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Delineating transcriptional networks of prognostic gene signatures refines treatment recommendations for lymph node-negative breast cancer patients

  • Author(s): Lanigan, F
  • Brien, GL
  • Fan, Y
  • Madden, SF
  • Jerman, E
  • Maratha, A
  • Aloraifi, F
  • Hokamp, K
  • Dunne, EJ
  • Lohan, AJ
  • Flanagan, L
  • Garbe, JC
  • Stampfer, MR
  • Fridberg, M
  • Jirstrom, K
  • Quinn, CM
  • Loftus, B
  • Gallagher, WM
  • Geraghty, J
  • Bracken, AP
  • et al.
Abstract

© 2015 FEBS. The majority of women diagnosed with lymph node-negative breast cancer are unnecessarily treated with damaging chemotherapeutics after surgical resection. This highlights the importance of understanding and more accurately predicting patient prognosis. In the present study, we define the transcriptional networks regulating well-established prognostic gene expression signatures. We find that the same set of transcriptional regulators consistently lie upstream of both 'prognosis' and 'proliferation' gene signatures, suggesting that a central transcriptional network underpins a shared phenotype within these signatures. Strikingly, the master transcriptional regulators within this network predict recurrence risk for lymph node-negative breast cancer better than currently used multigene prognostic assays, particularly in estrogen receptor-positive patients. Simultaneous examination of p16INK4Aexpression, which predicts tumours that have bypassed cellular senescence, revealed that intermediate levels of p16INK4A correlate with an intact pRB pathway and improved survival. A combination of these master transcriptional regulators and p16INK4A, termed the OncoMasTR score, stratifies tumours based on their proliferative and senescence capacity, facilitating a clearer delineation of lymph node-negative breast cancer patients at high risk of recurrence, and thus requiring chemotherapy. Furthermore, OncoMasTR accurately classifies over 60% of patients as 'low risk', an improvement on existing prognostic assays, which has the potential to reduce overtreatment in early-stage patients. Taken together, the present study provides new insights into the transcriptional regulation of cellular proliferation in breast cancer and provides an opportunity to enhance and streamline methods of predicting breast cancer prognosis.

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