Abstract

MATERIALS AND METHODS

RESULTS

Our searches retrieved a total of 7,268 unique citations. Of these, 6,887 were excluded after screening of titles and abstracts, and 381 were retrieved and reviewed in full text. We further excluded 246 papers after full-text review. The most common reasons for exclusion were case-only designs, assessment of irrelevant genes or polymorphisms, and assessment of noncancer conditions or cancers other than breast, lung, colorectal, ovarian, or endometrial. Overall, 135 articles were considered eligible for this review. Figure 1 presents the details of the search flow. A list of included studies is provided in the Web Appendix.

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Figure 1.

Search strategy and study eligibility flow in a systematic review of TP53 rs1042522 and 5 common epithelial cancers. CA, cancer; HuGENet, Human Genome Epidemiology Network; NIH GAD, National Institutes of Health Genetic Association Database.

In total, the eligible articles reported on 160 case-control substudies (some articles presented data on cases and controls sampled from different populations or reported on multiple cancers). We treated these 160 substudies as separate strata (“studies”) in our analyses because they pertained to different study bases (typically sampled from different geographical locations or belonging to different ethnicities). Overall, 68 studies investigated the association of rs1042522 with breast cancer, 42 with lung cancer, 26 with colorectal cancer, 16 with ovarian cancer, and 8 with endometrial cancer. The majority of studies reported on predominantly white (n = 96 (60%)) or East Asian (n = 35 (22%)) populations. Table 1 presents the characteristics of eligible studies stratified by the cancer type investigated, including details of the genotyping methods.

Table 1.

Characteristics of Eligible Studies in a Systematic Review of TP53 rs1042522 and 5 Common Epithelial Cancers (n = 160)

Study Characteristic	Breast Cancer (68 Studies)		Lung Cancer (42 Studies)		Colorectal Cancer (26 Studies)		Ovarian Cancer (16 Studies)		Endometrial Cancer (8 Studies)		All Studies (160 Studies)
	No.	% of Studiesa	No.	% of Studies	No.	% of Studies	No.	% of Studies	No.	% of Studies	No.	% of Studies
No. of cases	30,586		16,743		7,377		1,982		726		57,414
No. of controls	36,213		16,504		10,011		5,226		1,292		69,246
Median no. of cases (IQR)	166 (94–436)		147 (91–307)		121 (76–345)		109 (48–193)		94 (43–118)		137 (78–293)
Median no. of controls (IQR)	215 (109–486)		176 (133–379)		220 (140–347)		281 (74–446)		78 (31–310)		209 (109–423)
Ethnicity
White	45	66	16	38	16	62	13	81	6	75	96	60
East Asian	10	15	13	31	8	31	2	13	2	25	35	22
Black	1	1	2	5	0	0	1	6	0	0	4	3
Latino	1	1	3	7	1	4	0	0	0	0	5	3
Other/mixed/NR	11	16	8	19	1	4	0	0	0	0	20	13
Control selection
Healthy	61	90	24	57	19	73	15	94	6	75	125	78
Diseased	7	10	18	43	7	27	1	6	2	25	35	22
Matched controls
Yes	29	43	22	52	10	38	6	37	2	25	69	43
No/not applicable	39	57	20	48	16	62	10	63	6	75	91	57
Blinding to case-control status
Yes	7	10	9	21	3	12	2	12	0	0	21	13
No/NR	61	90	33	79	23	88	14	88	8	100	139	87
Use of genotyping qualitycontrol
Yes	26	38	17	40	11	42	9	56	2	25	65	41
No/NR	42	62	25	60	15	57	7	44	6	75	95	59
Genotyping methods
RFLP	32	47	24	57	13	50	2	12	3	38	74	46
Other methods	36	53	18	43	13	50	14	88	5	63	86	54
Hardy-Weinberg equilibrium
Compliant	53	78	36	86	24	92	13	81	7	88	133	83
In violation	15	22	6	14	2	8	3	19	1	12	27	17
Use of only tumor tissuefor genotypingb
Yes	9	13	3	7	6	23	2	12	2	25	22	14
No	59	87	39	93	20	77	14	88	6	75	138	86

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Abbreviations: IQR, interquartile range; NR, not reported; RFLP, restriction fragment length polymorphism.

^a Percentages have been rounded to the nearest integer. Percentages might not sum to 100 because of rounding.

^b In all cases, studies provided adequate data to evaluate the source of DNA for case genotyping.

All studies included in our analyses had a case-control design. Sixty-nine (43%) of the studies reported matching participants for at least 1 characteristic; age and sex (in lung and colorectal cancer studies) were the most commonly matched variables. The median number of cases was 137 (interquartile range, 78–293), and the median number of controls was 209 (interquartile range, 109–423). Studies of breast cancer were generally larger than studies of other cancers; across cancers, the number of participants increased over time (P < 0.001 for the numbers of both cases and controls).

Few studies reported that genotyping was blinded to the disease status of subjects (n = 21 (13%)). Genotyping quality control procedures were used in 65 (41%) of the studies. Twenty-two of the studies used tumor tissue as the only source of genotyping material for cases, 133 studies used nontumor sources, and 5 studies used both. Specifically, 9 studies on breast cancer, 3 on lung cancer, 6 on colorectal cancer, 2 on ovarian cancer, and 2 on endometrial cancer explicitly stated that tumor tissue was used as the source of genotyping material and did not report the use of any technique or method that suggested inclusion of an adequate amount of normal tissue (e.g., pathological examination or microdissection).

rs1042522 and cancer risk

Results of the Bayesian meta-analysis in which an informative prior (derived from the cervical cancer meta-analysis) was used suggested that, in analyses in which nontumor tissue was the source of genotyping material, the Pro allele could be associated with an increased risk of lung cancer (odds ratio (OR) = 1.09, 95% credible interval (CrI): 1.01, 1.16) but not breast (OR = 0.99, 95% CrI: 0.94, 1.03), colorectal (OR = 1.09, 95% CrI: 0.99, 1.20), ovarian (OR = 1.05, 95% CrI: 0.91, 1.19), or endometrial (OR = 1.08, 95% CrI: 0.88, 1.32) cancers (Figure 2 and Web Table 1). These results were confirmed in Bayesian meta-analyses with a noninformative prior (Web Table 2).

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Figure 2.

Summary results from a meta-analysis of the association between TP53 rs1042522 and breast, lung, colorectal, ovarian, and endometrial cancer, stratified by the source of genotyping material for cases. Estimates were derived from a Bayesian 2-level logistic regression model using an informative prior. The regression model incorporated evidence from all cancers to estimate the bias effect. Point estimates from studies using appropriate DNA sources are shown as black squares, and point estimates from studies using tumor tissue as the source of genotyping material are shown as white circles. Bars represent the 95% credible interval (CrI) for each estimate. OR, odds ratio.

DISCUSSION

TP53 rs1042522 is one of the most commonly investigated variants in cancer genetic epidemiology (13). The present systematic review suggests that this polymorphism is unlikely to be a risk factor for breast, colorectal, ovarian, or endometrial cancer and that the Pro allele at this locus might cause a small increase in the risk of lung cancer. More importantly, our work provides evidence that some of the findings of genetic association studies of this variant could have been driven by differential genotype misclassification, such as in cases where tumor tissue was used as the source of genotyping material for cancer cases. We used different analytical approaches that allowed us to borrow strength across cancers and increase the precision of the estimate of this bias effect. According to the published data on all 5 of the cancers we evaluated, use of tumor tissue appears to lead to underestimation of the genetic effect by approximately 20%. The probability that use of tumor tissue actually biases estimates of the genetic effect downward was higher than 99% when we incorporated prior evidence from a recent meta-analysis of the same polymorphism in cervical cancer and was higher than 95% in all analyses. Non-Bayesian analyses produced results very similar to those of analyses that used a noninformative prior, further indicating that the prior distributions used were “overwhelmed” by the data. That studies using cancer tissue are susceptible to bias is biologically plausible and has empirical support from studies of other cancers.

We hypothesize that the misclassification arises because of preferential LOH of the Pro allele in heterozygous individuals (16, 17, 19, 20). A substantial body of evidence, in which matched samples of peripheral blood (or other sources of genotyping material, including buccal swabs and saliva) and tumor tissue from cancer patients were used, demonstrates that LOH at the TP53 locus is nonrandom and preferentially involves the Pro allele. This phenomenon has been documented in the cancers considered in the present review as well as in other cancer types, such as cervical, urothelial, and head and neck cancer (17, 18, 20, 44–47). The biological mechanisms underlying this phenomenon are largely unknown, but it appears that the occurrence of TP53 mutations is more common on the DNA strand carrying the arginine-encoding allele (16, 48). It has been suggested that preferential retention of the Arg allele might be the result of an antiapoptotic advantage conferred by TP53 mutations.

Our findings are consistent with a large individual-patient data meta-analysis of 49 studies investigating the association between rs1042522 and cervical cancer risk (15). In that meta-analysis, studies in which the genotype of cases was determined from white blood cells produced null results; in contrast, studies in which genotype was determined from tumor tissue suggested a protective effect of the Pro allele. Our Bayesian analyses incorporated these findings in the form of an informative prior distribution and demonstrated that the bias toward a protective effect of the Pro allele operates across several cancers.

Our work suggests that use of tumor-derived DNA in genetic association studies should be avoided because it can appreciably bias the results of genetic association studies. This could be true particularly for variants in regions where LOH is known to occur, and it might present an important concern for pharmacogenetic studies where the only available source of genotyping material is often tumor tissue. When the interest is in identifying germline (i.e., nonsomatic) variants potentially associated with treatment outcomes, it might be prudent to obtain paired normal–tumor samples from at least a random sample of participants, to establish the extent of LOH as well as to gauge the effect it could have on the overall study results.

Our analyses consistently demonstrated an association between the Pro allele and a small increase in lung cancer risk. This finding is in agreement with previously published meta-analyses on this association (49, 50). However, given the small effect size we observed (OR < 1.10) and the fact that in Bayesian analyses the 95% credible interval for the lung cancer odds ratio was very close to 1, further studies could be necessary to confirm our results.

Several limitations need to be considered for interpretation of our results. Our analysis was based on published data, which prevented any statistical adjustment for individual-level factors that might modify the genetic effect, such as sex (for lung and colorectal cancer), age, or smoking. However, we note that the potential for confounding bias is limited because of the random assortment of alleles at meiosis (51). Furthermore, we could not assess gene-environment interactions because data on potential exposures of interest were unavailable from most studies. Nonetheless, it is unlikely that such factors would also influence the estimate of the bias effect. Finally, our findings should be viewed primarily as hypothesis-generating; large studies reporting on paired samples of normal tissue and tumor tissue obtained from the same patient are needed to confirm our observations. Also, it is unclear whether the phenomenon described herein occurs in other cancers or other genetic loci, but some caution could be warranted in evaluation of variants in genomic regions where little is known about the prevalence of LOH.

In conclusion, our analyses demonstrate that TP53 rs1042522 is unlikely to be associated with breast, colorectal, or endometrial cancer but that a weak association with lung cancer could exist. Across cancer types, there is compelling evidence that use of genetic material obtained from tumor tissue to genotype cases can bias the estimate of the genetic effect, leading to a 20% underestimation of the Pro allele's effect; the probability that bias is toward a protective effect for the Pro allele was at least 95% in our analyses. This finding, along with laboratory evidence indicating that LOH at the TP53 locus in many epithelial cancers is nonrandom, suggests that studies that used tumor tissue as the source of genotyping material for cases have been affected by differential genotype misclassification. In future studies, the use of tumor tissue as the primary source of genetic material should be avoided, particularly when the genetic loci of interest are known to exhibit LOH.

Supplementary Material

ACKNOWLEDGMENTS

REFERENCES