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

NCT01619358 · Status: UNKNOWN · Type: OBSERVATIONAL · Enrollment: 150

Last updated 2013-12-11

No results posted yet for this study

Summary

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

1. 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.
2. The investigators hypothesized that TRAF3 deletion or mutation and MYC activation will identify patients that will have a significantly better response to Velcade.
3. 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

Sponsors & Collaborators

  • National University Hospital, Singapore

    lead OTHER

Eligibility

Min Age
21 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2012-03-31
Primary Completion
2017-02-28

Countries

  • Singapore

Study Locations

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Entities

Diseases

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT01619358 on ClinicalTrials.gov