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

December 10, 2013 updated by: National University Hospital, Singapore

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

Study Overview

Status

Unknown

Conditions

Study Type

Observational

Enrollment (Anticipated)

150

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

  • Singapore
      • Singapore, Singapore
        • Recruiting
        • Nationa University Hospital
        • Contact:
        • Principal Investigator:
          • Wee Joo Chng, PhD

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

21 years and older (Adult, Older Adult)

Accepts Healthy Volunteers

No

Genders Eligible for Study

All

Sampling Method

Probability Sample

Study Population

Patients being treated with Multiple Myeloma at National University Hospital (Singapore)

Description

Inclusion Criteria:

  • All Patients fulfilling IMWG diagnostic criteria for myeloma

Exclusion Criteria:

  • Unable to take consent

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Observational Models: Cohort
  • Time Perspectives: Prospective

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
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
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:

  1. ASO-PCR
  2. FCM
  3. sFLC
  4. Serum Heavylite

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

National University Hospital, Singapore

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

General Publications

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start

March 1, 2012

Primary Completion (Anticipated)

February 1, 2017

Study Registration Dates

First Submitted

April 2, 2012

First Submitted That Met QC Criteria

June 12, 2012

First Posted (Estimate)

June 14, 2012

Study Record Updates

Last Update Posted (Estimate)

December 11, 2013

Last Update Submitted That Met QC Criteria

December 10, 2013

Last Verified

December 1, 2013

More Information

Terms related to this study

Additional Relevant MeSH Terms

Other Study ID Numbers

  • 2012/00058

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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