Four genes predict high risk of progression from smoldering to symptomatic multiple myeloma (SWOG S0120)

Abstract

© F e r r a t a S t o r t i F o u n d a t i o nGenomics of high-risk SMM haematologica | 2015; 100(9) 1215 Methods Eligibility criteria and study designPatients with SMM seen at the Myeloma Institute for Research and Therapy were included in a prospective, observational clinical trial (SWOG S0120) as part of a national cooperative group trial to identify biological correlates that may relate to progression to symptomatic disease. Other eligibility criteria included no prior therapy for the plasma cell disorder and willingness to submit samples for research. Diagnostic criteria for SMM were based on the International Myeloma Working Group convention.3 All patients signed informed consent, in keeping with the Declaration of Helsinki and federal and institutional guidelines. The protocol was approved by the National Cancer Institute and all participating centers' internal review boards.All patients underwent detailed clinical staging at initial registration, including full blood count, analysis of blood chemistry, and standard MM-related serological and urinary measurements. Nephelometric analysis was performed to determine serum immunoglobulin levels. Immunofixation analyses of serum and urine were performed to define the nature of the monoclonal protein present in serum and/or urine. Bone marrow aspirates and biopsies were obtained for cytological and histopathological evaluation of the degree of plasma cell infiltration, including immunohistochemical clonality assessment. Metaphase karyotyping was performed on at least 20 Giemsa-stained metaphases. 23 In most patients, serum FLC assays were used to quantify k and l light chains. Imaging studies involved standard metastatic bone surveys by X-ray examination, and, when possible, MRI of the entire spine was used to identify focal lesions. The minimum follow-up of patients involved MM-related laboratory studies at 3, 6, and 12 months in the first year, and then every 6 to 12 months. Gene expression profiling and statistical methodsA sample of bone marrow aspirate was collected to isolate CD138 + plasma cells with immunomagnetic bead selection (autoMACS; Miltenyi Biotec) as described elsewhere. 24 The purity of the plasma cells was monitored by flow cytometry and >85% purity was used as a criterion for inclusion of GEP data. Total RNA from these plasma cells was used for the GEP with Affymetrix U133 Plus 2.0 microarrays. We identified patients with SMM and baseline GEP data who were cared for at this institution. We evaluated 54,675 Affymetrix gene probes for their potential to predict time to myeloma therapy (TTT). Probes were ranked by their qvalues; 25 we used 10-fold cross validation to identify the number of genes at the top of this list, which collectively maximized the concordance between risk score and survival. Gene scores were computed by subtracting the sum of the expressions of the up-regulated probes from the sum of the expressions of the down-regulated probes, then dividing by the total number of probes. A running log-rank test was used to iden...

Diagnosis, risk stratification and management of monoclonal gammopathy of undetermined significance and smoldering multiple myeloma

“…In addition, the Arkansas group generated a risk-stratification model based on expression levels of only four genes combined with serum M-protein (≥30 g/L) and albumin levels (<35 g/L). The high-risk, intermediaterisk, and low-risk groups had a 2-year progression probability of 5.0%, 44.8%, and 85.7%, respectively [54].…”

“…Other factors that predict progression to symptomatic disease include abnormal plasma cell phenotype in ≥95% of cells, high plasma cell proliferative rate, hypogammaglobulinemia, gene expression profile of the purified MM cells, abnormal free lightchain ratio, increasing M-protein, presence and development of MRI abnormalities, or peripheral blood circulating plasma cells [27,43,44,[49][50][51][52][53][54]. Also, hyperdiploidy, del(17p), t(4;14), and ampl(1q) are adverse prognostic factors in SMM, independent of tumor load [55,56] (Figure 1).…”

Therapeutic Targets and Signaling Pathways for Diagnosis of Myeloma

“…The RNA-sequencing have been created and will be incorporated into GEP to enhance estimation of the outcome in the future [98]. Of these modifiers, non-coding RNA are mainly researched in MM since reports have already proved that micro-RNA contribute to myeloma formation and can be used to predict prognosis or response to auto-transplant [98]. MiR17 and miR886-5p have been observed as a strong prognostic indicator in a study of 163 newly diagnosed patients from the MRC Myeloma IX l trial [99].…”

Gene Expression Profiles in Myeloma: Ready for the Real World?

“…Investigators from UAMS has reported that 70-genes signature and its derivative are able to predict outcome in context of MGUS and SMM (23). In the context of PCL, in a cohort of 21 patients, a 27 gene expression signature was identified as an independent prognostic factor (24).…”