Genomic variation in myeloma: Design, content, and initial application of the Bank On A Cure SNP Panel to detect associations with progression-free survival

Brian Van Ness, Christine Ramos, Majda Haznadar, Antje Hoering, Jeff Haessler, John Crowley, Susanna Jacobus, Martin Oken, S Vincent Rajkumar, Philip Greipp, Bart Barlogie, Brian Durie, Michael Katz, Gowtham Atluri, Gang Fang, Rohit Gupta, Michael Steinbach, Vipin Kumar, Richard Mushlin, David JohnsonGareth Morgan

Research output: Contribution to journalArticle

39 Citations (Scopus)

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. Conclusion: 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.

Original languageEnglish (US)
Article number26
JournalBMC Medicine
Volume6
DOIs
StatePublished - Sep 8 2008

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Disease-Free Survival
Single Nucleotide Polymorphism
cdc Genes
Phase III Clinical Trials
Data Mining
Nucleic Acid Regulatory Sequences
Multiple Myeloma
Quality Control
Genes
Survivors
Genotype
Clinical Trials
Databases
Survival
DNA
Pharmaceutical Preparations
Population

ASJC Scopus subject areas

  • Medicine(all)

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Genomic variation in myeloma : Design, content, and initial application of the Bank On A Cure SNP Panel to detect associations with progression-free survival. / Van Ness, Brian; Ramos, Christine; Haznadar, Majda; Hoering, Antje; Haessler, Jeff; Crowley, John; Jacobus, Susanna; Oken, Martin; Rajkumar, S Vincent; Greipp, Philip; Barlogie, Bart; Durie, Brian; Katz, Michael; Atluri, Gowtham; Fang, Gang; Gupta, Rohit; Steinbach, Michael; Kumar, Vipin; Mushlin, Richard; Johnson, David; Morgan, Gareth.

In: BMC Medicine, Vol. 6, 26, 08.09.2008.

Research output: Contribution to journalArticle

Van Ness, B, Ramos, C, Haznadar, M, Hoering, A, Haessler, J, Crowley, J, Jacobus, S, Oken, M, Rajkumar, SV, Greipp, P, Barlogie, B, Durie, B, Katz, M, Atluri, G, Fang, G, Gupta, R, Steinbach, M, Kumar, V, Mushlin, R, Johnson, D & Morgan, G 2008, 'Genomic variation in myeloma: Design, content, and initial application of the Bank On A Cure SNP Panel to detect associations with progression-free survival', BMC Medicine, vol. 6, 26. https://doi.org/10.1186/1741-7015-6-26
Van Ness, Brian ; Ramos, Christine ; Haznadar, Majda ; Hoering, Antje ; Haessler, Jeff ; Crowley, John ; Jacobus, Susanna ; Oken, Martin ; Rajkumar, S Vincent ; Greipp, Philip ; Barlogie, Bart ; Durie, Brian ; Katz, Michael ; Atluri, Gowtham ; Fang, Gang ; Gupta, Rohit ; Steinbach, Michael ; Kumar, Vipin ; Mushlin, Richard ; Johnson, David ; Morgan, Gareth. / Genomic variation in myeloma : Design, content, and initial application of the Bank On A Cure SNP Panel to detect associations with progression-free survival. In: BMC Medicine. 2008 ; Vol. 6.
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AU - Ramos, Christine

AU - Haznadar, Majda

AU - Hoering, Antje

AU - Haessler, Jeff

AU - Crowley, John

AU - Jacobus, Susanna

AU - Oken, Martin

AU - Rajkumar, S Vincent

AU - Greipp, Philip

AU - Barlogie, Bart

AU - Durie, Brian

AU - Katz, Michael

AU - Atluri, Gowtham

AU - Fang, Gang

AU - Gupta, Rohit

AU - Steinbach, Michael

AU - Kumar, Vipin

AU - Mushlin, Richard

AU - Johnson, David

AU - Morgan, Gareth

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N2 - 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. Conclusion: 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.

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