A prognostic model for lymph node-negative breast cancer patients based on the integration of proliferation and immunity

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• 作者：Ensel Oh (1)
  Yoon-La Choi (2)
  Taesung Park (13)
  Seungyeoun Lee (4)
  Seok Jin Nam (5)
  Young Kee Shin (167) ykeeshin@snu.ac.kr
• 关键词：Lymph node ; negative breast cancer &#8211 ; Prognostic genes &#8211 ; Proliferation &#8211 ; Immune response &#8211 ; Parametric model &#8211 ; Gene signature
• 刊名：Breast Cancer Research and Treatment
• 出版年：2012
• 出版时间：April 2012
• 年：2012
• 卷：132
• 期：2
• 页码：499-509
• 全文大小：781.6 KB
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• 作者单位：1. Interdisciplinary Program in Bioinformatics, College of Natural Science, Seoul National University, Seoul, Korea2. Laboratory of Cancer Genomics and Molecular Pathology, Department of Pathology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea3. Department of Statistics, College of Natural Science, Seoul National University, Seoul, Korea4. Department of Applied Statistics, College of Natural Science, Sejoung University, Seoul, Korea5. Division of Breast and Endocrine Surgery, Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea6. Research Institute of Pharmaceutical Science, Department of Pharmacy, Seoul National University College of Pharmacy, Seoul, Korea7. Laboratory of Molecular Pathology and Cancer Genomics, Department of Pharmacy, College of Pharmacy, Seoul National University, 599 Gwanak-ro, Gwanak-gu, Seoul, 151-742 Korea
• 刊物类别：Medicine
• 刊物主题：Medicine & Public Health
  Oncology
  
• 出版者：Springer Netherlands
• ISSN：1573-7217

文摘

A model for a more precise prognosis of the risk of relapse is needed to avoid overtreatment of lymph node-negative breast cancer patients. A large derivation data set (n = 684) was generated by pooling three independent breast cancer expression microarray data sets. Two major prognostic factors, proliferation and immune response, were identified among genes showing significant differential expression levels between the good outcome and poor outcome groups. For each factor, four proliferation-related genes (p-genes) and four immunity-related genes (i-genes) were selected as prognostic genes, and a prognostic model for lymph node-negative breast cancer patients was developed using a parametric survival analysis based on the lognormal distribution. The p-genes showed a predominantly negative correlation (coefficient: −0.603) with survival time, while the i-genes showed a positive correlation (coefficient: 0.243), reflecting the beneficial effect of the immune response against deleterious proliferative activity. The prognostic model shows that approximately 54% of lymph node-negative breast cancer patients were predicted to be distant metastasis-free for more than 5 years with at least 85% survival probability. The prognostic model showed a robust and high prognostic performance (HR 2.85–3.45) through three external validation data sets. Based on the integration of proliferation and immunity, the new prognostic model is expected to improve clinical decision making by providing easily interpretable survival probabilities at any time point and functional causality of the predicted prognosis with respect to proliferation and immune response.