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IMPAKT 2017: Few Variations in Somatic Mutations Observed Between Pregnant and Nonpregnant Patients With Breast Cancer

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Key Points

  • 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 vs 1.27 in the TCGA cohort.
  • The most frequent somatic mutations occurring in both cohorts were TP53, PIK3CA, and GATA3.
  • PIK3CA mutations occurred significantly less frequently in the BCP cohort; 2.4% of pregnant compared to 22.0% of nonpregnant patients harbored PIK3CA mutation.

Findings comparing the mutational landscape in pregnant and nonpregnant patients with breast cancer that sought to define whether the disease may have a different biology in pregnant women were reported by Loibl et al at the 2017 IMPAKT Breast Cancer Conference, held in Brussels (Abstract 10P). The IMPAKT conference is presented by the European Society for Medical Oncology, the Breast International Group, and a multidisciplinary alliance of other European breast cancer organizations.

Pregnancy is estimated to be a factor in 1% to 3% of all breast cancers. Lead author Sibylle Loibl, MD, PhD, Medicine and Research, German Breast Group, presented data based on an evaluation of the patterns of somatic mutations between pregnant and nonpregnant patients with breast cancer. 

BCP Study

Dr. Loibl and colleagues compared a dataset of pregnant patients enrolled in the Breast Cancer in Pregnanacy (BCP) study (GBG 29; BIG 03-02), a multicenter, retrospective, observational study of women with simultaneous breast cancer and pregnancy to nonpregnant control patients with breast cancer obtained from The Cancer Genome Atlas (TCGA) database.

It is currently unknown whether breast cancer differs biologically between pregnant and nonpregnant patients, due to sparse available protein-expression data derived primarily by immunohistochemistry, according to Dr. Loibl. In this study, investigators analyzed formalin-fixed, paraffin-embedded 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 nonsynonymous mutations without germline origin were processed.

Analysis Results

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 vs 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% vs 29%, and GATA3 in 6% vs 18% in the BCP vs TCGA cohorts, respectively.

The investigators then performed exact matching of BCP and TCGA cohorts that identified 41 patients per cohort who were matched regarding age, grade, and hormone receptor and HER2 status. Within this comparison, lymph node–positive tumors were less frequent in BCP compared to TCGA patients (P = .046). PIK3CA mutations occurred significantly less frequently in the BCP cohort; 2.4% of pregnant compared to 22.0% of nonpregnant patients harbored PIK3CA mutations (P = .015). However, no significant difference was observed for the frequency of TP53 (P = .502) and GATA3 (P = 1.000) mutations in these cohorts.

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

Study Implications

According to the authors, the mutational landscape does not seem to differ between pregnant and nonpregnant 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 tumor material to perform further translational research.

The content in this post has not been reviewed by the American Society of Clinical Oncology, Inc. (ASCO®) and does not necessarily reflect the ideas and opinions of ASCO®.


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