Bing-Jian Feng

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.

Atypical cancer risk profile in carriers of Italian founder BRCA1 variant p.His1673del: Implications for classification and clinical management

Abstract Background BRCA1 :c.5017_5019del (p.His1673del) is a founder variant relatively frequent in Northern Italy. Despite previous suggestion of pathogenicity, variant classification in public databases is still conflicting, needing additional evidence. Methods Maximum likelihood penetrance of breast/ovarian and other cancer types was estimated using full pedigree data from 53 informative Italian families. The effect of the variant on BRCA1‐ABRAXAS1 interaction was assessed using a GFP‐fragment reassembly‐based PPI assay. Results were combined with additional data from multiple sources to classify the variant according to ACMG/AMP classification rules specified for BRCA1/2 . Results Variant‐carriers displayed increased risk for ovarian cancer (HR = 33.0, 95% CI = 7.0–155.0; cumulative risk at age 70 = 27.6%, 95% CI = 12.6–40.0%) but not for breast cancer (HR = 0.7, 95% CI = 0.2–2.2). An increased risk of uterine cancer (HR = 8.0, 95% CI = 1.03–61.6) emerged, warranting further evaluation. Likelihood‐ratio in favor of pathogenicity was 98898642.82 under assumption of standard BRCA1 breast and ovarian penetrance, and 104240832.84 after excluding breast cancer diagnoses (based on penetrance results). Functional analysis demonstrated that the variant abrogates the BRCA1‐ABRAXAS1 binding, supporting the PS3 code assignment within the ACMG/AMP rule‐based model. Collectively, these findings allowed to classify the variant as pathogenic. Conclusion Pathogenicity of BRCA1 :c.5017_5019del(p.His1673del) has been confirmed; however, breast cancer risk in Italian families is not increased, unlike in families from other countries and in carriers of most BRCA1 pathogenic variants. The knowledge of atypical risk profiles for this and other variants will pave the way for personalized management based on specific genotype.