このエントリーをはてなブックマークに追加
ID 60773
FullText URL
Author
Iwamoto, Takayuki Department of Breast and Endocrine Surgery, Okayama University Hospital Kaken ID researchmap
Kajiwara, Yukiko Department of Breast and Endocrine Surgery, Okayama University Hospital
Zhu, Yidan Department of Breast and Endocrine Surgery, Okayama University Hospital
Iha, Shigemichi Department of Breast Oncology, Miyake Ofuku Clinic
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.
Keywords
Biomarker
chemotherapy
breast cancer
gene expression
Published Date
2020-07
Publication Title
Chinese Clinical Oncology
Volume
volume9
Issue
issue3
Publisher
AME
Start Page
27
ISSN
2304-3865
Content Type
Journal Article
language
英語
OAI-PMH Set
岡山大学
File Version
publisher
PubMed ID
DOI
Web of Science KeyUT
Related Url
isVersionOf 10.21037/cco.2020.01.06
License
https://creativecommons.org/licenses/by-nc-nd/4.0/