The prediction models for postoperative overall survival and disease-free survival in patients with breast cancer
Daichi Shigemizu
Department of Medical Science Mathematics, Medical Research Institute, Tokyo Medical and Dental University, Tokyo, Japan
Laboratory for Medical Science Mathematics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
CREST, Japan Science and Technology Agency, Tokyo, Japan
Department for Medical Genome Sciences, Medical Genome Center, National Center for Geriatrics and Gerontology, Obu, Japan
Search for more papers by this authorTakuji Iwase
Department of Breast Surgical Oncology, Breast Oncology Center, Cancer Institute Hospital, Japanese Foundation for Cancer Research, Tokyo, Japan
Search for more papers by this authorYasuyo Suzuki
First Department of Surgery, Sapporo Medical University, School of Medicine, Sapporo, Japan
Search for more papers by this authorFuyuki Miya
Department of Medical Science Mathematics, Medical Research Institute, Tokyo Medical and Dental University, Tokyo, Japan
Laboratory for Medical Science Mathematics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
Search for more papers by this authorKeith A Boroevich
Laboratory for Medical Science Mathematics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
Search for more papers by this authorToyomasa Katagiri
Division of Genome Medicine, Institute for Genome Research, Tokushima University, Tokushima, Japan
Human Genome Center, Institute of Medical Science, The University of Tokyo, Tokyo, Japan
Search for more papers by this authorHitoshi Zembutsu
Division of Genetics, National Cancer Center Research Institute, Tokyo, Japan
These authors should be considered co-corresponding authors.Search for more papers by this authorCorresponding Author
Tatsuhiko Tsunoda
Department of Medical Science Mathematics, Medical Research Institute, Tokyo Medical and Dental University, Tokyo, Japan
Laboratory for Medical Science Mathematics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
CREST, Japan Science and Technology Agency, Tokyo, Japan
These authors should be considered co-corresponding authors.Correspondence
Tatsuhiko Tsunoda, Department of Medical Science Mathematics, Medical Research Institute, Tokyo Medical and Dental University, 1-5-45 Yushima, Bunkyo-ku, Tokyo 113-8510, Japan. Tel: +81 3 5803 4175; Fax: +81 3 5803 0182; E-mail: [email protected]
Search for more papers by this authorDaichi Shigemizu
Department of Medical Science Mathematics, Medical Research Institute, Tokyo Medical and Dental University, Tokyo, Japan
Laboratory for Medical Science Mathematics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
CREST, Japan Science and Technology Agency, Tokyo, Japan
Department for Medical Genome Sciences, Medical Genome Center, National Center for Geriatrics and Gerontology, Obu, Japan
Search for more papers by this authorTakuji Iwase
Department of Breast Surgical Oncology, Breast Oncology Center, Cancer Institute Hospital, Japanese Foundation for Cancer Research, Tokyo, Japan
Search for more papers by this authorYasuyo Suzuki
First Department of Surgery, Sapporo Medical University, School of Medicine, Sapporo, Japan
Search for more papers by this authorFuyuki Miya
Department of Medical Science Mathematics, Medical Research Institute, Tokyo Medical and Dental University, Tokyo, Japan
Laboratory for Medical Science Mathematics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
Search for more papers by this authorKeith A Boroevich
Laboratory for Medical Science Mathematics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
Search for more papers by this authorToyomasa Katagiri
Division of Genome Medicine, Institute for Genome Research, Tokushima University, Tokushima, Japan
Human Genome Center, Institute of Medical Science, The University of Tokyo, Tokyo, Japan
Search for more papers by this authorHitoshi Zembutsu
Division of Genetics, National Cancer Center Research Institute, Tokyo, Japan
These authors should be considered co-corresponding authors.Search for more papers by this authorCorresponding Author
Tatsuhiko Tsunoda
Department of Medical Science Mathematics, Medical Research Institute, Tokyo Medical and Dental University, Tokyo, Japan
Laboratory for Medical Science Mathematics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
CREST, Japan Science and Technology Agency, Tokyo, Japan
These authors should be considered co-corresponding authors.Correspondence
Tatsuhiko Tsunoda, Department of Medical Science Mathematics, Medical Research Institute, Tokyo Medical and Dental University, 1-5-45 Yushima, Bunkyo-ku, Tokyo 113-8510, Japan. Tel: +81 3 5803 4175; Fax: +81 3 5803 0182; E-mail: [email protected]
Search for more papers by this authorAbstract
The goal of this study is to establish a method for predicting overall survival (OS) and disease-free survival (DFS) in breast cancer patients after surgical operation. The gene expression profiles of cancer tissues from the patients, who underwent complete surgical resection of breast cancer and were subsequently monitored for postoperative survival, were analyzed using cDNA microarrays. We detected seven and three probes/genes associated with the postoperative OS and DFS, respectively, from our discovery cohort data. By incorporating these genes associated with the postoperative survival into MammaPrint genes, often used to predict prognosis of patients with early-stage breast cancer, we constructed postoperative OS and DFS prediction models from the discovery cohort data using a Cox proportional hazard model. The predictive ability of the models was evaluated in another independent cohort using Kaplan–Meier (KM) curves and the area under the receiver operating characteristic curve (AUC). The KM curves showed a statistically significant difference between the predicted high- and low-risk groups in both OS (log-rank trend test P = 0.0033) and DFS (log-rank trend test P = 0.00030). The models also achieved high AUC scores of 0.71 in OS and of 0.60 in DFS. Furthermore, our models had improved KM curves when compared to the models using MammaPrint genes (OS: P = 0.0058, DFS: P = 0.00054). Similar results were observed when our model was tested in publicly available datasets. These observations indicate that there is still room for improvement in the current methods of predicting postoperative OS and DFS in breast cancer.
Supporting Information
| Filename | Description |
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| cam41092-sup-0001-Supinfo.docxWord document, 724.4 KB |
Table S1. First and second discovery cohorts’ clinical information. Table S2. 37 MammaPrint genes and five genes associated with a poor OS and DFS used for prediction model construction. Table S3. Regression coefficients of 37 MammaPrint genes using a Cox proportional hazard model in discovery cohort and validation cohorts. Table S4. Independent OS and DFS predictions by our genes. Figure S1. Verification of our prediction models using GSE1456 cohort (validation cohort) obtained from the GEO database in OS. Figure S2. Verification of our prediction models using TCGA cohort (validation cohort) in OS. Figure S3. Verification of our prediction models using GSE1456 cohort (validation set) obtained from the GEO database in DFS. Figure S4. Verification of our prediction models without MammaPrint gene sets using an independent test set (validation set) obtained from GEO database. |
Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.
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