Biology subjects

Mai, P. L.

Publications and source records attributed to Mai, P. L..

3 recordsLinked to original sources

bioRxiv2026

Cell-of-origin shapes tumor subtype in BRCA1-associated triple-negative breast cancer

Pathogenic germline BRCA1 variants greatly increase lifetime breast cancer risk, with no targeted prevention. Accrual of mutations following DNA repair errors in luminal progenitors is considered the chief mechanism of triple-negative breast cancer (TNBC) initiation, which cannot explain the organ specificity nor the phenotypic spectrum of the disease. Here we show that TNBC also originates in basal-myoepithelial cells, and that the cell of origin shapes TNBC subtype through aberrant epithelial differentiation, likely due to pleiotropic role of BRCA1 in regulating hormone signaling. Single-cell RNA sequencing of 67,001 cells from Wap-Cre Brca1/p53 mice and reanalysis of published Blg-Cre data show that aberrant basal-myoepithelial differentiation (Wap-Cre) generates the mesenchymal subtype (TNBC-M) and aberrant luminal differentiation (Blg-Cre) the basal-like subtype (TNBC-BL1). We also show that both subtypes occur at comparable frequency in BRCA1 carriers. Aberrant basal-myoepithelial differentiation precedes tumor formation, and only tumors derived from transplanted basal cells reproduce the basal-containing phenotype of spontaneous tumors. Comparison with a developmental atlas identifies de-differentiation of myoepithelial cells into basal cells lacking myoepithelial markers, a fetal state, whereas experimental metastases shift toward luminal states while retaining a TNBC-M-like transcriptional program. These findings support the inclusion of basal-myoepithelial and luminal cells in targeted prevention strategies for BRCA1 carriers, and adoption of TNBC subtyping for patient stratification and improving outcomes.

cancer biology↗

bioRxiv2020

A pedigree-based prediction model identifies carriers of deleterious de novo mutations in families with Li-Fraumeni syndrome

De novo mutations (DNMs) are increasingly recognized as rare disease causal factors. Identifying DNM carriers will allow researchers to study the likely distinct molecular mechanisms of DNMs. We developed Famdenovo to predict DNM status (DNM or familial mutation (FM)) of deleterious autosomal dominant germline mutations for any syndrome. We introduce Famdenovo.TP53 for Li-Fraumeni syndrome (LFS) and analyze 324 LFS family pedigrees from four US cohorts: a validation set of 186 pedigrees and a discovery set of 138 pedigrees. The concordance index for Famdenovo.TP53 prediction was 0.95 (95% CI: [0.92, 0.98]). Forty individuals (95% CI: [30, 50]) were predicted as DNM carriers, increasing the total number from 42 to 82. We compared clinical and biological features of FM versus DNM carriers: 1) cancer and mutation spectra along with parental ages were similarly distributed; 2) ascertainment criteria like early-onset breast cancer (age 20 to 35 years) provides a condition for an unbiased estimate of the DNM rate: 48% (23 DNMs versus 25 FMs); 3) hotspot mutation R248W was not observed in DNMs, although it was as prevalent as hotspot mutation R248Q in FMs. Furthermore, we introduce Famdenovo.BRCA for hereditary breast and ovarian cancer syndrome, and apply it to a small set of family data from the Cancer Genetics Network. In summary, we introduce a novel statistical approach to systematically evaluate deleterious DNMs in inherited cancer syndromes. Our approach may serve as a foundation for future studies evaluating how new deleterious mutations can be established in the germline, such as those in TP53.

genetics↗

bioRxiv2019

Risk of differential cancer types over age in families with Li-Fraumeni syndrome: a validation study using multi-center cohorts

Li-Fraumeni syndrome (LFS) is a rare hereditary cancer syndrome associated with an autosomal dominant mutation inheritance in the TP53 tumor suppressor gene and a wide spectrum of cancer diagnoses. An accurate estimation of the penetrance of different cancer types in LFS is crucial to improve the clinical characterization and management of high-risk individuals of LFS. Our competing risk-based statistical model incorporates the pedigree structure efficiently into the penetrance estimation and corrects for the ascertainment bias. A set of TP53 penetrance for three cancer types (breast, BR/sarcoma, SA/others, OT) involved in LFS is then estimated from 186 pediatric-sarcoma families collected at MD Anderson Cancer Center. The penetrance was then validated on a mixed cohort of clinically ascertained families with cancer (total number of families=668). The age-dependent onset probability distributions of specific cancer types are different. For breast cancer, the TP53 penetrance goes up at an earlier age than the reported BRCA1/2 penetrance. We validated the prediction performance of the penetrance estimates via two independent cohorts combined (BR=85, SA=540, OT=158). We obtained areas under the ROC curves (AUCs) of 0.92 (BR), 0.75 (SA), and 0.81 (OT). Our R package, LFSPRO, provides risk estimates for the diagnosis of breast cancer, sarcoma, other cancers or death before cancer diagnosis in future.\n\nSignificanceCancer-specific penetrance can facilitate clinical characterization of LFS and will contribute to the management of families at high risk of LFS.

genetics↗