ESTIMATING CANCER PENETRANCES FROM GENETIC TEST RESULTS: Analysis of the Families from the Italian Registry of Hereditary Breast/ovarian Cancer Fabio Marroni, Paolo Aretini, Emma D'Andrea, Maria Adelaide Caligo, Alessandra Viel, Laura Cortesi, Enrico Ricevuto, Simona Agata, Roberta Bisegna, Mauro Boiocchi, Luigi Chieco-Bianchi, Giovanna Cipollini, Massimo Federico, Chiara Ghimenti, Clelia De Giacomi, Arcangela De Nicolo, Lara Della Puppa, Sergio Ferrari, Corrado Ficorella, Davide Iandolo, Paolo Marchetti, Chiara Menin, Marco Montagna, Manuela Santarosa, Vittorio Silingardi, Daniela Turchetti, Generoso Bevilacqua, Joan E. Bailey- Wilson, Giovanni Parmigiani, Silvano Presciuttini

Participating Institutions Department of Oncology, Transplants and New Technologies in Medicine, Section of Pathology; Department of Biomedicine University of Pisa, Italy Department of Oncology and Surgical Sciences, Section of Oncology; IST, Section of Viral and Molecular Oncology; Azienda Ospedaliera University of Padua, Italy Experimental Oncology ; Medical Oncology 3; Oncology Referral Centre, IRCCS Aviano (PN), Italy Department of Experimental Medicine University of L'Aquila, Italy Department of Biomedical Science, Section of Biological Chemistry; Department of Oncology and Hematology University of Modena and Reggio Emilia, Italy Inherited Disease Research Branch, NHGRI Baltimore, MD, USA Departments of Oncology and Biostatistics, JHU Baltimore, MD, USA

Introduction  A relevant proportion of breast and ovarian cancers is attributable to germline mutations in BRCA1 and BRCA2  Accurate evaluation of the probability that an individual carries a germline pathogenic mutation at BRCA1 or BRCA2 is therefore essential to help counselors and counselands decide whether testing is appropriate.

Computing carrier probability  BRCAPRO is a widely used software that compute the carrier probability for BRCA1/2 genes in probands, based on their family history of breast and ovarian cancer in first- and second-degree relatives.  In a previous validation study, we applied BRCAPRO to a series of 568 Italian families tested for BRCA1/2 (80 mutations found in BRCA1, and 53 in BRCA2).  The overall performance of BRCAPRO was better than that of other models; however, our results revealed promising prospects for substantial improvement.

A larger-than-predicted number of BRCA1/2 mutations was identified in families at relatively low risk A case of inaccurate predictions

The ability of discriminating between genes was limited in families stratified by profile A second example of inaccurate predictions

Aim of this work  In the present study we obtained improved estimates of the parameters (allele frequencies and cancer penetrances in carriers and non-carriers) that compose the genetic model on which prediction is formulated  We maximized the retrospective likelihood of the model, given the observed test results, using a MCMC approach; BRCAPRO was used as a probability calculation tool.  A total of 13 parameters were estimated: three for each of four penetrance functions (breast and ovarian cancer in BRCA1 and BRCA2 carriers) one for the ratio of BRCA1/BRCA2 mutation frequencies

Study design GENETIC MODEL Stop when convergence criteria are met Individual prediction for all families Calculation of total log-likelihood Explore new Parameter values MODIFIED MODEL Re-calculation of total log-likelihood Compare log-likelihoods Accept/Reject modified model

Results  Likelihood reached a stable value after about 5,000 iterations; chains were continued for about 10,000 additional iterations. The final acceptance rate was about 17%.  The final log-likelihood was about –326, vs. an initial value of about –396, with a difference of 70 log units; this difference is substantial, corresponding to a ratio of likelihood of over Our new genetic model is well supported.

1) new penetrance function of breast cancer in BRCA1 carriers Risk of Breast Cancer AgeOriginal values MCMC estimates 303%2% 5046%22% 7069%46% New estimate

2) new penetrance function of ovarian cancer in BRCA1 carriers Risk of Ovarian Cancer AgeOriginalMCMC %1% 5011%12% 7030%52% New estimate

3) new penetrance function of breast cancer in BRCA2 carriers Risk of Breast Cancer AgeOriginalMCMC 301% 5028%23% 7067%49% New estimate

4) new penetrance function of ovarian cancer in BRCA2 carriers Risk of Ovarian Cancer AgeOriginalMCMC %0.1% 503%2% 7019%22% New estimate

Examining the consequences of the new model (1) Expected/ observed number of mutations in families stratified by risk

Examining the consequences of the new model (2) Discriminating between the two genes

Discussion  We estimated the penetrance functions by maximizing the likelihood of the genotypes given the observed phenotypes; this is therefore what is called the “retrospective likelihood” (Kraft and Thomas, AJHG 2000).  The parameter estimates based on the retrospective likelihood remain unbiased even when the ascertainment scheme cannot be modeled.  The retrospective likelihood is not efficient in estimating absolute penetrance; we therefore estimated penetrance odds ratios and obtained absolute penetrances for carriers and non- carriers based on incidence of cancer in the general population

Conclusions  Our data refer to a substantial proportion of the families that currently require genetic counseling in Italy; therefore our new penetrance estimates provide the most accurate genetic model so far available for this population segment, and may lead to a mutation-predicting model specifically adapted to this country and to development of an Italian customized version of BRCAPRO.