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Identifying Circulating Tumor DNA Mutation Profiles in Metastatic Breast Cancer Patients with Multiline Resistance

Zhe-Yu Hu1, Ning Xie2, Can Tian2

  • 1Hunan Cancer Hospital, and the Affiliated Cancer Hospital of Xiangya Medical School, Central South University, Changsha 410013, China; Department of Breast Cancer Medical Oncology, Hunan Cancer Hospital, Changsha 410013, China; Department of Breast Cancer Medical Oncology, The Affiliated Cancer Hospital of Xiangya Medical School, Central South University, Changsha 410013, China; Central Laboratory, The Affiliated Cancer Hospital of Xiangya Medical School, Central South University, Changsha 410013, China.

Ebiomedicine
|May 30, 2018
PubMed
Abstract

Insights

Tumor gene mutations in metastatic breast cancer (MBC) patients predict drug resistance. Analyzing circulating tumor DNA (ctDNA) revealed distinct mutation patterns across subtypes, aiding in personalized treatment selection for improved outcomes.

Area of Science:

  • Oncology
  • Genetics
  • Molecular Biology

Background:

  • Tumor gene mutations are a significant cause of drug resistance and treatment failure in cancer patients.
  • In metastatic breast cancer (MBC), acquired mutations after multiline treatment reduce therapeutic efficacy.
  • Understanding these mutation patterns is crucial for predicting disease progression and resistance.

Purpose of the Study:

  • To evaluate gene mutation patterns in circulating tumor DNA (ctDNA) of MBC patients.
  • To correlate specific mutations with hormone receptor (HR)/human epidermal growth factor receptor 2 (HER2) subtypes.
  • To predict drug resistance and disease progression based on identified mutation profiles.

Main Methods:

  • Recruited 68 patients with metastatic breast cancer (MBC) who had undergone multiline treatment.
  • Analyzed circulating tumor DNA (ctDNA) mutations.
  • Compared mutation patterns across different HR/HER2 subgroups and correlated them with treatment response times.

Main Results:

  • Baseline ctDNA mutation patterns varied significantly among HR/HER2 subtypes (TNBC, HR+, HER2+).
  • Specific mutations like BRCA1/MED12 (TNBC), PIK3CA/FAT1 (HR+), and PIK3CA/ERBB2 (HER2+) were prevalent.
  • TERT, FAT1, NOTCH4, PIK3CA, TP53, MLL3, NOTCH2, and ERS1 mutations were associated with disease progression at different time points.
  • A ctDNA pattern of TP53 + PIK3CA mutations predicted progression within 6 months in a COX model.

Conclusions:

  • ctDNA gene mutation profiles are distinct across HR/HER2 subtypes in MBC.
  • Identifying mutations linked to treatment resistance can guide therapy selection.
  • This approach may improve treatment strategies for patients with advanced breast cancer receiving multiple treatment lines.
Keywords:
Circulating tumor DNA (ctDNA)Drug resistanceGene mutation patternHR/HER2 subtypeMetastatic breast cancerProgression-free survival

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