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Romm, Jane

Mayo Clinic

Johns Hopkins University

Citations 2

Identification of Two Genetic Loci Associated with Leukopenia after Chemotherapy in Patients with Breast Cancer
Fasching, Peter A. , Liu, Duan , Scully, Steve, Ingle, James N. , Lyra, Paulo C. , Rack, Brigitte , Hein, Alexander , Ekici, Arif B. , Reis, André , Schneeweiß, Andreas , Tesch, Hans , Heinrich, Georg, Beckmann, Matthias W. , Ruebner, Matthias , Huebner, Hanna , Lambrechts, Diether , Madden, Ebony , Shen, Jess, Romm, Jane, Doheny, Kim, Jenkins, Gregory D. , Cunningham, Julie M. , Janni, Wolfgang , Schaid, Daniel J. , Häberle, Lothar , Weinshilboum, Richard M. , Wang, Liewei , Lambrechts, Diether , Lambrechts, Diether , Li, Liang , Fridley, Brooke L , Cunningham, Julie M , Janni, Wolfgang , Monteiro, Alvaro N , Ingle, J , Lambrechts, Diether , Hein, Alexander , Ekici, Arif B , Reis, André , Morais Lyra, Paulo Cilas , Liu, Duan , Fehm, Tanja , Carlson, Erin E. , Li, Liang , Fridley, Brooke L. , Monteiro, Álvaro N.A. , Weinshilboum, Richard M.

Clinical Cancer Research | June 27, 2022 | Volume: 28 | Issue: 15 | Pages: 3342-3355

10.1158/1078-0432.ccr-20-4774 Get It

Abstract Purpose: To identify molecular predictors of grade 3/4 neutropenic or leukopenic events (NLE) after chemotherapy using a genome-wide association study (GWAS). Experimental Design: A GWAS was performed on patients in the phase III chemotherapy study SUCCESS-A (n = 3,322). Genotyping was done using the Illumina HumanOmniExpress-12v1 array. Findings were functionally validated with cell culture models and the genotypes and gene expression of possible causative genes were correlated with clinical treatment response and prognostic outcomes. Results: One locus on chromosome 16 (rs4784750; NLRC5; P = 1.56E-8) and another locus on chromosome 13 (rs16972207; TNFSF13B; P = 3.42E-8) were identified at a genome-wide significance level. Functional validation revealed that expression of these two genes is altered by genotype-dependent and chemotherapy-dependent activity of two transcription factors. Genotypes also showed an association with disease-free survival in patients with an NLE. Conclusions: Two loci in NLRC5 and TNFSF13B are associated with NLEs. The involvement of the MHC I regulator NLRC5 implies the possible involvement of immuno-oncological pathways.
The OncoArray Consortium: A Network for Understanding the Genetic Architecture of Common Cancers
Wang, Zhaoming , Schumacher, Fredrick R. , Gayther, Simon A. , Casey, Graham , Sellers, Thomas A. , Gruber, Stephen B., Dunning, Alison M. , Michailidou, Kyriaki , Fachal, Laura , Doheny, Kimberly F. , Li, Yafang , Xiao, Xiangjun , Romm, Jane, Pugh, Elizabeth, Coetzee, Gerhard A. , Hazelett, Dennis J. , Bojesen, Stig E. , Caga-Anan, Charlisse , Haiman, Christopher A. , Kamal, Ahsan , Luccarini, Craig , Tessier, Daniel C., Vincent, Daniel , Bacot, François, Berg, David Van Den , Nelson, Stefanie A. , Demetriades, Stephen, Goldgar, David E., Forman, Judith L., Conti, David V. , Bickeböller, Heike , Risch, Angela , Waldenberger, Mélanie , Brüske‐Hohlfeld, Irene, Hicks, Belynda , McGuffog, Lesley, Kuchenbaecker, Karoline , Soucy, Penny, Manz, Judith, Cunningham, Julie M. , Butterbach, Katja, Kote‐Jarai, Zsofia , Kraft, Peter , Lindström, Sara , Adams, Marcia, McKay, James , Phelan, Catherine M., Benlloch, Sara, Kelemen, Linda E., Brennan, Paul , Riggan, Marjorie J. , O’Mara, Tracy A. , Shen, Hongbing , Shi, Yongyong , Thompson, Deborah J. , Goodman, Marc T. , Nielsen, Sune F. , LaBoissière, Sylvie, Schmit, Stephanie L. , Shelford, Tameka, Edlund, Christopher K., Taylor, Jack A. , Field, John K. , Park, Sue K. , Offit, Kenneth , Thomassen, Mads , Schmutzler, Rita K., Ottini, Laura , Hung, Rayjean J., Olama, Ali Amin Al , Peters, Ulrike , Eeles, Rosalind A. , Seldin, Michael F., Gillanders, Elizabeth M. , Seminara, Daniela, Antoniou, Antonis C. , Chenevix‐Trench, Georgia , Simard, Jacques , Easton, Douglas F. , Durocher, Francine , Hung, Rayjean J. , Amos, Christopher I. , Dennis, Joe , Byun, Jinyoung , Hunter, David J. , Spurdle, Amanda B. , Couch, Fergus J. , Giles, Graham G. , Ling, Hua , Lee, Andrew , FitzGerald, Liesel M. , Berchuck, Andrew , Marchini, Jonathan , Pharoah, Paul D.P. , Chanock, Stephen Jacob , Hazelett, Dennis J , Eeles, Rosalind A , Van Den Berg, David J , Hung, Rayjean J , Wang, Zhaoming , O'Mara, Tracy A , Field, John K , Dunning, Alison M , Michailidou, Kyriaki , Taylor, Jack A , Kraft, Peter , Simard, Jacques , Chenevix-Trench, Georgia , Ottini, Laura , Conti, David V , Bojesen, Stig E , Risch, Angela , Bickeböller, Heike , Shen, Hongbing , Goodman, Marc T , Fachal, Laura

Cancer Epidemiology, Biomarkers & Prevention | October 3, 2016 | Volume: 26 | Issue: 1 | Pages: 126-135

10.1158/1055-9965.epi-16-0106 Get It

Abstract Background: Common cancers develop through a multistep process often including inherited susceptibility. Collaboration among multiple institutions, and funding from multiple sources, has allowed the development of an inexpensive genotyping microarray, the OncoArray. The array includes a genome-wide backbone, comprising 230,000 SNPs tagging most common genetic variants, together with dense mapping of known susceptibility regions, rare variants from sequencing experiments, pharmacogenetic markers, and cancer-related traits. Methods: The OncoArray can be genotyped using a novel technology developed by Illumina to facilitate efficient genotyping. The consortium developed standard approaches for selecting SNPs for study, for quality control of markers, and for ancestry analysis. The array was genotyped at selected sites and with prespecified replicate samples to permit evaluation of genotyping accuracy among centers and by ethnic background. Results: The OncoArray consortium genotyped 447,705 samples. A total of 494,763 SNPs passed quality control steps with a sample success rate of 97% of the samples. Participating sites performed ancestry analysis using a common set of markers and a scoring algorithm based on principal components analysis. Conclusions: Results from these analyses will enable researchers to identify new susceptibility loci, perform fine-mapping of new or known loci associated with either single or multiple cancers, assess the degree of overlap in cancer causation and pleiotropic effects of loci that have been identified for disease-specific risk, and jointly model genetic, environmental, and lifestyle-related exposures. Impact: Ongoing analyses will shed light on etiology and risk assessment for many types of cancer. Cancer Epidemiol Biomarkers Prev; 26(1); 126–35. ©2016 AACR.