Exploratory biomarker analysis from a phase II clinical trial of eribulin plus gemcitabine versus paclitaxel plus gemcitabine for HER2-negative metastatic breast cancer patients (KCSG BR13-11)

  • Ji-Yeon Kim
  • Eunjin Lee
  • Kyunghee Park
  • Seock-Ah Im
  • Joohyuk Sohn
  • Keun Seok Lee
  • Yee Soo Chae
  • Jee Hyun Kim
  • Tae-Yong Kim
  • Kyung Hae JungEmail author
  • Yeon Hee ParkEmail author
  • the Breast Cancer Committee of the Korean Cancer Study Group
Clinical trial



We conducted an exploratory biomarker study from a phase II clinical trial of eribulin plus gemcitabine (EG) versus paclitaxel plus gemcitabine (PG) in HER2-negative metastatic breast cancer (BC) patients.


We performed targeted deep sequencing with a customized cancer gene panel and RNA expression assay. Tumor mutation burden (TMB) and mutation signatures were determined based on genetic alteration in targeted regions. Gene set variation analysis was performed with PanCancer Immune Profiling and PanCancer Pathway Panels. Statistical analyses were conducted to identify the associations between genetic alterations and clinical outcomes.


Of 119 patients, 40 had available biomarker data. Among the 40 patients, 4 supported their post-treatment tissues. In targeted deep sequencing, FAT3 (48%) was the most frequently mutated gene, followed by PKHD1, TP53, GATA3, PARP4, and PIK3CA. In terms of gene expression, low expression of epithelial-mesenchymal transition (EMT) pathway genes was associated with prolonged progression-free survival (PFS) in the EG group, while high expression of the EMT pathway was associated with good prognosis in the PG group. Median TMB was 6.5 (range 2.44–46.34) and there was no relationship between TMB and patient prognosis. Analysis of mutation signatures showed that signatures 3, 20, and 26 were frequently observed in our cohort. Further survival analysis according to mutation signature showed that mutation signature 3, as a homologous recombinant deficiency-related signature, was highly associated with disease progression (hazard ratio (log2 scale) 8.21, 95% confidence interval 2.93–13.48, p = 0.002). Kaplan–Meier plot also showed that BCs with signature 3 had short PFS compared to those without these signatures (median PFS (months) for signature 3 (low vs. high): 17.2 vs. 8.1, p = 0.0026).


Mutation signature 3, found in about 30% of MBCs regardless of hormone receptor status, was associated with short PFS for patients with cytotoxic chemotherapy.

Trial registry number: NCT02263495.


Metastatic breast cancer Eribulin Paclitaxel Next-generation sequencing 



This research was supported by a Grant from the National Research Foundation of Republic of Korea (NRF-2018R1A2B6004690), the Ministry of Health and Welfare, Republic of Korea (HA17C0055), and the National R&D Program for Cancer Control, Ministry of Health and Welfare, Republic of Korea (1720150). This study was also supported by a Grant from Eisai Korea Inc.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflicts of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards our institutional and/or national research committee and with the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards.

Informed consent

Informed consent was obtained from all individual participants included in the study.

Supplementary material

10549_2019_5400_MOESM1_ESM.pdf (112 kb)
Supplementary material 1 (PDF 112 kb)
10549_2019_5400_MOESM2_ESM.xlsx (38 kb)
Supplementary material 2 (XLSX 39 kb)
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Supplementary material 3 (TIFF 1477 kb) Supplementary Fig. 1. OS and PFS according to FAT3 mutation
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Supplementary material 4 (TIFF 3252 kb) Supplementary Fig. 2. DEG analysis for angiogenesis-related genes in immune panel according to treatment arm and disease progression
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Supplementary material 5 (TIFF 2385 kb) Supplementary Fig. 3. DEG analysis for angiogenesis-related genes in cancer panel according to treatment arm and disease progression
10549_2019_5400_MOESM6_ESM.tif (1.7 mb)
Supplementary material 6 (TIFF 1748 kb) Supplementary Fig. 4. GSVA for nanostring (a) cancer panel and (b) immune panel
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Supplementary material 7 (TIFF 2516 kb) Supplementary Fig. 5. GSVA for (a) cancer panel and (b) immune panel using pre- and post-treatment samples
10549_2019_5400_MOESM8_ESM.tif (1.5 mb)
Supplementary material 8 (TIFF 1577 kb) Supplementary Fig. 6. Cox-regression and KM analysis according to mutation signature 3 in (a) EG arm and (b) PG arm


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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  • Ji-Yeon Kim
    • 1
  • Eunjin Lee
    • 2
  • Kyunghee Park
    • 2
  • Seock-Ah Im
    • 3
  • Joohyuk Sohn
    • 4
  • Keun Seok Lee
    • 5
  • Yee Soo Chae
    • 6
  • Jee Hyun Kim
    • 7
  • Tae-Yong Kim
    • 3
  • Kyung Hae Jung
    • 8
    Email author
  • Yeon Hee Park
    • 1
    Email author
  • the Breast Cancer Committee of the Korean Cancer Study Group
  1. 1.Division of Hematology-Oncology, Department of Medicine, Samsung Medical CenterSungkyunkwan University School of MedicineSeoulKorea
  2. 2.Samsung Medical CenterSamsung Genome InstituteSeoulKorea
  3. 3.Department of Internal Medicine, Seoul National University Hospital, Cancer Research InstituteSeoul National University, College of MedicineSeoulKorea
  4. 4.Division of Medical Oncology, Department of Internal MedicineYonsei University College of MedicineSeoulKorea
  5. 5.Center for Breast CancerNational Cancer CenterGoyangKorea
  6. 6.Kyungpook National University Medical CenterDaeguKorea
  7. 7.Department of Internal Medicine, Seoul National University Bundang HospitalSeoul National University College of MedicineSeongnamKorea
  8. 8.Department of Oncology, Asan Medical CenterUniversity of Ulsan College of MedicineSeoulKorea

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