Identification of a miRNA based model to detect prognostic subgroups in patients with aggressive B-cell lymphoma

Abstract

In order to differentiate prognostic subgroups of patients with aggressive B-cell lymphoma, we analyzed the expression of 800 miRNAs with the NanoString nCounter human miRNA assay on a cohort of 228 FFPE samples of patients enrolled in the RICOVER-60 and MegaCHOEP trials. We identified significant miRNA signatures for overall survival (OS) and progression-free survival (PFS) by LASSO-penalized linear Cox-regression. High expression levels of miR-130a-3p and miR-423-5p indicate a better prognosis, whereas high levels of miR-374b-5p, miR-590-5p, miR-186-5p, and miR-106b-5p increase patients’ risk levels for OS. Regarding PFS high expression of miR-365a-5p in addition to the other two miRNAs improves the prognosis and high levels of miR374a-5p, miR-106b-5p, and miR-590-5p, connects with increased risk and poor prognosis. We identified miRNA signatures to subdivide patients into two different risk groups. These prognostic models may be used in risk stratification in future clinical trials and help making personalized therapy decisions.

Keywords:

• Diffuse large B-cell lymphoma
• miRNA signature
• prognostic biomarker
• risk group stratification
• survival

Acknowledgements

The authors thank Theodora Nedeva for excellent technical assistance. This work has been carried out with the help of the Interdisciplinary Bank of Biomaterials and Data of the University Hospital of Würzburg and the Julius Maximilian University of Würzburg (ibdw). The implementation of the ibdw has been supported by a grant of the Federal Ministry for Education and Research (Grant number FKZ: 01EY1102).

Author contributions

C.N., M.T., H.E. and A.R. designed the research study. C.N., G.G., A.R., and H.R.W. performed the research, analyzed data and wrote the paper. G.G., M.A., M.Z. and R.S. performed statistical and clinical analysis and analyzed data. A.R., H.H., A.S., G.O., N.S. and G.H. provided cases, collected clinical and pathological data and analysedanalyzed data. All authors approved the final manuscript.

Disclosure statement

H.E. received financial support from Celgene/BMS, Janssen, Amgen, Sanofi, Takeda, and GSK. The other authors have no competing interests.

Additional information

Funding

This project and C.N. were supported by a fellowship of the Else Kröner Fresenius-Stiftung (2010_Kolleg.52). This work was also supported by the following grants: DFG FOR 2127 – FKZ SP938/3-2, BMBF Life Sciences – FKZ 031L0173, and by the Bavarian Ministry for Science and Art – bayresq.net (to R.S. and G.G.).