title: Genomic variation in myeloma: design, content, and initial application of the Bank On A Cure SNP Panel to detect associations with progression-free survival.
abstract: BACKGROUND
  We have engaged in an international program designated the Bank On A Cure, which has established DNA banks from multiple cooperative and institutional clinical trials, and a platform for examining the association of genetic variations with disease risk and outcomes in multiple myeloma. We describe the development and content of a novel custom SNP panel that contains 3404 SNPs in 983 genes, representing cellular functions and pathways that may influence disease severity at diagnosis, toxicity, progression or other treatment outcomes. A systematic search of national databases was used to identify non-synonymous coding SNPs and SNPs within transcriptional regulatory regions. To explore SNP associations with PFS we compared SNP profiles of short term (less than 1 year, n = 70) versus long term progression-free survivors (greater than 3 years, n = 73) in two phase III clinical trials.
  
  
  RESULTS
  Quality controls were established, demonstrating an accurate and robust screening panel for genetic variations, and some initial racial comparisons of allelic variation were done. A variety of analytical approaches, including machine learning tools for data mining and recursive partitioning analyses, demonstrated predictive value of the SNP panel in survival. While the entire SNP panel showed genotype predictive association with PFS, some SNP subsets were identified within drug response, cellular signaling and cell cycle genes.
  
  
  CONCLUSIONS
  A targeted gene approach was undertaken to develop an SNP panel that can test for associations with clinical outcomes in myeloma. The initial analysis provided some predictive power, demonstrating that genetic variations in the myeloma patient population may influence PFS.
authors.affiliation: Cancer Center, University of Minnesota, Minneapolis, MN, USA. vanne001@umn.edu
authors.forename: Brian
authors.initials: B
authors.lastname: Van Ness
authors.forename: Christine
authors.initials: C
authors.lastname: Ramos
authors.forename: Majda
authors.initials: M
authors.lastname: Haznadar
authors.forename: Antje
authors.initials: A
authors.lastname: Hoering
authors.forename: Jeff
authors.initials: J
authors.lastname: Haessler
authors.forename: John
authors.initials: J
authors.lastname: Crowley
authors.forename: Susanna
authors.initials: S
authors.lastname: Jacobus
authors.forename: Martin
authors.initials: M
authors.lastname: Oken
authors.forename: Vincent
authors.initials: V
authors.lastname: Rajkumar
authors.forename: Philip
authors.initials: P
authors.lastname: Greipp
authors.forename: Bart
authors.initials: B
authors.lastname: Barlogie
authors.forename: Brian
authors.initials: B
authors.lastname: Durie
authors.forename: Michael
authors.initials: M
authors.lastname: Katz
authors.forename: Gowtham
authors.initials: G
authors.lastname: Atluri
authors.forename: Gang
authors.initials: G
authors.lastname: Fang
authors.forename: Rohit
authors.initials: R
authors.lastname: Gupta
authors.forename: Michael
authors.initials: M
authors.lastname: Steinbach
authors.forename: Vipin
authors.initials: V
authors.lastname: Kumar
authors.forename: Richard
authors.initials: R
authors.lastname: Mushlin
authors.forename: David
authors.initials: D
authors.lastname: Johnson
authors.forename: Gareth
authors.initials: G
authors.lastname: Morgan
mesh_terms: D030541:Databases, Genetic; D018572:Disease-Free Survival; D020022:Genetic Predisposition to Disease; D023281:Genomics; D006801:Humans; D009101:Multiple Myeloma / Q000175:diagnosis* / Q000235:genetics*; D016366:Open Reading Frames; D020641:Polymorphism, Single Nucleotide; D011237:Predictive Value of Tests; D011401:Promoter Regions, Genetic
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