The effects of lymph node status on predicting outcome in ER+ /HER2- tamoxifen treated breast cancer patients using gene signatures
Creators
- 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/PMC4964078Additional details
Identifiers
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