Author ORCID Identifier


Date of Graduation


Document Type

Thesis (MS)

Program Affiliation

Biomedical Sciences

Degree Name

Masters of Science (MS)

Advisor/Committee Chair

Wenyi Wang

Committee Member

Guillermina Lozano

Committee Member

Nicholas Navin

Committee Member

Elmer Bernstam

Committee Member

Ryan Sun


Li-Fraumeni syndrome (LFS) is an inherited cancer syndrome caused by a deleterious mutation in TP53. An estimated 48% of LFS patients present due to a de novo mutation (DNM) in TP53. The knowledge of DNM status, DNM or familial mutation (FM), of an LFS patient requires genetic testing of both parents which is often inaccessible, making de novo LFS patients difficult to study. Famdenovo.TP53 is a Mendelian Risk prediction model used to predict DNM status of TP53 mutation carriers based on the cancer-family history and several input genetic parameters, including disease-gene penetrance. The good predictive performance of Famdenovo.TP53 was demonstrated using data collected from four historical US cohorts. We hypothesize that by incorporating penetrance estimates that are specific for different types of cancers diagnosed in family members, we can develop a model with further improved calibration, accuracy and prediction. We present Famdenovo.CS, which uses cancerspecific penetrance estimates that were derived previously using a Bayesian semiparametric competing risk model, to calculate the DNM probability. We validate Famdenovo.CS on 206 LFS families with known DNM status, from five different US cohorts. We used the concordance index (AUC), observed:expected ratios (OE) and Brier score (BS) to measure our model’s discrimination, calibration and accuracy, respectively. We use our model to analyze 101 families recently collected from the Clinical Cancer Genetic program at MD Anderson Cancer Center (CCG-MDA). We vii estimate the proportion of probands that present a DNM and compare DNM to FM carriers in several areas: cancer types diagnosed, age at diagnosis and mutations in TP53. Famdenovo.CS showed similar performance to Famdenovo.TP53 in terms of discrimination with AUC of 0.95 and 0.77 in validation sets A and B respectively; while improving on the model accuracy and calibration, demonstrated by a significant decrease in the BS (-0.091, 95%. CI [-0.19, -0.024]) and improved OE (1.17, 95% CI [0.90, 1.46]). Of the 101 probands in the CCG-MDA cohort, we predict 39 to be DNMs and 62 to be FMs. The cancer types and ages of diagnosis observed in FMs and DNMs are similarly distributed. DNMs in TP53 are a prevalent cause of LFS and we did not find differences in the clinical characteristics of DNM and FM carriers. Our model allows for a systematic identification and characterization of TP53 DNM carriers.


TP53, Li Fraumeni syndrome, de novo, germline mutations, Mendelian models



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