TY - JOUR
T1 - Peripheral blood DNA methylation predicts the early onset of primary tumor in TP53 mutation carriers
AU - Subasri, Vallijah
AU - Brew, Benjamin
AU - Laverty, Brianne
AU - Erdman, Lauren
AU - Guha, Tanya
AU - Hansford, Jordan R.
AU - Cairney, Elizabeth
AU - Portwine, Carol
AU - Elser, Christine
AU - Finlay, Jonathan L.
AU - Nichols, Kim E.
AU - Anson, Jo
AU - Kohlmann, Wendy
AU - Gong, Haifan
AU - Lees, Jodi
AU - Alon, Noa
AU - Brunga, Ledia
AU - Villani, Anita
AU - de Andrade, Kelvin C.
AU - Khincha, Payal P.
AU - Savage, Sharon A.
AU - Schiffman, Joshua D.
AU - Pugh, Trevor J.
AU - Malkin, David
AU - Goldenberg, Anna
N1 - Publisher Copyright:
© The Author(s) 2025.
PY - 2025/12
Y1 - 2025/12
N2 - Li-Fraumeni syndrome (LFS) confers high lifetime cancer risk due to germline TP53 pathogenic variants (PV). A comprehensive surveillance regimen termed the ‘Toronto Protocol’, has been adopted for early tumor detection, demonstrating improved survival among TP53 PV carriers. However, the protocol’s “one-size-fits-all” approach fails to consider individual cancer risk. To personalize screening, we developed a support vector machine model to predict early onset of primary tumors (age < 6) using peripheral blood methylation data of TP53 PV carriers (n = 237). Validation (n = 64) and external testing (n = 79) showed AUROC = 0.928 [0.835–1.000], F1-score = 0.692 [0.435–0.867], and NPV = 0.984 [0.946–1.000]. The model achieved 91% accuracy, correctly classifying 90% of patients with cancer before the age of six and 87% of cancer-free individuals in the external test set. Our tool enables risk stratification for early-onset malignancies, to optimize clinical surveillance and improve patient outcomes.
AB - Li-Fraumeni syndrome (LFS) confers high lifetime cancer risk due to germline TP53 pathogenic variants (PV). A comprehensive surveillance regimen termed the ‘Toronto Protocol’, has been adopted for early tumor detection, demonstrating improved survival among TP53 PV carriers. However, the protocol’s “one-size-fits-all” approach fails to consider individual cancer risk. To personalize screening, we developed a support vector machine model to predict early onset of primary tumors (age < 6) using peripheral blood methylation data of TP53 PV carriers (n = 237). Validation (n = 64) and external testing (n = 79) showed AUROC = 0.928 [0.835–1.000], F1-score = 0.692 [0.435–0.867], and NPV = 0.984 [0.946–1.000]. The model achieved 91% accuracy, correctly classifying 90% of patients with cancer before the age of six and 87% of cancer-free individuals in the external test set. Our tool enables risk stratification for early-onset malignancies, to optimize clinical surveillance and improve patient outcomes.
UR - https://www.scopus.com/pages/publications/105014158440
U2 - 10.1038/s41467-025-62894-5
DO - 10.1038/s41467-025-62894-5
M3 - Article
C2 - 40858599
AN - SCOPUS:105014158440
SN - 2041-1723
VL - 16
JO - Nature Communications
JF - Nature Communications
IS - 1
M1 - 7976
ER -