Evidence-based recommendations for gene-specific ACMG/AMP variant classification from the ClinGen ENIGMA BRCA1 and BRCA2 Variant Curation Expert Panel.

The ENIGMA research consortium develops and applies methods to determine clinical significance of variants in hereditary breast and ovarian cancer genes. An ENIGMA BRCA1/2 classification sub-group, formed in 2015 as a ClinGen external expert panel, evolved into a ClinGen internal Variant Curation Expert Panel (VCEP) to align with Food and Drug Administration recognized processes for ClinVar contributions. The VCEP reviewed American College of Medical Genetics and Genomics/Association of Molecular Pathology (ACMG/AMP) classification criteria for relevance to interpreting BRCA1 and BRCA2 variants. Statistical methods were used to calibrate evidence strength for different data types. Pilot specifications were tested on 40 variants and documentation revised for clarity and ease of use. The original criterion descriptions for 13 evidence codes were considered non-applicable or overlapping with other criteria. Scenario of use was extended or re-purposed for eight codes. Extensive analysis and/or data review informed specification descriptions and weights for all codes. Specifications were applied to pilot variants with pre-existing ClinVar classification as follows: 13 uncertain significance or conflicting, 14 pathogenic and/or likely pathogenic, and 13 benign and/or likely benign. Review resolved classification for 11/13 uncertain significance or conflicting variants and retained or improved confidence in classification for the remaining variants. Alignment of pre-existing ENIGMA research classification processes with ACMG/AMP classification guidelines highlighted several gaps in the research processes and the baseline ACMG/AMP criteria. Calibration of evidence strength was key to justify utility and strength of different data types for gene-specific application. The gene-specific criteria demonstrated value for improving ACMG/AMP-aligned classification of BRCA1 and BRCA2 variants.

Co-observation of germline pathogenic variants in breast cancer predisposition genes: Results from analysis of the BRIDGES sequencing dataset.

Co-observation of a gene variant with a pathogenic variant in another gene that explains the disease presentation has been designated as evidence against pathogenicity for commonly used variant classification guidelines. Multiple variant curation expert panels have specified, from consensus opinion, that this evidence type is not applicable for the classification of breast cancer predisposition gene variants. Statistical analysis of sequence data for 55,815 individuals diagnosed with breast cancer from the BRIDGES sequencing project was undertaken to formally assess the utility of co-observation data for germline variant classification. Our analysis included expected loss-of-function variants in 11 breast cancer predisposition genes and pathogenic missense variants in BRCA1, BRCA2, and TP53. We assessed whether co-observation of pathogenic variants in two different genes occurred more or less often than expected under the assumption of independence. Co-observation of pathogenic variants in each of BRCA1, BRCA2, and PALB2 with the remaining genes was less frequent than expected. This evidence for depletion remained after adjustment for age at diagnosis, study design (familial versus population-based), and country. Co-observation of a variant of uncertain significance in BRCA1, BRCA2, or PALB2 with a pathogenic variant in another breast cancer gene equated to supporting evidence against pathogenicity following criterion strength assignment based on the likelihood ratio and showed utility in reclassification of missense BRCA1 and BRCA2 variants identified in BRIDGES. Our approach has applicability for assessing the value of co-observation as a predictor of variant pathogenicity in other clinical contexts, including for gene-specific guidelines developed by ClinGen Variant Curation Expert Panels.

Challenges and approaches to calibrating patient phenotype as evidence for cancer gene variant classification under ACMG/AMP guidelines.

Since first publication of the American College of Medical Genetics and Genomics/Association for Medical Pathology (ACMG/AMP) variant classification guidelines, additional recommendations for application of certain criteria have been released (https://clinicalgenome.org/docs/), to improve their application in the diagnostic setting. However, none have addressed use of the PS4 and PP4 criteria, capturing patient presentation as evidence towards pathogenicity. Application of PS4 can be done through traditional case-control studies, or "proband counting" within or across clinical testing cohorts. Review of the existing PS4 and PP4 specifications for Hereditary Cancer Gene Variant Curation Expert Panels revealed substantial differences in the approach to defining specifications. Using BRCA1, BRCA2 and TP53 as exemplar genes, we calibrated different methods proposed for applying the "PS4 proband counting" criterion. For each approach, we considered limitations, non-independence with other ACMG/AMP criteria, broader applicability, and variability in results for different datasets. Our findings highlight inherent overlap of proband-counting methods with ACMG/AMP frequency codes, and the importance of calibration to derive dataset-specific code weights that can account for potential between-dataset differences in ascertainment and other factors. Our work emphasizes the advantages and generalizability of logistic regression analysis over simple proband-counting approaches to empirically determine the relative predictive capacity and weight of various personal clinical features in the context of multigene panel testing, for improved variant interpretation. We also provide a general protocol, including instructions for data formatting and a web-server for analysis of personal history parameters, to facilitate dataset-specific calibration analyses required to use such data for germline variant classification.

Shariant platform: Enabling evidence sharing across Australian clinical genetic-testing laboratories to support variant interpretation.

Sharing genomic variant interpretations across laboratories promotes consistency in variant assertions. A landscape analysis of Australian clinical genetic-testing laboratories in 2017 identified that, despite the national-accreditation-body recommendations encouraging laboratories to submit genotypic data to clinical databases, fewer than 300 variants had been shared to the ClinVar public database. Consultations with Australian laboratories identified resource constraints limiting routine application of manual processes, consent issues, and differences in interpretation systems as barriers to sharing. This information was used to define key needs and solutions required to enable national sharing of variant interpretations. The Shariant platform, using both the GRCh37 and GRCh38 genome builds, was developed to enable ongoing sharing of variant interpretations and associated evidence between Australian clinical genetic-testing laboratories. Where possible, two-way automated sharing was implemented so that disruption to laboratory workflows would be minimized. Terms of use were developed through consultation and currently restrict access to Australian clinical genetic-testing laboratories. Shariant was designed to store and compare structured evidence, to promote and record resolution of inter-laboratory classification discrepancies, and to streamline the submission of variant assertions to ClinVar. As of December 2021, more than 14,000 largely prospectively curated variant records from 11 participating laboratories have been shared. Discrepant classifications have been identified for 11% (28/260) of variants submitted by more than one laboratory. We have demonstrated that co-design with clinical laboratories is vital to developing and implementing a national variant-interpretation sharing effort. This approach has improved inter-laboratory concordance and enabled opportunities to standardize interpretation practices.

Clinical implications of VUS reclassification in a single-centre series from application of ACMG/AMP classification rules specified for BRCA1/2.

BACKGROUND: BRCA1/2 testing is crucial to guide clinical decisions in patients with hereditary breast/ovarian cancer, but detection of variants of uncertain significance (VUSs) prevents proper management of carriers. The ENIGMA (Evidence-based Network for the Interpretation of Germline Mutant Alleles) BRCA1/2 Variant Curation Expert Panel (VCEP) has recently developed BRCA1/2 variant classification guidelines consistent with ClinGen processes, specified against the ACMG/AMP (American College of Medical Genetics and Genomics/Association for Molecular-Pathology) classification framework. METHODS: The ClinGen-approved BRCA1/2-specified ACMG/AMP classification guidelines were applied to BRCA1/2 VUSs identified from 2011 to 2022 in a series of patients, retrieving information from the VCEP documentation, public databases, literature and ENIGMA unpublished data. Then, we critically re-evaluated carrier families based on new results and checked consistency of updated classification with main sources for clinical interpretation of BRCA1/2 variants. RESULTS: Among 166 VUSs detected in 231 index cases, 135 (81.3%) found in 197 index cases were classified by applying BRCA1/2-specified ACMG/AMP criteria: 128 (94.8%) as Benign/Likely Benign and 7 (5.2%) as Pathogenic/Likely Pathogenic. The average time from the first report as 'VUS' to classification using this approach was 49.4 months. Considering that 15 of these variants found in 64 families had already been internally reclassified prior to this work, this study provided 121 new reclassifications among the 151 (80.1%) remaining VUSs, relevant to 133/167 (79.6%) families. CONCLUSIONS: These results demonstrated the effectiveness of new BRCA1/2 ACMG/AMP classification guidelines for VUS classification within a clinical cohort, and their important clinical impact. Furthermore, they suggested a cadence of no more than 3 years for regular review of VUSs, which however requires time, expertise and resources.

Breast Cancer Risk Genes - Association Analysis in More than 113,000 Women.

BACKGROUND: Genetic testing for breast cancer susceptibility is widely used, but for many genes, evidence of an association with breast cancer is weak, underlying risk estimates are imprecise, and reliable subtype-specific risk estimates are lacking. METHODS: We used a panel of 34 putative susceptibility genes to perform sequencing on samples from 60,466 women with breast cancer and 53,461 controls. In separate analyses for protein-truncating variants and rare missense variants in these genes, we estimated odds ratios for breast cancer overall and tumor subtypes. We evaluated missense-variant associations according to domain and classification of pathogenicity. RESULTS: Protein-truncating variants in 5 genes (ATM, BRCA1, BRCA2, CHEK2, and PALB2) were associated with a risk of breast cancer overall with a P value of less than 0.0001. Protein-truncating variants in 4 other genes (BARD1, RAD51C, RAD51D, and TP53) were associated with a risk of breast cancer overall with a P value of less than 0.05 and a Bayesian false-discovery probability of less than 0.05. For protein-truncating variants in 19 of the remaining 25 genes, the upper limit of the 95% confidence interval of the odds ratio for breast cancer overall was less than 2.0. For protein-truncating variants in ATM and CHEK2, odds ratios were higher for estrogen receptor (ER)-positive disease than for ER-negative disease; for protein-truncating variants in BARD1, BRCA1, BRCA2, PALB2, RAD51C, and RAD51D, odds ratios were higher for ER-negative disease than for ER-positive disease. Rare missense variants (in aggregate) in ATM, CHEK2, and TP53 were associated with a risk of breast cancer overall with a P value of less than 0.001. For BRCA1, BRCA2, and TP53, missense variants (in aggregate) that would be classified as pathogenic according to standard criteria were associated with a risk of breast cancer overall, with the risk being similar to that of protein-truncating variants. CONCLUSIONS: The results of this study define the genes that are most clinically useful for inclusion on panels for the prediction of breast cancer risk, as well as provide estimates of the risks associated with protein-truncating variants, to guide genetic counseling. (Funded by European Union Horizon 2020 programs and others.).

CHEK2 is not a Li-Fraumeni syndrome gene: time to update public resources.

The gene-disease relationship for CHEK2 remains listed as 'Li-Fraumeni syndrome 2' in public resources such as OMIM and MONDO, despite published evidence to the contrary, causing frustration among Li-Fraumeni syndrome (LFS) clinical experts. Here, we compared personal cancer characteristics of 2095 CHEK2 and 248 TP53 pathogenic variant carriers undergoing multigene panel testing at Ambry Genetics against 15 135 individuals with no known pathogenic variant. Our results from a within-cohort logistic regression approach highlight obvious differences between clinical presentation of TP53 and CHEK2 pathogenic variant carriers, with no evidence of CHEK2 being associated with any of the TP53-related core LFS cancers. These findings emphasise the need to replace 'Li-Fraumeni syndrome 2' as the CHEK2-associated disease name, thereby limiting potential confusion.

Estimating the proportion of pathogenic variants from breast cancer case-control data: Application to calibration of ACMG/AMP variant classification criteria.

For genes with reliable estimates of disease risk associated with loss-of-function variants, case-control data can be used to estimate the proportion of variants of typical risk effect for defined groups of variants, of relevance for variant classification. A calculation was derived for a maximum likelihood estimate of the proportion of pathogenic variants of typical effect from case-control data and applied to rare variant counts for ATM, BARD1, BRCA1, BRCA2, CHEK2, PALB2, RAD51C, and RAD51D from published breast cancer studies: BEACCON (5770 familial cases and 5741 controls) and breast cancer risk after diagnostic sequencing (60,466 familial and population-based cases and 53,461 controls). There was significant evidence of pathogenic variants among rare noncoding variants, in particular deeper intronic variants, for BRCA1 (13%, p = 8.3 × 10-7 ), BRCA2 (6%, p = 0.016) and PALB2 (13%, p = 0.001). The estimated proportion of pathogenic missense variants varied markedly between genes, generally with enrichment in familial cases, for example, 9% for BRCA2 versus 60%-90% for CHEK2. Stratifying missense variants by position indicated that, for most genes, location within a functional domain significantly predicted pathogenicity, whereas location outside domains provided robust evidence against pathogenicity. Our approach provides novel insights into the spectrum of pathogenic variants of specific breast cancer genes and has wider application to inform gene-focused specifications of American College of Medical Genetics and Genomics (ACMG)/Association of Molecular Pathology (AMP) codes for variant curation.

Predictive functional assay-based classification of PMS2 variants in Lynch syndrome.

The large majority of germline alterations identified in the DNA mismatch repair (MMR) gene PMS2, a low-penetrance gene for the cancer predisposition Lynch syndrome, represent variants of uncertain significance (VUS). The inability to classify most VUS interferes with personalized healthcare. The complete in vitro MMR activity (CIMRA) assay, that only requires sequence information on the VUS, provides a functional analysis-based quantitative tool to improve the classification of VUS in MMR proteins. To derive a formula that translates CIMRA assay results into the odds of pathogenicity (OddsPath) for VUS in PMS2 we used a set of clinically classified PMS2 variants supplemented by inactivating variants that were generated by an in cellulo genetic screen, as proxies for cancer-predisposing variants. Validation of this OddsPath revealed high predictive values for benign and predisposing PMS2 VUS. We conclude that the OddsPath provides an integral metric that, following the other, higher penetrance, MMR proteins MSH2, MSH6 and MLH1 can be incorporated as strong evidence type into the upcoming criteria for MMR gene VUS classification of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology (ACMG/AMP).

Suspected clonal hematopoiesis as a natural functional assay of TP53 germline variant pathogenicity.

PURPOSE: Some variants identified by multigene panel testing of DNA from blood present with low variant allele fraction (VAF), often a manifestation of clonal hematopoiesis. Research has shown that the proportion of variants with low VAF is especially high in TP53, the Li-Fraumeni syndrome gene. Based on the hypothesis that variants with low VAF are positively selected as drivers of clonal hematopoiesis, we investigated the use of VAF as a predictor of TP53 germline variant pathogenicity. METHODS: We used data from 260,681 TP53 variants identified at 2 laboratories to compare the distribution of pathogenic and benign variants at different VAF intervals. RESULTS: Likelihood ratios toward pathogenicity associated with a VAF < 26% equated to the American College of Medical Genetics/Association of Molecular Pathology strong strength level and were applicable for 1 in 5 variants of unknown significance. CONCLUSION: In conclusion, detection of variants with low VAF in blood can be considered an in vivo functional assay to aid assessment of TP53 variant pathogenicity.

An updated quantitative model to classify missense variants in the TP53 gene: A novel multifactorial strategy.

Multigene panel testing has led to an increase in the number of variants of uncertain significance identified in the TP53 gene, associated with Li-Fraumeni syndrome. We previously developed a quantitative model for predicting the pathogenicity of P53 missense variants based on the combination of calibrated bioinformatic information and somatic to germline ratio. Here, we extended this quantitative model for the classification of P53 predicted missense variants by adding new pieces of evidence (personal and family history parameters, loss-of-function results, population allele frequency, healthy individual status by age 60, and breast tumor pathology). We also annotated which missense variants might have an effect on splicing based on bioinformatic predictions. This updated model plus annotation led to the classification of 805 variants into a clinically relevant class, which correlated well with existing ClinVar classifications, and resolved a large number of conflicting and uncertain classifications. We propose this model as a reliable approach to TP53 germline variant classification and emphasize its use in contributing to optimize TP53-specific ACMG/AMP guidelines.

Specifications of the ACMG/AMP variant interpretation guidelines for germline TP53 variants.

Germline pathogenic variants in TP53 are associated with Li-Fraumeni syndrome, a cancer predisposition disorder inherited in an autosomal dominant pattern associated with a high risk of malignancy, including early-onset breast cancers, sarcomas, adrenocortical carcinomas, and brain tumors. Intense cancer surveillance for individuals with TP53 germline pathogenic variants is associated with reduced cancer-related mortality. Accurate and consistent classification of germline variants across clinical and research laboratories is important to ensure appropriate cancer surveillance recommendations. Here, we describe the work performed by the Clinical Genome Resource TP53 Variant Curation Expert Panel (ClinGen TP53 VCEP) focused on specifying the American College of Medical Genetics and Genomics and the Association for Molecular Pathology (ACMG/AMP) guidelines for germline variant classification to the TP53 gene. Specifications were developed for 20 ACMG/AMP criteria, while nine were deemed not applicable. The original strength level for the 10 criteria was also adjusted due to current evidence. Use of TP53-specific guidelines and sharing of clinical data among experts and clinical laboratories led to a decrease in variants of uncertain significance from 28% to 12% compared with the original guidelines. The ClinGen TP53 VCEP recommends the use of these TP53-specific ACMG/AMP guidelines as the standard strategy for TP53 germline variant classification.

Differences in patient ascertainment affect the use of gene-specified ACMG/AMP phenotype-related variant classification criteria: Evidence for TP53.

The American College of Medical Genetics and Genomics/Association for Molecular Pathology (ACMG/AMP) guidelines for variant classification are widely used for clinical interpretation of gene test results. These guidelines may be specified to genes/syndromes of interest to improve their utility in the clinical setting. As part of these specifications, phenotype-related criteria can be detailed and weighted depending on the personal history of disease for a given variant carrier. We investigated how ascertainment can affect the significance and/or weight of patient phenotype as a predictor of germline-variant pathogenicity, using the Li-Fraumeni Syndrome gene TP53 as an example. Likelihood ratios in favor of variant pathogenicity were determined for a report of the personal history of several TP53-related cancers, using data from 2,656 probands undergoing single-gene testing (SGT) and 15,483 undergoing multi-gene panel testing (MGPT). Overall, TP53-associated cancers were more predictive of pathogenicity, and demonstrated greater evidence weight, in the MGPT versus SGT dataset. This observation is almost certainly explained by differences in proband ascertainment for the two streams of testing, and these findings have implications for germline-variant classification using ACMG/AMP guidelines.

Suggested application of HER2+ breast tumor phenotype for germline TP53 variant classification within ACMG/AMP guidelines.

Early onset breast cancer is the most common malignancy in women with Li-Fraumeni syndrome, caused by germline TP53 pathogenic variants. It has repeatedly been suggested that breast tumors from TP53 carriers are more likely to be HER2+ than those of noncarriers, but this information has not been incorporated into variant interpretation models for TP53. Breast tumor pathology is already being used quantitatively for assessing pathogenicity of germline variants in other genes, and it has been suggested that this type of evidence can be incorporated into current American College of Medical Genetics and Genomics/Association for Molecular Pathology (ACMG/AMP) guidelines for germline variant classification. Here, by reviewing published data and using internal datasets separated by different age groups, we investigated if breast tumor HER2+ status has utility as a predictor of TP53 germline variant pathogenicity, considering age at diagnosis. Overall, our results showed that the identification of HER2+ breast tumors diagnosed before the age of 40 can be conservatively incorporated into the current TP53-specific ACMG/AMP PP4 criterion, following a point system detailed in this manuscript. Further larger studies will be needed to reassess the value of HER2+ breast tumors diagnosed at a later age.

A quantitative model to predict pathogenicity of missense variants in the TP53 gene.

Germline pathogenic variants in the TP53 gene cause Li-Fraumeni syndrome, a condition that predisposes individuals to a wide range of cancer types. Identification of individuals carrying a TP53 pathogenic variant is linked to clinical management decisions, such as the avoidance of radiotherapy and use of high-intensity screening programs. The aim of this study was to develop an evidence-based quantitative model that integrates independent in silico data (Align-GVGD and BayesDel) and somatic to germline ratio (SGR), to assign pathogenicity to every possible missense variant in the TP53 gene. To do this, a likelihood ratio for pathogenicity (LR) was derived from each component calibrated using reference sets of assumed pathogenic and benign missense variants. A posterior probability of pathogenicity was generated by combining LRs, and algorithm outputs were validated using different approaches. A total of 730 TP53 missense variants could be assigned to a clinically interpretable class. The outputs of the model correlated well with existing clinical information, functional data, and ClinVar classifications. In conclusion, these quantitative outputs provide the basis for individualized assessment of cancer risk useful for clinical interpretation. In addition, we propose the value of the novel SGR approach for use within the ACMG/AMP guidelines for variant classification.

Current review of TP53 pathogenic germline variants in breast cancer patients outside Li-Fraumeni syndrome.

Pathogenic germline variants in TP53 predispose carriers to the multi-cancer Li-Fraumeni syndrome (LFS). Widespread multigene panel testing is identifying TP53 pathogenic variants in breast cancer patients outside the strict clinical criteria recommended for LFS testing. We aimed to assess frequency and clinical implications of TP53 pathogenic variants in breast cancer cohorts ascertained outside LFS. Classification of TP53 germline variants reported in 59 breast cancer studies, and publicly available population control sets was reviewed and identified evidence for misclassification of variants. TP53 pathogenic variant frequency was determined for: breast cancer studies grouped by ascertainment characteristics; breast cancer cohorts undergoing panel testing; and population controls. Early age of breast cancer onset, regardless of family history or BRCA1/BRCA2 previous testing, had the highest pick-up rate for TP53 carriers. Patients at risk of hereditary breast cancer unselected for features of LFS carried TP53 pathogenic variants at a frequency comparable to that of other non-BRCA1/2 breast cancer predisposing genes, and ∼threefold more than reported in population controls. These results have implications for the implementation of TP53 testing in broader clinical settings, and suggest urgent need to investigate cancer risks associated with TP53 pathogenic variants in individuals outside the LFS spectrum.

Improved, ACMG-compliant, in silico prediction of pathogenicity for missense substitutions encoded by TP53 variants.

Clinical interpretation of germline missense variants represents a major challenge, including those in the TP53 Li-Fraumeni syndrome gene. Bioinformatic prediction is a key part of variant classification strategies. We aimed to optimize the performance of the Align-GVGD tool used for p53 missense variant prediction, and compare its performance to other bioinformatic tools (SIFT, PolyPhen-2) and ensemble methods (REVEL, BayesDel). Reference sets of assumed pathogenic and assumed benign variants were defined using functional and/or clinical data. Area under the curve and Matthews correlation coefficient (MCC) values were used as objective functions to select an optimized protein multisequence alignment with best performance for Align-GVGD. MCC comparison of tools using binary categories showed optimized Align-GVGD (C15 cut-off) combined with BayesDel (0.16 cut-off), or with REVEL (0.5 cut-off), to have the best overall performance. Further, a semi-quantitative approach using multiple tiers of bioinformatic prediction, validated using an independent set of nonfunctional and functional variants, supported use of Align-GVGD and BayesDel prediction for different strength of evidence levels in ACMG/AMP rules. We provide rationale for bioinformatic tool selection for TP53 variant classification, and have also computed relevant bioinformatic predictions for every possible p53 missense variant to facilitate their use by the scientific and medical community.

Genetics of primary ovarian insufficiency: a review.

Primary ovarian insufficiency is one of the main causes of female infertility owing to an abnormal ovarian reserve. Its relevance has increased in more recent years due to the fact that age of motherhood is being delayed in developed countries, with the risk of having either primary ovarian insufficiency or less chances of pregnancy when women consider the option of having their first baby. Several exogenous factors can lead to this event, such us viral infections, metabolomic dysfunction, autoimmune diseases, and environmental or iatrogenic factors, although in most cases the mechanism that leads to the disorder is unknown. Genetic factors represent the most commonly identified cause and the impact of sex chromosome abnormalities (e.g., Turner syndrome or X structural abnormalities), autosomal and X-linked mutations on the genesis of primary ovarian insufficiency has also been well described. Yet in most cases, the genetic origin remains unknown and there are multiple candidate genes. This review aims to collect all the genetic abnormalities and genes associated with syndromic and non syndromic primary ovarian insufficiency that have been published in the literature to date using the candidate-gene approach and a genome-wide analysis.

TP53-associated early breast cancer: new observations from a large cohort.

BACKGROUND: A recent large, well-annotated international cohort of patients with Li-Fraumeni syndrome and early-stage breast cancer was examined for shared features. METHODS: This multicenter cohort study included women with a germline TP53 pathogenic or likely pathogenic variant and nonmetastatic breast cancer diagnosed between 2002 and 2022. Clinical and genetic data were obtained from institutional registries and clinical charts. Descriptive statistics were used to summarize proportions, and differences were assessed using χ2 or Wilcoxon rank sum tests. Metachronous contralateral breast cancer risk, radiation-induced sarcoma risk, and recurrence-free survival were analyzed using the Kaplan-Meier methodology. RESULTS: Among 227 women who met study criteria, the median age of first breast cancer diagnosis was 37 years (range = 21-71), 11.9% presented with bilateral synchronous breast cancer, and 18.1% had ductal carcinoma in situ only. In total, 166 (73.1%) patients underwent mastectomies, including 67 bilateral mastectomies as first breast cancer surgery. Among those patients with retained breast tissue, the contralateral breast cancer rate was 25.3% at 5 years. Among 186 invasive tumors, 72.1% were stages I to II, 48.9% were node negative, and the most common subtypes were hormone receptor-positive/HER2-negative (40.9%) and hormone receptor positive/HER2 positive (34.4%). At a median follow-up of 69.9 months (interquartile range = 32.6-125.9), invasive hormone receptor-positive/HER2-negative disease had the highest recurrence risk among the subtypes (5-year recurrence-free survival = 61.1%, P = .001). Among those who received radiation therapy (n = 79), the 5-year radiation-induced sarcoma rate was 4.8%. CONCLUSION: We observed high rates of ductal carcinoma in situ, hormone receptor-positive, and HER2-positive breast cancers, with a worse outcome in the hormone receptor-positive/HER2-negative luminal tumors, despite appropriate treatment. Confirmation of these findings in further studies could have implications for breast cancer care in those with Li-Fraumeni syndrome.

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

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.