Genetic Variants in Selected pre-mircroRNA Genes and Risk of Squamous Cell Carcinoma of the Head and Neck

Abstract

BACKGROUND

Single nucleotide polymorphisms (SNPs) in microRNAs (miRNAs) may alter processing, transcription, and expression of miRNAs, and thus contribute to cancer development. We hypothesized that common polymorphisms in pre-miRNAs individually, and more likely, collectively are associated with risk of squamous cell carcinoma of the head and neck (SCCHN).

METHODS

We genotyped four common polymorphisms in pre-miRNAs (hsa-mir-146a rs2910164 G>C, hsa-mir-149 rs2292832 G>T, hsa-mir-196a2 rs11614913 C>T, and hsa-mir-499 rs3746444 A>G) in 1109 SCCHN cases and 1130 cancer-free controls in a non-Hispanic white population frequency-matched by age and sex. We used univariable and multivariable logistic regression models to calculate crude and adjusted odds ratios (OR) and 95% confidence intervals (CI).

RESULTS

Of the four SNPs studied, hsa-mir-499 AG and GG genotypes were associated with reduced risk of SCCHN (OR, 0.83; 95% CI, 0.69–0.99). When we combined the four SNPs by putative risk genotypes, we found that the number of observed risk genotypes was associated with increased risk of SCCHN in a dose-response manner: OR=1.0, 1.20 and 1.40 for 0–1, 2–3 and 4 risk genotypes (P_trend = 0.037). Specifically, the risk was 1.23 fold (95% CI, 0.98–1.56) for subjects with 2–4 risk genotypes and 1.40 fold (95% CI, 1.02–1.92) for subjects with 4 risk genotypes, compared with subjects with 0–1 risk genotypes. This risk was more pronounced in men and patients with oropharyngeal cancer.

CONCLUSIONS

The combined risk genotypes of four common SNPs in pre-mircroRNAs were significantly associated with a moderately increased risk of SCCHN. Larger studies are needed to validate our findings.

INTRODUCTION

Squamous cell carcinoma of head and neck (SCCHN), including cancers of the oral cavity, pharynx, and larynx, are the sixth most common cancers worldwide.¹ In the United States, approximately 48,010 new cases were diagnosed and resulted in 11,260 deaths in 2009.² Although tobacco and alcohol are the known risk factors, only a fraction of smokers and drinkers develop SCCHN, suggesting the existence of genetic susceptibility to SCCHN. Indeed, numerous studies have demonstrated that genetic variations or single nucleotide polymorphisms (SNPs) have been associated with risk of developing SCCHN.^3–5

MicroRNAs (miRNAs) are small, single-stranded, non-protein-coding RNAs of about 22 nucleotides. To date, hundreds of miRNA molecules have been identified in the human genome, which play key roles in a broad range of physiologic and pathologic processes.^{6, 7} Although their biological functions remain largely unclear, recent studies have demonstrated that miRNAs may function as tumor suppressors and/or oncogenes.^8–12 It has been shown that aberrant expression of miRNAs was related to the etiology, diagnosis and prognosis of many cancers, including SCCHN.^13–21 For example, mir-let-7, like mir-16, mir-18, mir-21, mir-146 and miRNA-211 were highly expressed in SCCHN cell lines and tumor tissues,^{17, 22} and high miR-211 expression may be associated with progression and poor outcomes of oral cancer,¹⁵ while mir-342, mir-346 and mir-373 had low expression in SCCHN cell lines,^{16, 17}

Although the role of miRNA genetic variants in cancer susceptibility is largely unknown, the importance of miRNA SNPs has been implicated in many cancers. It is well known that common SNPs in miRNAs and SNPs within their targets (miRNA-binding SNPs) may affect miRNA target expression and functions and thus may contribute to cancer risk,^{23, 24} Studies have shown that polymorphisms of miRNAs were associated with risk of lung cancer,^{25, 26} bladder cancer,²⁷ thyroid cancer,²⁸ renal cell carcinoma,²⁹ colon cancer,³⁰ and breast cancer.¹⁸ For example, a hsa-mir-196a2 polymorphism was found to be associated with survival in patients with non-small cell lung cancer²⁵, whereas hsa-mir-196a2 C>T and hsa-mir-499 A>G variant genotypes were found to be associated with increased risks of breast cancer.³¹ These associations appear to be biologically plausible, because it has been demonstrated that a pre-mir-146a polymorphism may affect the miRNA expression.²⁸

Few studies investigated miRNA expression in head and neck cancer tissues, to the best of our knowledge. Previous studies have demonstrated that hsa-146a was over-expressed in SCCHN cell lines and tumor tissues and hsa-mir-149 was down-regulated in squamous cell carcinoma of the tongue,^15,16,32 and a resent study reported that the hsa-mir-146a G>C, hsa-mir-149 G>T, hsa-mir-196a2 C>T and hsa-mir-499 A>G polymorphisms were associated with risk of lung cancer. Because tobacco smoke is a major risk factor for both lung cancer and SCCHN and given an important role for miRNAs in the development of cancers, including SCCHN, we hypothesized that SNPs in these miRNAs may also contribute to susceptibility to SCCHN. To test this hypothesis, we genotyped and analyzed association of the previously described four common polymorphisms in pre-miRNAs²⁵ with risk of SCCHN in a hospital-based case-control study of 1109 SCCHN cases and 1130 cancer-free controls in a non-Hispanic white population.

MATERIALS AND METHODS

Study Subjects

The subjects were recruited from an ongoing SCCHN study as described previously.³³ Briefly, the cases were patients with newly diagnosed, untreated SCCHN that were histologically confirmed at The University of Texas M D Anderson Cancer Center between October 1999 and October 2007. Patients with second SCCHN primary tumors, primary tumors of the nasopharynx or sinonasal tract, primary tumors outside the upper aerodigestive tract, cervical metastases of unknown origin, or any histopathological diagnosis other than SCCHN were excluded. Of the eligible cases, the response rate was approximately 93% and only few minority subjects were recruited. As a result, the analysis included 1109 non-Hispanic white subjects with primary tumors of the oral cavity (n = 326; 29.4%), oropharynx (n = 566; 51.0%), or larynx / hypo-pharynx (n = 217; 19.6%).

Among the eligible control subjects with a response rate of 85%, 1130 cancer-free controls were recruited from hospital visitors accompanying the patients to the clinics but not seeking medical care, who were genetically unrelated to the enrolled case subjects or each other. We first surveyed potential control subjects at the clinics by using a short questionnaire to determine their willingness to participate in research studies and to obtain demographic information for frequency matching to the cases by age (±5 years) and sex. Having obtained a written informed consent, we interviewed each eligible subject to collect additional information about risk factors, such as tobacco smoking and alcohol use and a one-time sample of 30 ml of blood for biomarker tests. The research protocol was approved by the M. D. Anderson Cancer Center institutional review board.

Genotyping

From each blood sample, a leukocyte cell pellet obtained from the buffy coat by centrifugation of 1 ml of the whole blood was used for DNA extraction by using the Qiagen DNA Blood Mini kit (Qiagen, Valencia, CA) according to the manufacturer’s instructions. The DNA purity and concentration were determined by spectrophotometer measurement of absorbance at 260 and 280 nm. For genotyping, we chose the four miRNA SNPs that have been reported as important,²⁵ because each of these miRNA targeted several important genes (e.g., hsa-mir-146-3p targeting MST1R,MNAT1,MUC1,IL6, and ATG7; hsa-mir-146-5p targeting IRAK1,GTF2H4,CETN2,CYP11A1, and TRAF6; hsa-mir-196a-3p targeting LSP1,KIF20A,PSMD10,BAG3, and ALOX15; hsa-mir-196a-5p targeting HOXB8,MYC,PFKFB1,TOX3, and NME4; hsa-mir-499-3p targeting GPR1,FAT,NBN,IL1RL1, and BCL2L14, and hsa-mir-499-5p targeting GPR1,LECT1,KCNN3,PSIP1, and RBP2). The PCR-restriction fragment length polymorphism method was used to amplify the fragments that contain polymorphisms of hsa-mir-146a (G>C, rs2910164), hsa-mir-196a2 (C>T, rs11614913) or hsa-mir-499 (A>G, rs3746444) as described previously. For the hsa-mir-149 (G>T, rs2292832) polymorphism, the primers were newly designed with a forward primer, 5’-GTTTCTGGGAGAATTGAGG-3’ and a reverse primer, 5’-GGAATCGTTTGAATCTGGAG-3’. The PCR profile included an initial melting step of 94°C for 5 min, 35 cycles of 94°C 60 s, 53°C for 45 s and 72°C for 1 min and a final extension step of 72°C for 10 min. These primers generated a PCR product of 250 bp (the TT genotype) that was digested by PvuII (New England Biolabs) into fragments of 122 bp and 40 bp for CC and 250 bp, 122 bp, and 40 bp for CT. The genotyping assays for 10% of the samples were repeated, and the results were 100% concordant.

Statistical analysis

Differences in select demographic variables, smoking, and alcohol consumption between SCCHN cancer cases and controls were evaluated by using the χ²-test. The associations between risk of SCCHN and genotypes of miRNA SNPs were estimated by computing the odds ratio (ORs) and their 95% confidence intervals (CIs) from both univariable and multivariable logistic regression analyses. Those subjects who had smoked more than 100 cigarettes in their lifetime were defined as ever smokers as traditionally used in epidemiological studies; those who had quit smoking for >1 year previously were considered as former smokers, and the rest were considered current smokers. Subjects who drank alcoholic beverages at least once a week for more than 1 year in previous years were defined as ever drinkers; of these, those who had quit drinking for more than 1 year previously were defined as former drinkers and the others as current drinkers. The ORs and their 95% CIs for the miRNA genotypes were calculated by logistic regression analysis with adjustment for age (in years), sex, smoking status and alcohol use. In logistic regression analysis, the miRNA genotypes were recorded as a dummy variable. Considering potential joint effect of the four miRNA polymorphisms on SCCHN risk, we evaluated the association between risk of SCCHN and the combined genotypes of these polymorphisms. Stratified analysis was used to estimate risk for subgroups by age, sex, smoking status, drinking status and tumor site. All statistical analyses were performed with the SAS software (version 9.1.3; SAS Institute, Inc., Cary, NC).

RESULTS

The distributions of selected characteristics of the cases and controls are presented in Table 1. There were no significant differences in the distributions of age and sex between the cases and the controls (P = 0.466 and 0.727, respectively) with a similar mean age for cases (57.2 ±11.1 years) and controls (56.8 ±11.0 years) (P = 0.898). There were more ever smokers and ever drinkers in the cases than in the controls (72.3% versus 51.1% and 72.7% vs. 56.3%, respectively, P< 0.001 for both). However, all these variables were further adjusted for any residual confounding effect in later multivariate logistic regression analyses.

Table 1.

Frequency Distributions of Selected Variables in SCCHN Cases and Cancer-free Controls

	No. %
Characteristic	Cases, n = 1109		Controls, n = 1130		P*
Age (years)
≤ 50	301	27.1	318	28.1	0.466
51–57	290	26.2	270	23.9
> 57	518	46.7	542	48.0
Sex
Female	272	24.5	270	23.9	0.727
Male	837	75.5	860	76.1
Smoking status
Never	307	27.7	553	48.9	< 0.001
Former	380	34.3	412	36.5
Current	422	38.0	165	14.6
Alcohol use
Never	303	27.3	494	43.7	< 0.001
Former	242	21.8	182	16.1
Current	564	50.9	454	40.2
Tumor site
Oral cavity	326	29.4
Oropharynx	566	51.0
Larynx/Hypopharynx†	217	19.6

^*Two-sided χ² test.

^†Included both larynx (n=174) and hypopharyngeal (n=43) cancer cases.

The genotype and allele frequencies of the hsa-mir-146a (G>C, rs2910164), hsa-mir-149 (G>T, rs2292832), hsa-mir-196a2 (C>T, rs11614913), and hsa-mir-499 (A >G, rs3746444) SNPs and their associations with risk of SCCHN are summarized in Table 2. The genotype distribution of the four SNPs in the controls was all in agreement with that of the Hardy-Weinberg equilibrium (P = 0.449 for hsa-mir-146a, 0.271 for hsa-mir-149, 0.737 for hsa-mir-196a2, and 0.441 for hsa-mir-499), and there was no overall difference in the genotype distributions between cases and controls. However, compared with the hsa-mir-499 AA genotype, the variant AG and GG+AG genotypes were associated with a statistically significantly decreased risk of SCCHN (adjusted OR, 0.80; 95% CI, 0.66–0.97 and 0.83; 0.69–0.99; P = 0.023 and 0.040, respectively), and this risk was not observed for other three SNPs (Table 2).

Table 2.

Frequency Distribution of pre-miRNA Genotypes and Their Associations with Risk of SCCHN

	No. (%)			Adjusted
Genotypes	Cases	Controls	P†	OR (95% CI) ‡
All subjects	1109 (100.0)	1130 (100.0)
hsa-mir-146a:G>C
GG	630 (56.8)	655 (58.0)	0.834	1.00
CG	411 (37.1)	405 (35.8)		1.01 (0.84–1.22)
CC	68 (6.1)	70 (6.2)		1.00 (0.69–1.45)
CC/CG	479 (43.2)	475 (42.0)		1.01 (0.85–1.21)
C allele	0.247	0.241	0.670
hsa-mir-149:G>T
GG	580 (52.3)	586 (51.8)	0.779	1.00
GT	441 (39.8)	445 (39.4)		0.97 (0.81–1.16)
TT	88 (7.9)	99 (8.8)		0.87 (0.63–1.21)
TT/GT	529 (47.7)	544 (48.0)		0.95 (0.80–1.13)
T allele	0.278	0.285	0.637
hsa-mir-196a2:C>T
CC	350 (31.6)	383 (33.9)	0.404	1.00
CT	565 (50.9)	545 (48.2)		1.17 (0.96–1.42)
TT	194 (17.5)	202 (17.9)		1.03 (0.79–1.33)
TT/CT	759 (68.4)	747 (66.1)		1.13 (0.94–1.36)
T allele	0.430	0.420
hsa-mir-499:A>G
AA	745 (67.2)	710 (62.8)	0.065	1.00
AG	309 (27.9)	366 (32.4)		0.80 (0.66–0.97)
GG	55 (4.9)	54 (4.8)		1.01 (0.67–1.51)
GG/AG	364 (32.8)	420 (37.2)		0.83 (0.69–0.99)
G allele	0.189	0.210	0.081

^*The observed genotype frequency among the control subjects was in agreement with the Hardy-Weinberg equilibrium (p² + 2pq + q² = 1) (χ² = 0.486, P = 0.4486 for hsa-mir-146a G>C, χ² =1.211, P = 0.271 for has-mir-149C>T, χ² = 0.113, P = 0.737 for hsa-mir-196a2C>T, χ² = 0.594, P = 0.441 for hsa-mir-499).

^†p-values of two-sided χ² test for either genotype distribution or allele frequency

^‡Adjusted for age, sex, smoking status, and alcohol use in a logistic regression model.

Because each of the other three non-significant SNPs appeared to have some minor effect on risk of SCCHN, we then performed combined analysis of all four SNPs to evaluate potentially modifying effect of the combined genotypes on risk of SCCHN (Table 3). We categorized each putative risk (OR > 1.0) genotypes of all SNPs into a new variable according to the number of risk genotypes (for the protective (OR < 1.0) genotype, we reversed the reference group). We found that those who had 4 risk genotypes had the highest risk (adjusted OR, 1.45; 95% CI, 0.82–2.55), although the trend test was not statistically significant (P_trend = 0.070). In trichotomized groups of 0–1, 2–3, and 4 risk genotypes, only individuals with 4 risk genotypes had a significantly increased risk of SCCHN (adjusted OR, 1.40; 95% CI, 1.02–1.92), compared with individuals with 0–1 risk genotypes, but the trend of three groups (0–1, 2–3 and 4 risk genotypes) in risk was statistically significant (P_trend = 0.037). To facilitate further stratified analysis, we dichotomized all subjects into groups of 0–1 and 2–4 risk genotypes, and individuals with 2–4 risk genotypes also had a significantly increased risk of SCCHN (adjusted OR, 1.23; 95% CI, 0.98–1.56), compared with individuals with 0–1 risk genotypes.

Table 3.

Association of Combined pre-miRNA hsa-146a, hsa-196a, hsa-149 and hsa499 Genotypes with Risk of SCCHN

	No. %				(95% CI)*
Risk group	Cases (n=1109)		Controls (n=1130)		Crude OR	Adjusted OR
Combined genotype
0	30	2.7	34	3.0	Ref.	Ref.
1	141	12.7	171	15.1	0.94 (0.55–1.60)	1.04 (0.59–1.84)
2	402	36.3	394	34.9	1.16 (0.69–1.93)	1.26 (0.74–2.14)
3	375	33.8	385	34.1	1.10 (0.66–1.84)	1.23 (0.72–2.11)
4	161	14.5	146	12.9	1.25 (0.73–2.14)	1.45 (0.82–2.55)
p, Trend					0.152	0.070
Trichotomized
0 – 1	171	15.4	205	18.1	Ref.	Ref.
2 – 3	777	70.1	779	69.0	1.20 (0.95–1.50)	1.20 (0.95–1.52)
4	161	14.5	146	12.9	1.32 (0.98–1.79)	1.40 (1.02–1.92)
p, Trend					0.065	0.037
Dichotomized
0 – 1	171	15.4	205	18.1	Ref.	Ref.
2 – 4	938	84.6	925	81.9	1.22 (0.97–1.52)	1.23 (0.98–1.56)

^*Adjusted for age, sex, smoking status, and alcohol use in a logistic regression model.

^†Two-sided χ² test for difference in frequency distribution of genotype between cases and controls by adjusted for age, sex, smoking and alcohol consumption.

We then stratified the data of dichotomized risk genotypes by age group, sex, smoking and alcohol status, and cancer histology. We estimated the ORs associated with 2–4 risk genotypes (as the risk group) compared with 0–1 risk genotypes (as the reference group) with adjustment for the aforementioned variables (Table 4). When the age was categorized into two groups based on the median value of the controls, younger individuals (≤ 57 years) with 2–4 risk genotypes exhibited a borderline significantly higher risk (adjusted OR, 1.34; 95% CI, 1.00–1.87) than the reference group. The ORs associated with 2–4 risk genotypes were more evident for men (adjusted OR, 1.29; 95% CI, 1.00–1.69) than for women as well as for never smokers (adjusted OR, 1.41; 95% CI, 1.00–2.08) than for ever smokers. Finally, the histological-specific risk was more pronounced for the patients with oropharyngeal cancer (OR, 1.32; 95% CI, 1.00–1.76) than those with cancers of oral cavity and larynx/hypopharynx.

Table 4.

Stratification Analysis of SCCHN Risk Associated with pre-miRNA hsa-146a,hsa-196a, hsa-149 and hsa499 Combined Genotypes

	No. of cases (%)		No. of controls (%)		Adjusted OR (95% CI)*
Characteristic	Ref. Group	Risk Group	Ref. Group	Risk Group	Ref. Group	Risk Group
	(0–1)	(2–4)	(0–1)	(2–4)	(0–1)	(2–4)
Age (years)
≤ 57	78 (13.2)	513 (86.8)	100 (17.0)	488 (83.0)	Ref.	1.34 (1.00–1.87)
> 57	93 (18.0)	425 (82.0)	105 (19.4)	437 (80.6)	Ref.	1.17 (0.84–1.62)
Sex
Male	128 (15.3)	709 (84.7)	160 (18.6)	700 (81.4)	Ref.	1.29 (1.00–1.69)
Female	43 (15.8)	229 (84.2)	45 (16.7)	225 (83.3)	Ref.	1.06 (0.65–1.73)
Smoking status
Never	43 (14.0)	264 (86.0)	103 (18.6)	450 (81.4)	Ref.	1.41 (1.00–2.08)
Ever	128 (16.0)	674 (84.0)	102 (17.7)	475 (82.3)	Ref.	1.16 (0.86–1.57)
Alcohol use
Never	42 (13.9)	261 (86.1)	89 (18.0)	405 (82.0)	Ref.	1.36 (0.91–2.04)
Ever	129 (16.0)	677 (84.0)	116 (18.2)	520 (81.8)	Ref.	1.18 (0.88–1.57)
Tumor site
Oral cavity	53 (16.3)	273 (83.7)	205 (18.1)	925 (81.9)	Ref.	1.06 (0.75–1.51)
Oropharynx	83 (14.7)	483 (85.3)	205 (18.1)	925 (81.9)	Ref.	1.32 (1.00–1.76)
Larynx/Hypopharynx	35 (16.1)	182 (83.9)	205 (18.1)	925 (81.9)	Ref.	1.12 (0.72–1.75)

^*Adjusted for age, sex, smoking status, and alcohol use in a logistic regression model.

DISCUSSION

In the current study, we examined associations between previously reported four important polymorphisms (pre-miRNA hsa-mir-146a, hsa-mir-149, hsa-mir-196a2 and hsa-mir-499)²⁵ and risk of SCCHN in non-Hispanic whites. To the best of our knowledge, this is the first and largest study of the role of these pre-mircroRNA polymorphisms in the etiology of SCCHN. Of the four polymorphisms we found that only the hsa-mir-499 was significantly associated with risk of SCCHN; however, we did observe an effect of the combined risk genotypes of all the four polymorphisms on risk of SCCHN in a dose-response manner. For example, individuals with 4 risk genotypes had a 40% significantly increased risk of SCCHN compared with individuals with 0–1 genotypes, and the risk was more pronounced in subgroups of younger age, men, and never smokers. These findings suggest that these four pre-miRNA polymorphisms may have a joint effect on the risk of SCCHN, although the exactly mechanism by which these variants may influence the risk of SCCHN is not clear. It is possible that these variant may be either functional itself, or it may be in linkage disequilibrium with other functional variants that are involved in the etiology of SCCHN. Such possibilities need to be explored in future studies.

Recent studies have shown that miRNAs may play an important role in human carcinogenesis, and SNPs located either in the pre-miRNAs or within miRNA-binding sites are likely to affect the expression of the miRNA targets and thus may contribute to the susceptibility to cancer.^24,34 For example, one study found that the expression of pre-miRNA-146a variant C allele was 1.9-fold lower than the G allele and that the amount of mature miRNA-146a variant C allele was 1.8-fold lower than that of the G allele, suggesting that the pre-miRNA-146a G>C substitution may lead to reduced amounts of mature miRNA-146a; however, the hsa-mir-146a GC heterozygous genotype was associated with an increased risk of papillary thyroid carcinoma, while the variant homozygous CC genotype was protective.²⁸ These data also suggest that the C allele may be tumor-specific in cancers with different etiologies.

In the present study, we found that frequencies of the hsa-mir-146 GG, CG and CC genotypes of 58%, 35.8% and 6.2%, respectively, in 1130 non-Hispanic controls, which are consistent with 58.4%, 35.5% and 6.1% found in Jazdzewski’s 901 Caucasian controls.²⁸ Although there have been no previous reports of an association between the hsa-mir-146a polymorphism and SCCHN risk, a recent study reported that pre-miRNA-146 was over-expressed in the head and neck cancer cell lines and tumor tissues.^16,22 Our results suggest that hsa-mir-146a rs2910164 variant C genotypes may not play a major role in the development of SCCHN. Similarly, other studies of associations between the hsa-mir-146a rs2910164 variant C genotypes and the risk of bladder cancer, renal cancer and breast cancer failed to show any overall association in Caucasian^27,29 or Chinese populations.³¹

To date, few studies have examined the effect of the hsa-mir-196a2 rs11614913 C>T polymorphism on human cancers. One study reported that carriers of the hsa-mir-196a2 CC genotype had a reduced survival in NSCLC in a Chinese population.²⁵ In another study of 1009 breast cancer patients and 1093 healthy Chinese population controls, the same authors also found that the hsa-mir-196a2 CC and CC/CT genotypes were associated with significantly increased breast cancer risk.³¹ More recently, Hoffman et al. found that has-mir-196a2 TC and TT were significantly associated with decreased breast cancer risk.³⁵ Our hsa-mir-196a2 C>T genotype data from 1109 SCCHN patients and 1130 controls in a non-Hispanic white population had similar distribution of hsa-mir-196a2 CC, CT, and TT genotypes (33.9%, 48.2% and 17.9%) in controls, respectively, to that (31%, 50% and 19%) in the HapMap database, but we did not find an association of the variant genotypes with risk of SCCHN. Consistent with our present study, other studies have also failed to find an association between the hsa-mir-196a2 polymorphism and risk of bladder cancer and renal cancer in Caucasian populations.^27,29

Thus far, few epidemiologic studies have investigated the association of the hsa-mir-499 rs3746444 A>G SNP with cancer risk and survival. In one Chinese study, the hsa-mir-499 rs3746444 A>G genotypes were not associated with risk of the non-small cell lung cancer survival.²⁵ In another case-control study of 1009 breast cancer cases and 1093 controls in a Chinese population, the same research team found that the hsa-mir-499 variant GG and GG/AG genotypes had a significant increased risk of breast cancer, compared with the AA genotype.³¹ However, no reported studies have investigated the association between hsa-mir-499 A>G genotypes and cancer risk in Caucasian populations. In the present study, however, we observed that the hsa-mir-499 variant AG and GG/AG genotypes were associated with a significantly moderately reduced risk of SCCHN, suggesting that the hsa-mir-499 variant G genotypes may play a role in the etiology of SCCHN.

Finally, we found that the combined effect of these four polymorphisms (hsa-146a, hsa-196a, hsa-149 and hsa499) were associated with risk of SCCHN in a risk-genotype dose-response manner, particularly in subjects with 4 risk genotypes, compared with those with 0–1 risk genotype. This finding implies that combined genotypes of these pre-miRNAs may jointly have a significant effect on risk of SCCHN. Furthermore, when comparing 2–4 risk genotyoes with 0–1 risk genotypes, the risk of SCCHN was higher in never smokers than in ever smokers, indicating that the risk in non-smokers may be more genetically determined in the absence of exposure to smoking. This risk appeared to be more evident for oropharyngeal cancer than for oral cavity cancer and laryngeal/hypopharyngeal cancers. It has been shown that human papillomavirus infection plays a major role in the etiology of oropharyngeal cancer,^36,37 suggesting that these pre-microRNAs may have an interaction with oncogenic proteins. However, this hypothesis needs to be tested in future studies.

The limitations of this study also exist. Possible selection bias could not be ruled out, because this was a hospital-based case-control study, and the controls were not selected from the same population from which the cases arose. Also, our analysis was limited to non-Hispanic white subjects, so it is uncertain whether these results are generalizable to other populations. However, by matching on age, sex, and ethnicity, potential confounding factors might be minimized. To confirm the role of these polymorphisms in cancer risk requires further larger studies in different populations and other types of cancer.

In summary, in this case-control study, we found some evidence of an association of the hsa-mir-499 polymorphism with risk of SCCHN in a non-Hispanic white population. Our results also suggest that the four SNPs may have a joint effect on risk of SCCHN, especially among men, never smokers and patients with oropharyngeal cancer. However, because this is the first study concerning the combined effects of pre-miRNA polymorphisms on the risk of SCCHN, additional larger replication studies are needed to confirm these results.

Abbreviations

SNP

single nucleotide polymorphism

SCCHN

squamous cell carcinoma of the head and neck

OR

odds ratio

CI

confidence interval