Biology of breast cancer during pregnancy using genomic profiling
Hatem A Azim1, Sylvain Brohée2, Fedro A Peccatori2
1Department of MedicineInstitut Jules Bordet, BrEAST Data Centre, Université Libre de Bruxelles (ULB), Boulevard de Waterloo, 121, 1000 Brussels, BelgiumBreast Cancer Translational Research Laboratory (BCTL) J. C. HeusonInstitut Jules Bordet, Université Libre de Bruxelles (ULB), Brussels, BelgiumFertility and Procreation UnitDepartment of Gynecologic Oncology, European Institute of Oncology, Milan, ItalyTranslational Breast Cancer Genomic LabCancer Therapeutics Program, Peter MacCallum Cancer Centre, East Melbourne, Victoria, AustraliaSir Peter MacCallum Department of OncologyUniversity of Melbourne, Parkville, Victoria, AustraliaVesalius Research CentreVIB, Leuven, BelgiumLaboratory of Translational GeneticsDepartment of Oncology, University of Leuven, Leuven, BelgiumDepartment of PathologyDivision of Epidemiology and BiostatisticsEuropean Institute of Oncology, Milan, ItalyDepartment of MedicineMedical Oncology Clinic, Institut Jules Bordet, Université Libre de Bruxelles (ULB), Brussels, BelgiumDepartment of MedicineInstitut Jules Bordet, BrEAST Data Centre, Université Libre de Bruxelles (ULB), Boulevard de Waterloo, 121, 1000 Brussels, BelgiumBreast Cancer Translational Research Laboratory (BCTL) J. C. HeusonInstitut Jules Bordet, Université Libre de Bruxelles (ULB), Brussels, BelgiumFertility and Procreation UnitDepartment of Gynecologic Oncology, European Institute of Oncology, Milan, ItalyTranslational Breast Cancer Genomic LabCancer Therapeutics Program, Peter MacCallum Cancer Centre, East Melbourne, Victoria, AustraliaSir Peter MacCallum Department of OncologyUniversity of Melbourne, Parkville, Victoria, AustraliaVesalius Research CentreVIB, Leuven, BelgiumLaboratory of Translational GeneticsDepartment of Oncology, University of Leuven, Leuven, BelgiumDepartment of PathologyDivision of Epidemiology and BiostatisticsEuropean Institute of Oncology, Milan, ItalyDepartment of MedicineMedical Oncology Clinic, Institut Jules Bordet, Université Libre de Bruxel
Abstract:
Breast cancer during pregnancy is rare and is associated with relatively poor prognosis. No information is available on its biological features at the genomic level. Using a dataset of 54 pregnant and 113 non-pregnant breast cancer patients, we evaluated the pattern of hot spot somatic mutations and did transcriptomic profiling using Sequenom and Affymetrix respectively. We performed gene set enrichment analysis to evaluate the pathways associated with diagnosis during pregnancy. We also evaluated the expression of selected cancer-related genes in pregnant and non-pregnant patients and correlated the results with changes occurring in the normal breast using a pregnant murine model. We finally investigated aberrations associated with disease-free survival (DFS). No significant differences in mutations were observed. Of the total number of patients, 18.6% of pregnant and 23% of non-pregnant patients had a PIK3CA mutation. Around 30% of tumors were basal, with no differences in the distribution of breast cancer molecular subtypes between pregnant and non-pregnant patients. Two pathways were enriched in tumors diagnosed during pregnancy: the G protein-coupled receptor pathway and the serotonin receptor pathway (FDR <0.0001). Tumors diagnosed during pregnancy had higher expression of PD1 (PDCD1; P=0.015), PDL1 (CD274; P=0.014), and gene sets related to SRC (P=0.004), IGF1 (P=0.032), and β-catenin (P=0.019). Their expression increased almost linearly throughout gestation when evaluated on the normal breast using a pregnant mouse model underscoring the potential effect of the breast microenvironment on tumor phenotype. No genes were associated with DFS in a multivariate model, which could be due to low statistical power. Diagnosis during pregnancy impacts the breast cancer transcriptome including potential cancer targets.
