A gene expression-based predictor for myeloma patients at high risk of developing bone disease on bisphosphonate treatment

Wu, P., Walker, B. A., Brewer, D., Gregory, W. M., Ashcroft, J., Ross, F. M., Jackson, G. H., Child, A. J., Davies, F. E. and Morgan, G. J. (2011) A gene expression-based predictor for myeloma patients at high risk of developing bone disease on bisphosphonate treatment. Clinical Cancer Research, 17 (19), 6347-6355. (doi:10.1158/1078-0432.CCR-11-0994).

Abstract

Purpose: Myeloma bone disease impairs quality of life and is associated with impaired survival. Even with effective bisphosphonate treatment, a significant proportion of patients still develop skeletal-related events (SRE). Identifying such patients at presentation would allow treatment modification.

Experimental Design: To investigate the molecular basis of bone disease at presentation and to develop a predictive signature for patients at high risk of developing SREs on bisphosphonates, 261 presenting myeloma samples were analyzed by global gene expression profiling. The derived “SRE gene signature” was complemented by the integration of associated clinical parameters to generate an optimal predictor.

Results: Fifty genes were significantly associated with presenting bone disease, including the WNT signaling antagonist DKK1 and genes involved in growth factor signaling and apoptosis. Higher serum calcium level and the presence of bone disease and hyperdiploidy at presentation were associated with high risk of SRE development. A gene signature derived from the fourteen genes overexpressed in the SRE group was able to identify patients at high risk of developing an SRE on treatment. These genes either belonged to the IFN-induced family or were involved in cell signaling and mitosis. Multivariate logistic model selection yielded an optimal SRE predictor comprising seven genes and calcium level, which was validated as an effective predictor in a further set of patients.

Conclusions: The simple expression-based SRE predictor can effectively identify individuals at high risk of developing bone disease while being on bisphosphonates. This predictor could assist with developing future trials on novel therapies aimed at reducing myeloma bone disease

This record has no associated files available for download.

Contributors

Download statistics