Gene Expression Profiling in Multiple Myeloma—Reporting of Entities, Risk, and Targets in Clinical Routine

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. Ó2011 AACR.

Association of Antigen-Specific T-cell Responses with Antigen Expression and Immunoparalysis in Multiple Myeloma

“…In contrast, MAGE-A2, MAGE-A3, and NY-ESO-1 are not expressed on normal bone marrow plasma cells, but aberrantly in malignant plasma cells (21,36). In our study, the specific T-cell responses against HM1.24 were used to analyze the general stage-dependent impact of myelomaspecific immunosuppression.…”

“…Of the four CTA used, HM1.24 is expressed on all normal and malignant plasma cells (36). In contrast, MAGE-A2, MAGE-A3, and NY-ESO-1 are not expressed on normal bone marrow plasma cells, but aberrantly in malignant plasma cells (21,36).…”

The 7p15.3 (rs4487645) association for multiple myeloma shows strong allele-specific regulation of the MYC-interacting gene CDCA7L in malignant plasma cells

“…Expressions sets were analyzed using PEER 6,7 to infer broad variance components in the data and computed residuals of expression were used for eQTL analyses. …”

“…6 Expression data have been deposited in ArrayExpress (E-MTAB-2299) and Gene Expression Omnibus (GSE21349). Analyses were undertaken using R (v.2.8).…”

Understanding the multiple biological aspects leading to myeloma

“…80,81 Gene expression profiling (GEP) can also define independent signatures that could also predict outcome. [112][113][114][115] Identifying these groups and designing clinical trials for them will refine our current management strategies, avoiding over or under treating specific subgroups. Some clinical trials have already been designed in this respect.…”