Biomarkers of neoadjuvant/adjuvant chemotherapy for breast cancer

Takayuki Iwamoto, Yukiko Kajiwara, Yidan Zhu, Shigemichi Iha

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

The improvement of tumor biomarkers prepared for clinical use is a long process. A good biomarker should predict not only prognosis but also the response to therapies. In this review, we describe the biomarkers of neoadjuvant/adjuvant chemotherapy for breast cancer, considering different breast cancer subtypes. In hormone receptor (HR)-positive/human epidermal growth factor 2 (HER2)-negative breast cancers, various genomic markers highly associated with proliferation have been tested. Among them, only two genomic signatures, the 21-gene recurrence score and 70-gene signature, have been reported in prospective randomized clinical trials and met the primary endpoint. However, these genomic markers did not suffice in HER2-positive and triple-negative (TN) breast cancers, which present only classical clinical and pathological information (tumor size, nodal or distant metastatic status) for decision making in the adjuvant setting in daily clinic. Recently, patients with residual invasive cancer after neoadjuvant chemotherapy are at a high-risk of recurrence for metastasis, which, in turn, make these patients best applicants for clinical trials. Two clinical trials have shown improved outcomes with post-operative capecitabine and ado-trastuzumab emtansine treatment in patients with either TN or HER2-positive breast cancer, respectively, who had residual disease after neoadjuvant chemotherapy. Furthermore, tumor-infiltrating lymphocytes (TILs) have been reported to have a predictive value for prognosis and response to chemotherapy from the retrospective analyses. So far, TILs have to not be used to either withhold or prescribe chemotherapy based on the absence of standardized evaluation guidelines and confirmed information. To overcome the low reproducibility of evaluations of TILs, gene signatures or digital image analysis and machine learning algorithms with artificial intelligence may be useful for standardization of assessment for TILs in the future.

Original languageEnglish
Pages (from-to)27
Number of pages1
JournalChinese Clinical Oncology
Volume9
Issue number2
DOIs
Publication statusPublished - Jun 1 2020

Keywords

  • Biomarker
  • breast cancer
  • chemotherapy
  • gene expression

ASJC Scopus subject areas

  • Oncology

Fingerprint Dive into the research topics of 'Biomarkers of neoadjuvant/adjuvant chemotherapy for breast cancer'. Together they form a unique fingerprint.

Cite this