Current best practices and rationalistic perspectives in causation-based prevention, early detection and multidisciplinary treatment of breast and gastric cancer

Gastric & Breast Cancer e-journal
DOI: 10.2122/gbc.2010.0116


Very early (T1a,bN0) breast cancer: HER2 and algorithmic approach to predict and treat patients at high recurrence risk

George Zografos, M.D.

Affiliation: Head of the Breast Unit, Head of 1st Department of Propaedeutic Surgery, University of Athens, Greece.

Tel: +306932524836, Fax: +302651007094



Most women with small, node-negative breast cancer (T1a,bN0M0) have an excellent prognosis. But despite this early disease, a subset of these patients experiences recurrence with fatal outcome. How could these high-risk women be identified and appropriately be treated to prevent this poor outcome?

Two recent retrospective studies from highly specialized institutions in the USA and Europe found that among women with pT1a,bN0M0 tumor, those with HER2-posistive as compared with those with HER-negative tumor had a significantly higher risk of recurrence. The absolute risk of recurrence at 5-years reached in up to 23% for HER2-positive, pT1a,bN0M0. Therefore, the authors propose treatment with trastuzumab which is currently indicated only for patients with larger tumors (> 1 cm ) and/or node-positive disease. Could such a treatment more harm rather than benefit HER2-positive, pT1a,bN0M0 patients?

In this critical review, the limitations of these small studies with no randomizations are discussed. An algorithmic approach is suggested considering standard clinicopathologic features, micrometastases or isolated tumor cells in lymph nodes and multigene expression profiling signatures (Oncotype DX, Mammaprint). Moreover, the future perspectives of prognostic and predictive markers development through molecular systems biology approaches and cancer stem cells research are described.

This 9 pages (pp. 36-44) review article includes:

  • 1 Flowchart - decision tree for clinical decision-making treatment
  • 1 Table
  • 1 Figure on cancer cells treatment response variability


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Online ISSN : 1109 - 7647
   Print ISSN : 1109 - 7655

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last update: 30 January 2010