Gene expression profiling in multiple myeloma - reporting of entities, risk, and targets in clinical routine

• Verfasst von: Meißner, Tobias [VerfasserIn]
• Verfasst von: Seckinger, Anja [VerfasserIn]
• Verfasst von: Rème, Thierry [VerfasserIn]
• Verfasst von: Hielscher, Thomas [VerfasserIn]
• Verfasst von: Möhler, Thomas [VerfasserIn]
• Verfasst von: Neben, Kai [VerfasserIn]
• Verfasst von: Goldschmidt, Hartmut [VerfasserIn]
• Verfasst von: Klein, Bernard [VerfasserIn]
• Verfasst von: Hose, Dirk [VerfasserIn]
• Titel: Gene expression profiling in multiple myeloma - reporting of entities, risk, and targets in clinical routine
• Verf.angabe: Tobias Meißner, Anja Seckinger, Thierry Rème, Thomas Hielscher, Thomas Möhler, Kai Neben, Hartmut Goldschmidt, Bernard Klein, and Dirk Hose
• E-Jahr: 2011
• Jahr: November 30 2011
• Umfang: 8 S.
• Fussnoten: Gesehen am 17.08.2022
• Titel Quelle: Enthalten in: Clinical cancer research
• Ort Quelle: Philadelphia, Pa. [u.a.] : AACR, 1995
• Jahr Quelle: 2011
• Band/Heft Quelle: 17(2011), 23, Seite 7240-7247
• ISSN Quelle: 1557-3265
• DOI: doi:10.1158/1078-0432.CCR-11-1628
• Datenträger: Online-Ressource
• Sprache: eng
• K10plus-PPN: 1814532528

Abstract

Purpose: Multiple myeloma is an incurable malignant plasma cell disease characterized by survival ranging from several months to more than 15 years. Assessment of risk and underlying molecular heterogeneity can be excellently done by gene expression profiling (GEP), but its way into clinical routine is hampered by the lack of an appropriate reporting tool and the integration with other prognostic factors into a single “meta” risk stratification.Experimental Design: The GEP-report (GEP-R) was built as an open-source software developed in R for gene expression reporting in clinical practice using Affymetrix microarrays. GEP-R processes new samples by applying a documentation-by-value strategy to the raw data to be able to assign thresholds and grouping algorithms defined on a reference cohort of 262 patients with multiple myeloma. Furthermore, we integrated expression-based and conventional prognostic factors within one risk stratification (HM-metascore).Results: The GEP-R comprises (i) quality control, (ii) sample identity control, (iii) biologic classification, (iv) risk stratification, and (v) assessment of target genes. The resulting HM-metascore is defined as the sum over the weighted factors gene expression-based risk-assessment (UAMS-, IFM-score), proliferation, International Staging System (ISS) stage, t(4;14), and expression of prognostic target genes (AURKA, IGF1R) for which clinical grade inhibitors exist. The HM-score delineates three significantly different groups of 13.1%, 72.1%, and 14.7% of patients with a 6-year survival rate of 89.3%, 60.6%, and 18.6%, respectively.Conclusion: GEP reporting allows prospective assessment of risk and target gene expression and integration of current prognostic factors in clinical routine, being customizable about novel parameters or other cancer entities. Clin Cancer Res; 17(23); 7240-7. ©2011 AACR.