Serum miRNA–based Prediction of Axillary Lymph Node Metastasis in Breast Cancer

Sho Shiino, Juntaro Matsuzaki, Akihiko Shimomura, Junpei Kawauchi, Satoko Takizawa, Hiromi Sakamoto, Yoshiaki Aoki, Masayuki Yoshida, Kenji Tamura, Ken Kato, Takayuki Kinoshita, Yuukou Kitagawa, Takahiro Ochiya

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

Purpose: Sentinel lymph node biopsy (SLNB) is the gold-standard procedure for evaluating axillary lymph node (ALN) status in patients with breast cancer. However, the morbidity of SLNB is not negligible, and the procedure is invasive for patients without ALN metastasis. Here, we developed a diagnostic model for evaluating ALN status using a combination of serum miRNAs and clinicopathologic factors as a novel less-invasive biomarker. Experimental Design: Preoperative serum samples were collected from patients who underwent surgery for primary breast cancer or breast benign diseases between 2008 and 2014. A total of 958 serum samples (921 cases of primary breast cancer, including 630 cases in the no ALN metastasis group and 291 cases in the ALN metastasis group, and 37 patients with benign breast diseases) were analyzed by miRNA microarray. Samples were randomly divided into training and test sets. Logistic LASSO regression analysis was used to construct diagnostic models in the training set, which were validated in the test set. Results: An optimal diagnostic model was identified using a combination of two miRNAs (miR-629-3p and miR-4710) and three clinicopathologic factors (T stage, lymphovascular invasion, and ultrasound findings), which showed a sensitivity of 0.88 (0.84–0.92), a specificity of 0.69 (0.61–0.76), an accuracy of 0.818, and an area under the receiver operating characteristic curve of 0.86 in the test set. Conclusions: Serum miRNA profiles may be useful for the diagnosis of ALN metastasis before surgery in a less-invasive manner than SLNB.

Original languageEnglish
Pages (from-to)1817-1827
Number of pages11
JournalClinical Cancer Research
Volume25
Issue number6
DOIs
Publication statusPublished - 2019 Jan 1

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Lymph Nodes
Breast Neoplasms
Neoplasm Metastasis
MicroRNAs
Sentinel Lymph Node Biopsy
Serum
Breast Diseases
ROC Curve
Gold
Research Design
Biomarkers
Logistic Models
Regression Analysis
Morbidity

ASJC Scopus subject areas

  • Oncology
  • Cancer Research

Cite this

Shiino, S., Matsuzaki, J., Shimomura, A., Kawauchi, J., Takizawa, S., Sakamoto, H., ... Ochiya, T. (2019). Serum miRNA–based Prediction of Axillary Lymph Node Metastasis in Breast Cancer. Clinical Cancer Research, 25(6), 1817-1827. https://doi.org/10.1158/1078-0432.CCR-18-1414

Serum miRNA–based Prediction of Axillary Lymph Node Metastasis in Breast Cancer. / Shiino, Sho; Matsuzaki, Juntaro; Shimomura, Akihiko; Kawauchi, Junpei; Takizawa, Satoko; Sakamoto, Hiromi; Aoki, Yoshiaki; Yoshida, Masayuki; Tamura, Kenji; Kato, Ken; Kinoshita, Takayuki; Kitagawa, Yuukou; Ochiya, Takahiro.

In: Clinical Cancer Research, Vol. 25, No. 6, 01.01.2019, p. 1817-1827.

Research output: Contribution to journalArticle

Shiino, S, Matsuzaki, J, Shimomura, A, Kawauchi, J, Takizawa, S, Sakamoto, H, Aoki, Y, Yoshida, M, Tamura, K, Kato, K, Kinoshita, T, Kitagawa, Y & Ochiya, T 2019, 'Serum miRNA–based Prediction of Axillary Lymph Node Metastasis in Breast Cancer', Clinical Cancer Research, vol. 25, no. 6, pp. 1817-1827. https://doi.org/10.1158/1078-0432.CCR-18-1414
Shiino S, Matsuzaki J, Shimomura A, Kawauchi J, Takizawa S, Sakamoto H et al. Serum miRNA–based Prediction of Axillary Lymph Node Metastasis in Breast Cancer. Clinical Cancer Research. 2019 Jan 1;25(6):1817-1827. https://doi.org/10.1158/1078-0432.CCR-18-1414
Shiino, Sho ; Matsuzaki, Juntaro ; Shimomura, Akihiko ; Kawauchi, Junpei ; Takizawa, Satoko ; Sakamoto, Hiromi ; Aoki, Yoshiaki ; Yoshida, Masayuki ; Tamura, Kenji ; Kato, Ken ; Kinoshita, Takayuki ; Kitagawa, Yuukou ; Ochiya, Takahiro. / Serum miRNA–based Prediction of Axillary Lymph Node Metastasis in Breast Cancer. In: Clinical Cancer Research. 2019 ; Vol. 25, No. 6. pp. 1817-1827.
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AU - Takizawa, Satoko

AU - Sakamoto, Hiromi

AU - Aoki, Yoshiaki

AU - Yoshida, Masayuki

AU - Tamura, Kenji

AU - Kato, Ken

AU - Kinoshita, Takayuki

AU - Kitagawa, Yuukou

AU - Ochiya, Takahiro

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N2 - Purpose: Sentinel lymph node biopsy (SLNB) is the gold-standard procedure for evaluating axillary lymph node (ALN) status in patients with breast cancer. However, the morbidity of SLNB is not negligible, and the procedure is invasive for patients without ALN metastasis. Here, we developed a diagnostic model for evaluating ALN status using a combination of serum miRNAs and clinicopathologic factors as a novel less-invasive biomarker. Experimental Design: Preoperative serum samples were collected from patients who underwent surgery for primary breast cancer or breast benign diseases between 2008 and 2014. A total of 958 serum samples (921 cases of primary breast cancer, including 630 cases in the no ALN metastasis group and 291 cases in the ALN metastasis group, and 37 patients with benign breast diseases) were analyzed by miRNA microarray. Samples were randomly divided into training and test sets. Logistic LASSO regression analysis was used to construct diagnostic models in the training set, which were validated in the test set. Results: An optimal diagnostic model was identified using a combination of two miRNAs (miR-629-3p and miR-4710) and three clinicopathologic factors (T stage, lymphovascular invasion, and ultrasound findings), which showed a sensitivity of 0.88 (0.84–0.92), a specificity of 0.69 (0.61–0.76), an accuracy of 0.818, and an area under the receiver operating characteristic curve of 0.86 in the test set. Conclusions: Serum miRNA profiles may be useful for the diagnosis of ALN metastasis before surgery in a less-invasive manner than SLNB.

AB - Purpose: Sentinel lymph node biopsy (SLNB) is the gold-standard procedure for evaluating axillary lymph node (ALN) status in patients with breast cancer. However, the morbidity of SLNB is not negligible, and the procedure is invasive for patients without ALN metastasis. Here, we developed a diagnostic model for evaluating ALN status using a combination of serum miRNAs and clinicopathologic factors as a novel less-invasive biomarker. Experimental Design: Preoperative serum samples were collected from patients who underwent surgery for primary breast cancer or breast benign diseases between 2008 and 2014. A total of 958 serum samples (921 cases of primary breast cancer, including 630 cases in the no ALN metastasis group and 291 cases in the ALN metastasis group, and 37 patients with benign breast diseases) were analyzed by miRNA microarray. Samples were randomly divided into training and test sets. Logistic LASSO regression analysis was used to construct diagnostic models in the training set, which were validated in the test set. Results: An optimal diagnostic model was identified using a combination of two miRNAs (miR-629-3p and miR-4710) and three clinicopathologic factors (T stage, lymphovascular invasion, and ultrasound findings), which showed a sensitivity of 0.88 (0.84–0.92), a specificity of 0.69 (0.61–0.76), an accuracy of 0.818, and an area under the receiver operating characteristic curve of 0.86 in the test set. Conclusions: Serum miRNA profiles may be useful for the diagnosis of ALN metastasis before surgery in a less-invasive manner than SLNB.

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