familial associations between cancer sites

Computers and Biomedical Research 32, 517–529 (1999)Article ID cbmr.1999.1525, available online at http://www.idealibrary.com on

Familial Associations between Cancer Sites

Alun Thomas,*,† Lisa Cannon-Albright,†,‡ Aruna Bansal,†,‡,1 andMark H. Skolnick*,†

*Myriad Genetics Inc., 390 Wakara Way, Salt Lake City, Utah 84108; †Genetic Epidemiology,Department of Medical Informatics, University of Utah, 391 Chipeta Way D2, Utah 84108;

and ‡IHC Genetic Research, 391 Chipeta Way C, Utah 84108

Received February 19, 1999

The Utah Population Database links together genealogical records, the Utah Cancer Registry,and Utah death certificates and allows identification of cancer clusters. Groups of individualswith cancers of some types tend to fall into related clusters within the genealogy. We examinethe apparent tendency of cases of two types of cancer to cluster together and distinguish realclusters from chance occurrences. Some established associations are found, whereas some aresurprisingly absent. Some new associations are also suggested. q 1999 Academic Press

Key Words: genealogy; cancer; kinships; association.

1. INTRODUCTION

The Utah Population Database, or UPDB, (1–4), is a unique combination ofdistinct types of data that make it possible to examine the familial nature of cancerin a large population. At the core of the UPDB is the genealogy of the Utah pioneersand their descendants. This consists of approximately one million individuals fromaround 180,000 families. To this have been linked the Utah Cancer Registry andthe Utah death certificates, although the information from death certificates is notused in this study.

We have previously analyzed the database to estimate the degree of familialcoaggregation of pairs of cancer sites using Utah Cancer Registry records from1952 to 1982 (5–10). The record linking of the 10 most recent years of cancerdata, through to 1992, has nearly doubled the available records. This provides aview of 25 years of cancer in this population, allowing identification of cancer inmore than one generation in many cases.

In our most recent analysis of the current data (11) we examined familialclustering of cancer by site and within site subdivided by age of onset, histology,and sex. Most cancer sites showed excess familiality. Subsets of individuals with

1 To whom correspondence should be addressed.

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0010-4809/99 $30.00Copyright q 1999 by Academic Press

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518 THOMAS ET AL.

certain characteristics showed unusually high levels of clustering, specificallylymphocytic leukemias and especially chronic lymphocytic leukemia, lobular breastcancer, early lip cancer, early melanoma, and female lung cancers of alveolar–adenoma histology.

In addition to the recognized familial nature of most cancers, it has also beennoted that groups of cancer types tend to coaggregate in families. Although somesuch coaggregation might be expected by chance, especially for common sites, itmight also suggest genetic susceptibilities which are responsible for multiple cancersites. Although such observations have long been made anecdotally, no systematictests of such hypotheses have been made. In this paper we extend our previousanalysis of the familiality of cancer by site to an analysis of coaggregation ofcancer between pairs of sites.

2. MATERIALS AND METHODS

2.1. The Utah Population Database

The construction of the UPDB began in 1974 and is based on group sheetssubmitted to Genealogical Society of Utah (2). Each group sheet contains informa-tion of a full sibship and their parents, including for each individual: name, placeand date of birth, place and date of death, marriage date, and name and date ofdeath of any spouses. The names of grandparents are also included.

Much of the current population of Utah consists of descendants of the pioneerswho were members of the Church of Jesus Christ of Latter Day Saints, or LDS.Most members of the LDS church abide by its proscriptions against consumptionof coffee, tea, tobacco and alcohol. There were approximately 10,000 foundingpioneers who were largely unrelated, and genetic studies of the population haveshown that it is genetically representative of a Northern European population (12).Due to a continued influx of immigrants it has normal levels of inbreeding (13).

The Utah Cancer Registry was initiated in 1958, made statewide in 1966, andincludes cancer records dating back to 1952. All cancers except basal and squamouscarcinomas of the skin must be reported to the Registry by order of the Utah StateBoard of Health. In 1973, the registry became one of 11 population-based registriesof the Surveillance Epidemiology and End Results, or SEER, program of theNational Cancer Institute. The registry maintains abstracts of clinical records andfollow-up information on all cases. In August 1992 there were 125,904 entries inthe cancer registry files representing 117,407 individuals, 41,940, or 35.7%, ofwhom were also present in the genealogical files of the UPDB, to which they havebeen linked. The rate of linked records reflects the fact that not all cancer casesare individuals who would be represented in the genealogy of the Utah pioneersand the rate of linked records is lower for females than for males because namechanges reduce the probability of successfully linking an adult woman’s record.

The records are coded by site according to the International Classification ofDiseases of Oncology (14) and contain detailed information on diagnosis, histology,treatment, and survival of patients. Definitions of cancer sites are by primary siteand histology and behavior codes as described in the International Classification

FAMILIAL ASSOCIATIONS BETWEEN CANCER SITES 519

of Diseases of Oncology (14). The lymphoma site grouping is based on histology,not primary site, and includes all lymphoma histologies regardless of primary site.All other site groups exclude lymphoma histologies. A technical report summarizingcancer groupings is available upon request (15).

Cancer rates in Utah for the years 1966 to 1990 are low compared to the U.S.Third National Cancer Survey (16). Utah males have a lifetime risk of developingcancer of approximately 20% and Utah females have a lifetime risk of approxi-mately 24%. Utah has the lowest overall cancer incidence in the SEER program.This is largely due to the much lower Utah rates for smoking-associated cancers;Utah has the lowest smoking rates of any state in national surveys. Cancer incidencecomparisons between LDS and non-LDS have been described (17).

State of the art methods for record linking have been implemented in the UPDB.Originally a probabilistic record-linking program, LNX, developed by R. Kerber,was used to link cancer registry records to the genealogy. Its linking algorithm issimilar to that pioneered by Newcombe and Kennedy (18) and implemented inthe program GIRLS (19). New records are linked using the Automatch recordlinkage software, developed and marketed by Matchware Technologies. Automatchalso uses a probabilistic record linkage scheme (20). It derives links from eachindividual’s first, middle, and last name, their birth date, and for women, theirmaiden name.

2.2. The Genealogical Index of Familiality

The Genealogical Index of Familiality, or GIF, was initially developed to measurethe degree of familial clustering in the UPDB. It is based on the Malecot coefficientof kinship (21) which quantifies the degree of relatedness between two individuals.This coefficient of kinship is defined as the probability that randomly selectedhomologous genes from two individuals are identical by descent from a commonancestor. In our previous studies (5,6,8,11), we defined the GIF within a particulargroup of n individuals to be the mean coefficient of kinship between all n(n 2 1)/2 pairs of individuals, multiplied by 100,000 for convenience. In this study wedefine the GIF between two nonintersecting groups of n and m individuals to bethe mean coefficient of kinship between all nm pairs consisting of one from thefirst group and one from the second, again multiplied by 100,000 for convenience.

Kinship calculations are based on searching for paths of common descent. Eachpath of common descent to a pair of individuals contributes an exponent of 1/2to the total kinship; the value of the exponent is equal to the number of individualsalong the path. Since we do not require a breakdown of the total kinship by pairsin this analysis, we save computational time by calculating the total kinship betweenone individual in the first group and all individuals in the second as a single paralleloperation. This has allowed us to greatly increase the number of control samplesthat we take. The method is described fully by Gholami and Thomas (22). Previousanalyses of this type based on kinship (5–9) have used approximations to thekinship coefficient based on consideration of only the closest relationship betweena pair of individuals or on paths shorter than a certain length. In this study we

520 THOMAS ET AL.

search for paths exhaustively and thus our results are based on the true kinshipcoefficients relative to the whole genealogy.

2.3. Case Groups and Control Groups

Individuals with cancer were partitioned into 24 case groups according to thesite of first diagnosis. This prevents individuals with cancer at more than one sitefrom overinfluencing the GIF. The number of cases for each site is given in Table 1.

The incompleteness of genealogical records or the lack of appropriate genealogi-cal links will result in an underestimation of the mean coefficient of kinship for

TABLE 1

Number of Cases of Cancer at Each Site

Site of first Number One-way Familialdiagnosis Mnemonic of cases GIF relative riska Significant excess (1%)

Bladder Bl 1620 2.99 1.53 My, PrBrain Bn 544 3.58 1.96 My, StBreast Br 5585 3.23 1.83 Lp, PrCervix Cx 1016 3.12 1.74 Lp, Lm, LuColon Co 3267 3.53 2.67 Sm, Lp, Rt, PrGallbladder Gb 298 3.68 2.13Kidney Kd 696 3.13 2.45 MyLeukemia Lk 1372 3.84 2.97,b 5.69c Ts, So, Lp, St, Ml, Rc, Lm, PrLip 775 4.75 2.72 Sm, Lv, Ts, My, Ov, Cx, St, Ml,

Lp Lk, Lm, Lu, Co, Br, PrLiver Lv 156 2.95 NAd LpLung Lu 2227 3.33 2.55 Lp, CxLymphoma Lm 1852 3.38 1.27,e 1.68f So, Th, My, Lp, Cx, Lk, PrMelanoma, skin Ml 1093 4.06 2.10 So, My, Lp, Lk, PrMyeloma My 582 3.96 4.34 Bn, Kd, Lp, Ml, Bl, Lm, PrOvary Ov 888 3.38 2.05 LpPancreas Pc 870 2.90 1.25Prostate 7610 3.70 2.21 Th, My, Lp, Ml, Lk, Bl, Lm,

Pr Co, BrRectum Rt 1211 3.05 1.78 So, Lk, CoSmall intestine Sm 127 4.83 NAd Th, Lp, CoSoft tissue So 289 3.72 1.92 Th, Ml, Rc, Lk, LmStomach St 972 3.17 2.09 Bn, Lp, LkTestes Ts 276 4.60 8.32 Lp, LkThyroid Th 567 4.43 8.60 Sm, So, Lm, PrUterus Ut 1844 2.90 1.32Total 35,737 2.90

a From Goldgar et al. (10).b Granulocytic.c Lyphocytic.d Data unavailable from Goldgar et al. (10).e Hodgkin’s.f Non-Hodgkin’s.


a set of individuals. It is, therefore, important to ensure that there is no inherentdifference in the standard of information between cases and controls. For a cancercase to be considered in this analysis it must first be ascertained by the UtahCancer Registry. This registry has essentially complete ascertainment (17) so thatthere should be no bias introduced simply by appearance in the registry. The cancercases considered here must also be record linked into the genealogy. This requiresa unique match of name and date of birth in the genealogy so we require that thesedata are also available on our controls.

We stratify the controls by sex, place of birth—inside or outside Utah, and dateof birth—within 16 five-year age bands, giving 64 strata in all. This is to accountfor the different linking rates and incidences for females and males, the differentinformation available for those individuals who have been in Utah longer, and theage cohort effect on both information available and incidence. Previously weconsidered restricting controls to those who do not have a death date before 1966,when the Registry became statewide, and to those with a death certificate datedafter 1966, but the differing methods were shown to have little effect on theresults (8).

We first calculated the GIF for each pair of sites. Then for each pair, we drewcontrol sets. Sampling without replacement, we drew two nonintersecting controlgroups, one for each site in the pair, and calculated the GIF between these groups.This was repeated 100 times for each pair. As a check this procedure was carriedout independently for both pair orderings. Thus, for instance, we have 100 GIFsfor lip cancer controls with liver cancer controls, and 100 GIFs for liver cancercontrols with lip cancer controls, giving in all a sample of 200 observations fromthe same distribution. As was seen previously (11) the mean GIF for controls wasstable across sites, with less variation than that noted between cancer sites. Thisis not surprising given that control groups share similar year of birth distributionsand that kinship did not vary greatly for different time periods (5).

For each pair, the case GIF can be compared with the mean of control GIFs. AGaussian approximation was used to obtain a P value as a measure of the signifi-cance of any excess of case GIF over the control GIFs. Since we are performingmultiple comparisons we use this simply as a measure of extremity and not toperform formal tests of hypotheses.

3. RESULTS

Table 1 shows the one-way GIF (11) for each cancer and gives lists of cancersfor which there is evidence of excess pairwise incidence at the 1% level. All threesites which show no excess incidence with another cancer—gallbladder, pancreas,uterus—also have a nonsignificant one-way GIF, suggesting that the majority ofcases are environmentally caused, or else caused by a gene of very low penetrance.No evidence was found of their being involved in syndromic cancer. Table 2 givesthe two-way GIFs for each pair of sites, and Table 3 gives the comparison of theseto control means, derived from a combined sample of size 200. The results arepresented graphically in Fig. 1.

Given the large number of associations being tested, one would expect some

522 THOMAS ET AL.

TABLE 2

Two-Way GIFs

Sm Lv Ts So Gb Bn Th My Kd Lp Pc

Small intestine 1.6 2.4 3.9 4.3 2.3 3.7 2.4 3.3 4.1 2.3Liver 1.6 2.1 2.9 3.1 2.3 3.3 2.6 3.4 4.0 2.4Testis 2.4 2.1 2.7 3.1 2.5 2.6 2.8 2.4 3.2 2.4Soft tissue 3.9 2.9 2.7 3.5 2.6 3.6 3.3 2.5 2.8 3.1Gallbladder 4.3 3.1 3.1 3.5 2.6 2.8 2.9 2.5 2.6 3.0Brain 2.3 2.3 2.5 2.6 2.6 2.5 3.4 2.8 3.1 2.7Thyroid 3.7 3.3 2.6 3.6 2.8 2.5 2.8 2.6 2.7 2.9Myeloma 2.4 2.6 2.8 3.3 2.9 3.4 2.8 3.3 3.4 2.8Kidney 3.3 3.4 2.4 2.5 2.5 2.8 2.6 3.3 2.8 3.0Lip 4.1 4.0 3.2 2.8 2.6 3.1 2.7 3.4 2.8 3.2Pancreas 2.3 2.4 2.4 3.1 3.0 2.7 2.9 2.8 3.0 3.2Ovary 2.9 2.5 2.7 3.2 2.4 2.7 2.4 3.1 2.5 3.4 3.1Cervix 3.3 2.7 2.7 2.3 2.9 2.5 2.7 2.9 3.0 3.3 2.9Stomach 3.3 2.4 2.7 2.8 2.4 3.2 2.6 2.8 2.7 3.2 2.8Melanoma 3.3 2.9 3.2 3.4 3.1 2.8 2.9 3.3 3.0 3.2 2.8Rectum 3.7 3.1 2.7 3.6 2.4 2.8 2.8 2.9 2.9 3.0 2.7Leukemia 2.9 2.8 3.2 3.7 2.9 2.7 3.0 3.0 2.8 3.2 2.8Bladder 2.7 3.0 2.9 2.7 2.5 2.8 2.7 3.2 2.7 2.9 2.9Uterus 3.1 2.8 2.8 3.2 3.0 2.8 2.5 3.0 2.6 3.0 2.7Lymphoma 3.3 2.8 3.0 3.2 2.8 2.7 3.1 3.2 2.7 3.2 3.0Lung 2.9 2.6 2.5 2.8 2.7 2.7 2.5 2.9 2.9 3.1 2.5Colon 3.5 2.5 2.5 3.1 2.7 2.7 2.7 2.9 2.8 3.1 2.8Breast 3.2 2.7 2.7 2.9 3.1 2.6 2.9 3.0 2.9 3.1 2.8Prostate 3.3 3.2 2.7 3.0 3.1 2.8 3.0 3.3 2.9 3.2 3.0

proportion of them to have arisen by chance. We have made 23 3 22 5 506comparisons, which would be expected to yield 25.3 false positives at the 5%level, 5.06 at the 1% level, and 0.5 at the 0.1% level. In reality, 85, 44, and 22significant associations were found for the three levels of significance respectively,suggesting that most of those detected are true positives.

4. DISCUSSION

The genetic study of rare families in which a variety of cancers occur hasincreased understanding of the process of carcinogenesis, and given clues to thehistogenesis of sporadic cancers. A consistent feature of familial cancer syndromesis variable expression between and within families, so a gene currently associatedwith site-specific cancer may only have been explored in relation to one end ofits spectrum of phenotype. Of course it may be unclear which of the clustersobserved are genetic in origin, and which are the result of other aspects of theshared family environment. Smoking is known to be familial, and is known to bea risk factor for many cancers. Similarly alcohol consumption, also familial, appearsto act synergistically in the pathogenesis of many epithelial cancers. Chronic alcohol


TABLE 2

Two-Way GIFs—Continued

Ov Cx St Ml Rt Lk Bl Ut Lm Lu Co Br Pr

2.9 3.3 3.3 3.3 3.7 2.9 2.7 3.1 3.3 2.9 3.5 3.2 3.32.5 2.7 2.4 2.9 3.1 2.8 3.0 2.8 2.8 2.6 2.5 2.7 3.22.7 2.7 2.7 3.2 2.7 3.2 2.9 2.8 3.0 2.5 2.5 2.7 2.83.2 2.3 2.8 3.4 3.6 3.7 2.7 3.2 3.2 2.8 3.1 2.9 3.12.4 2.9 2.4 3.1 2.4 2.9 2.5 3.0 2.8 2.7 2.7 3.1 3.22.7 2.5 3.2 2.8 2.8 2.7 2.8 2.8 2.7 2.7 2.7 2.6 2.92.4 2.7 2.6 2.9 2.8 3.0 2.7 2.5 3.1 2.5 2.7 2.9 3.13.1 2.9 2.8 3.3 2.9 3.0 3.2 3.0 3.2 2.9 2.9 3.0 3.32.5 3.0 2.7 3.0 2.9 2.8 2.7 2.6 2.7 2.9 2.8 2.9 2.93.4 3.3 3.2 3.2 3.0 3.2 2.9 3.0 3.2 3.1 3.1 3.1 3.23.1 2.9 2.8 2.8 2.7 2.8 2.9 2.7 3.0 2.5 2.8 2.8 3.0

2.8 2.7 2.9 2.6 2.7 2.7 2.9 2.7 2.6 2.6 2.8 2.92.8 2.6 2.9 2.8 2.8 2.6 2.6 2.9 3.0 2.7 2.7 2.82.7 2.6 2.9 2.8 3.2 2.7 2.5 2.9 2.8 2.9 2.7 2.92.9 2.9 2.9 2.9 3.2 2.8 2.7 2.9 2.8 2.9 2.7 3.02.6 2.8 2.8 2.9 3.0 2.7 2.8 2.7 2.8 3.3 2.8 2.92.7 2.8 3.2 3.2 3.0 2.9 2.9 3.2 2.7 2.9 2.9 3.12.7 2.6 2.7 2.8 2.7 2.9 2.7 2.8 2.7 2.7 2.7 3.02.9 2.6 2.5 2.7 2.8 2.9 2.7 2.8 2.5 2.7 2.7 2.92.7 2.9 2.9 2.9 2.7 3.2 2.8 2.8 2.8 2.9 2.8 3.12.6 3.0 2.8 2.8 2.8 2.7 2.7 2.5 2.8 2.7 2.7 2.82.6 2.7 2.9 2.9 3.3 2.9 2.7 2.7 2.9 2.7 2.8 3.02.8 2.7 2.7 2.7 2.8 2.9 2.7 2.7 2.8 2.7 2.8 3.02.9 2.8 2.9 3.0 2.9 3.0 3.0 2.9 3.0 2.8 2.9 3.0

abuse is also an important risk factor for carcinoma of the liver parenchyma, andprimary hepatocellular carcinoma occurs more commonly in patients with cirrhosis.

Nonetheless, anecdotal evidence of clustering of various cancer types in largepedigrees has led to the identification of syndromes. One such example is HNPCC(23) which is characterized primarily by cancers of the colon and endometrium.HNPCC may be a factor in the associations we see between colon, small intestine,and lip cancers. Lip cancer shows excess familiality in the presence of 14 othercancers, with highest GIF values in relation to cancers of the liver and of the smallintestine which had the highest single site GIF. This is a case where sharedenvironmental risk factors almost certainly also play a role. Frisch and Melbye(24) hypothesize that the general effect of smoking might act on all human squamousepithelia. Occupational factors may also be important. It has been reported (25)that exposure to asbestos is a risk factor for cancer of both the small intestine andlip cancer. Although rare in the UPDB, “Cancer in Utah 1966–1990” (26) showedthat lip cancer has more than threefold incidence in Utah compared to the UnitedStates as a whole. The site-specific age-adjusted incidence ratio was 4.00 forfemales, and 3.00 for males at this site. Because smoking rates are low in Utah,

524 THOMAS ET AL.

TABLE 3

Case GIF Minus Mean Control GIF (3100)

Sm Lv Ts So Gb Bn Th My Kd Lp Pc

Small intestine 2117 229 113 *139 240 8105 239 52 8130 244Liver 2117 252 23 42 244 60 218 *70 8130 235Testis 229 252 8 57 28 0 17 219 858 219Soft tissue 113 23 8 *86 211 ●101 *61 219 9 31Gallbladder *139 42 57 *86 211 25 14 219 215 30Brain 240 244 28 211 211 211 869 10 31 6Thyroid 8105 60 0 ●101 25 211 12 25 1 27Myeloma 239 218 17 *61 14 869 12 859 859 6Kidney 52 *70 219 219 219 10 25 859 6 27Lip 8130 ●130 858 9 215 31 1 859 6 *41Pancreas 244 235 219 31 30 6 27 6 27 *41Ovary 10 223 10 *51 233 4 226 28 224 ●67 *34Cervix *66 3 14 237 23 218 5 19 *35 ●65 22Stomach 59 236 13 15 229 857 23 4 0 848 13Melanoma 53 28 *59 871 *46 14 *30 ●58 831 ●55 11Rectum *86 37 11 ●93 237 14 19 16 16 23 28Leukemia 19 16 861 ●104 16 21 *34 25 14 848 11Bladder 213 28 35 26 225 8 4 845 25 17 13Uterus 26 0 23 *47 26 7 218 20 28 18 22Lymphoma 54 12 *39 851 8 21 840 847 23 843 *27Lung 10 214 26 8 24 26 211 10 19 830 226Colon 875 222 28 *37 21 22 5 13 8 ●37 1Breast *44 2 11 17 *33 26 *24 *21 *20 ●38 0Prostate *50 *44 17 *33 *35 14 ●38 ●51 *18 ●40 *22

Note. A * indicates an excess significant at 5%, a 8 at 1%, and a ● at 0.1%.

it is likely that sunshine exposure, especially in rural areas, may be the moreimportant factor.

Other genes have been linked to pairs or groups of cancers. Marsh et al. (27)report on the effects of the tumor suppressor PTEN, which maps to 10q23 andwas shown recently to play a broad role in human malignancy (28). Somaticmutations have been found in sporadic breast, brain, prostate, and kidney cancercell lines and in several primary tumors such as endometrial carcinomas, malignantmelanoma, and thyroid tumors. Of these we observed strong links only betweenprostate and each of thyroid, breast, and melanoma.

Similarly, another gene, MTS1, which encodes the inhibitor, p16, of cyclin-dependent kinase 4, has been found to be mutated in cell lines derived from tumorsof the lung, brain, bone, skin, bladder, kidney, ovary, and lymphocyte (29), as wellas in more than half of all melanoma lines (30). We found coaggregation ofmelanoma cases with connective tissue, prostate, lip, myeloma, and moststrongly leukemia.

The gene BRCA1 on chromosome 17q has been shown to predispose to breastand ovarian cancer (31–33). Ford et al. (34) also found significant excesses of


TABLE 3

Case GIF Minus Mean Control GIF (3100)—Continued

Ov Cx St Ml Rt Lk Bl Ut Lm Lu Co Br Pr

10 *66 59 53 *86 19 213 26 54 10 875 *44 *50223 3 236 28 37 16 28 0 12 214 222 2 *44

10 14 13 *59 11 861 35 23 *39 26 28 11 17*51 237 15 871 ●93 ●104 26 *47 851 8 *37 17 *33

233 23 229 *46 237 16 225 26 8 24 21 *33 *354 218 857 14 14 21 8 7 21 26 22 26 14

226 5 23 *30 19 *34 4 218 840 211 5 *24 ●3828 19 4 ●58 16 25 845 20 847 10 213 *21 ●51

224 *35 0 *31 16 14 25 28 23 19 8 *20 *18●67 ●65 848 •55 23 848 17 18 843 830 ●37 ●38 ●40*34 22 13 11 28 11 13 22 *27 226 1 0 *22

9 2 24 29 4 25 14 2 215 28 4 *159 0 *23 10 16 27 214 830 833 2 22 112 0 *30 11 849 27 227 18 9 15 2 12

24 *23 *30 *25 ●55 13 26 *21 9 *21 6 ●3129 10 11 *25 831 0 6 2 2 ●53 5 14

4 16 ●49 ●55 831 *22 14 ●50 25 *21 *16 ●3325 27 27 13 0 *22 26 13 25 1 0 82014 214 227 26 6 14 26 5 223 24 21 102 830 18 *21 2 ●50 13 5 4 *16 *12 ●32

215 833 9 9 2 25 25 223 4 22 27 2128 2 15 *21 ●53 *21 1 24 *16 22 2 ●17

4 22 2 6 5 *16 0 21 *12 27 2 ●24*15 11 12 ●31 14 ●33 820 10 ●32 21 ●17 ●24

Note. A * indicates an excess significant at 5%, a 8 at 1%, and a ● at 0.1%.

cancers of the prostate and of the colon among carriers in their set. It has been shown(35,36) that a large proportion of remaining familial breast cancer is attributable toBRCA2 on 13q12. Easton et al. (37) reported that carriers of mutations in thisgene exhibited significant excess risk of ovarian cancer (RR 5 17.69), laryngealcancer (RR 5 7.67), and prostate cancer (RR 5 2.89). We detected only thebreast–prostate link. Current knowledge concerning the risks associated withBRCA1 and BRCA2 would suggest that cancers of the breast and ovary shouldhave a significantly high pairwise GIF. In fact, the observed GIF of 2.77 liesapproximately in the middle of the range when either of these cancers is comparedwith the remaining 22. Breast cancer is most highly associated with cancer of thesmall intestine (GIF 5 3.22), and ovarian cancer is most highly associated withcancer of the lip (GIF 5 3.40). Breast cancer and to a lesser extent ovarian cancerare common and have been associated with a number of environmental and lifestylefeatures. It is likely that the commonness of sporadic breast and ovarian cancersand the rarity of BRCA1 and BRCA2 mutations are primary reasons why theassociation between these two diseases is difficult to detect by the GIF approach.The Goldgar et al. (10) study of data from the UPDB also failed to find increased

526 THOMAS ET AL.

FIG. 1. Dashed lines join sites for which the case GIF is significantly (1%) greater than the meanof the control GIFs. Solid lines join sites for which the case GIF is significantly (1%) greater than0.1 1 the control mean. Bold lines join sites for which the case GIF is significantly (1%) greaterthan 0.2 1 the control mean.

frequency of breast cancer among ovarian cancer probands or an increased fre-quency of ovarian cancer among breast cancer probands.

Certain breast cancer families have been also reported to show excesses of softtissue sarcomas, leukemia, and brain tumors (38,39); others show excesses ofovarian cancer (40) or gastrointestinal cancers (41). The sources of many of theseassociations have now been characterized as being due to rare dominantly inheritedsusceptibility genes whose effect would be masked in a large population-basedstudy such as this one. The associations we see here encompass the effects ofmutations in specific, possibly more common, genes, and their interaction withenvironmental risk factors which are shared among family members, such as diet,exposure to sunshine and smoking.

A somewhat unexpected result is that prostate cancer, like lip cancer, associateswith a large number, 9, of other sites. This contrasts with the results of Isaacset al. (42) who concluded that prostate cancer is a relatively site-specific disease,not part of other hereditary cancer syndromes. In keeping with our results, theyfound a statistically significant higher risk for tumors of the CNS in families withhereditary prostate cancer (RR 5 3.2), but in contrast, they failed to find signifi-cantly increased risk of cancer of the breast.

Our results indicate that the majority of cancers coaggregate with cancer of atleast one other site, and this effect may be attributable in part to mutations which


promote non-site-specific tumorigenesis and whose ultimate action may be deter-mined by the nature of whatever combination of environmental triggers the carrieris exposed to. Case–control and linkage studies are needed to determine the natureof the common predisposing factor, whether it is solely genetic, solely environmen-tal, or the result of a possibly complex interplay of both genetic and environmen-tal factors.

ACKNOWLEDGMENTS

This work was supported by the Utah Cancer Registry, which is funded by National Cancer InstituteContract N01-CN-6700, and National Institute of Health Grant R01 CA-64477, with additional supportfrom the Utah Department of Health and the University of Utah.

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