BACKGROUND: Aberrant expression of microRNAs (miRNAs) is associated with cancer progression, initiation and metastasis. MiR34a is a miRNA that has been previously described as a tumour suppressor. Herein, we assess the expression of miR34a in three independent breast cancer cohorts using a quantitative in situ hybridisation assay (qISH) and determined its association with disease-specific death in breast cancer.
METHODS: The qISH method was applied to three independent primary breast cancer cohorts (Cohort 1 with 461, Cohort 2 with 279 and Cohort 3 with 795 patients) using 5' and 3' double DIG-labelled LNA-modified probe against miR34a using the protocol described previously. Level of expression measured as automated quantitative analysis (AQUA) score for miR34a was determined for each patient and assessed for association with risk of disease-specific death. An optimal cutpoint was determined using the X-tile software for disease-specific survival in Cohort 1 and this cutpoint was then applied to the other two cohorts after median normalisation of AQUA scores.
RESULTS: Loss of miR34a is associated with poor outcome in three independent breast cancer cohorts (uncorrected log-rank P=0.0188 for Cohort 1, log-rank P=0.0024 for Cohort 2 and log-rank P=0.0455 for Cohort 3). In all three cohorts, loss of miR34a is able to stratify patients with poor disease-specific survival among node-negative patients, but not in node-positive population. Multivariate Cox proportional hazards analysis in Cohort 1 (P=0.0381) and Cohort 2 (P=0.0468) revealed that loss of miR34a is associated with poor outcome, independent of age, node status, receptor status and tumour size.
CONCLUSION: Loss of the tumour suppressor, miR34a, identifies a subgroup of breast cancer patients with poor disease-specific survival. This study is consistent with the well-established preclinical observations for miR34a as a tumour suppressor and suggests that miR34a may have future value as a biomarker in breast cancer.
- Biomarkers, Tumor
- Breast Neoplasms
- Cohort Studies
- Proportional Hazards Models
- Prospective Studies
- Survival Analysis
- Treatment Outcome