Genomic-Based Diagnosis, Classification and Targeted Treatment of Multiple Myeloma

Study Overview
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Brief Summary
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Multiple myeloma is an incurable bone marrow cancer characterized by an abnormal expansion of plasma cells that secretes monoclonal immunoglobulin. Over the years, the molecular and genetic heterogeneity of the disease have been dissected. With the maturation of technologies, the time is ripe now to apply genomics to diagnose, classify, risk-stratify and prognosticate myeloma in the clinical setting and use this information to guide current treatment. The investigators hypothesize that the use of gene expression profiling as a single test will be more economical, efficient and accurate compared to the current standard panel of tests done at diagnosis. The investigators also hypothesize that the investigator can use predictive markers to identify prospectively patients who will respond to Velcade and that with more effective trebasedonatment, ability to measure depth of response beyond conventional complete response become important since more patients are achieving conventionally determined complete response. Using a cohort of patients treated on a standard treatment protocol based on Velcade-based induction treatment followed by consolidation and maintenance treatment, the investigators will study specifically the feasibility and accuracy of gene expression diagnostics, the predictive power of the investigators predefined predictive markers and the clinical utility of minimal residual disease measurement in myeloma. The results of the investigators study will allow us to improve the diagnosis, and prognostication of MM patients The investigators hypothesized that this will speed up diagnosis, provide comprehensive information for the classification and risk stratification of MM patients and can completely replace the current FISH assay and may be cheaper. The investigators hypothesized that TRAF3 deletion or mutation and MYC activation will identify patients that will have a significantly better response to Velcade. Modern treatment induced deeper response. More sensitive method of disease detection will allow us to know the fully extent of response to these treatment

Conditions
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Multiple Myeloma

Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: All Patients fulfilling IMWG diagnostic criteria for myeloma Exclusion Criteria: Unable to take consent

Ages Eligible for Study
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Minimum Age: 21 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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No

Study Plan
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How is the study designed?
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What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Prospectively validate the use of gene expression profiling (GEP) for the risk-stratification and classification of MM | All patients will have additional bone marrow taken for GEP studies after informed consent at entry into the treatment protocol. CD138 positive cells will be selected using magnetic beads and RNA extracted. The quality of RNA will be checked using the Agilent Bioanalyzer. GEP will be performed using Affymetrix U133plus2.0 chip. |  | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Prospectively validate predictive biomarkers in MM | We will prospectively validate 4 predictive makers we have previously identified for Velcade. Using diagnostic samples from patients entered into the above treatment protocol, we will assay for MYC activationusing IHC, TRAF3 inactivation using FISH for TRAF3 deletion and sequencing to check for TRAF3 mutations, NKFB index by GEP, and MYC activation index (MAI) by GEP. |  | 
| Study the impact of different treatment phases on minimal residual disease (MRD) and their impaction outcome. | We will be assessing MRD using 4 methods: ASO-PCR FCM sFLC Serum Heavylite |  |