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. Author manuscript; available in PMC: 2021 Aug 4.
Published in final edited form as: Cancer Epidemiol. 2014 Aug 15;38(5):583–590. doi: 10.1016/j.canep.2014.07.003

An analysis of genetic factors related to risk of inflammatory bowel disease and colon cancer

Bríd M Ryan 1, Roger K Wolff 2, Valeri Nicola 3, Mohammed Khan 1, Robinson Dillon 1, Alessio Paone 4, Elise D Bowman 1, Abbie Lundgreen 2, Bette Caan 5, John Potter 6,7,8, Derek Brown 1, Carlo Croce 4, Martha L Slattery 2, Curtis C Harris 1
PMCID: PMC8336584  NIHMSID: NIHMS616776  PMID: 25132422

Abstract

Background and Aims

Patients with inflammatory bowel disease (IBD) have a higher risk of developing colorectal cancer than the general population. Genome-wide association studies have identified and replicated several loci associated with risk of IBD however it is currently unknown whether these loci are also associated with colon cancer risk.

Methods

We selected 15 validated SNPs associated with risk of either Crohn's disease, ulcerative colitis, or both in previous GWAS and tested whether these loci were also associated with colon cancer risk in a two-stage study design.

Results

We found that rs744166 in STAT3 was associated with colon cancer risk in two studies; however, the direction of the observation was reversed in TP53 mutant tumors possibly due to a nullification of the effect by mutant p53. The SNP, which lies within intron 1 of the STAT3 gene, was not associated with altered expression of either the 6 STAT3 mRNA isoforms or phospho-STAT3.

Conclusions

These data suggest that the STAT3 locus is associated with both IBD and cancer. Understanding the function of this variant, or the identification and function of one in linkage with it, could possibly explain the role of this gene in autoimmunity and cancer. Furthermore, an analysis of this locus, specifically in a population with IBD, could help to resolve the relationship between this SNP and cancer.

Keywords: Inflammatory bowel disease, colon cancer, STAT3

Introduction

Inflammatory bowel disease (IBD), a chronic disorder affecting the intestinal mucosa presents as one of two main forms: Crohn's disease (CD) or ulcerative colitis (UC). UC affects the inner lining of the large intestine, whereas CD is more widespread and extends deeper in to the intestinal wall. Although the exact etiology of these diseases is unknown, genetics, ethnicity, diet, appendectomy, antibiotic use, socioeconomic factors, and non-steroidal anti-inflammatory drugs are considered as risk factors [1]. Decreases in beneficial bacteria and increases in pathogenic bacteria [2-5] have been linked with IBD. Indeed, a key challenge faced by the immune system is maintenance of a balance between commensal and pathogenic microorganisms. It is thought that IBD develops through the loss of such homeostatic controls and a key population of T cells, called Th17 cells, has recently emerged as a player in the context of IBD. The importance of these cells, which express the IL-23 receptor and regulate autoimmunity, is exemplified by recent genome wide association studies (GWAS) that have shown a connection between genetic variation in IL-23 and risk of both CD and UC [6-9].

Although there is no unifying risk factor for both CD and UC, genetic susceptibility appears to be common to the etiology of both conditions [6, 10-15]. Both diseases display strong relative sibling risk [16, 17] and through GWAS, multiple risk loci have been identified and indeed replicated [6, 10-14, 17, 18]. Patients with IBD have a higher risk of developing colorectal cancer than the general population [19-22], an association that was first described by Crohn in 1925 [23]. Risk of colorectal cancer is a direct function of the length of time an individual has had IBD and the extent of intestinal involvement [24]. Colorectal cancer accounts for between 10% and 15% of deaths in patients with IBD [25]. In addition, mortality rates for colorectal cancer patients are higher among IBD-associated colorectal cancer cases, compared to colorectal cancer associated with other risk factors [26, 27]. Collectively, this suggests a directional link between IBD and colorectal cancer. Current trends in molecular pathological epidemiology converge on the theme of defining risk in terms of tumor subtype or tumor-specific exposures [28-30] and accumulating evidence suggests that IBD-associated colorectal cancer has a pathobiology that is distinct from non-IBD colorectal cancer. For example, the mean age of developing CRC in the setting of IBD is lower than for non-IBD CRC (40-50 vs. 60 years); dysplasia in ulcerative colitis (UC) is preceded by a long history of chronic inflammation whereas dysplasia in non-IBD colon cancer is usually associated with a discrete polyp without inflammation; RAS mutations are frequent in sporadic colon cancers but are not as common in IBD-associated colorectal cancer [31]; and loss of heterozygosity and mutations in TP53 are more common in IBD-associated colon cancer than non-IBD colorectal cancer [32, 33].

There is currently no clear way of identifying which patients with IBD will develop colorectal cancer [34], something which has substantially impacted and overburdened the clinical management of IBD. In this study we reasoned that, if some forms of colorectal cancer shared a common pathobiology with IBD, then loci associated with susceptibility to IBD might also be associated with risk of colorectal cancer. To test this hypothesis, we analyzed SNPs previously identified from GWAS of IBD and asked whether these loci are also associated with risk of colorectal cancer.

Materials and Methods

Study Populations

The NCI-University of Maryland Colorectal Cancer Case-Control Study

This study population consisted of 691 subjects. Incident colorectal cancer cases (n=245) and controls (n=446) were recruited from 1992-2003 and 1998-2003, respectively from the greater Baltimore, Maryland area. The controls were accrued from both a hospital setting (n=236) and a community setting (n=210). The inclusion and exclusion criteria have been previously described [35]. In brief, subjects were self-reported European American or African Americans born in the United States. Subjects were excluded if they self-reported a history of cancer other than colon, HIV, HBV, HCV, or IV drug use, were institutionalized, or had a mental impairment. Information to determine disease stage, treatment, and survival was obtained from medical records and pathology reports, Social Security Death Index, and the National Death Index. Disease staging was completed according to the tumor-node-metastasis system of the American Joint Committee on Cancer. The survival period was determined from date of hospital admission for surgery to date of last completed search for death entries in the Social Security Death Index (2010). Informed consent was obtained from all participants, and epidemiological questionnaires including personal history, family medical history, past medical history, tobacco history, dietary information, and information on work environment, were administered to all subjects. The study was approved by the institutional review boards of the participating institutions. The characteristics of this study population are described in Table 1.

Table 1. Characteristics of the study populations.
Characteristics NCI-MD Study DALS Study
Cases Total Controls Population Controls Hospital Controls Cases Controls
n 245 446 236 210 1578 1980
Age ± SD 64.7 ± 11.7 65.0 ± 11.0 66.8 ± 9.7 63.1 ± 12.1 64.9 ± 9.8 65.0 ± 10.1
Gender (%)
 Male 185 (75) 212 (48) 115 (48) 97 (46) 884 (56) 1060 (54)
 Female 60 (25) 234 (52) 121 (51) 113 (54) 694 (44) 920 (46)
Race (%)
 African American* or Hispanic 97 (40) 190 (43) 121 (51) 69 (33) 132 (8) 130 (7)
 European American 148 (60) 256 (57) 115 (49) 141 (67) 1446 (92) 1850 (93)
Stage (%)
 Unknown 4 (2) 186 (12)
 I 38 (16) 475 (30)
 II 69 (29) 408 (26)
 III 79 (33) 380 (24)
 IV 51 (21) 129 (8)
Survival
 Overall (median months, IQR) 56 (19 - 86) 62 (42, 86)
 Colon Cancer Deaths 19 (9 - 40) 25 (16, 41)
 All Deaths 19 (9 - 40) 32 (20, 52)
 Alive (includes lost to follow-up) 74 (52 - 104) 73 (57, 94)
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*

NCI-MD study did not include Hispanic participants

Diet Activity and Lifestyle Study

Participants from the Diet, Activity and Lifestyle Study were enrolled in a population-based case-control study of incident colon cancer (cases n=1,555) and population-based controls (n=1,956) who were identified between October 1, 1991 and September 30, 1994. It included people living in the Twin Cities Metropolitan Area, Kaiser Permanente Medical Care Program of Northern California (KPMCP) and a seven-county area of Utah. Cases were between 30 and 79 years old at time of diagnosis with adenocarcinoma, English speaking, mentally competent to complete the interview, with no previous history of colorectal cancer (CRC), and no known familial adenomatous polyposis, ulcerative colitis, or Crohn'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 younger controls were randomly selected from drivers' license lists. Controls were selected from drivers' license and state-identification lists in Minnesota. Details of the study have been previously reported [36, 37]. Interview data were collected by trained and certified interviewers using laptop computers. All interviews were audio-taped and reviewed for quality control purposes [38]. The referent period for the study was two years prior to diagnosis for cases and prior to selection for controls. Tumor registry data were obtained to determine disease stage at diagnosis and months of survival after diagnosis. Disease stage was categorized centrally by one pathologist in Utah using the sixth edition of the American Joint Committee on Cancer (AJCC) staging criteria. Local tumor registries also provided information on patient follow-up including vital status, cause of death, and contributing cause of death. The characteristics of this study population are described in Table 1.

SNP Selection and genotyping

The NCI-University of Maryland Colorectal Cancer Case-Control Study

We selected SNPs previously associated with risk of ulcerative colitis and Crohn's disease [6, 11-13] to test for a potential association with risk of colorectal (NCI-MD) and colon (DALS) cancer (Supplementary Table 1). For the NCI-MD study, genomic DNA was isolated from buffy coat or colorectal tissue using the Qiagen FlexiGene DNA Kit or the DNAeasy tissue kit, respectively (Qiagen, Valencia, CA). Cases and controls were genotyped at the Ohio State University Genotyping Core using Taqman assays (Life Technologies, Carlsbad, CA) for each SNP. The case, control, negative controls, and duplicate samples were randomly distributed for order of processing, with 10% duplicates to test both inter- and intra-plate concordance. All parties involved in genotyping were blinded to the case, control, and duplicate status of the samples. Samples that failed to genotype were recorded as undetermined. Both inter- and intra-plate duplicates were > 97% concordant and completion rates for all SNPs, except rs10761659, were > 95% (Supplementary Table 1).

Diet Activity and Lifestyle Study

DNA was extracted from whole blood. Rs744166 (STAT3) and rs10883365 (NKX2-3) were genotyped using TaqMan based assays. Genotyping reagents were purchased as complete assays from Applied Biosystems (Foster City, CA). For each 5 μl PCR reaction contained 20ng of genomic DNA, primers, probes, TaqMan Universal PCR Master Mix (containing AmpErase UNG, AmpliTaq Gold enzyme, dNTPs, and reaction buffer). PCR was carried out under the following conditions: 50°C for 2 minutes to activate UNG, 95°C for 10 min, followed by 40 cycles of 92°C for 15 sec, and 60°C for 1 minute using a 384 well dual block ABI 9700. Fluorescent endpoints of the TaqMan reactions were measured using a 7900HT sequence detection instrument. Control samples representing all three possible genotypes were included at four positions each in every 384-well tray. In addition, internal replicates representing >1% of the sample set were blinded and included.

Statistical Analysis

The NCI-University of Maryland Colorectal Cancer Case-Control Study

Statistical analyses of data from the NCI-MD study were performed using STATA 12.0 (College Station, TX). A P value of less than 0.05 was used as the criterion for statistical significance, and all statistical tests were two-sided. Departures from Hardy-Weinberg equilibrium were determined using a χ2 test. For the NCI-MD study, odds ratios (OR) and their corresponding 95% confidence intervals (CI) were estimated using an unconditional logistic regression model adjusted for age (continuous) and sex (categorical). Hazard ratios (HR) and 95% CI were estimated using a Cox proportional hazards regression model adjusted for age, sex, and stage of disease, as well as death from causes other than colorectal carcinoma. Proportional hazards assumptions were verified by visual inspection of log-log plots and using a non-zero slope test of the Schoenfeld residuals [39] (P=0.052 for African Americans, P=0.627 for European Americans). The method of Kaplan and Meier was used for plotting genotypes and survival. Statistical significance was tested using the Log-rank method. Tests for trend were conducted by calculating P-values for the β coefficient in logistic regression models with genotypes coded as an ordinal variable.

Diet Activity and Lifestyle Study

In the Diet, Activity and Lifestyle Study, statistical analyses were performed using SAS® version 9.2 (SAS Institute, Cary, NC). We report ORs and 95% CIs assessed from multivariable logistic regression models adjusting for age, center, race/ethnicity, and sex. P values for linear trend were assessed by comparing the likelihood ratio of a model with the ordinal genotype variable to the likelihood ratio of a model without the genotype variable using a chi-square test with 1 degree of freedom; p values for interaction were determined using a likelihood-ratio test comparing a full model including an ordinal multiplicative interaction term to a reduced model without an interaction term. Survival-months were calculated based on month and year of diagnosis and month and year of death or date of last contact. Associations between SNPs and colorectal cancer mortality were evaluated using Cox proportional hazards models to obtain multivariable HRRs and 95% confidence intervals. We adjusted for age at diagnosis, study center, race, sex, tumor molecular phenotype, and AJCC stage to estimate HRs.

Tumor Marker Data

We have previously evaluated tumors for CpG Island Methylator Phenotype (CIMP), microsatellite instability (MSI), TP53 mutations, and KRAS mutations [40-43] and were therefore able to evaluate variation in the specified genes in relation to molecularly defined subsets of CRC. Details for methods used to evaluate epigenetic and genetic changes have been described [40-42]. In order to compare specific types of mutations to controls while adjusting for the tumor mutations simultaneously in cases, generalized estimating equations (GEEs) with multinomial outcomes were used to calculate odds ratios, because case subjects could have multiple tumor alterations or mutations [44]. GEEs were implemented in SAS using the GENMOD procedure as described by Kuss and McLerran [45]. Trend p values are based on likelihood ratio tests from multiple logistic regression models comparing cases stratified by tumor marker type to controls.

TCGA Data

The Cancer Genome Atlas (TCGA) is supported by the National Cancer Institute and the National Human Genome Research Institute to chart the molecular landscape of tumor samples for more than 20 types of cancer (https://tcga-data.nci.nih.gov/tcga/). We used level-3 normalized data to infer the effects of single nucleotide polymorphisms on gene expression [46]. We downloaded matched samples by participants' sequence data, which have been processed by the Illumina GA Sequencer RNA-seq version 2 pipeline (Mapsplice alignment algorithm and the RSEM algorithm) to generate expression values for STAT3, NKX2-3, uc001kps.2 (DQ372722) and uc001kpt.2 (C10ORF139). For each sample, six individual files are generated by this pipeline and stored at TCGA FTP site. The files are: 1) non-normalized expression values of genes and 2) of isoforms; 3) normalized expression values of genes and 4) of isoforms; and 5) expression quantifications for exons and 6) junctions. Genotype calls for rs744166 and rs10883365 were extracted from Affymetrix GenomeWide SNP6.0 platform data, which had already been processed using Birdseed, were obtained from TCGA. Protein expression data for phospho-stat3 (tyrosine 05) were extracted from the MD Anderson Reverse Phase Protein Array. Genotype, protein expression and isoform-specific data from samples that did not pass the TCGA quality control (per the TCGA copy number Sample Data Relationship Format file) were removed. Genotype calls were coded as 0, 1, or 2 according to the number of variant alleles and filtered according to a Birdseed confidence threshold of 0.05. Differences in mRNA isoform expression and phospho-stat3 levels were compared across genotypes using the rank-sum test in STATA.

Results

SNPs associated with risk of both IBD and colorectal cancer

Of the 15 SNPs analyzed, three deviated from Hardy-Weinberg equilibrium (Supplementary Table 1). A SNP in NKX2-3, rs10883365, was associated with an increased risk of colorectal cancer; however, after adjustment for age, sex and race, the observation was observed only among individuals carrying the heterozygote genotype (ORAG vs. AA 1.59, 95% C.I. 1.08-2.35; P=0.019; n=714) (Table 2). Although our multivariable analysis of the homozygote genotype was sufficiently powered to detect an association, none was observed. This phenomenon, when a heterozygote has a more extreme phenotype that either of its parents, is called over-dominance and is unusual in genetic association studies [47]. Although African Americans with IBD are not at a greater risk of developing colorectal cancer compared with European Americans [48] differences in risk loci have been found [49, 50]. Our study had both African American and European American participants therefore we conducted a stratified analysis. The association was observed only in the European American population (Supplementary Table 2). We also found a SNP in STAT3, rs744166, that was associated with a lower risk of colorectal cancer (ORGG vs. AA 0.54, 95% C.I. 0.34-0.85; P=0.007; n=713) (Table 2). Again, this observation was found only in European Americans (ORGG vs. AA 0.46, 95% C.I. 0.24-0.81; P=0.007; n=416) (Supplementary Table 2). The NCI-MD study included both hospital and population controls. As hospital controls can introduce bias in genetic association studies, we conducted a sensitivity analysis including only the population controls in the reference group. The relationship between rs744166 and risk remained statistically significant (ORGG vs. AA 0.45, 95% C.I. 0.21-0.95; P=0.036; cases=288, population controls=236), suggesting that our results were not biased by the selection of population and hospital controls. There were no other significant associations found.

Table 2. Risk associations for IBD GWAS loci and colorectal cancer risk in the NCI-MD study.

Gene (SNP) Genotype Controls Cases Univariable Multivariable*
Odds Ratio (95% C.I.) P Odds Ratio (95% C.I.) P
KIF21B-CACNA1S
rs17419032		 CC 285 (65%) 182 (64%) Reference Reference
CT 130 (30%) 88 (31%) 1.06 (0.76 - 1.47) 0.728 1.03 (0.72 - 1.47) 0.878
TT 22 (5%) 15 (5%) 1.07 (0.54 - 2.11) 0.851 0.99 (0.48 - 2.07) 0.993
IL17REL
rs5771069		 GG 130 (30%) 87 (31%) Reference Reference
GA 219 (50%) 132 (48%) 0.90 (0.64 - 1.27) 0.544 0.90 (0.61 - 1.29) 0.553
AA 88 (20%) 58 (21%) 0.98 (0.64 - 1.51) 0.944 0.93 (0.59 - 1.45) 0.742
IL12B
rs6887695		 GG 175 (41%) 100 (37%) Reference Reference
GC 204 (48%) 136 (50%) 1.17 (0.84 - 1.62) 0.357 1.10 (0.78 - 1.55) 0.580
CC 49 (11%) 34 (13%) 1.21 (0.74 - 2.01) 0.448 1.15 (0.68 - 1.95) 0.605
PTPN2
rs2542151		 TT 291 (68%) 192 (69%) Reference Reference
TG 129 (30%) 84 (30%) 0.98 (0.71 - 1.37) 0.938 0.97 (0.69 - 1.36) 0.851
GG 10 (2%) 1 (1%) 0.15 (0.02 - 1.19) 0.073 0.15 (0.02 - 1.19) 0.073
BSN
rs9858542		 GG 226 (53%) 142 (53%) Reference Reference
GA 166 (39%) 112 (42%) 1.07 (0.78 - 1.48) 0.661 1.15 (0.82 - 1.60) 0.415
AA 32 (8%) 13 (5%) 0.64 (0.33 - 1.27) 0.207 0.69 (0.34 - 1.39) 0.298
IRGM
rs13361189		 TT 271 (63%) 177 (64%) Reference Reference
TC 126 (29%) 71 (26%) 0.86 (0.61 - 1.22) 0.404 0.79 (0.53 - 1.18) 0.254
CC 35 (8%) 28 (10%) 1.22 (0.72 - 2.08) 0.455 1.23 (0.66 - 2.31) 0.516
STAT3
rs744166		 AA 100 (23%) 83 (30%) Reference Reference
AG 192 (44%) 128 (46%) 0.80 (0.56 - 1.16) 0.242 0.75 (0.51 - 1.11) 0.154
GG 142 (33%) 68 (24%) 0.58 (0.38 - 0.87) 0.009 0.54 (0.34 - 0.85) 0.007
SLC22A23
rs17309827		 TT 252 (59%) 143 (53%) Reference Reference
TG 149 (35%) 106 (39%) 1.25 (0.91 - 1.73) 0.170 1.19 (0.84 - 1.70) 0.331
GG 29 (7%) 24 (9%) 1.46 (0.82 - 2.60) 0.201 1.38 (0.73 - 2.59) 0.319
NKX2-3
rs10883365		 AA 127 (29%) 63 (23%) Reference Reference
AG 194 (44%) 147 (53%) 1.53 (1.05 - 2.12) 0.025 1.59 (1.08 - 2.35) 0.019
GG 116 (27%) 67 (24%) 1.16 (0.76 - 1.78) 0.484 1.23 (0.79 - 1.93) 0.354
SMURF1/KPNA7
rs7809799		 AA 370 (84%) 246 (86%) Reference Reference
AG 66 (15%) 38 (13%) 0.87 (0.56 - 1.33) 0.512 0.88 (0.56 - 1.39) 0.590
GG 3 (1%) 1 (1%) 0.50 (0.05 - 4.85) 0.552 0.51 (0.05 - 5.36) 0.578
IL23R
rs11209026		 GG 389 (90%) 251 (90%) Reference Reference
GA 44 (10%) 26 (9%) 0.92 (0.55 - 1.53) 0.735 1.06 (0.62 - 1.83) 0.824
AA 0 0(%) 1 (1%) NA NA NA
Intergenic
rs12035082		 CC 193 (44%) 127 (45%) Reference Reference
CT 155 (36%) 106 (38%) 1.04 (0.75 - 1.45) 0.821 0.86 (0.58 - 1.29) 0.474
TT 86 (20%) 47 (17%) 0.83 (0.55 - 1.26) 0.386 0.72 (0.43 - 1.20) 0.211
Intergenic
rs10761659		 GG 111 (26%) 69 (25%) Reference Reference
GA 208 (49%) 131 (18%) 1.01 (0.69 - 1.47) 0.945 1.03 (0.69 - 1.53) 0.881
AA 109 (25%) 75 (27%) 1.10 (0.73 - 1.69) 0.636 1.05 (0.66 - 1.65) 0.845
CCNY
rs3936503		 GG 164 (38%) 102 (38%) Reference Reference
GA 196 (45%) 131 (49%) 1.07 (0.77 - 1.50) 0.671 1.09 (0.77 - 1.55) 0.637
AA 74 (17%) 34 (13%) 0.74 (0.46 - 1.19) 0.212 0.77 (0.46 - 1.27) 0.302
HERC2
rs916977		 GG 191 (44%) 126 (45%) Reference Reference
GA 126 (29%) 80 (29%) 0.96 (0.67 - 1.38) 0.835 1.02 (0.67 - 1.56) 0.909
AA 120 (27%) 74 (26%) 0.93 (0.65 - 1.35) 0.719 1.13 (0.66 - 1.95) 0.657
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*

Adjusted for age, gender and race

We also examined a SNP in the IL-23 receptor (rs11209026) that has been associated with increased risk of IBD in several studies [6]. We did not find an association between this SNP and risk of colorectal cancer. However, as STAT3 is a mediator of signaling from the IL-23 receptor, we evaluated whether there was an interaction between the two SNPs (STAT3 rs744166 and IL-23 rs11209026): we did not find any evidence to support this (data not shown). We also tested whether rs744166 was associated with colorectal cancer survival in our population. In a model adjusted for age, sex and stage at diagnosis, there was no association between this SNP and outcome (HRGG vs. AA 0.72, 95% C.I. 0.34-1.49; P=0.372; n=162).

Our replication of STAT3 rs744166 in the Diet, Activity and Lifestyle Study (DALS) showed a slightly increased risk associated with the G allele with colon cancer after adjusting for age, race, sex and study center (ORGG vs. AA 1.27, 95% C.I. 1.05-1.54; n=3,558) (Table 3). It is important to notice that the association was in the opposite direction to that observed in the NCI-MD study. We also evaluated rs10883365, but did not observe a statistically significant relationship in the DALS data. Assessment of interaction between age, sex, NSAID use, exogenous estrogen exposure, cigarette smoking, family history of colorectal cancer, and BMI during the referent period with STAT3 rs744166 in the DALS data revealed several statistically marginal associations: Colon cancer risk was most likely to be observed in individuals less than 65 years of age at diagnosis (ORGG vs. AA 1.47, 95% C.I. 1.09-1.99; Ptrend=0.010), in women (ORGG vs. AA 1.46, 95% C.I. 1.10-1.94; Ptrend=0.008), those with recent aspirin or NSAID use (ORAG vs. AA 1.48, 95% C.I. 1.14-1.93; ORGG vs. AA 1.38, 95% C.I. 0.99-1.93; Ptrend=0.025), those with no exogenous exposure (ORGG vs. AA 1.54, 95% C.I. 1.07-2.21; Ptrend=0.020), recent cigarette smokers (ORAG vs. AA 1.44, 95% C.I. 1.02-2.04; ORGG vs. AA 1.61, 95% C.I. 1.02-2.55; Ptrend=0.022), those with no family history of colorectal cancer (ORGG vs. AA 1.28, 95% C.I. 1.04-1.57; Ptrend=0.015), and those with BMI of <25 (ORGG vs. AA 1.57, 95% C.I. 1.14-2.17; Ptrend=0.005) (Supplementary Table 3). Tumors from patients harboring the G allele were also more likely to be located in the proximal colon, than in the distal colon (ORGG vs. AA 1.39, 95% C.I. 1.10-1.77; Ptrend=0.006) (Supplementary Table 3). As observed in the NCI-MD study, there were no associations between rs744166 with colon cancer survival in this population.

Table 3. Risk Associations for rs744166 and rs108883365 and colon cancer in the DALS study.

DALS Study
Gene SNP Genotype Controls Cases Odds Ratio (95% C.I.) P*
STAT3
rs744166		 AA 677 (34%) 471 (30%) Reference
AG 938 (47%) 785 (50%) 1.20 (1.03 - 1.40)
GG 365 (18%) 322 (21%) 1.27 (1.05 - 1.54) 0.019
P Trend 0.008
AA 677 (34%) 471 (30%) Reference
AG/GG 1303 (66%) 1107 (70%) 1.22 (1.06 - 1.41) 0.006
NKX2-3
rs10883365		 AA 544 (27%) 451 (28%) Reference
AG 971 (49%) 757 (48%) 0.95 (0.81 - 1.11)
GG 465 (23%) 370 (23%) 0.96 (0.79 - 1.15) 0.789
PTrend 0.614
AA 544 (27%) 451 (28%) Reference
AG/GG 1436 (73%) 1127 (72%) 0.95 (0.82 - 1.10) 0.496
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*

Adjusted for age, center, race and gender

Association between rs744166 and risk of TP53 mutant colon cancer

Evaluation of tumor molecular phenotype available within the DALS Study included assessment of CpG island methylated phenotype (CIMP), KRAS, TP53, and microsatellite instability (MSI). The association between the G allele of STAT3 rs744166 was restricted to TP53-mutant tumors (ORGG vs. AA 1.35, 95% C.I. 1.06-1.73; Ptrend=0.010) (Table 4). We did not find an association between rs744166 and risk of KRAS-mutated colon cancer (Table 4) and there was no association between NKX2-3 rs10883365 and any of the molecular phenotypes of colorectal cancer evaluated (Table 4).

Table 4. Association between rs10883365 and rs744166 with colon cancer risk stratified by tumor marker in the DALS study.

Controls N CIMP High KRAS mutation TP53 mutation MSI unstable
N OR (95% C.I.) N OR (95% C.I.) N OR (95% C.I.) N OR (95% C.I.)
STAT3
(rs744166)
AA 677 83 Reference 113 Reference 151 Reference 53 Reference
AG 938 138 1.13 (0.87 - 1.46) 162 0.95 (0.75 - 1.20) 251 1.14 (0.93 - 1.40) 101 1.32 (0.96 - 1.83)
GG 365 55 1.08 (0.78 - 1.50) 79 1.14 (0.86 - 1.51) 118 1.35 (1.06 - 1.73) 35 1.09 (0.72 - 1.66)
*P Trend 0.313 0.223 0.01 0.252
AA 677 83 Reference 113 Reference 151 Reference 53 Reference
AG/GG 1303 193 1.11 (0.87 - 1.43) 241 1.00 (0.80 - 1.25) 369 1.20 (0.99 - 1.46) 136 1.26 (0.92 - 1.71)
NKX2-3
(rs10883365)
AA 544 72 Reference 102 Reference 140 Reference 51 Reference
AG 971 143 1.11 (0.84 - 1.45) 165 0.90 (0.70 - 1.15) 246 0.99 (0.80 - 1.22) 86 0.96 (0.68 - 1.34)
GG 465 61 0.93 (0.67 - 1.29) 87 0.96 (0.72 - 1.27) 134 1.10 (0.86 - 1.40) 52 1.18 (0.81 - 1.72)
*P Trend 0.701 0.822 0.466 0.436
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*

Adjusted for age, center, race, and sex

CIMP denotes CpG Island Methylator Phenotype

rs744166 does not modulate STAT3 isoform expression in colorectal cancer tissue

STAT3 rs744166 lies within intron 1 of the STAT3 gene. Analysis of the Haploreg database (http://www.broadinstitute.org/mammals/haploreg/haploreg.php) suggested that the SNP lay within a binding site for the transcription factors MAX and MXI-1. We therefore tested whether the SNP resided at an expression Quantitative Trait Locus (eQTL) using TCGA data. Specifically, we downloaded data for rs744166 and all of the six known isoforms of STAT3 from the colorectal cancer database. RPKM values corresponding to normalized expression levels of each STAT3 isoform were compared across samples with known rs744166 genotypes. Of the six variants analyzed, uc010wgh.1 (672 aa), which contains 23 exons, was the most abundantly expressed STAT3 isoform, followed by uc002hzl.1 (770 aa), uc002hzk.1 (722 aa), uc002hzn.1 (770 aa), uc002hzm.1 (769 aa) and uc010cyf.1 (89 aa) (Figure 1A). The last of these was barely detectable. Samples were then categorized based on rs744166 genotype and expression of each isoform was compared across each group. As shown in Figure 1A, there was no statistically significant difference in the expression of any STAT3 isoform across the three genotypes of rs744166. We also extracted data for phosphorylation of tyrosine 705 in STAT3 and compared its relative expression across the three rs744166 genotypes. Again, we did not observe any differences (Figure 1B). These data indicate that the rs744166 locus does not modulate STAT3 transcription or Y705 phosphorylation in colon cancer samples. Several SNPs within intron 1 lie in strong linkage with rs744166. We also tested STAT3 mRNA expression across the 8 other SNPs but did not find any significant associations (Supplementary Figure 1).

Figure 1.

Figure 1

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(A) Expression of the six STAT3 mRNA isoforms in colorectal carcinoma and STAT3 mRNA isoform expression stratified by rs744166 genotypes. (B) Phospho-tyrosine705 expression stratified by rs744166 genotype. Data were downloaded from TCGA website. mRNA isoform names refer to the former UCSC system of transcript identification, taken from Illumina RNA-seq version 2 data. SNP data was extracted from the Affymetrix SNP6.0 array. Phospho-stat3 expression was extracted from the MD Anderson Reverse Phase Protein array.

Discussion

We found that that the STAT3 SNP, which was previously associated with risk of IBD in several GWAS studies, was associated with lower risk of colorectal cancer in the NCI-MD study. This association was primarily restricted to a European American population. Our result was consistent with previous IBD GWAS studies, where the G allele of this SNP was also associated with reduced risk of UC and CD [11, 51]. Replication of these findings in a second study also showed a significant association between this SNP and colon cancer risk, however the direction of the association was reversed and restricted to TP53-mutant tumors. We are not sure why we observed the opposite direction of association in this population. One relevant possibility is that, unlike the NCI-MD study, the DALS population excluded individuals with a history of IBD and included only colon cancer cases and not rectal cancer. In addition, the DALS study included only population controls, whereas the NCI-MD study included both hospital and population controls. However, as a sub-group analysis of the SNP that included only the population controls in the NCI-MD study did not change the result, this is also unlikely to have been the cause of difference in direction of the association. However, as we observed that the positive association between the G allele and rs744166 with risk of colon cancer was restricted to TP53-mutated cancers in the DALS study, it is possible that mutant TP53 could reverse, or nullify, the association between this SNP and risk. This hypothesis is supported by a recent report showing that, in cancer cells, high levels of active STAT3 are correlated with mutant TP53 [52] and that loss of heterozygosity for TP53 is an early event IBD-associated colorectal cancer [32, 33]. Unfortunately, data were not available in the NCI-MD study to assess this possibility in that cohort. Notably, rs744166 represents a shared locus for several traits, many of which also demonstrate disparate connections. For example, rs744166-G is a “protective” allele for lung cancer [53], a “risk” allele for multiple sclerosis [18, 54, 55], and a “protective” allele for UC and CD [11, 51]. Jones and Cross tested the hypothesis that rs744166 predisposes to myeloproliferative neoplasms, as the incidence of this disease is reported to be higher in individuals with a prior history of CD [56]; however, they did not find evidence that the locus was involved [57]. These data suggest that the relationship between the STAT3 locus and this diverse range of phenotypes is complex.

rs744166 lies within intron 1 of STAT3. Analysis of the Haploreg database which includes ENCODE data indicated that the SNP was contained within a binding site for the transcription factors MAX and MXI-1. If this was the case, the SNP could potentially affect binding, and therefore, mRNA abundance. Indeed, an analysis of eQTL data from a normal blood-based eQTL database suggested that rs744166 was a eQTL locus for STAT3 mRNA expression (P=2.16E-20) [58]. We used TCGA data to directly address this possibility, and although we had sufficient resolution in our data to look at each of the six STAT3 mRNA isoforms, we did not observe a change in STAT3 expression across the three rs744166 genotypes in colon cancer tissue, nor did we observe a change in the phosphorylation status of Y705. Although it is possible that the SNP affects phosphorylation of serine 727, a marker that was not on the array, the data suggest that either the SNP affects some other aspect of STAT3 function or the SNP affects STAT3 expression in a tissue-specific manner. Either way, further study is needed in this region to decipher to functional interplay of these loci and their relationship to autoimmunity and cancer. Of note, four other SNPs in STAT3 have emerged as associated with phenotypic traits in GWAS; rs2293152 in multiple sclerosis [59] (R2=0.234, D′=0.739) , rs9891119 in CD [60] (R2=0.811, D′=1), rs12942547 in IBD [61] (R2=0.966, D′=1.0), and rs11871801 in CD [12] (R2=0.208, D′=0.653). Other SNPs in linkage with rs744166 (based on R2 ≥0.7 and/or D′=1) are also located within an intronic region of STAT3. We tested 8 of these again using the TCGA data (these were the only ones tagged) but again did not see any associations with mRNA expression.

The rs10883365 locus on chromosome 10 is another commonly associated region with IBD [10-13, 17, 61, 62]. Although we observed an association between this SNP and colorectal cancer in the NCI-MD study, it did not replicate with colon cancer in the DALS study. The SNP is described as residing upstream of the NKX2-3 gene, but it actually lies within a long non-coding RNA (lncRNA) called LINC00200. The TCGA analysis suggests that expression of this RNA could be higher in the presence of the variant allele (Supplementary Figure 2). Although an association with cancer may not be likely, the region may be of relevance to the susceptibility and biology of IBD and, as such, warrants further study.

The management of IBD is a difficult clinical challenge, one that is often compounded by the lack of clear indicators as to which patients with IBD will develop colorectal cancer and which patients will not. Identifying common genetic loci that mediate susceptibility to both IBD and cancer, will not only help in the clinical management of IBD, but it will also facilitate a greater understanding of the mechanisms of carcinogenesis in these patients. Genome-wide association studies have now identified approximately 99 susceptibility loci/genes relating to IBD. The work described here represents a step towards resolving which of these loci are also involved in cancer progression. The next step will be to ask whether these SNPs are associated with risk of colon cancer among a specific IBD population. Although the results of the NCI-MD and DALS studies differed in regard to rs744166, the previous GWAS studies combined with our data indicate that this region is potentially important for autoimmune diseases [11, 12, 14, 53-55, 63-66] and colon and rectal cancer. Larger studies, specifically in IBD populations, will be needed to understand the actual implications in colorectal cancer development in patients both with and without IBD.

Supplementary Material

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Highlights.

  • We examine the relationship between susceptibility loci associated with risk of IBD for their association with colorectal cancer

  • We undertook a two-stage study design using the NCI-MD and DALS studies

  • A SNP in STAT3, rs744166, is associated with risk of colon cancer

  • The relationship between the SNP and risk may be modulated by TP53 mutation status

  • The SNP may be associated with STAT3 expression, only in TP53 wild-type tumors

Acknowledgments

We gratefully acknowledge contributions from the TCGA Research Network. BMR and CCH were involved in the conception and design of the study; BMR, RKW, NV, MK, AP, EDB, AL, BC, JP, CC and MLS were involved in the acquisition of the data; BMR, DR, DB AL, MLS and RKW were involved in the analysis of the data, BMR, CCH and MLS were involved in the interpretation of the data; BMR drafted the manuscript, BMR, RKW, NV, MK, DR, DB, AP, EDB, AL, BC, JP, CC MLS, and CCH revised the manuscript; BMR, RKW, NV, MK, DR, DB, AP, EDB, AL, BC, JP, CC MLS, and CCH gave final approval of manuscript submission.

This work was funded by the intramural research program of the National Cancer Institute (NCI) and R01-CA48998 (NCI).

Footnotes

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Supplementary Materials

01
NIHMS616776-supplement-01.doc (136KB, doc)
02
NIHMS616776-supplement-02.ppt (108KB, ppt)
03
NIHMS616776-supplement-03.pptx (3.5MB, pptx)

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