Cancer Risks Associated With TP53 Pathogenic Variants: Maximum Likelihood Analysis of Extended Pedigrees for Diagnosis of First Cancers Beyond the Li-Fraumeni Syndrome Spectrum

Abstract

PURPOSE

Establishing accurate age-related penetrance figures for the broad range of cancer types that occur in individuals harboring a pathogenic germline variant in the TP53 gene is essential to determine the most effective clinical management strategies. These figures also permit optimal use of cosegregation data for classification of TP53 variants of unknown significance. Penetrance estimation can easily be affected by bias from ascertainment criteria, an issue not commonly addressed by previous studies.

MATERIALS AND METHODS

We performed a maximum likelihood penetrance estimation using full pedigree data from a multicenter study of 146 TP53-positive families, incorporating adjustment for the effect of ascertainment and population-specific background cancer risks. The analysis included pedigrees from Australia, Spain, and United States, with phenotypic information for 4,028 individuals.

RESULTS

Core Li-Fraumeni syndrome (LFS) cancers (breast cancer, adrenocortical carcinoma, brain cancer, osteosarcoma, and soft tissue sarcoma) had the highest hazard ratios of all cancers analyzed in this study. The analysis also detected a significantly increased lifetime risk for a range of cancers not previously formally associated with TP53 pathogenic variant status, including colorectal, gastric, lung, pancreatic, and ovarian cancers. The cumulative risk of any cancer type by age 50 years was 92.4% (95% CI, 82.2 to 98.3) for females and 59.7% (95% CI, 39.9 to 81.3) for males. Females had a 63.3% (95% CI, 35.6 to 90.1) cumulative risk of developing breast cancer by age 50 years.

CONCLUSION

The results from maximum likelihood analysis confirm the known high lifetime risk for the core LFS-associated cancer types providing new risk estimates and indicate significantly increased lifetime risks for several additional cancer types. Accurate cancer risk estimates will help refine clinical recommendations for TP53 pathogenic variant carriers and improve TP53 variant classification.

Study refines TP53 germline variant risks for diverse cancers beyond the Li-Fraumeni syndrome core spectrum.

INTRODUCTION

Li-Fraumeni syndrome (LFS) is a hereditary cancer disorder caused by germline pathogenic variants in the TP53 gene, which predispose individuals to a wide range of cancers. Most of these cancers are rare and have an earlier age of onset than in the general population. The most characteristic cancers are female breast cancer, osteosarcoma, soft tissue sarcoma, brain tumors, and adrenocortical carcinoma, termed the core LFS cancers.^1,2 Although TP53 genetic testing was previously recommended only for individuals meeting certain clinical criteria, termed the classic LFS or Chompret 2015 criteria,^3,4 the identification of TP53 carriers in multigene panel testing has demonstrated that LFS has a broader cancer spectrum than previously recognized.⁵ A wider cancer spectrum is also supported by studies of the International Agency for Research on Cancer (IARC) TP53 database⁶ and the National Cancer Institute,⁷ which indicate the need to better understand the LFS cancer spectrum. To provide effective clinical management, it is important to identify which cancers have a significantly increased risk associated with TP53 germline pathogenic variants (relative to population risk), as well as calculating the lifetime personal risk for each cancer. Accurate penetrance estimates are also required as a defined parameter for Bayesian segregation analysis methods that have been shown to outperform meiosis counting in the assessment of the causality of variants of uncertain clinical significance.⁸

CONTEXT

• Key Objective

• To provide more accurate estimates of cancer risks associated with Li-Fraumeni syndrome (LFS), a hereditary cancer disorder caused by TP53 gene pathogenic variants, by using a statistically sophisticated approach that addresses issues around ascertainment bias and the wide range of competing risks.

• Knowledge Generated

• By conducting a comprehensive analysis of diverse cancer types in TP53 pathogenic variant carriers, the study provides accurate estimates of cancer risks, including beyond the core LFS cancers. This study revealed that individuals with TP53 germline pathogenic variants have a significantly increased risk of developing a broad spectrum of cancers, including colorectal, lung, gastric, leukemia, melanoma, and more, with higher risks in females compared with males.

• Relevance

• This information is crucial for improving clinical management strategies, which may include personalized surveillance and screening approaches for TP53 pathogenic variant carriers to detect and manage cancer at an earlier stage.

A number of primarily observational studies report an increased risk of noncore cancer types in LFS families, including melanoma, lung cancer, GI cancers, thyroid cancer, prostate cancer, ovarian cancer, leukemias, and lymphomas, among others.^4,9-17 As some of these cancers are relatively common in the general population, the studies to date have not been able to provide conclusive evidence to determine if these are causally linked to germline TP53 variants. Even for the core LFS cancers, with a firmly established association with TP53 pathogenic variant status, the specific age-related risk for these has not been clearly established or validated across different cohorts.

Six previous studies have estimated the TP53-associated penetrance for specific cancer types using a range of different methods, selection criteria, and number of pedigrees (summarized in Table 1).^10,18-21 Of these six studies, three investigated risk in seven or fewer families, with only one using a segregation-based method. For all studies, sample size and methods used restricted penetrance estimation to only a subset of cancer types. Furthermore, most of these studies analyzed TP53 families that were highly selected on the basis of existing testing criteria. It is likely that the results from analysis of families recruited based only on the proband's diagnosis (ie, not considering the cancer family history) are less susceptible to ascertainment bias. However, there is known to be variation in the disease risk and cancer spectrum associated with individual TP53 variants, and even the details of the proband's diagnosis could introduce an element of selection bias. To minimize these concerns, it is important to conduct penetrance estimations from a large number of pedigrees using information from as many family members as possible, addressing issues around ascertainment bias through the use of pedigree data that are able to take the context of the family history into account. The segregation-based maximum likelihood method represents a powerful way to address these issues by conditioning the analysis on the family component that led to the ascertainment and providing the ability to consider the whole pedigree structure and population background incidence. The strength of this approach has been demonstrated by international collaborations that have successfully analyzed the cancer risks associated with pathogenic variants in several cancer genes, including PALB2 (524 pedigrees), RAD51C (125 pedigrees) and RAD51D (60 pedigrees), POLE and POLD (50 pedigrees), and BRCA1 (906 pedigrees) and BRCA2 (367 pedigrees),^22-25 as well as a recent population-based breast cancer study of 17,425 families.²⁶

TABLE 1.

Overview of Studies Investigating Cancer Risk/Incidence Associated With TP53 Germline Pathogenic Variants

Study	No. of TP53-Positive Pedigrees	Selection criteria	Methods	Reported Findingsa
Hwang et al,18 2003	7	Cancer history consistent with the classic LFS criteria	Kaplan-Meier analysis	Cumulative cancer risk by ages 20, 30, 40, and 50 years of 18%, 40%, 77%, and 93%, respectively, in females and 10%, 21%, 33%, and 68%, respectively, in males
Wu et al,19 2006	7	Childhood soft tissue sarcoma	Segregation-based	Cumulative cancer risk by ages 20, 40, and 60 years of 96%, 100%, and 100%, respectively, in females and 40%, 86%, and 98%, respectively, in males
Mai et al,10 2017	107	NCI LFS study—meeting clinical criteria for classic LFS or Li-Fraumeni–like syndrome, as well as those with choroid plexus carcinoma, adrenocortical carcinoma, or ≥3 cancers, as well as those identified to carry a germline TP53 variant	Kaplan-Meier analysis	Cumulative cancer incidence by age 31 years of 50% for females and 46 years for males, and almost 100% by age 70 years for both sexes
Fan et al,20 2021	5	Participants unselected for personal or family history of breast cancer	Kaplan-Meier analysis	Breast cancer risk of 25% by age 40 years and 44% by age 50 years
de Andrade et al,7 2022	143 (includes families analyzed by Mai et al,10 2017)	NCI LFS study—meeting clinical criteria for classic LFS or Li-Fraumeni–like syndrome, as well as those with choroid plexus carcinoma, adrenocortical carcinoma, or ≥3 cancers, as well as those identified to carry a germline TP53 variant	Observational study using family-clustered Cox regression models and competing risk methods	Breast cancer risk by age 60 years of 56%. LFS individuals had 24 times higher incidence of any cancer compared with the general population
Evans et al,21 2023	17 total: 6 (c.455C>T [p.Pro152Leu]), and 11 (codon 245/248)	Families from research studies tested for very early onset breast cancer and LFS Chompret criteria	Kaplan-Meier analysis	Families with c.455C>T (p.Pro152Leu) had a lower risk of nonadrenal cancers and no increased risk of breast cancer. Families with codon 245/248 variants had a 100% risk of breast cancer by age 36 years and 100% risk of all cancers before age 60 years

Abbreviation: LFS, Li-Fraumeni syndrome.

^aSee publication for cancer-specific figures.

In this study, we applied the maximum likelihood approach to the analysis of pedigree data from families with a known TP53 pathogenic variant from three countries. The study aimed to refine the list of cancers known to have a significantly increased risk in individuals harboring a TP53 pathogenic germline variant and provide improved estimates of the cumulative cancer risk by age.

MATERIALS AND METHODS

Data Sets

A total of 146 unique informative pedigrees (4,028 individuals) from five different sites in three countries were used for cancer risk analyses, with a median of 33 individuals per family. Details and selection criteria are described in Table 2. Families were considered informative and therefore included in the analyses, if at least two family members had been genotyped. There were a total of 741 genotyped individuals regardless of the cancer affected status, with a median of four genotyped individuals per family. Where available for any family member, the data collected included date of birth/death, cancer status, age at diagnosis, TP53 result, date of any prophylactic surgeries, and date of last follow-up. The analysis included families with a variant reported as pathogenic or likely pathogenic (P/LP) by local diagnostic laboratories, which were then checked against ClinVar or TP53 quantitative models.^27,28 Families segregating the reduced-penetrance Brazilian founder variant NM_000546.6(TP53):c.1010G>A (p.R337H), which is classified as P/LP in ClinVar, were not included. The list of unique variants included along with ClinVar and quantitative model data is provided in the Data Supplement (Table S1), as well as the number of informative pedigrees with each variant.

TABLE 2.

Overview of Sample Sets Used in the Analysis

Country	Site	Families	Individuals	Selection Criteria
Australia	ISKS	7	277	Personal or family history of sarcoma
Australia	kConFab	12	468	Personal or family history of breast-ovarian cancer
Australia	ICCon	50	1,545	Personal or family history of cancer indicating hereditary disease
Spain	Catalan Institute of Oncology	13	375
US (Utah)	University of Utah	64	1,363

Abbreviations: ICCon, Inherited Cancer Connect; ISKS, International Sarcoma Kindred Study.

This study has been approved by the QIMR Berghofer MRI Human Research Ethics Committee (P1051). This study received the IDIBELL institutional review board (IRB) approval PR025/10. This study has been approved by the University of Utah IRB (IRB_00046740). Consent for research had previously been obtained for individuals previously recruited into research cohorts, and requirement for consent was waived by the IRB for sharing of deidentified data for the remainder of individuals in cohorts ascertained clinically.

Statistical Analyses

Pedigree Data

Pedigree data were collected, cleaned, and exported in an analyzable format, using Progeny software (version 10.6.2.0). Families from the three Australian sites identified to overlap were merged into a single pedigree for analyses. Individuals were censored as affected at the age of first cancer diagnosis, or, if unaffected, at the earliest of age at risk-reducing surgery, death, or last follow-up. Family members with missing ages of cancer diagnosis were not considered in the analyses, unless information was available on age of death or last follow-up, which was used conservatively as an age of diagnosis in 43 individuals (median age, 44 years). Individuals with nonmelanoma skin cancers (C44) and benign tumors were considered as unaffected for all analyses, but were censored at the age of these diagnoses if no other relevant cancer or later follow-up age information. Where an individual had a TP53 pathogenic variant confirmed to be de novo by genotyping or mosaicism, their ancestors were excluded from the analyses. This was the case for 10 (13%) of all 146 families, a figure compatible with the reported frequency of TP53 de novo events between 7% and 20%.²⁹ The pedpro program available on the COOL website (COOL, Co-segregation Online)⁸ was used to correct for family structure errors.

Cancer Population Incidence

Data on population cancer incidence were retrieved from the IARC website³¹ for the population most relevant to our data sets (Australia 2003-2007, Spain-Girona 2003-2007, United States Utah 2003-2007) and combined proportionally to the number of observed cases and person-years at risk. International Classification of Diseases code definitions for each of the cancers analyzed are specified in the Data Supplement (Table S2).

Hazard Ratio and Cumulative Cancer Risk Calculations

Hazard ratios (HRs) associated with each cancer were calculated as the ratio of developing a given cancer type as a first cancer among TP53 P/LP carriers in comparison with the general population. The HR was calculated independently for the following malignancies and groupings: all cancer types in the data set, all core LFS cancers (except breast cancer), adrenocortical carcinoma, breast cancer, brain cancers, osteosarcoma, soft tissue sarcoma, osteosarcoma + soft tissue sarcoma including unspecified sarcomas, colorectal cancer, gastric cancer, leukemia, lung cancer, melanoma, non-Hodgkin lymphoma, pancreatic cancer, renal cancer, cervical cancer, ovarian cancer, and prostate cancer. For other cancers such as endometrial cancer, head and neck cancer, liver cancer, and thyroid cancer, there were no known carriers except for a single individual with thyroid cancer. The HR could therefore not be calculated for these cancers, given their rarity in our data sets and/or absence of sufficient genotyped affected individuals. To calculate the HRs, we used a maximum likelihood analysis method,²² which is implemented in a modified version of the software MENDEL.³² This method considers the whole pedigree structure and assigns a probability of being a carrier to each individual on the basis of the known genotype information within the pedigree, in an iterative process that continues until the genotype probability estimates are found that result in the best fit to the observed phenotype and genotype data. The effect of ascertainment bias was controlled for by conditioning on the likelihood of data on the basis of the proband's genotype and all family members' phenotypes. HRs were calculated using a constant model for each malignancy, in addition to age-dependent continuous models for those with the highest number of affected/genotyped individuals. To fit age-dependent models, three age groups were assigned on the basis of existing clinical criteria³³ as well as commonly investigated age groups for specific cancers, with the middle group calculated by interpolation. Separate models were fitted for all cancer types, ≤18 years versus >45 years; core LFS cancers, ≤18 years versus >45 years; breast cancer, ≤30 years versus >50 years; brain cancer, ≤45 years versus >45 years; and prostate cancer, ≤60 years versus >60 years. Significant HRs were converted to cumulative cancer risks by age using population background cancer incidence at 5-year age groups from 0 to 75 (considered lifetime) for core LFS cancers and for all cancer types combined. Cumulative cancer risks by age were calculated for age groups from 0 only up to age 60 years for all other cancers, a conservative approach to account for the lower number of confirmed genotyped individuals in this latter group. A secondary age-dependent analysis was performed for all cancer types and core LFS cancers, using ≤18 years versus >60 years as age groups.

RESULTS

Overview of the Cancer Spectrum

A summary of the spectrum of first cancers according to sex (irrespective of pathogenic variant status as well as in confirmed TP53 carriers) is shown in Table 3. Details of the number of first cancer diagnoses according to age group, sex, and TP53 status is provided in the Data Supplement (Table S2). Of all 4,028 individuals denoted in the pedigrees, 2,014 (50%) were female, 2,014 (50%) were male, and 971 (24%) were affected with at least one cancer; of the cancer-affected individuals, 206 were affected with multiple cancers. In females, core LFS cancers represented 60% of all cancers and 15% without including breast cancer. Breast cancer was the most common cancer in females (45% of all total malignancies), followed by brain cancer (6%) and lung cancer (5%). In males, core LFS cancers represented 26% of all cancers. Brain cancer was the most common cancer in males (14%), followed by prostate cancer (13%) and colorectal cancer (10%).

TABLE 3.

Spectrum of First Cancers According to Sex in all Individuals From the Data Set (2,014 females and 2,014 males) With the Number of Confirmed TP53 Carriers for Each Cancer

Cancer (first)	Females (carriers)	Males (carriers)
All cancer typesa	552 (179)	419 (92)
Adrenocortical carcinoma	10 (8)	2 (1)
Breast cancer	248 (104)	4 (0)
Brain cancer	35 (11)	60 (19)
Osteosarcoma	22 (8)	21 (10)
Soft tissue sarcoma	16 (9)	27 (19)
Unspecified sarcoma	16 (5)	9 (2)
Cervical cancer	9 (3)	NA
Colorectal cancer	22 (2)	42 (5)
Gastric cancer	11 (1)	18 (2)
Leukemia	19 (2)	19 (4)
Lung cancer	27 (4)	41 (1)
Melanoma	15 (3)	17 (5)
Non-Hodgkin lymphoma	7 (0)	7 (2)
Ovarian cancer	17 (5)	NA
Prostate cancer	NA	54 (11)
Pancreatic cancer	7 (0)	11 (0)
Renal cancer	4 (1)	8 (1)
Other/Unknown	67 (13)	79 (10)

Abbreviation: NA, not applicable.

^a This includes all cancers in the data set including classified as other and unknown.

HRs Associated With Each Cancer Type

HR estimates for each cancer type according to sex are shown in Table 4. The combined HR for all cancers was nonsignificantly higher in females than in males, both using the constant model (10.6 v 6.7) and at the different age groups analyzed by the age-dependent model. For both sexes, the LFS core cancers had the highest individual HRs. Of note, both females and males continued to have a significant HR of developing all cancer types as well as core LFS cancers after age 45 years, and after age 60 years in the secondary age-dependent model (Data Supplement, Table S3). The core LFS cancer with the highest HR was adrenocortical carcinoma in females (HR, 78.3), with all cases occurring before age 18 years but there were insufficient data in males to calculate a HR for this cancer. The HR associated with breast cancer in females was 10.7; however, the age-dependent model revealed the HR to be highest before age 30 years (HR, 43.6) and not significant after age 50 years. For males, the HR was significant for all cancers analyzed except melanoma and renal cancer. For females, the HRs for lung cancer, melanoma, ovarian cancer, and renal cancer were statistically significant.

TABLE 4.

HR Estimated for Different Cancer Types Derived from Maximum Likelihood Analysis of 146 TP53+ Families

Cancer (first)	Females			Males
	HR	Lower 95% CI	Upper 95% CI	HR	Lower 95% CI	Upper 95% CI
All cancer typesa (constant)	10.6	7.7	14.6	6.7	4.6	9.8
All cancer typesa ≤18 years	41.6	26.3	65.8	17.2	9.0	32.9
All cancer typesa >45 years	5.1	3.1	8.7	4.2	2.4	7.1
Core LFS cancersb (constant)	9.5	5.7	16.0	20.4	9.4	44.2
Core LFS cancersb ≤18 years	40.5	19.1	85.8	24.0	8.5	67.6
Core LFS cancersb >45 years	3.3	1.1	10.1	15.3	3.3	72.2
Adrenocortical carcinoma	78.3	44.2	138.9	No data
Breast cancer (constant)	10.7	7.1	16.1	No data
Breast cancer ≤30 years	43.6	18.9	100.9	No data
Breast cancer >50 years	2.2	0.8	6.3	No data
Brain cancer (constant)	42.8	15.9	114.9	15.8	5.9	41.8
Brain cancer ≤45 years	55.1	19.4	156.5	16.2	5.3	49.8
Brain cancer >45 years	No data			14.4	2.0	104.8
Osteosarcoma	44.7	6.3	318.0	42.1	11.3	156.2
Soft tissue sarcoma	23.7	3.8	146.6	21.3	4.8	95.4
Osteosarcoma + soft tissue sarcomac	79.5	25.0	253.3	34.6	12.1	99.3
Cervical cancer	4.4	0.2	95.2	NA
Colorectal cancer	1.5	0.3	6.3	6.0	2.1	16.6
Gastric cancer	6.7	0.8	57.1	11.0	1.6	74.2
Leukemia	4.0	0.8	19.4	4.0	1.0	15.4
Lung cancer	9.1	2.3	36.0	4.8	1.5	15.6
Melanoma	5.4	1.2	23.4	2.1	0.6	7.5
Non-Hodgkin lymphoma	No data			6.3	1.4	28.3
Ovarian cancer	11.1	2.0	60.3	NA	NA	NA
Pancreatic cancer	No data			12.0	1.9	74.8
Prostate cancer (constant)	NA			5.6	2.3	13.4
Prostate cancer ≤60 years	NA			13.8	4.6	41.3
Prostate cancer >60 years	NA			3.2	1.1	9.2
Renal cancer	15.4	2.1	111.8	4.0	0.6	27.0

Abbreviations: HR, hazard ratio; LFS, Li-Fraumeni syndrome; NA, not applicable.

^a This includes all cancers in the data set including others and unknown.

^b This includes adrenocortical carcinoma, brain cancer, osteosarcoma, soft tissue sarcoma, as well as unknown sarcoma subtypes.

^c This includes unknown sarcoma subtypes.

Cumulative First Cancer Risks for All Cancer Types and LFS Core Cancers

On converting the significant HRs from the analysis to age-specific cumulative cancer risks on the basis of population background incidences, the risk of developing any cancer type in females was 41% by age 30 years and 98% by age 70 years. In males, this was 19% by age 30 years and 92% by age 70 years (Fig 1, details in the Data Supplement, Tables S4 and S5).

FIG 1.

Cumulative risk of first cancer diagnosis for all cancer types and individual core LFS cancers, for (A) females and (B) males. ^aCumulative risks calculated using an age-dependent model. ^bResults from females only because of lack of data in males.

In females, the LFS core cancer with the highest lifetime risk was breast cancer (7% by age 30 years and 71% by age 70 years), followed by brain cancer (9% lifetime risk), soft tissue sarcoma (4%), osteosarcoma (3%), and adrenocortical carcinoma (2%). When including unspecified sarcoma subtypes, assumed to be either osteosarcoma or soft tissue sarcoma, the lifetime risk of developing any of these malignancies was 17% (Data Supplement, Table S4). When analyzed together excluding breast cancer, the lifetime risk of developing a first core LFS cancer in females was 30% (Data Supplement, Table S4).

In males, the LFS core cancer with the highest lifetime risk was brain cancer (15%), followed by soft tissue sarcoma (6%) and osteosarcoma (4%), with no data available for adrenocortical carcinoma. When including unspecified sarcoma subtypes, the lifetime risk was 11% (Data Supplement, Table S5). When analyzed together, the lifetime risk of developing a first core LFS cancer was 23% (Data Supplement, Table S5).

Cumulative First Cancer Risks for Cancer Types Outside the LFS Core Spectrum

Age-specific cumulative risks were also calculated for cancers outside the LFS core spectrum that had a significantly increased HR in the maximum likelihood analysis (Fig 2). In females, the risk of developing a cancer type outside the LFS core spectrum by age 60 years was highest for melanoma (8%), followed by lung cancer (7%), ovarian cancer (6%), and renal cancer (4%). In males, this risk was highest for prostate cancer (22%), followed by colorectal cancer (12%), lung cancer (9%), non-Hodgkin lymphoma (5%), gastric cancer (4%), pancreatic cancer (4%), and leukemia (2%).

FIG 2.

Cumulative risk of first cancer diagnosis for cancers outside the LFS spectrum shown to have statistically significant associations, for (A) females and (B) males. ^aCumulative risks calculated using an age-dependent model.

DISCUSSION

To our knowledge, this study of 146 families is the first to provide age-specific risks of diverse cancer types in TP53 pathogenic variant carriers using maximum likelihood segregation analysis. Our estimated penetrance figures are somewhat lower at earlier ages than reported for previous studies, likely because of the methodological approach that allows for stringent correction for ascertainment and takes advantage of the whole pedigree structure. Nevertheless, a >90% lifetime risk of developing any cancer was reached earlier in females (50 years) than in males (70 years), reflecting the very high risk of breast cancer for women and reinforcing the extremely high lifetime risk of cancer associated with TP53 pathogenic germline variants. The findings also revealed statistically significant increases in the risk of other cancer types beyond the LFS spectrum, such as colorectal, lung, gastric, pancreatic, and ovarian cancers. This is consistent with previous suggested and/or reported associations,^4,9-17 but our results additionally provide estimates of the extent of association with TP53 considering the population background incidence, which has implications for recommendations on clinical management.

Wu et al¹⁹ found females had cumulative cancer risks of 96%, 100%, and 100% at ages 20, 40, and 60years, respectively, while males had risks of 40%, 86%, and 98%. In our study, female risks were 18%, 75%, and 96%, respectively, and 9%, 35%, 80% for males. Other studies reported risks as high as 22% by age 5 years and 41% by age 18 years.⁴ The analysis by Mai et al¹⁰ of 107 families reported a cumulative cancer incidence of 50% by age 31 years in females and age 46 years in males, approaching 100% by age 70 years. In our study, female cancer risk by age 30 years was 41% and male risk by age 45 years was 47%. Our cumulative cancer risks for all core LFS cancers are generally lower than those of Mai et al,¹⁰ except for female brain cancer.

As expected, the LFS core cancers had the highest HRs in both males and females. However, when the rarity of most of the core cancers in the general population was taken into account, the lifetime absolute risk for these core cancer types occurring as first cancer was eclipsed by the absolute risk of other cancers more common in the population, such as lung or colorectal cancer. Although most previous studies have reported that LFS core cancers are the most common to occur among TP53 carriers, the cancer spectrum of our data and results from maximum likelihood analysis suggest otherwise. For example, in males, the lifetime cumulative risk of developing a core LFS cancer was estimated to be 23% (30% in females when excluding breast cancer), while this was >95% for any cancer type in both sexes, indicating the preponderance of cancer types outside the LFS spectrum. This study provides statistical evidence that an increased risk of a broad range of other cancers is associated with TP53 pathogenic variants, in particular, colorectal cancer, gastric cancer, leukemia, lung cancer, melanoma, non-Hodgkin lymphoma, pancreatic cancer, renal cancer, ovarian cancer, and prostate cancer. As we lacked data on cancer verification, there is a potential for some degree of misestimation in our results for these other cancers. The lack of statistical significance in one sex versus the other for certain cancers that do not show major sex differences in the population most likely reflects limited power because of limited numbers of genotyped affected individuals rather than an actual significant sex difference, as evidenced from the broad CIs around the HRs for non-LFS core cancers. This is especially relevant for females, where approximately 25% were affected with breast cancer as first cancer, limiting power to accurately assess the risk of nonbreast cancer as first cancer diagnosis. Future larger analyses that model these individual cancer types simultaneously with risk of core LFS cancers will be required to more accurately assess the HRs for noncore cancers while adequately conditioning for ascertainment, as has recently been conducted for nonbreast and nonovary cancer types for BRCA1 and BRCA2.²⁵

Our study was restricted to the analysis of first cancers, to avoid the introduction of potential biases because of the incidence of second cancers being influenced by the medical or surgical management of the first cancer or the described effect of radiotherapy on second cancer rates in LFS. It is therefore critical to emphasize that our results represent risks of these cancers occurring as first cancer in the absence of other competing risks. As hypothesized by de Andrade et al, ⁷ there might be a trigger effect combining biological and/or treatment-related factors affecting individuals with multiple cancers. Future studies that are able to account for these potentially complex relationships would be beneficial to provide reliable estimates for risk of cancers beyond the first cancer.

Our results could also improve TP53 variant classification, for example, calibration of criteria that use proband's phenotype as evidence for/against pathogenicity and improved cosegregation modeling via the online segregation tool COOL,⁸ which currently relies on results from seven TP53-positive families.

In conclusion, this analysis of 146 families harboring pathogenic variants in TP53 from three countries has demonstrated the value of using maximum likelihood analysis to calculate accurate cancer risk estimates associated with TP53 pathogenic variants for diverse cancer types. This rigorous maximum likelihood method has confirmed the high risk for a wide spectrum of cancer types associated with TP53 pathogenic variant status, supporting the use of broad surveillance strategies including dedicated brain and whole-body magnetic resonance imaging.^34-37 The findings emphasize the critical role of dedicated breast screening for women from a young age. They also raise the question of whether more consideration should be given to offering other targeted risk management such as colonoscopy, prostate cancer screening, and risk-reducing bilateral salpingo-oophorectomy as standard care for TP53 pathogenic variant carriers.¹⁶ It should be noted that the UKCGG Consensus Group indicated there was a strong disagreement about colonoscopy, and did not provide any recommendations about prostate or ovarian cancer, in relation to clinical management of TP53 carriers.³⁷ Applying this approach to even larger data sets modeling multiple cancer types simultaneously would be valuable to better assess the lifetime risk of cancer types outside the LFS spectrum. Further personalization of clinical management may also be possible if larger data sets were available to allow investigation of variation in cancer risk by more age groupings, variant location/effect, and for so-called reduced-penetrance TP53 variants.

APPENDIX

TABLE A1.

kConFab MEMBERS (as of November 12, 2023)

Name	Address	Phone	Email	Qualifications
David Amor	Medical Geneticist, Genetic Health Services, Victoria Royal Children's Hospital, Melbourne, VIC 3050	Ph: 03 8341 1391	david.amor@mcri.edu.au	MBBS, PhD
Lesley Andrews	Hereditary Cancer Clinic, Prince of Wales Hospital Randwick, NSW 2031	Ph: 02 9382 2590	lesley@radonc.sesahs.nsw.gov.au	MBBS
Yoland Antill	Dept. Haem and Medical Oncology, Peter MacCallum Cancer Centre, St Andrews Place, East Melbourne, VIC 3002	Ph: 03 9656 1111	yoland.antill@petermac.org	MBBS, PhD
Rosemary Balleine	Department of Translational Oncology, C/- Department of Medical Oncology, Westmead Hospital, Westmead, NSW 2145	Ph: 02 9845 7754	rosemary_balleine@mail.wmi.usyd.edu.au	MBBS, PhD FRCPA
Jonathan Beesley	Research Officer, Queensland Institute of Medical Research, Herston Road Herston, Qld 4002, Australia		Jonathan.Beesley@qimr.edu.au	PhD
Ian Bennett	Silverton Place, 101 Wickham Terrace, Brisbane, QLD 4000	Ph: 07 3839 0006	icben@bigpond.com.au	MBBS, FRACS, FACS
Michael Bogwitz	Familial Cancer Centre, The Royal Melbourne Hospital, Grattan Street Parkville, Victoria 3050, Australia	Ph: 61 3 9342 7151	Michael.Bogwitz@mh.org.au	PhD
Simon Bodek	Consultant Clinical Geneticist Austin Health, Melbourne		Simon.BODEK@austin.org.au	MBBS
Leon Botes	Clinical Nurse Specialist, Hereditary Cancer Centre, Prince of Wales Hospital, Barker St, Randwick, NSW 2031, Australia	Ph: 02 9382 5213	Leon.Botes@health.nsw.gov.au	PhD
Meagan Brennan	NSW Breast Cancer Institute, PO Box 143, Westmead, NSW 2145	Ph: 02 9845 6728	meaganb@bci.org.au	FRACGP, FASBP, PhD
Melissa Brown	Department of Biochemistry, University of Queensland, St Lucia, QLD 4072	Ph: 07 3365 4628	melissa.brown@mailbox.uq.edu.au	PhD
Michael Buckley	Molecular and Cytogenetics Unit, Prince of Wales Hospital, Randwick, NSW 2031	Ph: 02 9382 9164	buckleymf@sesahs.nsw.gov.au	MBBS, PhD FRCPA
Jo Burke	ICON Cancer Care, 2 Melville St, Hobart, TAS 7000	Ph: 0408 127 363	Jo.Burke@icon.team	PhD
Phyllis Butow	Medical Psychology Unit, Royal Prince Alfred Hospital, Camperdown, NSW 2204	Ph: 02 9351 2859	phyllisb@med.usyd.edu.au	PhD
Liz Caldon	Replication and Genome Stability Cancer Division, Garvan Institute of Medical Research, 370 Victoria Street, Darlinghurst, NSW 2010, Australia	Ph: 02 9355 5878	l.caldon@garvan.org.au	PhD
Ian Campbell	Peter MacCallum Cancer Centre, St Andrew's Place, East Melbourne, VIC 3002	Ph: 03 9656 1803	ian.campbell@petermac.org	PhD
Michelle Cao	Tasmanian Clinical Genetics Service, Tasmanian Health Service, Royal Hobart Hospital, GPO Box Hobart 7001	Ph: 03 6166 8296 1061	michelle.cao@ths.tas.gov.au
Anannya Chakrabarti	Specialist Breast Cancer Surgery, Richmond 3121		dranannya@gmail.com
Deepa Chauhan	School of Psychology, Brennan McCallum (Building A18), University of Sydney, 2006	Ph: 02 9036 6129	deepac@psych.usyd.edu.au	PhD
Manisha Chauhan	St Vincents Hospital Cancer Genetics Clinic, The Kinghorn Cancer Centre, Sydney, NSW		manishachauhan@hotmail.com	GDip Gen Couns
Georgia Chenevix-Trench	Queensland Institute of Medical Research, Royal Brisbane Hospital, Herston, QLD 4029	Ph: 07 3362 0390; Fx: 07 3362 0105	georgiaT@qimr.edu.au	PhD
Alice Christian	Genetics Department, Central Region Genetics Service, Wellington Hospital, New Zealand		Alice.christian@ccdhb.org.nz	BSc (Hons) FHGSA
Paul Cohen	Director of Gynaecological Cancer Research, St John of God Subiaco Hospital, 12 Salvado Road, Subiaco, WA 6008, Australia		Paul.Cohen@sjog.org.au	MD, FRANZCOG, Dip Obs, BMBCh
Alison Colley	Department of Clinical Genetics, Liverpool Health Service, PO Box 103, Liverpool, NSW 2170	Ph: 02 9828 4589	A.Colley@unsw.edu.au	PhD
Ashley Crook	Department of Clinical Genetics, Level 3E, Royal North Shore Hospital, St Leonards, NSW 2065	Ph: 02 9463 1554	akcrook@nsccahs.health.nsw.gov.au	GDip Gen Couns
James Cui	Epidemiology and Preventive Medicine, Monash University, Prahan, Vic 3004, Australia	Ph: 03 9903 0570	james.cui@med.monash.edu.au	PhD
Eliza Courtney	Department of Clinical Genetics, Level 3E, Royal North Shore Hospital, St Leonards, NSW 2065		ECourtney@ccia.org.au
Margaret Cummings	Department of Pathology, University of Queensland Medical School, Herston, NSW 4006	Ph: 07 3365 1530	M.Cummings@mailbox.uq.edu.au	MBBS, PhD FRCPA
Sarah-Jane Dawson	Molecular Genetics Unit, Peter MacCallum Cancer Centre, Melbourne	Ph: 03 855 97132	sarahjane.dawson@gmail.com	MBBS, PhD
Anna deFazio	Dept. of Gynaecological Oncology, Westmead Institute for Cancer Research, Westmead Hospital, Westmead, NSW 2145	Ph: 0 2 9845 7376	anna_defazio@wmi.usyd.edu.au	PhD
Martin Delatycki	Director, Clinical Genetics, Austin Health, Heidelberg Repatriation Hospital, PO Box 5444, Heidelberg West, Vic 3081, Australia	Ph: 3 9496 4355	martin.delatycki@austin.org.au	MBBS, PhD
Rebecca Dickson	Associate Genetic Counsellor, Level 2, Block 51, Royal North Shore Hospital, North Shore, NSW 2408	Ph: 02 9926 6872	RDickson@nsccahs.health.nsw.gov.au	GDip Gen Couns
Joanne Dixon	Central Regional Genetic Services, Wellington Hospital, Private Bag 7902, Wellington, New Zealand	Ph: 04 385 5310	woutjwd@mash.wnhealth.co.nz	MB ChB, FRACP
Ted Edkins	Clinical Chemistry, Princess Margret Hospital for Children, Box D184, Perth, WA 6001	Ph: 08 9340 8595	tedkins@cygnus.uwa.edu.au	PhD
Stacey Edwards	Department of Biochemistry and Molecular Biology, University of Queensland, St Lucia, Qld 4072, Australia	Ph: 07 3365 4634	stacey.edwards@uq.edu.au	PhD
Gelareh Farshid	Tissue Pathology, IMVS, Adelaide, SA 5000	Ph: 08 8222 3259	gelareh.farshid@imvs.sa.gov.au	MBBS, PhD FRCPA
Andrew Fellows	Molecular Diagnostic Development, Pathology Department, Peter MacCallum Cancer Centre, Melbourne, East Melbourne, Vic 3002	Ph: 03 9656-3595	andrew.fellowes@petermac.org	PhD
Georgina Fenton	South West Family Cancer Clinic, Liverpool Hospital, Liverpool, BC, NSW 1871	Ph: 02 9828 4665	georginafenton@hotmail.com	GDip Gen Couns
Michael Field	Clinical Geneticist, Royal North Shore Hospital, Level 2, Vindin House, St Leonards, NSW 2065	Ph: 02 9926 7497	mjfield@nsccahs.health.nsw.gov.au	MBBS, PhD
James Flanagan	Epigenetics Unit, Department of Surgery and Oncology, Imperial College London, London, W12 0NN, England	Ph: +44 (0) 20 759, 41804	j.flanagan@imperial.ac.uk	PhD
Peter Fong	Medical Oncology Department, Regional Cancer and Blood Services, Level 1, Building 7, Auckland City Hospital, 2 Park Rd., Grafton, Auckland 1023, New Zealand	Ph: +6493074949; Extn. 23867	pfong@adhb.govt.nz	MBBS, FRACP
Laura Forrest	Psychosocial Cancer Genetics Research Group, Parkville Familial Cancer Centre, 305 Grattan Street, Melbourne, Vic 3000, Australia	Ph: 3 85596191	Laura.Forrest@petermac.org	PhD
Stephen Fox	Pathology Department, Level 1, Peter MacCallum Cancer Centre, St Andrew's Place, East Melbourne, Vic 3002	Ph: 03 9656 1529	Stephen.Fox@petermac.org	BSc, MBChB, FRCPath, FFSc, FRCPA, DPhil
Juliet French	School of Molecular and Microbial Sciences, University of Queensland, St Lucia, Qld 4072	Ph: 07 3365 4634	j.french@uq.edu.au	PhD
Michael Friedlander	Professor of Medicine, Department of Medical Oncology, Prince of Wales Hospital, Randwick, NSW 2031	Ph: 02 9382 2606	m.friedlander@unsw.edu.au	MBChB, MRCP, FRACP PhD
Clara Gaff	Victorian Clinical Genetics Service, Royal Melbourne Hospital, Parkville, VIC 3052	Ph: 03 9342 7151	clara.gaff@mh.org.au	PhD
Mike Gattas	Queensland Clinical Genetic Service, Royal Children's Hospital, Bramston Terrace, Herston, QLD 4020	Ph: 07 3636 1686	Michael_Gattas@health.qld.gov.au	MBBS, FRACP
Peter George	Clinical Biochemistry Unit, Canterbury Health Labs, PO Box 151, Christchurch, New Zealand	Ph: 64 3 364 0336	pgeorge@clear.net.nz	PhD
Sian Greening	Illawarra Cancer Centre, Wollongong Hospital, Private Mail Bag 8808, South Coast Mail Centre, NSW 2521	Ph: 02 4222 5576	Sian.Greening@SESIAHS.HEALTH.NSW.GOV.AU	GDip Gen Couns
Marion Harris	Familial Cancer Clinic, Peter MacCallum Cancer Centre, St Andrews Place, East Melbourne, VIC 3002	Ph: 03 9656 1199	marion.harris@optusnet.com.au	MBBS, FRACP
Stewart Hart	Breast and Ovarian Cancer Genetics, Monash Medical Centre, 871 Centre Road, Bentleigh East, VIC 3165	Ph: 03 9579 6122	centreroad@ozmail.com.au	MBBS, FRACS
Nick Hayward	Queensland Institute for Medical Research, Royal Brisbane Hospital, Post Office, Herston, QLD 4029	Ph: 07 3362 0306	nickH@qimr.edu.au	PhD
John Hopper	Centre for M.E.G.A. Epidemiology, University of Melbourne, Level 1, 723 Swanston Street, Carlton, VIC 3010	Ph: 03 8344 0697	j.hopper@gpph.unimelb.edu.au	PhD
Cass Hoskins	Parkville Familial Cancer Centre, Peter MacCallum Cancer Centre and The Royal Melbourne Hospital, Melbourne, 3000	Ph: 03 8559 5322	Cass.Hoskins@petermac.org	BSci
Clare Hunt	Southern Health Familial Cancer Centre, Monash Medical Centre, Special Medicine Building, 246, Clayton Rd, Clayton, Victoria 3168, Australia	Ph: 03 9594 2009	Clare.Hunt@southernhealth.org.au	GDip Gen Couns
Paul James	Clinical Geneticist, Genetic Health Services, Monash Medical Centre, Clayton, Vic	Ph: 03 9594 2026	paul.james@ghsv.org.au	MBBS, PhD
Mark Jenkins	Centre for M.E.G.A. Epidemiology, The University of Melbourne, 723 Swanston Street, Carlton, VIC 3053	Ph: 03 8344 0902	m.jenkins@unimelb.edu.au	PhD
Alexa Kidd	Clinical Genetics Departments, Central Regional Genetics Service, Wellington Hospital, New Zealand		Alexa.Kidd@ccdhb.org.nz	MBBS, MRCP, MRCGP
Judy Kirk	Familial Cancer Service, Department of Medicine, Westmead Hospital, Westmead, NSW 2145	Ph: 02 9845 6947	judy.kirk@sydney.edu.au	MBBS, PhD
Jessica Koehler	Hereditary Cancer Clinic, Prince of Wales Hospital, Randwick, NSW 2031	Ph: 02 9382 3415	Jessica.koehler@SESIAHS.health.nsw.gov.au	GDip Gen Couns
James Kollias	Breast Endocrine and Surgical UnitRoyal Adelaide Hospital, North Terrace, SA 5000	Ph: 08 8215 0123	jkollias@rah.sa.gov.au	MBBS, FRACS
Sunil Lakhani	UQ Centre for Clinical Research, Level 6, Building 71/918, University of Queensland, The Royal Brisbane and Women's Hospital, Herston 4029	Ph: 07 3346 6052	s.lakhani@uq.edu.au
Mitchell Lawrence	Prostate Cancer Research Program, 19 Innovation Walk, Level 3, Monash University, Clayton 3800	Ph: 03 9902 9286	mitchell.lawrence@monash.edu	PhD
Jason Lee	Epigenetics and Disease Laboratory, QIMR Berghofer Medical Research Institute, Brisbane 4006	Ph: 07 3845 3951	Jason.Lee@qimrberghofer.edu.au
Shuai Li	Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Level 3, 207 Bouverie Street, Carlton, VIC 3053	Ph: 03 9035 8224	shuai.li@unimelb.edu.au
Geoff Lindeman	Breast Cancer Laboratory, Walter and Eliza Hall Institute, PO Royal Melbourne Hospital, Parkville, VIC 3050	Ph: 03 9342 2611	Lindeman@wehi.edu.au	BSc, MBBS, PhD, FRACP FAHMS FAA
Jocelyn Lippey	Department of Surgery St Vincent's Hospital, Melbourne		jlippey@gmail.com	MBBS, PhD
Lara Lipton	Medical Oncology and Clinical Haematology Unit, Western Hospital, Footscray, VIC		Lara.Lipton@mh.org.au	BSc, MBBS, PhD
Liz Lobb	Medical Psychology Research Unit, Room 332, Brennan MacCallum Building (A18), The University of Sydney, Camperdown 2006	Ph: 02 9351 4597	lizl@psych.usyd.edu.au	PhD
Sherene Loi	Head of the Translational Breast Cancer, Genomics and Therapeutics Laboratory, Medical Oncologists, The Peter MacCallum Cancer Centre, Melbourne 3000		Sherene.Loi@petermac.org
Graham Mann	Westmead Institute for Cancer Research, Westmead Millennium Institute, Westmead, NSW 2145	Ph: 02 9845 9056	gmann@mail.usyd.edu.au	MBBS, PhD, FRACP
Deborah Marsh	Kolling Institute of Medical Research, Royal North Shore Hospital, St Leonards, NSW 2065	Ph: 02 9926 6873	Debbie_Marsh@med.usyd.edu.au	PhD
Sue Anne McLachlan	Department of Oncology, St Vincent's Hospital, 41 Victoria Parade, Fitzroy, VIC 3065	Ph: 03 9288 3155	mclachsa@mail.svhm.org.au	MBBS, PhD
Bettina Meiser	Hereditary Cancer Clinic, Prince of Wales Hospital, Randwick, NSW 2031	Ph: 02 9382 2638	b.meiser@unsw.edu.au	PhD
Roger Milne	Centro Nacional de Investigaciones Oncologicas, C/Melchor Fernández Almagro, 3, E-28029 Madrid, Spain		rlm@unimelb.edu.au	PhD
Sophie Nightingale	Western Health and Peter MacCallum Cancer Centre, Consultant, General, Breast and Melanoma Surgeon, St Andrews Place, East Melbourne, Victoria 3002	Ph: 03 9318 6027	mail@sophienightingale.com.au	MB ChB, MS, FRACS
Shona O'Connell	Southern Health Familial Cancer Centre, Special Medicine Building, 246 Clayton Road, Clayton, Vic 3168	Ph: 03 9594 2009	Shona.OConnell@southernhealth.org.au	GDip Gen Couns
Sarah O'Sullivan	Genetic Services of Western, Level 3, Agnes Walsh House, 374 Bagot Road, Subiaco, WA 6008, Australia	Ph: 8 6458 1603	Sarah.O'Sullivan@health.wa.gov.au	GDip Gen Couns
David Gallego Ortega	Tumour Development Group, Garvan Institute of Medical Research, The Kinghorn Cancer Centre, 370 Victoria St, Darlinghurst, NSW 2010, Australia	Ph: 61 (0)2 9355 5776	d.gallego@garvan.org.au	PhD
Nick Pachter	Familial Cancer and Clinical Genetics, Royal Melbourne Hospital, Grattan Street, Parkville, VIC 3050, Australia	Ph: 03 9342 4244	nick.pachter@mh.org.au	MB ChB
Jia-Min Pang	Molecular Pathology Department Peter, MacCallum Cancer Centre, Melbourne, 3000	Ph: 03 8559 6501	Jia-Min.Pang@petermac.org
Gargi Pathak	Clinical Geneticist, Genetic Services of Western Australia, Women and Newborn Health Service, Agnes Walsh House, King Edward Memorial Hospital, 374 Bagot Road, Subiaco, WA 6008	Ph: 08 6458 1603	gargi.pathak@health.wa.gov.au
Briony Patterson	Tas Clinical Genetics Service, Royal Hobart Hospital, GPO Box 1061, Hobart, Tasmania 7001, Australia	Ph: 03 6222 8296	briony.patterson@dhhs.tas.gov.au	GDip Gen Couns
Amy Pearn	The Gene Council, Perth, Australia, PO Box 510, North Perth, WA 6906, Australia	Ph: (08) 6118 3586	amypearn@thegenecouncil.com.au	GDip Gen Couns
Kelly Phillips	Department of Medical Oncology, Peter MacCallum Cancer Centre, St Andrews Place, East Melbourne, VIC 3002	Ph: 03 9656 1810	kelly.phillips@petermac.org	MBBS, MD, FRACP
Ellen Pieper	Associate Genetic Counsellor, Parkville Familial Cancer Centre and Genomic Medicine, VCCC, Grattan Street, Melbourne, Vic 3000, Australia	Ph: 61 3 9342 7151	Ellen.Pieper@mh.org.au	GDip Gen Couns
Susan Ramus	School of Women's and Children's Health, Adult Cancer Program, Level 2, Lowy Cancer Research, Centre, Cnr High and Botany St, UNSW	Ph: 02 9385 1720	s.ramus@unsw.edu.au
Edwina Rickard	Familial Cancer Centre, Westmead Hospital, Westmead, NSW 2145	Ph: 02 9845 6947	edwina_rickard@wmi.usyd.edu.au	GDip Gen Couns
Bridget Robinson	Oncology Service, Christchurch Hospital, Private Bag 4710, Christchurch, New Zealand	Ph: 03 364 0020	brobinson@chmeds.ac.nz	BMedSc MD FRACP
Mona Saleh	Centre for Genetic Education, Prince of Wales Hospital, Randwick, NSW 2031	Ph: 02 9926 7324	msaleh@nsccahs.health.nsw.gov.au	PhD
Anita Skandarajah	Deputy Director, General Surgery, The Royal Melbourne Hospital, Consultant, Breast and Endocrine Surgeon, The Royal Melbourne Hospital and Peter Mac Callum Centre, The University of Melbourne	Ph: 03 93475785	anita.skandarajah@mh.org.au
Elizabeth Salisbury	Anatomical Pathology, Conjoint Associate Professor, UNSW, Prince of Wales Hospital, Randwick, 2031 NSW	Ph: 02 9382 9025	E.Salisbury@westernsydney.edu.au	MBBS, FRCPA
Christobel Saunders	Director, Breast Surgery, The Royal Melbourne Hospital, The Royal Melbourne Hospital and Peter Mac Callum Centre, The University of Melbourne	Ph: 93475785	christobel.saunders@uwa.edu.au	MB BS, FRCS, FRACS, FAAHMS
Jodi Saunus	Breast Pathology, University of Queensland Centre for Clinical Research, Building 71/918, The Royal Brisbane and Women's Hospital, Herston, Qld 4029	Ph: 07 3346 6048	j.saunus@uq.edu.au	PhD
Peter Savas	Peter MacCallum Cancer Centre, Department of Medical Oncology, St Andrews Place, East Melbourne, VIC 3002	Ph: 03 8559 7134	Peter.savas@petermac.org	MBBS, PhD,FRACP
Rodney Scott	Hunter Area Pathology Service, John Hunter Hospital, Locked Bag 1, Regional Mail Centre, NSW 2310	Ph: 02 4921 3000	Rodney.Scott@hnehealth.nsw.gov.au	PhD
Clare Scott	Research Department, WEHI C/o, Royal Melbourne Hospital, Parkville, 3050	Ph: 03 9345 2555	scottc@wehi.edu.au	MBBS, PhD,FRACP
Adrienne Sexton	Familial Cancer Centre, Royal Melbourne Hospital, Grattan Street, Parkville, Vic 3050	Ph: 9342 7151	Adrienne.Sexton@mh.org.au	GDip Gen Couns
Joanne Shaw	Executive Director, Psycho-Oncology Cooperative Research Group (PoCoG), Senior Research Fellow School of Psychology, Faculty of Science, The University Of Sydney	Ph: 02 9351 3761	joanne.shaw@sydney.edu.au	PhD
Andrew Shelling	Obstetrics and Gynaecology, University of Auckland, New Zealand		a.shelling@auckland.ac.nz	PhD
Shweta Srinivasa	Staff Specialist in Cancer Genetics, Westmead Familial Cancer Service	Ph: 02 8890 6947	Shweta.Srinivasa@health.nsw.gov.au	MBBS
Peter Simpson	The University of Queensland, Building 71/918, RBWH Campus, Herston, Qld 4029	Ph: 07 3346 6048	p.simpson@uq.edu.au	PhD
Melissa Southey	Genetic Epidemiology Laboratory, Department of Pathology, University of Melbourne, VIC 3010	Ph: 03 8344 4895	msouthey@unimelb.edu.au	PhD
Amanda Spurdle	Cancer Unit, Queensland Institute of Medical Research, Herston, QLD 4029	Ph: 07 3362 0371	mandyS@qimr.edu.au	PhD
Jessica Taylor	Familial Cancer and Genetics Medicine, Royal Melbourne Hospital, 2nd Floor, Grattan Street, Parkville, Vic 3050, Australia	Ph: 03 9342 7151	jessica.taylor@mh.org.au	GDip Gen Couns
Renea Taylor	Deputy Head, Cancer Program, Monash University, Rm 349, Level 3, Building 76, 19 Innovation Walk, Clayton, VIC 3800	Ph: 03 9902 9287	renea.taylor@monash.edu	PhD
Heather Thorne	Research Department, Peter MacCallum Cancer Centre, St Andrews Place, East Melbourne, VIC 3002	Ph: 03 96561542	heather.thorne@petermac.org	Grad Dip Clin Res
Alison Trainer	University of NSW, Prince of Wales Hospital, Barker Street, Randwick, NSW 2031	Ph: 02 9382 2551	Alison.Trainer@sesiahs.health.nsw.gov.au	MBBS, PhD
Kathy Tucker	Heredity Cancer Clinic, Prince of Wales Hospital, Randwick, NSW 2031	Ph: 02 93822551	TuckerK@sesahs.nsw.gov.au	MBBS, FRACP
Jane Visvader	The Walter and Eliza Hall Institute of Medical Research, Post Office Royal Melbourne Hospital, Parkville, VIC 3050	Ph: 03 9342 2555	visvader@wehi.edu.au	PhD
Logan Walker	Molecular Cancer Epidemiology Laboratory, Queensland Institute of Medical Research, P.O. Royal Brisbane Hospital, Herston, Qld 4027, Australia	Ph: 07 3362 0395	logan.walker@qimr.edu.au	PhD
Rachael Williams	Family Cancer Clinic, St Vincent's Hospital, Darlinghurst, NSW 2010	Ph: 02 8382 3395	rwilliams@stvincents.com.au	GDip Gen Couns
Ingrid Winship	Department of Genetics, Royal Melbourne Hospital, Parkville, 3050	Ph: 03 9342 7000	Ingrid.Winship@mh.org.au	MB ChB, MD, FRACP, FACD, FAICD
Mary Ann Young	Genome.One, 370 Victoria St, Darlinghurst, 2010 NSW	Ph: 02 9359 8002	m.young@garvan.org.au	MHSc
Milita Zaheed	Staff Specialist, Prince of Wales Hereditary Cancer Centre, Level 1, Bright Building, Barker Street, Randwick, NSW 2031	Ph: 02 9382 5107	Milita.Zaheed@health.nsw.gov.au

AUTHOR CONTRIBUTIONS

Conception and design: Cristina Fortuno, Bing-Jian Feng, David Goldgar, Paul A. James, Amanda B. Spurdle

Financial support: Amanda B. Spurdle

Administrative support: Elisa Cops, Amanda B. Spurdle

Provision of study materials or patients: Wendy Kohlmann, Conxi Lázaro, Lidia Feliubadaló, Silvia Iglesias, Mireia Menéndez, David M. Thomas, Ainsley Campbell, Judy Kirk, Nicola Poplawski, Rachel Susman, Kathy Tucker, Rachel Williams, Elisa Cops, Paul A. James

Collection and assembly of data: Bing-Jian Feng, Giovanni Innella, Wendy Kohlmann, Conxi Lázaro, Joan Brunet, Lidia Feliubadaló, Silvia Iglesias, Mireia Menéndez, Alex Teulé, Mandy L. Ballinger, David M. Thomas, Ainsley Campbell, Mike Field, Judy Kirk, Nicholas Pachter, Rachel Susman, Kathy Tucker, Mathew Wallis, Rachel Williams, Elisa Cops, Paul A. James, Amanda B. Spurdle

Data analysis and interpretation: Cristina Fortuno, Bing-Jian Feng, Courtney Carroll, Giovanni Innella, Conxi Lázaro, Alex Teulé, Marion Harris, Judy Kirk, Nicola Poplawski, David Goldgar, Paul A. James, Amanda B. Spurdle

Manuscript writing: All authors

Final approval of manuscript: All authors

Accountable for all aspects of the work: All authors

AUTHORS' DISCLOSURES OF POTENTIAL CONFLICTS OF INTEREST

The following represents disclosure information provided by authors of this manuscript. All relationships are considered compensated unless otherwise noted. Relationships are self-held unless noted. I = Immediate Family Member, Inst = My Institution. Relationships may not relate to the subject matter of this manuscript. For more information about ASCO's conflict of interest policy, please refer to www.asco.org/rwc or ascopubs.org/po/author-center.

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