Skip to main page content
Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2014 May 17;7:25.
doi: 10.1186/1755-8794-7-25.

Translating a Gene Expression Signature for Multiple Myeloma Prognosis Into a Robust High-Throughput Assay for Clinical Use

Affiliations
Free PMC article

Translating a Gene Expression Signature for Multiple Myeloma Prognosis Into a Robust High-Throughput Assay for Clinical Use

Ryan van Laar et al. BMC Med Genomics. .
Free PMC article

Abstract

Background: Widespread adoption of genomic technologies in the management of heterogeneous indications, including Multiple Myeloma, has been hindered by concern over variation between published gene expression signatures, difficulty in physician interpretation and the challenge of obtaining sufficient genetic material from limited patient specimens.

Methods: Since 2006, the 70-gene prognostic signature, developed by the University of Arkansas for Medical Sciences (UAMS) has been applied to over 4,700 patients in studies performed in 4 countries and described in 17 peer-reviewed publications. Analysis of control sample and quality control data compiled over a 12-month period was performed.

Results: Over a 12 month period, the 70-gene prognosis score (range 0-100) of our multiple myeloma cell-line control sample had a standard deviation of 2.72 and a coefficient of variance of 0.03. The whole-genome microarray profile used to calculate a patient's GEP70 score can be generated with as little as 15 ng of total RNA; approximately 30,000 CD-138+ plasma cells. Results from each GEP70 analysis are presented as either low (70-gene score <45.2) or high (≥45.2) risk for relapse (newly diagnosed setting) or shorter overall survival (relapse setting). A personalized and outcome-annotated gene expression heat map is provided to assist in the clinical interpretation of the result.

Conclusions: The 70-gene assay, commercialized under the name 'MyPRS®' (Myeloma Prognostic Risk Score) and performed in Signal Genetics' CLIA-certified high throughput flow-cytometry and molecular profiling laboratory is a reproducible and standardized method of multiple myeloma prognostication.

Figures

Figure 1
Figure 1
Inter-laboratory reproduciblity; Analysis of GEP70 scores calculated on 99 clinical bone marrow aspirate specimens analyzed in parallel by UAMS Myeloma Instiute for Research and Treatment (MIRT) (1a. y-axis) and Signal Genetics CLIA laboratory (1b x-axis). Lines at 45.2 correspond to the low/high risk threshold.
Figure 2
Figure 2
Analysis of MyPRS Control Sample stability over time. MyPRS Control Sample stability over time; (A) H929 Control sample GEP70 scores generated bewteen August 2012 and August 2013 exhitit high stability over time. No gradual shift up or down in risk score is observed. Standard deviation of risk scores in this analysies was 2.72 and a CV of 0.03. (B) Control sample data from September 2013 to February 2014 (new aliquot of H929) shows further improvements in assay stability. Standard deviation 1.70, CV 0.019.
Figure 3
Figure 3
Intra-laboratory reproducibility; Comparison of GEP70 scores from 30 specimens analyzed in duplicate. Correlation coefficient of 0.98 shows an extremely high degree of reproducibility between experiments.
Figure 4
Figure 4
A-D: Analysis of bone marrow aspirate specimen variability vs. RNA quality and GEP70 risk score; The relative CD138+ cell content (pre- and post- sorting) vs RNA integrity and GEP70 risk score of 1000 randomly selected clinical specimens submitted for MyPRS analysis is shown above. The wide range in cellularity of specimens submitted for MyPRS analysis (0.25 - 96.2%) does not impact on the quality of the RNA isolated for gene expression profiling, nor the final GEP70 risk score.
Figure 5
Figure 5
Personalized MyPRS eene expression heatmaps; Generated for each MyPRS analysis performed to visualize the assocaition between the individual gene expression levels (green = low expression, red = high expression), GEP70 score and patient outcome. Yellow line indicates the expression profile of the patient currently being analyzed, with the horizontal position determined by the individual GEP70 score. The red/blue panel at the top of the heatmap corresponds to 5 year relapse events, as observed in the algorithm training series.

Similar articles

See all similar articles

Cited by 7 articles

See all "Cited by" articles

References

    1. Veer LJ, v ’t Dai H, van de Vijver MJ, He YD, Hart AA, Mao M, Peterse HL, van der Kooy K, Marton MJ, Witteveen AT, Schreiber GJ, Kerkhoven RM, Roberts C, Linsley PS, Bernards R, Friend SH. Gene expression profiling predicts clinical outcome of breast cancer. Nature. 2002;7(6871):530–536. doi: 10.1038/415530a. - DOI - PubMed
    1. Van Laar RK. An online gene expression assay for determining adjuvant therapy eligibility in patients with stage 2 or 3 colon cancer. Br J Cancer. 2010;7(12):1852–1857. doi: 10.1038/sj.bjc.6605970. - DOI - PMC - PubMed
    1. Bittner M, Meltzer P, Chen Y, Jiang Y, Seftor E, Hendrix M, Radmacher M, Simon R, Yakhini Z, Ben-Dor A, Sampas N, Dougherty E, Wang E, Marincola F, Gooden C, Lueders J, Glatfelter A, Pollock P, Carpten J, Gillanders E, Leja D, Dietrich K, Beaudry C, Berens M, Alberts D, Sondak V. Molecular classification of cutaneous malignant melanoma by gene expression profiling. Nature. 2000;7(6795):536–540. doi: 10.1038/35020115. - DOI - PubMed
    1. Roepman P, Jassem J, Smit EF, Muley T, Niklinski J, van de Velde T, Witteveen AT, Rzyman W, Floore A, Burgers S, Giaccone G, Meister M, Dienemann H, Skrzypski M, Kozlowski M, Mooi WJ, van Zandwijk N. An immune response enriched 72-gene prognostic profile for early-stage non-small-cell lung cancer. Clin Cancer Res. 2009;7(1):284–290. doi: 10.1158/1078-0432.CCR-08-1258. - DOI - PubMed
    1. Perou C, Sorlie T, Eisen M, van de Rijn M, Jeffrey S, Rees C, Pollack J, Ross D, Johnsen H, Akslen L. Molecular portraits of human breast tumours. Nature. 2000;7(6797):747–752. doi: 10.1038/35021093. - DOI - PubMed
Feedback