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Novel Gene and Network Associations Found for Acute Lymphoblastic Leukemia Using Case-Control and Family-Based Studies in Multiethnic Populations.

Author(s): Nakka, Priyanka; Archer, Natalie P; Xu, Heng; Lupo, Philip J; Raphael, Benjamin J; et al

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dc.contributor.authorNakka, Priyanka-
dc.contributor.authorArcher, Natalie P-
dc.contributor.authorXu, Heng-
dc.contributor.authorLupo, Philip J-
dc.contributor.authorRaphael, Benjamin J-
dc.contributor.authorYang, Jun J-
dc.contributor.authorRamachandran, Sohini-
dc.date.accessioned2021-10-08T19:47:03Z-
dc.date.available2021-10-08T19:47:03Z-
dc.date.issued2017-10en_US
dc.identifier.citationNakka, Priyanka, Archer, Natalie P, Xu, Heng, Lupo, Philip J, Raphael, Benjamin J, Yang, Jun J, Ramachandran, Sohini. (2017). Novel Gene and Network Associations Found for Acute Lymphoblastic Leukemia Using Case-Control and Family-Based Studies in Multiethnic Populations.. Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology, 26 (10), 1531 - 1539. doi:10.1158/1055-9965.epi-17-0360en_US
dc.identifier.issn1055-9965-
dc.identifier.urihttp://arks.princeton.edu/ark:/88435/pr12g14-
dc.description.abstract<b>Background:</b> Acute lymphoblastic leukemia (ALL) is the most common childhood cancer, suggesting that germline variants influence ALL risk. Although multiple genome-wide association (GWA) studies have identified variants predisposing children to ALL, it remains unclear whether genetic heterogeneity affects ALL susceptibility and how interactions within and among genes containing ALL-associated variants influence ALL risk.<b>Methods:</b> Here, we jointly analyzed two published datasets of case-control GWA summary statistics along with germline data from ALL case-parent trios. We used the gene-level association method PEGASUS to identify genes with multiple variants associated with ALL. We then used PEGASUS gene scores as input to the network analysis algorithm HotNet2 to characterize the genomic architecture of ALL.<b>Results:</b> Using PEGASUS, we confirmed associations previously observed at genes such as <i>ARID5B, IKZF1, CDKN2A/2B</i>, and <i>PIP4K2A</i>, and we identified novel candidate gene associations. Using HotNet2, we uncovered significant gene subnetworks that may underlie inherited ALL risk: a subnetwork involved in B-cell differentiation containing the ALL-associated gene <i>CEBPE</i>, and a subnetwork of homeobox genes, including <i>MEIS1</i><b>Conclusions:</b> Gene and network analysis uncovered loci associated with ALL that are missed by GWA studies, such as <i>MEIS1</i> Furthermore, ALL-associated loci do not appear to interact directly with each other to influence ALL risk, and instead appear to influence leukemogenesis through multiple, complex pathways.<b>Impact:</b> We present a new pipeline for <i>post hoc</i> analysis of association studies that yields new insight into the etiology of ALL and can be applied in future studies to shed light on the genomic underpinnings of cancer. <i>Cancer Epidemiol Biomarkers Prev; 26(10); 1531-9. ©2017 AACR</i>.en_US
dc.format.extent1531 - 1539en_US
dc.languageengen_US
dc.language.isoen_USen_US
dc.relation.ispartofCancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncologyen_US
dc.rightsAuthor's manuscripten_US
dc.titleNovel Gene and Network Associations Found for Acute Lymphoblastic Leukemia Using Case-Control and Family-Based Studies in Multiethnic Populations.en_US
dc.typeJournal Articleen_US
dc.identifier.doidoi:10.1158/1055-9965.epi-17-0360-
dc.identifier.eissn1538-7755-
pu.type.symplectichttp://www.symplectic.co.uk/publications/atom-terms/1.0/journal-articleen_US

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