Abstract
CYP19A1, or aromatase, influences estrogen-metabolizing enzymes and may influence cancer risk. We examine variation in the CYP19A1 gene and risk of colorectal cancer using data from population-based case–control studies (colon n = 1,574 cases, 1,970 controls; rectal n = 791 cases, 999 controls). Four SNPs were statistically significantly associated with colon cancer and four were associated with rectal cancer. After adjustment for multiple comparisons, the AA genotype of rs12591359 was associated with an increased risk of colon cancer (OR 1.44 95% CI 1.16–1.80) and the AA genotype of rs2470144 was associated with a reduced risk of rectal cancer (OR 0.65 95% CI 0.50–0.84). Variants of CYP19A1 were associated with CIMP+ and CIMP+/KRAS2-mutated tumors. CT/TT genotypes of rs1961177 were significantly associated with an increased likelihood of a MSI+ colon tumor (OR 1.77 95% CI 1.26–2.37). We observed statistically significant interactions between genetic variation in NFκB1 and CYP19A1 for both colon and rectal cancer. Our data suggest the importance of CYP19A1 in the development of colon and rectal cancer and that estrogen may influence risk through an inflammation-related mechanism.
Keywords: Colon cancer, Rectal cancer, CYP19A1, NFκB1, Aspirin, BMI, CIMP+, KRAS2, MSI
Introduction
The association between estrogen and risk of colon and rectal cancer is well documented [1–3]. In both observational studies and clinical trials women taking HRT have been shown to be at reduced risk of colorectal cancer (CRC) [1, 2, 4]. Estrogen status also has been shown to modify associations with BMI in some studies [5], linked to MSI+ tumors [6], and shown to influence survival after diagnosis with colon cancer [7]. The mechanisms by which estrogen influences risk of colon and rectal cancer are thought to go beyond those of estrogen as a sex steroid and include interaction with both insulin- and inflammation-related factors [8–11]. Studies have shown that estrogen status and aspirin use interact to alter colon cancer risk [12]. NFκB and cytokines have been shown to influence estrogen levels [8, 13, 14]. Estrogen working through an inflammation-related mechanism in the etiology of colon and rectal cancer is feasible [15–17].
Few studies have evaluated genetic variation in estrogen-related genes and risk of colon and rectal cancer. We have previously assessed genetic variation in the estrogen receptor alpha and beta (ESR1 and ESR2) and the androgen receptor (AR) genes and observed stronger associations for ESR2 than for ESR1 and risk of colon cancer [18]. A study by Lin et al. [19] evaluated ESR1 and ESR2 and aromatase cytochrome p450 enzyme (CYP19A1) which is responsible for the conversion of estrone to estradiol, in 158 incident cases of colon and rectal cancer; they did not have the ability to examine colon and rectal cancer separately. One CYP19A1 SNP, rs10046, was associated with increased risk of CRC.
Individual variability in estradiol metabolism is influenced by genetic variation in CYP19A1 [20]. CYP19A1 influences estrogen-metabolizing enzymes and may importantly influence the effect of estrogen on cancer, including colon and rectal cancer. In this study, we evaluate genetic variation in the CYP19A1 gene and risk of colon and rectal cancer. We evaluate how variation in CYP19A1 may interact with variation in other genes involved in regulating estrogen and androgen signaling, ESR1, ESR2, and AR; we have previously reported primary associations with genetic variation in ESR1, ESR2, and AR and colon cancer [18]. We evaluate possible interaction between estrogen status, BMI, recent use of NSAIDs/aspirin, and genetic variation in the NFκB1 gene to obtain a better understanding of the role of variation in CYP19A1 in colon and rectal cancer etiology and the possibility that estrogen may be operating through an inflammation-related pathway. We examine specific phenotypes by evaluating associations with specific tumor markers and we determined whether variation in CYP19A1 influences survival after diagnosis.
Methods
Two study populations are included in these analyses. The first study, a population-based case–control study of colon cancer, included cases (n = 1,593) and controls (n = 1,994) identified between 1 October 1991 and 30 September 1994 [21] living in the Twin Cities Metropolitan Area, Kaiser Permanente Medical Care Program of Northern California (KPMCP) and a seven-county area of Utah. The second study, with identical data collection methods, included cases with cancer of the rectosigmoid junction or rectum (n = 790) and controls (n = 999) who were identified between May 1997 and May 2001 in Utah and KPMCP [22]. Eligible cases were between 30 and 79 years of age at time of diagnosis, English speaking, mentally competent to complete the interview, had no previous history of CRC, and no known (as indicated on the pathology report) familial adenomatous polyposis, ulcerative colitis, or Cohn’s disease.
Controls were matched to cases by sex and by 5-year age groups. At KPMCP, controls were randomly selected from membership lists; in Utah, controls 65 years and older were randomly selected from the Health Care Financing Administration lists and controls younger than 65 years were randomly selected from driver’s license lists. In Minnesota, controls were selected from driver’s license and state-identification lists [23, 24].
Interview data collection
Data were collected by trained and certified interviewers using laptop computers. All interviews were audio-taped as previously described and reviewed for quality control purposes [25]. The referent period for the study was 2 years prior to diagnosis for cases and selection for controls. Detailed information was collected on diet, physical activity, medical history, reproductive history and use of hormone replacement therapy (HRT), regular use of aspirin and non-steroidal anti-inflammatory drugs, and body size.
Tumor registry data
Tumor registry data were obtained to determine disease stage at diagnosis and months of survival after diagnosis. Disease stage was categorized by Surveillance, Epidemiology, and End Results (SEER) staging of local, regional, and distant disease as well as by the American Joint Committee on Cancer (AJCC) staging criteria. Local tumor registries provided information on patient follow-up including vital status, cause of death, and contributing cause of death. Survival-months were calculated based on month and year of diagnosis and month and year of death or date of last contact for those individuals who were still alive.
Tumor marker data
We have previously evaluated tumors for CpG island methylator phenotype (CIMP), microsatellite instability (MSI), TP53 mutations, and KRAS2 mutations [26–29] and were therefore able to evaluate genes in relation to tumors with specific characteristics or markers. Details for methods used to evaluate these epigenetic and genetic changes have been described in previous publications [26–29].
TagSNP selection and genotyping
TagSNPs were selected for CYP19A1 using the following parameters: an r2 = 0.8 defined LD blocks using a Caucasian LD map, minor allele frequency or maf > 0.1, range = −1,500 bps from the initiation codon to +1,500 bps from the termination codon, and 1 SNP/LD bin. All markers were genotyped using a multiplexed bead array assay format based on GoldenGate chemistry (Illumina, San Diego, CA). A genotyping call rate of 99.85% was attained. Blinded internal replicates represented 4.4% of the sample set. The duplicate concordance rate was 100.00%; Supplemental table contains a list of all tagSNPs evaluated for CYP19A1. Genotyping methods for ESR1, ESR2, and AR have been previously reported [18]. NFκB1 was evaluated in the same manner as CYP19A1, using the GoldenGate Illumina platform.
Statistical methods
All statistical analyses were performed using SAS® version 9.2 (SAS Institute, Cary, NC) unless otherwise specified. Hardy–Weinberg equilibrium (HWE) testing was performed with the allele procedure using null markers; all SNPs were in HWE. We identified SNPs first by examination of SNPs using an additive model and then applying a stepwise regression models to identify the individual SNPs and their corresponding inheritance models that contributed uniquely to the overall fit of the model for colon and rectal cancer, for specific tumor markers, and for survival. SNPs identified as important from stepwise were then run with appropriate adjustments to correct for confounding. In addition to minimal adjustments for age, sex, race, and study center, other SNPs returned from stepwise are controlled for within the regression model. Adjustment for multiple comparisons of the 27 CYP19A1 tagSNPs using the methods of Conneely and Boehnke [30] was performed via R version 2.11.0 (R Foundation for Statistical Computing, Vienna, Austria). Wald p values associated with ORs presented in main tables were used for adjustment to determine pACT values that were generated using the Conneely and Boehnke methods.
The haplotype procedure was used to estimate haplotypes by race using the EM algorithm and assuming linkage equilibrium. Haplotype probabilities were assigned to individuals and logistic regression models were weighted accordingly when assessing risk estimates. SAS Genetics routines were also used to test for marker-trait associations within the frameworks of the haplotype procedure. Associations for haplotype were compared to all other haplotypes and are presented for a single copy of the combined alleles. In evaluating haplotypes, we created haplotypes of those tagSNPs that were statistically significantly associated with colon and rectal cancer; since one marker was selected per LD bin, we did not create haplotypes based on LD bins. Minimal adjustments for age, sex, race, and study center are presented; additional adjustments for BMI (kg/m2), use of aspirin or NSAIDs within 2 years of the referent period, and cigarette smoking status (ever or never regularly smoked) did not alter associations.
We evaluated interactions between CYP19A1 and ESR1, ESR2, AR, and NFκB1. Differences in effect by race, sex, age (30–64 or 65–79), recent aspirin or NSAID use, recent estrogen use, BMI (<25, 25–30, >30) were evaluated given the hypothesized mechanisms we proposed for CYP19A1. We observed no differences by sex or age. p Values for interaction were determined by comparing a full model that included a categorical multiplicative interaction term to a reduced model without an interaction term, using a likelihood ratio test.
Tumors were defined by specific alterations detected; any TP53 mutation, any KRAS2 mutation, MSI+, or CIMP+ defined as at least two of five markers methylated. As the proportion of MSI+ tumors in the rectal cases was <3% [31], there was insufficient power to examine these tumor markers with genotype data. Population-based controls were used to assess associations for the population overall when examining multiple outcomes defined by tumor status. Test for heterogeneity were conducted comparing those with a specific tumor phenotype to other cases without that phenotype. This allowed us to determine unique associations with specific tumor molecular phenotype.
Months of survival were determined based on date of diagnosis and date of last contact or death. Associations between SNPs and risk of dying after diagnosis of colorectal cancer were evaluated using stepwise selection and Cox proportional hazards models to estimate multivariate hazard rate ratios (HRRs) and 95% confidence intervals adjusted for age at diagnosis, study center, race, sex, tumor molecular phenotype, and AJCC stage. The false discovery rate for HRRs was controlled for using the methods of Benjamini and Hochberg [32].
Results
The demographics of the study population are shown in Table 1. The majority of participants were male, over 60 at the time of diagnosis, and NHW. Hispanic participants represented the second largest ethnic group.
Table 1.
Description of study population
| Colon |
Rectal |
|||||||
|---|---|---|---|---|---|---|---|---|
| Male |
Female |
Male |
Female |
|||||
| Control n (%) |
Case n (%) |
Control n (%) |
Case n (%) |
Control n (%) |
Case n (%) |
Control n (%) |
Case n (%) |
|
| Center | ||||||||
| Utah | 201 (19.20) | 142 (16.32) | 177 (19.47) | 107 (15.62) | 201 (37.15) | 156 (34.59) | 164 (39.23) | 118 (38.94) |
| KPMCP | 439 (41.93) | 428 (49.20) | 348 (38.28) | 316 (46.13) | 340 (62.85) | 295 (65.41) | 254 (60.77) | 185 (61.06) |
| Minnesota | 407 (38.87) | 300 (34.48) | 384 (42.24) | 262 (38.25) | NA | NA | NA | NA |
| Age | ||||||||
| 30–39 | 22 (2.10) | 13 (1.49) | 18 (1.98) | 10 (1.46) | 10 (1.85) | 12 (2.66) | 11 (2.63) | 7 (2.31) |
| 40–49 | 70 (6.69) | 56 (6.44) | 58 (6.38) | 46 (6.72) | 55 (10.17) | 47 (10.42) | 46 (11.00) | 49 (16.17) |
| 50–59 | 169 (16.14) | 163 (18.74) | 157 (17.27) | 127 (18.54) | 133 (24.58) | 119 (26.39) | 110 (26.32) | 77 (25.41) |
| 60–69 | 371 (35.43) | 306 (35.17) | 302 (33.22) | 232 (33.87) | 200 (36.97) | 161 (35.70) | 129 (30.86) | 89 (29.37) |
| 70–79 | 415 (39.64) | 332 (38.16) | 374 (41.14) | 270 (39.42) | 143 (26.43) | 112 (24.83) | 122 (29.19) | 81 (26.73) |
| Race/ethnicity | ||||||||
| NHW | 974 (93.03) | 799 (91.84) | 854 (93.95) | 629 (91.82) | 458 (84.66) | 365 (80.93) | 366 (87.56) | 260 (85.81) |
| Hispanics | 39 (3.72) | 33 (3.79) | 36 (3.96) | 26 (3.80) | 36 (6.65) | 37 (8.20) | 27 (6.46) | 24 (7.92) |
| Black | 34 (3.25) | 38 (4.37) | 19 (2.09) | 30 (4.38) | 29 (5.36) | 17 (3.77) | 14 (3.35) | 12 (3.96) |
| Asian | 0 | 0 | 18 (3.33) | 32 (7.10) | 11 (2.63) | 7 (2.31) | ||
Four SNPs in the CYP19A1 gene not in LD were identified as being statistically significantly associated with colon cancer (Table 2); rs11856927 appeared to confound associations with other SNPs although not exhibiting a clear independent association. Evaluation of the haplotypes of remaining four SNPs showed that one copy of 1 common and 1 rarer haplotype were associated with decreased risk of colon cancer. The strongest risk was associated with rs12591359, where an OR of 1.44 (95% CI 1.16–1.80) was observed; the adjusted p value for multiple testing for this SNP was 0.02. Adjusted p values for other SNPs were 0.10 for rs3751591, 0.12 for rs1961177, and 0.22 for rs17523880. Assessment of specific tumors markers (data not shown in table) showed rs1961177 associated with CMP+/KRAS, CIMP+, and MSI tumors, with the CT/TT genotypes increasing risk. However, the p for heterogeneity was not significant. Additionally, rs12591359 AA and rs17523880 CA/AA genotypes showed a significant 50% increased risk of CMP+ tumors and rs18523880 CA/AA showed a significant 40% increased risk of MSI tumors; however, the p for heterogeneity was not statistically significant for these associations.
Table 2.
Associations between CYP19A1 and risk of colon cancer
| Controls n |
Cases n |
ORa (95% CI) | Wald p value | pACT | |
|---|---|---|---|---|---|
| CYP19A1 (rs12591359) | 0.00102 | 0.02231 | |||
| GG/GA | 1659 | 1276 | 1 | ||
| AA | 297 | 278 | 1.44 (1.16–1.80) | ||
| CYP19A1 (rs17523880) | 0.01525 | 0.22143 | |||
| CC | 1454 | 1126 | 1 | ||
| CA/AA | 502 | 430 | 1.23 (1.04–1.45) | ||
| CYP19A1 (rs1961177) | 0.00683 | 0.11669 | |||
| CC | 1547 | 1161 | 1 | ||
| CT/TT | 410 | 394 | 1.26 (1.06–1.48) | ||
| CYP19A1 (rs3751591) | 0.00575 | 0.10496 | |||
| TT | 1333 | 1115 | 1 | ||
| TC/CC | 624 | 441 | 0.81 (0.70–0.94) | ||
| CYP19A1 rs12591359(G>A) and rs17523880(C>A) and rs1961177(C>T) and rs3751591(T>C) | |||||
| Frequency | Per copy risk (95% CI) | Global p value |
|
|---|---|---|---|
| G-C-C-T | 0.38 | 0.89 (0.80–0.99) | 0.0059 |
| A-C-C-T | 0.25 | 1.06 (0.94–1.20) | |
| G-A-C-T | 0.09 | 1.14 (0.96–1.35) | |
| A-C-C–C | 0.09 | 0.82 (0.69–0.97) | |
| A-C-T-T | 0.05 | 1.45 (1.17–1.79) | |
| G-A-C-C | 0.04 | 0.92 (0.71–1.18) | |
| G-C-T-T | 0.04 | 1.05 (0.84–1.31) | |
| G-C-C-C | 0.02 | 0.9 (0.65–1.25) | |
| G-C-T-C | 0.01 | 0.92 (0.59–1.45) |
Adjusted for age, center, race, sex, other genotypes, and rs11856927
For rectal cancer, four SNPs not in LD appeared to be associated independently with disease risk (Table 3). Estimates of risk ranged from 0.66 (95% CI 0.51–0.84) for rs2470144 to 1.32 (95% CI 1.06–1.64) for rs7174997. rs2470144 had a statistically significant p value of 0.02 after adjusting for multiple comparisons. The only potentially meaningful difference by race was observed for rs1961177 among non-white participants and rectal cancer, where the OR was 0.39 (95% CI 0.23–0.67), although CI overlap with those presented in Table 2. For rectal cancer three SNPs were uniquely associated with specific tumor markers (data not shown in table): rs12591359 AA genotype was associated with CIMP+/KRAS tumors (OR 3.59 95% CI 1.50–8.61, Wald p value 0.004; pACT 0.08, p heterogeneity 0.0076); rs10519295 TT/CC genotypes were associated with CIMP+ tumors (OR 0.30 95% CI 0.11–0.84, Wald p value 0.023, pACT 0.31, p heterogeneity 0.039); and rs1961177 CT/TT genotypes were associated with CIMP+ tumors (OR 0.18 95% CI 0.06–0.51; Wald p value 0.001; pACT 0.027; p heterogeneity 0.0009). Other SNPs showed roughly a doubling of risk of having a CIMP+/KRAS-mutated tumor (rs700519 CT/TT, rs80251 91 AG/GG, rs17703883 TC/CC, rs1961177 CC, rs2470144 GG/GA, and rs28757184 CT/TT), however, the p for heterogeneity was greater than 0.05.
Table 3.
Associations between CYP19A1 and risk of rectal cancer
| Controls n |
Cases n |
ORa (95% CI) | Wald p value | pACT | |
|---|---|---|---|---|---|
| CYP19A1 (rs1961177) | 0.0188 | 0.2713 | |||
| CC | 715 | 583 | 1.00 | ||
| CT/TT | 244 | 171 | 0.75 (0.59–0.95) | ||
| CYP19A1 (rs2470144) | 0.001 | 0.0214 | |||
| GG/GA | 690 | 576 | 1.00 | ||
| AA | 269 | 178 | 0.66 (0.51–0.84) | ||
| CYP19A1 (rs7174997) | 0.0149 | 0.233 | |||
| GG | 660 | 492 | 1.00 | ||
| GT/TT | 299 | 262 | 1.32 (1.06–1.64) | ||
| CYP19A1 rs1961177(C>T) and CYP19A1 rs2470144(G>A) and CYP19A1 rs7174997(G>T) | |||||
| Frequency | Per copy risk (95% CI) | Global p value | |
|---|---|---|---|
| C-G-G | 0.37 | 1.17 (1.02–1.34) | 0.4652 |
| C-A-G | 0.33 | 0.86 (0.74–0.99) | |
| C-A-T | 0.19 | 1.12 (0.93–1.34) | |
| T-G-G | 0.11 | 0.83 (0.68–1.01) |
Adjusted for age, center, race, sex, and other genotypes
We assessed gene × gene interactions and found no meaningful interactions with ESR1, ESR2, or AR. However, several SNPs in NFκB1 interacted significantly with CYP19A1 SNPs in analyses of both colon and rectal cancer (Table 4). For colon cancer rs1259191359 and rs3751591 interacted with NFκB1. For rectal cancer rs4646 and rs700519 interacted with several NFκB1 SNPs, of these, the interaction between CYP19A1 rs700519 and NFκB1 rs1609798 and rs230510 had pACT values of 0.03.
Table 4.
Interaction between CYP19A1 and NFκB1 and colon and rectal cancer
| Controls | Cases | ORa (95% CI) | Controls | Cases | OR (95% CI) | p Interaction | pACT | |
|---|---|---|---|---|---|---|---|---|
| Colon cancer | ||||||||
| CYP19A1 (rs12591359) | ||||||||
| NFκB1 (rs3821958) | GG/GA | AA | ||||||
| AA | 572 | 447 | 1.00 | 114 | 96 | 1.08 (0.80–1.46) | 0.0215 | 0.2890 |
| AG | 787 | 615 | 1.00 (0.85–1.18) | 142 | 119 | 1.07 (0.81–1.41) | ||
| GG | 300 | 213 | 0.91 (0.73–1.12) | 40 | 63 | 2.01 (1.32–3.05) | ||
| CYP19A1 (rs3751591) | ||||||||
| NFκB1 (rs230510) | TT | TC/CC | ||||||
| AA | 454 | 343 | 1.00 | 183 | 165 | 1.2 (0.93–1.55) | 0.0040 | 0.0730 |
| AT | 615 | 545 | 1.19 (0.99–1.42) | 310 | 197 | 0.84 (0.67–1.06) | ||
| TT | 263 | 226 | 1.16 (0.92–1.45) | 131 | 79 | 0.81 (0.59–1.11) | ||
| NFκB1 (rs3774964) | ||||||||
| AA | 531 | 450 | 1.00 | 261 | 169 | 0.76 (0.61–0.96) | 0.0190 | 0.2647 |
| AG | 600 | 516 | 1.01 | 287 | 191 | 0.78 (0.63–0.98) | ||
| GG | 201 | 148 | 0.86 | 76 | 81 | 1.26 (0.90–1.77) | ||
| Rectal cancer | ||||||||
| CYP19A1 (rs4646) | ||||||||
| NFκB1 (rs3774964) | CC | CA/AA | ||||||
| AA/AG | 395 | 343 | 1.00 | 434 | 279 | 0.74 (0.60–0.92) | 0.0061 | 0.1908 |
| GG | 74 | 59 | 0.93 (0.64–1.35) | 56 | 73 | 1.46 (1.00–2.13) | ||
| CYP19A1 (rs700519) | ||||||||
| NFκB1(rs11722146) | CC | CT/TT | ||||||
| GG | 458 | 299 | 1.00 | 27 | 38 | 2.02 (1.20–3.41) | 0.0026 | 0.0972 |
| GA | 337 | 294 | 1.32 (1.06–1.63) | 49 | 34 | 0.99 (0.62–1.58) | ||
| AA | 78 | 83 | 1.59 (1.13–2.24) | 10 | 6 | 0.86 (0.31–2.42) | ||
| NFκB1 (rs1609798) | ||||||||
| CC | 432 | 286 | 1.00 | 25 | 37 | 2.09 (1.22–3.57) | 0.0009 | 0.0398 |
| CT | 358 | 292 | 1.22 (0.99–1.52) | 49 | 35 | 1.01 (0.63–1.60) | ||
| TT | 81 | 97 | 1.77 (1.27–2.47) | 12 | 6 | 0.72 (0.27–1.96) | ||
| NFκB1 (rs1801) | ||||||||
| GG | 362 | 237 | 1.00 | 21 | 34 | 2.33 (1.31–4.13) | 0.0036 | 0.1235 |
| GC | 394 | 327 | 1.26 (1.01–1.57) | 52 | 35 | 0.96 (0.60–1.52) | ||
| CC | 117 | 112 | 1.44 (1.06–1.95) | 13 | 9 | 0.98 (0.41–2.35) | ||
| NFκB1 (rs230510) | ||||||||
| AA | 260 | 250 | 1.00 | 40 | 26 | 0.63 (0.37–1.07) | 0.0007 | 0.0328 |
| AT | 437 | 328 | 0.78 (0.63–0.98) | 42 | 40 | 0.94 (0.59–1.50) | ||
| TT | 176 | 98 | 0.58 (0.43–0.79) | 4 | 12 | 2.98 (0.94–9.38) | ||
| NFκB1 (rs4648068) | ||||||||
| AA | 417 | 279 | 1.00 | 22 | 35 | 2.23 (1.28–3.91) | 0.0026 | 0.0955 |
| AG | 364 | 305 | 1.23 (0.99–1.53) | 53 | 36 | 0.94 (0.60–1.48) | ||
| GG | 92 | 92 | 1.46 (1.05–2.03) | 11 | 7 | 0.89 (0.34–2.35) | ||
Adjusted for age, center, race, and sex
Assessment of interactions with NSAIDs, estrogen status, and BMI did not yield consistent associations across any CYP19A1 SNPs for colon cancer. However, for rectal cancer, we saw statistically significant interactions with both NSAID use and BMI. Differences in associations across levels of these variables are shown with haplotypes of SNPS not in LD with each other that interacted significantly with these variables, rs11856927, rs2470144, and rs7174997 (Table 5). The TGG and the GAG haplotypes were significantly associated with both NSAID use and BMI.
Table 5.
Associations among aspirin, BMI, CYP19A1, and rectal cancer risk
|
CYP19A1 rs11856927(T>G) and rs2470144(G>A) and rs7174997(G>T) | |||
|---|---|---|---|
| No recent aspirin use OR (95% CI)1 |
Recent aspirin use OR (95% CI) |
p Interaction | |
| T-G-G | 0.81 (0.66–0.98) | 1.16 (0.92–1.47) | 0.0116 |
| G-G-G | 1.16 (0.94–1.44) | 1.27 (0.96–1.67) | 0.6567 |
| G-A-G | 1.10 (0.88–1.39) | 0.63 (0.47–0.85) | 0.0004 |
| T-A-T | 1.09 (0.85–1.40) | 1.15 (0.85–1.56) | 0.6397 |
| T-A-G | 0.89 (0.69–1.16) | 0.81 (0.59–1.13) | 0.5768 |
| G-A-T | 1.18 (0.69–2.02) | 1.00 (0.49–2.03) | 0.7665 |
| Normal (<25) OR (95% CI) |
Overweight (25–29) OR (95% CI) |
Obese (≥30) OR (95% CI) |
p Interaction | |
|---|---|---|---|---|
| T-G-G | 0.95 (0.73–1.25) | 0.81 (0.64–1.01) | 1.20 (0.89–1.61) | 0.0125 |
| G-G-G | 0.86 (0.64–1.15) | 1.39 (1.06–1.81) | 1.57 (1.12–2.20) | 0.0026 |
| G-A-G | 1.12 (0.82–1.53) | 0.89 (0.67–1.19) | 0.68 (0.48–0.95) | 0.0082 |
| T-A-T | 1.17 (0.83–1.66) | 1.25 (0.93–1.70) | 0.88 (0.61–1.27) | 0.1149 |
| T-A-G | 0.96 (0.66–1.40) | 0.80 (0.58–1.10) | 0.83 (0.57–1.22) | 0.1546 |
| G-A-T | 1.09 (0.52–2.27) | 1.34 (0.69–2.59) | 0.75 (0.31–1.84) | 0.2901 |
Adjusted for age, center, race, and sex
After adjusting for AJCC stage at diagnosis and tumor markers, having the TT genotype of rs7174997 increased the likelihood of death after colon cancer diagnosis by 70% (Table 6). For rectal cancer, the A allele for rs12591359 were inversely associated with survival time, as was the GG genotype of rs17601876, rs1902584 AT/TT genotype, rs2470158 TT genotype, and the CA/AA genotype of rs4646.
Table 6.
Associations between CYP19A1 SNPs and colorectal cancer survival center, race, sex, AJCC stage, tumor markers, and other SNPs
| Death/person years | HRR (95% CI) | Wald p value | FDR p value | |
|---|---|---|---|---|
| Colon | ||||
| CYP19A1 (rs7174997) | 0.0403 | 0.6803 | ||
| GG/GT | 281/6189 | 1 | ||
| TT | 17/193 | 1.7 (1.02–2.82) | ||
| Rectal | ||||
| CYP19A1 (rs12591359) | 0.0005 | 0.0061 | ||
| GG | 33/1100 | 1 | ||
| GA/AA | 117/2143 | 2.3 (1.45–3.67) | ||
| CYP19A1 (rs17601876) | 0.0002 | 0.0059 | ||
| AA/AG | 115/2402 | 1 | ||
| GG | 35/851 | 2.6 (1.57–4.31) | ||
| CYP19A1 (rs1902584) | 0.01 | 0.0677 | ||
| AA | 123/2764 | 1 | ||
| AT/TT | 27/489 | 1.78 (1.15–2.77) | ||
| CYP19A1 (rs2470158) | 0.0084 | 0.0677 | ||
| CC/CT | 149/3242 | 1 | ||
| TT | 1/11 | 15.78 (2.03–122.91) | ||
| CYP19A1 (rs4646) | 0.0401 | 0.2167 | ||
| CC | 71/1770 | 1 | ||
| CA/AA | 79/1483 | 1.5 (1.02–2.22) |
Hazard Rate Ratios (HRR) adjusted for age, sex, center, tumor marker, and AJCC stage
Discussion
Our data suggest that genetic variation in CYP19A1 influences risk of developing colon and rectal cancer. The specific molecular pathways of most relevance appear to be those involving CIMP+, KRAS2-mutated, and MSI+ tumors. Given the observed gene–gene and gene–environment interactions, it is reasonable to postulate that the influence of estrogen on colon and rectal cancer risk may involve inflammation-related mechanisms.
We observed several SNPs in the CYP19A1 gene independently associated with both colon and rectal cancer. Three haplotypes were associated with colon cancer and one haplotype was associated with rectal cancer risk. These haplotypes consisted of SNPs not in LD with each other and added little information beyond that gained by examining-independent SNPs. Of interest is the observation that although CYP19A1 polymorphisms were associated with colon and rectal cancer, the polymorphisms that were most important differed for colon and rectal cancer. We have frequently observed that associations between colon and rectal cancer differ, suggesting that although the genes are important to both, that the specific mechanism whereby the gene is working may differ. However, we observed greater similarities in the associations when examining molecular tumor phenotypes. For both colon and rectal cancer CYP19A1 SNPS were associated with CIMP+/KRAS and CIMP+ tumors. Other markers appeared to be important for MSI+ colon tumors, and thus the low frequency of MSI+ rectal tumors could account for the lack of association of these SNPs with rectal cancer overall. Our previous work has suggested that estrogens may be involved in MSI tumors [6]; this work corroborates those earlier findings. MSI+ and CIMP+ tumors often cluster together. Our data suggest that a CIMP+ pathway and CIMP+/KRAS2-mutated tumors may be related to estrogen. Others have suggested that sex is associated with CIMP+ colon tumors [33].
Several variants in CYP19A1 have been associated with variable circulating estrogen levels [34–37], and haplo-block analysis has shown that this variability can be captured by analyzing tagSNPs [34]. CYP19A1 haplotypes also have been investigated in association with cancer risk at various sites [38–41]. It should be noted that two of the markers that we demonstrate as being associated with rectal cancers; rs1961177, and with colon cancer; rs7174997, resides within 6 and 9 kb, respectively, of two tightly linked SNPs in the 5′ flanking region of CYP19A1 (rs6493497 and rs7176005) that have previously been shown to be associated with increased circulating estradiol levels [42]. Further investigation will be required to determine if rs7174997 and rs1961177 are directly associated with plasma estradiol levels. However, some associations became evident when interactions with other genes and/or exposures were examined [43, 44].
Data have shown that estrogen can enhance an inflammatory response by activating the NFκB complex pathway [13]. NFκB signaling pathway has been identified as one of the key pathways through which anti-estrogens and aromatase inhibitors exert their effects [45]. We observed statistically significant interactions between genetic variants of NFκB1 and CYP19A1 for both colon and rectal cancer. For rectal cancer, we also observed significant interaction between CYP19A1 variants and regular use of aspirin/NSAIDs and BMI. These observations also suggest that the estrogen associations with colon and rectal cancer may operate via an inflammation-related pathway.
Our data show that variation in the CYP19A1 gene can influence survival after diagnosis with colon cancer. We have previously reported that HRT use influences colon cancer survival, possible through an MSI-related pathway [6, 7]. Others have shown that estrogen levels in colon tumors are statistically significantly associated with prognostic factors and may influence the progression of the disease [46]. Our data suggest that genetic factors that may influence estrogen levels also may relate to survival after diagnosis.
The study has many strengths, the data set is rich in exposure data, genetic data, tumor marker data, and survival information. Because of this, we have the ability to thoroughly evaluate CYP19A1 to determine not only broad independent associations, but also to help identify molecular pathways through which they may operate. In doing this, we made many comparisons. However, several p values remained statistically significant even after adjustment for these comparisons. To better understand these findings, functional studies are needed to elucidate the role of CYP19A1 and colon and rectal cancer.
In summary, our findings support a role of CYP19A1 and colon and rectal cancer development and survival. Our data further suggest that CIMP+ and MSI+ are important molecular subtypes in this association. Given the significant interactions between variants of CYP19A1 and NFκB1, aspirin, and BMI, we postulate that an estrogen-related inflammation driven pathway is central to carcinogenesis in these CRC subtypes.
Supplementary Material
Acknowledgments
This study was funded by NCI Grants CA48998 and CA61757. This research also was supported by the Utah Cancer Registry, which is funded by Contract #N01-PC-67000 from the National Cancer Institute, with additional support from the State of Utah Department of Health, the Northern California Cancer Registry, and the Sacramento Tumor Registry. The contents of this manuscript are solely the responsibility of the authors and do not necessarily represent the official view of the National Cancer Institute. We would like to acknowledge the contributions of Sandra Edwards, Roger Edwards, Leslie Palmer, Donna Schaffer, Dr. Kristin Anderson, and Judy Morse for data management and collection.
Footnotes
Electronic supplementary material The online version of this article (doi:10.1007/s10552-011-9768-x) contains supplementary material, which is available to authorized users.
Conflict of interest No authors have any conflict of interest to report.
Contributor Information
Martha L. Slattery, Department of Internal Medicine, University of Utah Health Sciences Center, 295 Chipeta Way, Salt Lake City, UT 84108, USA
Abbie Lundgreen, Department of Internal Medicine, University of Utah Health Sciences Center, 295 Chipeta Way, Salt Lake City, UT 84108, USA.
Jennifer S. Herrick, Department of Internal Medicine, University of Utah Health Sciences Center, 295 Chipeta Way, Salt Lake City, UT 84108, USA
Susan Kadlubar, University of Arkansas, Little Rock, AR, USA.
Bette J. Caan, Division of Research, Kaiser Permanente Medical Research Program, Oakland, CA, USA
John D. Potter, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
Roger K. Wolff, Department of Internal Medicine, University of Utah Health Sciences Center, 295 Chipeta Way, Salt Lake City, UT 84108, USA
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