henderson BE, et al. Breast cancer in a multiethnic cohort in Hawaii and Los Angeles: risk factor-adjusted incidence in Japanese equals and in Hawaiians exceeds that in whites.
Cancer Epidemiol Biomarkers Prev
2002
;
11
:
795
–800.
16
Gauderman WJ. Sample size requirements for association studies of gene-gene interaction.
Am J Epidemiol
2002
;
155
:
478
–84.
17
Hunter DJ, Riboli E, Haiman CA, et al. A candidate gene approach to searching for low-penetrance breast and prostate cancer genes.
Nat Rev Cancer
2005
;
5
:
977
–85.

Supplementary data