00421244284Int J CancerInt. J. CancerInternational journal of cancer0020-71361097-021527194394509481010.1002/ijc.30197NIHMS825269ArticleRisk of extracolonic cancers for people with biallelic and monoallelic mutations in MUTYHWinAung Ko1*ReeceJeanette C.1DowtyJames G.1BuchananDaniel D.12ClendenningMark2RostyChristophe23SoutheyMelissa C.4YoungJoanne P.567ClearySean P.8KimHyeja8CotterchioMichelle9MacraeFinlay A.101112TuckerKatherine M.13BaronJohn A.14BurnettTerrilea15Le MarchandLoïc15CaseyGraham16HaileRobert W.17NewcombPolly A.1819ThibodeauStephen N.20HopperJohn L.121GallingerSteven6WinshipIngrid M.1011LindorNoralane M.22JenkinsMark A.1Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Victoria, Australia.
Colorectal Oncogenomics Group, Genetic Epidemiology Laboratory, Department of Pathology, The University of Melbourne, Parkville, Victoria, Australia.
School of Medicine, University of Queensland, Herston, Queensland, Australia.
Genetic Epidemiology Laboratory, Department of Pathology, The University of Melbourne, Parkville, Victoria, Australia.
Departments of Haematology and Oncology, The Queen Elizabeth Hospital, Woodville, South Australia, Australia.
SAHMRI Colorectal Node, Basil Hetzel Institute for Translational Research, Woodville, South Australia, Australia.
School of Medicine, University of Adelaide, South Australia, Australia.
Lunenfeld Tanenbaum Research Institute, Mount Sinai Hospital, University of Toronto, Toronto, Ontario, Canada.
Prevention and Cancer Control, Cancer Care Ontario, Toronto, Ontario, Canada.
Genetic Medicine and Family Cancer Clinic, Royal Melbourne Hospital, Parkville, Australia.
Department of Medicine, The University of Melbourne, Parkville, Victoria, Australia.
Colorectal Medicine and Genetics, Royal Melbourne Hospital, Parkville, Victoria, Australia.
Hereditary Cancer Clinic, Prince of Wales Hospital, Randwick, New South Wales, Australia
Department of Medicine, University of North Carolina, Chapel Hill, North Carolina, USA.
University of Hawaii Cancer Center, Honolulu, Hawaii, USA.
Department of Preventive Medicine, Keck School of Medicine and Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, California, USA.
Department of Medicine, Division of Oncology, Stanford University, California, USA.
School of Public Health, University of Washington, Seattle, Washington, USA.
Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA.
Molecular Genetics Laboratory, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota, USA.
Department of Epidemiology and Institute of Health and Environment, School of Public Health, Seoul National University, Seoul, Korea.
Department of Health Science Research, Mayo Clinic Arizona, Scottsdale, Arizona, USA.
Corresponding author, Aung Ko Win, PhD, Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, Level 3, 207 Bouverie Street, The University of Melbourne VIC 3010 Australia, Phone: +61 3 9035 8238, Fax: +61 3 9349 5815, awin@unimelb.edu.au271020160262016110201601102017139715571563
Germline mutations in the DNA base excision repair gene MUTYH are known to increase a carrier’s risk of colorectal cancer. However, the risks of other (extracolonic) cancers for MUTYH mutation carriers are not well defined. We identified 266 probands (91% Caucasians) with a MUTYH mutation (41 biallelic and 225 monoallelic) from the Colon Cancer Family Registry. Mutation status, sex, age, and histories of cancer from their 1,903 first- and 3,255 second-degree relatives, were analysed using modified segregation analysis conditioned on the ascertainment criteria. Compared with incidences for the general population, hazard ratios (HRs) (95% confidence intervals [CIs]) for biallelic MUTYH mutation carriers were: urinary bladder cancer, 19(3.7–97); and ovarian cancer, 17(2.4–115). The HRs (95%CI) for monoallelic MUTYH mutation carriers were: gastric cancer, 9.3(6.7–13); hepatobiliary cancer, 4.5(2.7–7.5); endometrial cancer, 2.1(1.1–3.9); and breast cancer, 1.4(1.0–2.0). There was no evidence for an increased risk of cancers at the other sites examined (brain, pancreas, kidney or prostate). Based on the USA population incidences, the estimated cumulative risks (95%CI) to age 70 years for biallelic mutation carriers were: bladder cancer, 25%(5%–77%) for males and 8%(2%–33%) for females; and ovarian cancer, 14%(2%–65%). The cumulative risks (95%CI) for monoallelic mutation carriers were: gastric cancer, 5%(4%–7%) for males and 2.3%(1.7%–3.3%) for females; hepatobiliary cancer, 3%(2%–5%) for males and 1.4%(0.8%–2.3%) for females; endometrial cancer, 3%(2%–6%); and breast cancer 11%(8%–16%). These unbiased estimates of both relative and absolute risks of extracolonic cancers for people, mostly Caucasians, with MUTYH mutations will be important for their clinical management.
Germline mutations in the base excision repair gene, MUTYH (MIM# 604933), cause increased risks of colorectal adenomas and carcinomas,1 presumably due to an increase in unrepaired, 8-oxoG-induced somatic G:C to T:A transversions in tumour suppressor genes.2
Biallelic (compound heterozygous or homozygous) MUTYH mutations i.e., inherited from both parents, occurring in 0.01–0.04% of the Caucasian population, are associated with a 18- to 100-fold increased risk of colorectal adenomas and cancer compared with the general population3-6; commonly known as MUTYH-associated polyposis (MAP) (OMIM #608456).1, 7 The risks of extracolonic cancers for biallelic mutation carriers, however, are not well defined.8-16 Several studies have reported an increased risk of duodenal cancer for biallelic mutation carriers.7, 12, 17, 18 Some studies have also reported an increased risk of bladder, ovarian, skin,12 breast,12, 19 and endometrial10, 13 cancer for biallelic mutation carriers; while others studies failed to confirm associations with breast11, 16, 20 or endometrial12, 21 cancer. Case reports of cancers of the sebaceous glands,9, 10, 22 hair follicles,23 stomach,18 and thyroid9, 10, 12, 15, 18 in biallelic mutation carriers have been documented but these studies did not determine whether the incidence of these cancers exceeded the expected population risk.
Monoallelic (heterozygous) MUTYH mutations, i.e., inherited from only one parent, occurring in 1–2% of the Caucasian population,24 are associated with a moderately increased risk of colorectal cancer.3, 5, 6, 25 Previous studies have reported an increased risk of gastric, liver, and endometrial,26 and breast cancer27-29 for monoallelic mutation carriers while other studies did not find statistical evidence for an increased risk of breast11, 20 or liver30 cancer.
Given the rarity of biallelic and monoallelic MUTYH mutation carriers, most of the previous studies have been underpowered to provide reliable estimates for the risks of extracolonic cancers. Clarity on these cancer risks is important for the clinical management of MUTYH mutation carriers. In the current study, using a large dataset from the Colon Cancer Family Registry we estimated extracolonic cancer risks for people with biallelic and monoallelic MUTYH mutations.
MATERIALS AND METHODSStudy Sample
The study sample was from the Colon Cancer Family Registry that has been described in detail elsewhere31 and at www.coloncfr.org. Between 1997 and 2012, the Colon Cancer Family Registry recruited families via: population-based probands who were recently diagnosed colorectal cancer cases from state or regional population cancer registries in the USA (Washington, California, Arizona, Minnesota, Colorado, New Hampshire, North Carolina, and Hawaii), Australia (Victoria) and Canada (Ontario); and clinic-based probands who were enrolled from multiple-case families referred to family cancer clinics in the USA (Mayo Clinic, Rochester, Minnesota, and Cleveland Clinic, Cleveland, Ohio), Canada (Ontario), Australia (Melbourne, Adelaide, Perth, Brisbane, Sydney) and New Zealand (Auckland). Probands were asked for permission to contact their relatives to seek their enrolment in the Cancer Family Registry. For population-based families, first-degree relatives of probands were recruited and recruitment was extended to more distant relatives by some registries. For clinic-based families, recruitment was based on availability but attempts were made to recruit up to second-degree relatives of affected individuals (detailed in Newcomb et al.31). Informed consent was obtained from all study participants, and the study protocol was approved by the institutional research ethics review board at each registry.
Data Collection
Information on demographics, personal characteristics, personal and family history of cancer, cancer-screening history, history of polyps, polypectomy, and other surgeries was obtained by questionnaires from all probands and participating relatives. Participants were followed approximately every 5 years after baseline to update this information. For the present study, each individual’s lifetime cancer history was based on the most recent data (baseline or most recent follow-up). Reported cancer diagnoses and age at diagnosis were confirmed using pathology reports, medical records, cancer registry reports, and death certificates, where possible. We collected family history of cancer from all participants, thus may obtain multiple reports on a single individual. If so and reports conflict or vary, we used the specific protocol of algorithms for selecting reports of cancer. For example, in Australia reports of cancer were selected over reports of no cancer, detailed dates of death/birth are selected over estimates, and relative sources were selected as follows (in the hierarchy): self-report; the spouse or partner; a parent or adult son/daughter; brother or sister; grandparent or grandchild; aunt, uncle, nephew or niece; cousin; other. The tumour anatomic location and histology were coded and stored using the International Classification of Diseases for Oncology (ICD-O).32 We attempted to obtain blood samples from all participants and tumour tissue samples from participants affected with colorectal cancer.
<italic>MUTYH</italic> mutation testing
As previously described by Cleary et al.,3 genomic DNA extracted from each proband was tested for 12 previously identified MUTYH variants: c.536A>G p.(Tyr179Cys), c.1187G>A p.(Gly396Asp), c.312C>A p.(Tyr104Ter), c.821G>A p.(Arg274Gln), c.1438G>T p.(Glu480Ter), c.1171C>T p.(Gln391Ter), c.1147delC p.(Ala385ProfsTer23), c.933+3A>C p.(Gly264TrpfsX7), c.1437_1439delGGA p.(Glu480del), c.721C>T, p.(Arg241Trp), c.1227_1228dup p.(Glu410GlyfsX43), and c.1187-2A>G p.(Leu397CysfsX89) using the MassArray MALDI-TOF Mass Spectrometry (MS) system (Sequenom, San Diego, CA). To confirm the MUTYH mutation and identify additional mutations, screening of the entire MUTYH coding region, promoter, and splice site regions was performed on all samples exhibiting MS mobility shifts using denaturing high-performance liquid chromatography (Transgenomic Wave 3500HT System; Transgenomic, Omaha, NE). All MS-detected variants and WAVE mobility shifts were submitted for sequencing for mutation confirmation (ABI PRISM 3130XL Genetic Analyser). That is, if a heterozygous MUTYH mutation was identified, then the MUTYH gene was screened for any additional mutations not captured by the Sequenom genotyping screen to ensure all potential compound heterozygous carriers were identified. The relatives of probands with a pathogenic MUTYH germline mutation underwent testing for the specific variant identified in the proband.
Statistical Analysis
The median, range, mean, and standard deviation of the ages at cancer diagnoses were calculated using Stata 13.0 (StataCorp, College Station, TX, 2013). Hazard ratios (HRs), i.e. the age-, sex- and country-specific cancer incidence for carriers divided by that for the general population, were estimated for each cancer site. Age- and sex-specific cancer incidences in 1988–1992 for each country (the USA, Canada and Australia) were obtained from Cancer Incidence in Five Continents.33 The period of 1988–1992 was selected for analysis because it was the closest available dataset to the mean calendar year of cancer diagnoses in the sample. We used a modified segregation analysis,34, 35 (as described in detail in the Appendix of Dowty et al.36). This analytical method is not subject to population stratification, can be rigorously adjusted for ascertainment and uses data on all study participants, whether genotyped or not, thereby maximising statistical power. Models were fitted by the method of maximum likelihood with the statistical package MENDEL 3.2.37
For each cancer site, the age at cancer diagnosis was modelled as a random variable whose hazard was the relevant population incidence rate multiplied by a site-specific HR. Observation time for each individual started at birth and ended at first diagnosis of any cancer, last follow-up or death, whichever occurred first. Where age at diagnosis of a cancer was not reported (22% of all cancer cases), we assumed the age of diagnosis to be the median age at that cancer diagnosis for the general population obtained from SEER Cancer Statistics Review (1975–2008).38
Estimates were appropriately adjusted for the clinic- and population-based ascertainment of families using a combination of retrospective likelihood and ascertainment-corrected joint likelihood,35, 39, 40 in which each pedigree’s data was conditioned on the proband’s genotype, cancer status and age of onset (for population-based families) or on the proband’s genotype and the affected statuses and ages of onset of all family members at the time of ascertainment, i.e. when the proband was found to be a MUTYH mutation carrier (for clinic-based families). Our estimates are therefore the parameter values which maximize the conditional likelihood of the observed data conditioned on the relevant ascertainment criteria. Our estimates are unaffected by the selective ascertainment of families into our study.
Estimated cumulative risks (penetrance) of cancers to age 70 years and corresponding 95% CIs for MUTYH mutation carriers were calculated for each sex from the HR estimates and the age- and sex-specific USA population incidences incidencei at age i using the formula:
1−e−∑i=o70HR⋅incidencei
The total number of carriers was estimated by summing MUTYH carrier probabilities for all individuals, as calculated from Mendel’s laws of inheritance, the known genetic relationship of each individual to his or her genotyped relatives and a population allele frequency of 0.0085 (but not any affected statuses).26 These calculations were performed using R 2.15.041 and a modified version of Mendel 3.2.37
RESULTS
We identified 276 probands who were known to carry germline mutations in the MUTYH gene from the Colon Cancer Family Registry. We excluded 10 probands who were also known to carry a pathogenic germline mutation in a DNA mismatch repair gene (Lynch syndrome).42 Of the remaining 266 probands, 41 (15%) were biallelic MUTYH mutation carriers and 225 (85%) were monoallelic MUTYH mutation carriers. Of these, 91% (n = 241) were Caucasians and 9% (n = 25) were others (9 African Americans, 5 Latinos, 2 Native Americans, 1 Portuguese and 8 unknown). 237 (89%) probands were ascertained via population-based resources (Figure 1). There were 140 (53%) families recruited from the USA, 81 (30%) from Canada, and 45 (17%) from Australia and New Zealand. The MUTYH variants of the probands are shown in Supplementary Table 1. Of the 12 MUTYH variants examined, 73% of biallelic MUTYH mutations were compound heterozygous or homozygous p.(Tyr179Cys) or p.(Gly396Asp) mutations. Similarly, 92% of monoallelic MUTYH mutations were either p.(Tyr179Cys) or p.(Gly396Asp).
We obtained data on a total of 1,903 (929 female) first-degree relatives and 3,255 (1,623 female) second-degree relatives of the 266 probands. MUTYH mutation status was tested for 290 relatives (13 were found to be biallelic mutation carriers, 138 were monoallelic mutation carriers, and 139 were non-carriers). We estimated that there were additional 40 biallelic and 1,874 monoallelic mutation carriers among non-genotyped relatives, giving a total estimated number of 53 biallelic and 2,012 monoallelic mutation-carrying relatives in our study sample.
Table 1 shows the numbers and mean ages of diagnoses of cancers at various sites in the affected first- and second-degree relatives (combined) of the probands. Of these cancer diagnoses in the relatives, 17% were verified by pathology report, medical clinical records, cancer registry reports and/or death certificates (Supplementary Table 2).
Biallelic MUTYH mutation carriers had urinary bladder cancer incidence 19 (95% CI, 3.7–97) times and ovarian cancer incidence 17 (95% CI, 2.4–115) times higher than the general population. Monoallelic MUTYH mutation carriers had gastric cancer incidence 9.3 (95% CI, 6.7–13) times and hepatobiliary cancer incidence 4.5 (95% CI, 2.7–7.5) times higher than the general population. Monoallelic MUTYH mutation carriers also had a slightly higher incidence of endometrial cancer (HR, 2.1; 95% CI, 1.1–3.9) and breast cancer (HR, 1.4; 95% CI, 1.0–2.0). We did not find evidence for an increased risk of cancers at the other sites that we were able to estimate HRs (kidney, pancreas, brain and prostate) (Table 2). For cancers at some sites (e.g., small bowel, thyroid, ureter), we were not able to estimate reliable HRs. A sensitivity analysis excluding all relatives with missing age at cancer diagnosis showed results similar to those of the main analysis (details not shown).
The estimated cumulative risks to age 70 years of specific cancer sites for carriers from the USA are provided in Table 2. It is estimated that 25% (95% CI, 5%–77%) and 8% (95% CI, 2%–33%) of male and female biallelic MUTYH mutation carriers, respectively, will be diagnosed with urinary bladder cancer by the age of 70 years, whereas 14% (95% CI, 2%–65%) will be diagnosed with ovarian cancer. For monoallelic MUTYH mutation carriers, 5% (95% CI, 4%–7%) and 2.3% (95% CI, 1.7%–3.3%) of males and females, respectively, will be diagnosed with gastric cancer while 3% (95% CI, 2%–5%) and 1.4% (95% CI, 0.8%–2.3%), respectively, will be diagnosed with hepatobiliary cancer. Of female monoallelic MUTYH mutation carriers, 3% (95% CI, 2%–6%) will develop endometrial cancer and 11% (95% CI, 8%–16%) will develop breast cancer (Table 2). The corresponding cumulative risks for carriers living in Canada and Australia are given in Supplementary Table 3.
DISCUSSION
We have estimated the risk of extracolonic cancers for biallelic and monoallelic MUTYH mutation carriers, mostly Caucasians, using one of the world’s largest resources of these carriers.
We estimated that biallelic MUTYH mutation carriers had a 19-fold increased risk of urinary bladder cancer and a 17-fold increased risk of ovarian cancer, compared with the general population. This is consistent with a previous study by Vogt et al.12, which found an increased risk of urinary bladder cancer (standardized incidence ratio [SIR], 7.2; 95% CI, 2.0–18.4) and ovarian cancer (SIR, 5.7; 95% CI, 1.2–16.7). These estimates are not statistically different from our estimates (p=0.34 and p=0.37, respectively, based on the method proposed by Altman and Bland43). Cancer screening guidelines for carriers of biallelic mutations in MUTYH currently only address cancer of the colon and upper gastrointestinal tracts.44-46 Although our study confirms the previous report of Vogt et al.12 of increased risks of bladder and ovarian cancers for biallelic mutation carriers, it may be too early to advise clinicians to consider implementing early detection at these sites given the wide confidence intervals around our estimates as well as the lack of evidence for the efficacy of screening methods for these cancers.47, 48 Further, our study was unable to examine previous suggestions that biallelic mutations in MUTYH increase the susceptibility to duodenal,7, 12, 17, 18 breast,12, 19 endometrial,10, 13 and gastric18 cancer, possibly because of the small numbers of cases of these cancers in our study sample.
For monoallelic MUTYH mutation carriers, we found an increased risk of gastric and liver cancers, as well as a slightly increased risk of endometrial and breast cancers. In the current analysis, we observed only a slightly elevated risk of breast cancer, consistent with previous reports.27-29 For example, in a population-based case-control study of Jewish descendants of North African origin, Rennert et al. reported an elevated risk of breast cancer for carriers of a MUTYH p.(Gly396Asp) variant (odds ratio [OR] = 1.86, 95% CI 1.02–3.39).28 In a Chinese case-control study, Zu et al. reported an association between AluYb8 insertion in MUTYH and a modest increased risk of breast cancer (OR = 1.26, 95% CI 1.01–1.56) although we did not test for this variant in our study.29 Wasielewski et al. also reported a higher frequency of monoallelic MUTYH mutations in families with both breast and colorectal cancer compared with the population (4.1% vs. 1.9%).27 Other studies failure to find evidence for an increased risk of breast cancer for monoallelic mutation carriers may be due to the lack of power given the modest increase in the risk of breast cancer and the small sample sizes.11, 20
The wide confidence intervals for some cancer risks observed in the present study are due to limited sample size and/or variability in risk due to genetic heterogeneity or the influence of environmental risk factors. This is especially seen in our estimates for urinary bladder and ovarian cancer risks for biallelic mutation carriers. In a previous study, we have shown a substantial variation in colorectal cancer risks using a polygenic model that mimics the effect of a large number of cancer-susceptibility loci, in additional to the MUTYH mutation effect.6 To our knowledge, thus far the only study conducted to investigate environmental modifiers of colorectal cancer risk for MUTYH mutation carriers was on the relationship with hormone replacement therapy,5 which reported no evidence of interaction between hormone replacement therapy and MUTYH mutations.
The strengths of the study are the relatively large sample size (although the numbers of the biallelic mutation carriers were small), established registry with up to 15 years of follow-up, and its multinational populations (increasing generalizability). This study avoided potential survival bias as deceased cases were represented using methods that estimated carrier probabilities based on the genetic relationship of the deceased and untested individuals to their confirmed carrier and non-carrier relatives. Furthermore, ascertainment bias (due to inclusion of relatives’ cancers that resulted in ascertainment of the family) was avoided in this study as estimates were appropriately adjusted for the clinic- and population-based ascertainment of families.
A potential limitation of our study is that self-reported unverified cancer cases in the relatives (83%) may affect the accuracy of estimates. However, the majority of our families were recruited from population cancer registries (89%) and we tested their MUTYH mutation status after surveying family history. Therefore, any measurement error (under- or over-reporting) of family history of cancer will be non-differential with respect of mutation status and our results comparing cancer risks for carriers with the general population is likely to be attenuated. Further, previous studies showed a high probability of agreement between proband-reported cancer status in first-degree relatives and the validated report; for example, 95.4% (95% CI, 92.6-98.3) for female breast cancer, 83.3% (95% CI, 72.8-93.8) for ovarian cancer; and 79.3% (95% CI, 70.0-88.6) for prostate cancer.49 We systematically attempted to estimate HR for each cancer site separately for monoallelic and biallelic mutation carriers. However, for many sites there were insufficient numbers of cancer diagnosis to generate reasonable estimates of HR. Because of many more relatives of monoallelic mutation carriers compared with biallelic mutation carriers (225 vs. 41 families), we were able to estimate the risk of more cancer sites for monoallelic mutation carriers while we were only able to estimate the cancer risk of two sites (urinary bladder and ovary) for biallelic mutation carriers. Further, we did not have sufficient power to examine cancer risks associated with specific variants of the MUTYH gene in our study. Some studies have reported associations of specific MUTYH variants with particular disease types and severity. For example, monoallelic or biallelic mutation carriers of a MUTYH p.(Tyr179Cys) variant had a higher risk of colorectal cancer than carriers of a MUTYH p.(Gly396Asp) variant.5, 6 Our results might have limited relevance for non-Caucasian populations, since our cohort was comprised mainly of individuals with MUTYH variants that commonly occur in Caucasians, and there are ethnic and geographical differences in MUTYH variants.50 Finally, most of the relatives included in the study (including those affected with a cancer) were not tested for their mutation status, leading to less precise estimates than if every relative was genetically tested, so our estimates should be replicated in larger studies to obtain more precise estimates.
In summary, we found that biallelic MUTYH mutation carriers are at increased risks of developing urinary bladder and ovarian cancers and monoallelic carriers are at increased risks of gastric, liver, breast, and endometrial cancers. Further studies investigating cancer risks and disease characteristics associated with specific MUTYH mutation variants are warranted.
Supplementary MaterialACKNOWLEDGEMENTS
The authors thank all study participants of the Colon Cancer Family Registry and staff for their contributions to this project.
FUNDING
Grant sponsor: National Cancer Institute; Grant numbers: UM1 CA167551 (Colon Cancer Family Registry), U01 CA074778 and U01/U24 CA097735 (Australasian Colorectal Cancer Family Registry), U01/U24 CA074800 (Mayo Clinic Cooperative Family Registry for Colon Cancer Studies), U01/U24 CA074783 (Ontario Familial Colorectal Cancer Registry), U01/U24 CA074794 (Seattle Colorectal Cancer Family Registry), U01/U24 CA074806 (University of Hawaii Colorectal Cancer Family Registry) and U01/U24 CA074799 (USC Consortium Colorectal Cancer Family Registry);
Grant sponsor: Surveillance, Epidemiology and End Results (SEER) Program of the National Cancer Institute with additional support from the Fred Hutchinson Cancer Research Center; Grant numbers: N01-CN-67009 (1996-2003), N01-PC-35142 (2003-2010) and HHSN2612013000121 (2010-2017) (Cancer Surveillance System of the Fred Hutchinson Cancer Research Center);
Grant sponsor: Hawaii Department of Health as part of the state-wide cancer reporting program mandated by Hawaii Revised Statutes; SEER Program of the National Cancer Institute; Grant numbers: N01-PC-67001 (1996-2003), N01-PC-35137 (2003-2010), HHSN26120100037C (2010-2013) and HHSN261201300009I (2010-current) (University of Hawaii);
Grant sponsor: California Department of Public Health as part of the state-wide cancer reporting program mandated by California Health and Safety Code Section 103885; SEER Program of the National Cancer Institute; Grant numbers: HHSN261201000140C (Cancer Prevention Institute of California), HHSN261201000035C (University of Southern California) and HHSN261201000034C (Public Health Institute);
Grant sponsor: Centers for Disease Control and Prevention’s National Program of Cancer Registries; Grant number: U58DP003862-01 (California Department of Public Health);
Grant sponsor: National Health and Medical Research Council (NHMRC), Australia; Grant numbers: APP1042021 (Centre for Research Excellence), APP1074383 (program grant), APP1073395 (Early Career Fellowship to AKW), APP1020493 (Senior Research Fellowship to MAJ) and APP1023434 (Senior Principal Research Fellowship to JLH);
Grant sponsor: University of Melbourne Research at Melbourne Accelerator Program (R@MAP); Grant number: 13947 (Senior Research Fellowship to DDB).
Authors’ Contributions
Aung Ko Win, Mark A. Jenkins: study concept and design; acquisition of data; statistical analysis; interpretation of data; drafting and critical review of the manuscript for important intellectual content; approval of the final version of the manuscript
Jeanette C. Reece: interpretation of data; drafting and critical review of the manuscript for important intellectual content; approval of the final version of the manuscript
James G. Dowty: statistical analysis; interpretation of data; drafting and critical review of the manuscript for important intellectual content; approval of the final version of the manuscript
Daniel D. Buchanan, Mark Clendenning, Christophe Rosty, Melissa C. Southey, Joanne P. Young, Sean P. Cleary, Hyeja Kim, Michelle Cotterchio, Finlay A. Macrae, Katherine M. Tucker, John A. Baron, Terrilea Burnett, Loïc Le Marchand, Graham Casey, Robert W. Haile, Polly A. Newcomb, Stephen N. Thibodeau, John L. Hopper, Steven Gallinger, Ingrid M. Winship, Noralane M. Lindor: acquisition of data; interpretation of data; critical review of the manuscript for important intellectual content; approval of the final version of the manuscript
DISCLAIMER
The content of this manuscript does not necessarily reflect the views or policies of the National Cancer Institute or any of the collaborating centers in the CFRs, nor does mention of trade names, commercial products, or organizations imply endorsement by the US Government or the CFR. Authors had full responsibility for the design of the study, the collection of the data, the analysis and interpretation of the data, the decision to submit the manuscript for publication, and the writing of the manuscript.
DISCLOSURE
The authors have no conflict of interest to declare with respect to this manuscript.
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Selection of study sample
Numbers and mean ages at diagnosis of extracolonic cancers in the first- and second-degree relatives (combined) of probands
Male (n=2,552)
Female (n=2,606)
Site of cancer
N
Mean age (SD)
N
Mean age (SD)
Stomach
27
68.4 (9.39)
26
73.2 (12.5)
Hepatobiliary tract
15
62.1 (12.9)
10
72.9 (8.37)
Brain
10
57.9 (12.7)
12
54.0 (12.1)
Urinary bladder
4
66.0 (10.7)
5
78.4 (12.3)
Renal pelvis/Kidney
6
64.7 (11.3)
9
66.4 (12.0)
Pancreas
4
64.1 (10.3)
6
72.0 (11.2)
Small bowel
0
1
52
Ureter
1
59
0
Thyroid
1
29
4
41.0 (17.3)
Pharynx
9
62.7 (6.71)
6
69.0 (9.54)
Esophagus
7
63.8 (8.22)
2
72.0 (1.41)
Lung
46
63.7 (12.6)
15
62.7 (10.0)
Bone
7
67.3 (18.7)
4
55.5 (19.7)
Ovary
10
52.7 (12.8)
Endometrium
22
66.1 (14.0)
Breast
106
60.7 (12.0)
Cervix
5
37.4 (12.1)
Prostate
63
69.4 (8.41)
N, total number of affected relatives; SD, standard deviation
Hazard ratios and corresponding cumulative risks % to age 70 years of extracolonic cancers for carriers of germline monoallelic and biallelic mutations in MUTYH
Site of cancer
HR (95% CI)*
Cumulative risk % (95% CI)**
Males
Females
Biallelic carriers
Urinary bladder
19 (3.7–97)
25 (5.4–77)
7.6 (1.5–33)
Ovary
17 (2.4–115)
14 (2.2–65)
Monoallelic carriers
Stomach
9.3 (6.7–13)
5.0 (3.6–6.9)
2.3 (1.7–3.3)
Hepatobiliary tract
4.5 (2.7–7.5)
2.9 (1.7–4.7)
1.4 (0.8–2.3)
Endometrium
2.1 (1.1–3.9)
3.3 (1.8–6.2)
Breast
1.4 (1.0–2.0)
11 (8.3–16)
Ovary
0.4 (0.1–2.6)
Prostate
0.5 (0.3–1.0)
Brain
2.1 (0.9–4.9)
Renal pelvis/Kidney
2.3 (0.1–3.1)
Pancreas
2.3 (0.2–4.1)
CI, confidence interval; HR, hazard ratio
HR was provided for both males and females combined given that HRs were not different by sex.
Cumulative risks were estimated only for cancers that were significantly associated with MUTYH mutations. These cumulative risks were calculated for carriers of germline monoallelic and biallelic mutations in MUTYH living in USA. See Supplementary Table 3 for cumulative risks for carriers living in Canada and Australia.
NOVELTY AND IMPACT STATEMENT
People with a biallelic mutation in MUTYH are at increased risks of developing urinary bladder and ovarian cancers and people with a monoallelic mutation are at increased risks of gastric, liver, breast, and endometrial cancers. This information will be useful for their clinical management.