Published July 28, 2016 | Version v1
Journal article

The effects of lymph node status on predicting outcome in ER+ /HER2- tamoxifen treated breast cancer patients using gene signatures

  • 1. Department of Oncology, Juravinski Hospital and Cancer Centre, Hamilton (Canada)
  • 2. Department of Biochemistry and Biomedical Sciences, Centre for Functional Genomics, McMaster University, Hamilton (Canada)
  • 3. Department of Pathology, Juravinski Hospital and Cancer Centre, Hamilton (Canada)

Description

Lymph node (LN) status is the most important prognostic variable used to guide ER positive (+) breast cancer treatment. While a positive nodal status is traditionally associated with a poor prognosis, a subset of these patients respond well to treatment and achieve long-term survival. Several gene signatures have been established as a means of predicting outcome of breast cancer patients, but the development and indication for use of these assays varies. Here we compare the capacity of two approved gene signatures and a third novel signature to predict outcome in distinct LN negative (-) and LN+ populations. We also examine biological differences between tumours associated with LN- and LN+ disease. Gene expression data from publically available data sets was used to compare the ability of Oncotype DX and Prosigna to predict Distant Metastasis Free Survival (DMFS) using an in silico platform. A novel gene signature (Ellen) was developed by including patients with both LN- and LN+ disease and using Prediction Analysis of Microarrays (PAM) software. Gene Set Enrichment Analysis (GSEA) was used to determine biological pathways associated with patient outcome in both LN- and LN+ tumors. The Oncotype DX gene signature, which only used LN- patients during development, significantly predicted outcome in LN- patients, but not LN+ patients. The Prosigna gene signature, which included both LN- and LN+ patients during development, predicted outcome in both LN- and LN+ patient groups. Ellen was also able to predict outcome in both LN- and LN+ patient groups. GSEA suggested that epigenetic modification may be related to poor outcome in LN- disease, whereas immune response may be related to good outcome in LN+ disease. We demonstrate the importance of incorporating lymph node status during the development of prognostic gene signatures. Ellen may be a useful tool to predict outcome of patients regardless of lymph node status, or for those with unknown lymph node status. Finally we present candidate biological processes, unique to LN- and LN+ disease, that may indicate risk of relapse. The online version of this article (doi:10.1186/s12885-016-2501-0) contains supplementary material, which is available to authorized users

Availability note (English)

Available from http://dx.doi.org/10.1186/s12885-016-2501-0; Available from http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4964078

Additional details

Publishing Information

Journal Title
BMC cancer (Online)
Journal Volume
16
Journal Page Range
vp.
ISSN
1471-2407

INIS

Country of Publication
United Kingdom
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
47088230
Subject category
S62: RADIOLOGY AND NUCLEAR MEDICINE;
Descriptors DEI
COMPUTER CODES; FORECASTING; GENES; LYMPH NODES; MAMMARY GLANDS; NEOPLASMS; PATIENTS
Descriptors DEC
BODY; DISEASES; GLANDS; LYMPHATIC SYSTEM; ORGANS

Optional Information

Copyright
Copyright (c) Cockburn et al. 2016
Notes
PMCID: PMC4964078; PMID: 27469239; PUBLISHER-ID: 2501; OAI: oai:pubmedcentral.nih.gov:4964078