ID | 60773 |
フルテキストURL | |
著者 |
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
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抄録 | 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.
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キーワード | Biomarker
chemotherapy
breast cancer
gene expression
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発行日 | 2020-07
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出版物タイトル |
Chinese Clinical Oncology
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巻 | 9巻
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号 | 3号
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出版者 | AME
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開始ページ | 27
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ISSN | 2304-3865
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資料タイプ |
学術雑誌論文
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言語 |
英語
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OAI-PMH Set |
岡山大学
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論文のバージョン | publisher
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PubMed ID | |
DOI | |
Web of Science KeyUT | |
関連URL | isVersionOf 10.21037/cco.2020.01.06
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ライセンス | https://creativecommons.org/licenses/by-nc-nd/4.0/
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