Pcarrier: Individual and family distributions of a susceptibility gene for breast and ovarian cancer based on family history.

Abstract

e13005 Background: Most of the BRCA1/2 and PALB2 analyses performed in patients with a personal and familial history (FH) of breast/ovarian cancer are negative. In this context, there is no targeted analysis available to identify relatives at high risk (carrier of the causal hypothetical mutated gene). Thus, the recommendations of surveillance to all relatives are based only on the FH of cancer. At the Institut Curie we assess the degree of severity of the FH by calculating the probability of carrying a single autosomal dominant susceptibility gene without taking into account genotyping results but using the LINKAGE software with the parameters of the Claus-Easton model (1993). This reliable but old tool has a slow console interactive interface (roughly 15 min of clinicians time for each assessed family). Methods: We rewrite the model as a Bayesian network combining Mendelian genetics with classical survival analysis. All probabilistic computations are performed through belief propagation (sum-product algorithm) over real numbers or polynomials. The programming language is C++. Results: pCarrier is a modern and efficient implementation of the Claus-Easton model for clinicians with the following features: 1) fast non-interactive command line ( < 1s to process a previously registered family) combined with a graphical user-friendly interface; 2) computations dealing with monozygotic twins or loops without any human intervention (ex: loop breaking); 3) choice between the original discretized model (individual FH into 14 classes) and its continuous version (piecewise constant hazard); 4) marginal individual carrier distribution for all individuals in the pedigree; 5) joint distribution of the number of carriers among any group of individuals (ex: in the entire family, among the living only). Conclusions: pCarrier is experimented since January 2017 in the Institut Curie as a replacement of the existing tool and appears so far to be dramatically faster and easier to use for the clinicians, highly reliable (consistence with the existing tool), and able to provide new useful decision-making probabilities using the distribution of the number of carriers.