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IMPAKT 2017: Few Variations in Somatic Mutations Observed Between Pregnant and Non-Pregnant Patients with Breast Cancer

The frequencies of some specific mutations differ by hormone receptor status and between pregnant versus non-pregnant patients
04 May 2017
Translational Research;  Cancer and Pregnancy
Breast Cancer

Findings comparing the mutational landscape in pregnant and non-pregnant patients with breast cancer that sought to define whether the disease may have a different biology in pregnant women were reported at the IMPAKT Breast Cancer Conference, held in Brussels, Belgium, 4 to 6 May, 2017. Pregnancy is estimated to be a factor in 1 to 3% of all breast cancers.

IMPAKT 2017 Abstract 10P

Consort statement
Credit: Sibylle Loibl

Lead author Sibylle Loibl, Medicine and Research, German Breast Group, Neu-Isenburg, Germany presented data based on an evaluation of the patterns of somatic mutations between pregnant and non-pregnant patients with breast cancer. Professor Loibl and colleagues compared a dataset of pregnant patients enrolled in the BCP study (GBG 29; BIG 03-02), a multicentre, retrospective, observational study of women with simultaneous breast cancer and pregnancy to non-pregnant control patients with breast cancer obtained from the TCGA database.

It is currently unknown whether breast cancer differs biologically between pregnant and non-pregnant patients, due to sparse available protein expression data that is derived primarily by immunohistochemistry, according to Professor Loibl.

In this study, investigators analysed FFPE core biopsies taken prior to therapy for somatic mutations using an Ion Torrent Proton/PGM sequencing platform. The samples were assayed on a custom designed breast cancer gene panel (BCPv2) comprising 236 amplicons split into two primer pools and covers 138 exons located in hotspot regions of 25 genes. Only non-synonymous mutations without germline origin were processed.

Pregnant patients more often have TP53 mutations but significantly fewer PIK3CA mutations

IMPAKT 2017 Abstract 10P

Mutation patterns overall in BCP vs. non-pregnant controls
Credit: Sibylle Loibl

Overall, the investigation of the mutational patterns of BCP compared to TCGA data identified slightly fewer mutations in pregnant patients; an average of 1.03 mutations per patient was observed in the BCP cohort versus 1.27 in the TCGA cohort. The most frequent somatic mutations occurring in both cohorts were TP53, PIK3CA, and GATA3.TP53 was seen more often in 65% of the BCP cohort compared to 37% in the TCGA cohort. PIK3CA was seen in 11% versus 29%, and GATA3 in 6% versus 18% in the BCP versus TCGA cohorts, respectively.

IMPAKt 2017 Abstract 10P

Mutation patterns by HR status in BCP vs. non-pregnant controls
Credit: Sibylle Loibl

The investigators then performed exact matching of BCP and TCGA cohorts that identified 41 patients per cohort that were matched regarding age, grade, and hormone receptor (HR) and HER2 status. Within this comparison, lymph node positive tumours were less frequent in BCP compared to TCGA patients (p = 0.046). PIK3CA mutations occurred significantly less frequently in the BCP cohort; 2.4% of pregnant compared to 22.0% of non-pregnant patients harboured PIK3CA mutations (p = 0.015). However, no significant difference was observed for the frequency of TP53 (p = 0.502) and GATA3 (p = 1.000) mutations in these cohorts.

IMPAKT 2017 Abstract 10P

Mutation patterns by HR status in BCP vs. non-pregnant controls
Credit: Sibylle Loibl

Evaluation of the data by HR status revealed that TP53 was the most frequently mutated gene overall with higher mutational rate in HR-negative compared to HR-positive patients; TP53 mutations were observed in 52.4% versus 75% of HR-positive versus HR-negative patients in the BCP cohort and in 23.8% versus 85.0% of HR-positive versus HR-negative patients in the TCGA cohort.


According to the authors, the mutational landscape does not seem to differ between pregnant and non-pregnant patients. They explained that the imbalance in the PIK3CA mutational rate after matching may be due to a remaining bias caused by differences in sensitivity or specificity of methods used to detect mutations or by differences in variables not used for matching.

The investigators plan additional comparisons using other datasets and are currently looking into gene expression patterns. They are continuing to collect tumour material to perform further translational research.


Funding from the German Cancer Consortium-DKTK and the BANSS Foundation was disclosed.


10P - S. Loibl, et al. Comparison of the mutational landscape of breast cancer during pregnancy and non-pregnant controls.

Last update: 04 May 2017

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