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

NCT01619358 | Unknown DMC

• 1 other identifier: 2012/00058
• Study Type: observational
• Target: 150
• Locations: 1 country
• Sites: 1

Brief 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. 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. 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. 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

Multiple Myeloma

Outcome Measures

Primary Outcomes (1)

• 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 Outcomes (2)

• Prospectively validate predictive biomarkers in MM

• Study the impact of different treatment phases on minimal residual disease (MRD) and their impaction outcome.

Eligibility Criteria

• Age: 21 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Probability Sample

Study Population

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

You may qualify if:

• All Patients fulfilling IMWG diagnostic criteria for myeloma

You may not qualify if:

• Unable to take consent

Sponsors & Collaborators

• National University Hospital, Singapore: lead

Study Sites (1)

Nationa University Hospital

Singapore, Singapore

RECRUITING

Related Publications (2)

• Bergsagel PL, Kuehl WM, Zhan F, Sawyer J, Barlogie B, Shaughnessy J Jr. Cyclin D dysregulation: an early and unifying pathogenic event in multiple myeloma. Blood. 2005 Jul 1;106(1):296-303. doi: 10.1182/blood-2005-01-0034. Epub 2005 Mar 8.

  PMID: 15755896 BACKGROUND

• Chng WJ, Braggio E, Mulligan G, Bryant B, Remstein E, Valdez R, Dogan A, Fonseca R. The centrosome index is a powerful prognostic marker in myeloma and identifies a cohort of patients that might benefit from aurora kinase inhibition. Blood. 2008 Feb 1;111(3):1603-9. doi: 10.1182/blood-2007-06-097774. Epub 2007 Nov 15.

  PMID: 18006703 BACKGROUND

MeSH Terms

Conditions

Multiple Myeloma

Condition Hierarchy (Ancestors)

Neoplasms, Plasma Cell; Neoplasms by Histologic Type; Neoplasms; Hemostatic Disorders; Vascular Diseases; Cardiovascular Diseases; Paraproteinemias; Blood Protein Disorders; Hematologic Diseases; Hemic and Lymphatic Diseases; Hemorrhagic Disorders; Lymphoproliferative Disorders; Immunoproliferative Disorders; Immune System Diseases

Central Study Contacts

Wee Joo Chng, PhD

CONTACT

+65 6779 5555; Wee_Joo_Chng@nuhs.edu.sg

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: April 2, 2012
• First Posted: June 14, 2012
• Study Start: March 1, 2012
• Primary Completion: February 1, 2017
• Last Updated: December 11, 2013

Record last verified: 2013-12

Locations

SG (1)