Matthew L. Kosel
Mayo Clinic
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Featured researches published by Matthew L. Kosel.
Nature Genetics | 2009
Margaret Wrensch; Robert B. Jenkins; Jeffrey S. Chang; Ru Fang Yeh; Yuanyuan Xiao; Paul A. Decker; Karla V. Ballman; Mitchel S. Berger; Jan C. Buckner; Susan M. Chang; Caterina Giannini; Chandralekha Halder; Thomas M. Kollmeyer; Matthew L. Kosel; Daniel H. Lachance; Lucie McCoy; Brian Patrick O'Neill; Joe Patoka; Alexander R. Pico; Michael D. Prados; Charles P. Quesenberry; Terri Rice; Amanda L. Rynearson; Ivan Smirnov; Tarik Tihan; Joseph L. Wiemels; Ping Yang; John K. Wiencke
The causes of glioblastoma and other gliomas remain obscure. To discover new candidate genes influencing glioma susceptibility, we conducted a principal component–adjusted genome-wide association study (GWAS) of 275,895 autosomal variants among 692 adult high-grade glioma cases (622 from the San Francisco Adult Glioma Study (AGS) and 70 from the Cancer Genome Atlas (TCGA)) and 3,992 controls (602 from AGS and 3,390 from Illumina iControlDB (iControls)). For replication, we analyzed the 13 SNPs with P < 10−6 using independent data from 176 high-grade glioma cases and 174 controls from the Mayo Clinic. On 9p21, rs1412829 near CDKN2B had discovery P = 3.4 × 10−8, replication P = 0.0038 and combined P = 1.85 × 10−10. On 20q13.3, rs6010620 intronic to RTEL1 had discovery P = 1.5 × 10−7, replication P = 0.00035 and combined P = 3.40 × 10−9. For both SNPs, the direction of association was the same in discovery and replication phases.
Nature Genetics | 2012
Robert B. Jenkins; Yuanyuan Xiao; Hugues Sicotte; Paul A. Decker; Thomas M. Kollmeyer; Helen M. Hansen; Matthew L. Kosel; Shichun Zheng; Kyle M. Walsh; Terri Rice; Paige M. Bracci; Lucie McCoy; Ivan Smirnov; Joseph S. Patoka; George Hsuang; Joseph L. Wiemels; Tarik Tihan; Alexander R. Pico; Michael D. Prados; Susan M. Chang; Mitchel S. Berger; Alissa Caron; Stephanie R. Fink; Chandralekha Halder; Amanda L. Rynearson; Brooke L. Fridley; Jan C. Buckner; Brian Patrick O'Neill; Caterina Giannini; Daniel H. Lachance
Variants at 8q24.21 have been shown to be associated with glioma development. By means of tag SNP genotyping and imputation, pooled next-generation sequencing using long-range PCR and subsequent validation SNP genotyping, we identified seven low-frequency SNPs at 8q24.21 that were strongly associated with glioma risk (P = 1 × 10−25 to 1 × 10−14). The most strongly associated SNP, rs55705857, remained highly significant after individual adjustment for the other top six SNPs and two previously published SNPs. After stratifying by histological and tumor genetic subtype, the most significant associations of rs55705857 were with oligodendroglial tumors and gliomas with mutant IDH1 or IDH2 (odds ratio (OR) = 5.1, P = 1.1 × 10−31 and OR = 4.8, P = 6.6 × 10−22, respectively). Strong associations were observed for astrocytomas with mutated IDH1 or IDH2 (grades 2–4) (OR = 5.16–6.66, P = 4.7 × 10−12 to 2.2 × 10−8) but not for astrocytomas with wild-type IDH1 and IDH2 (smallest P = 0.26). The conserved sequence block that includes rs55705857 is consistently modeled as a microRNA.
Breast Cancer Research | 2010
Roger L. Milne; Mia M. Gaudet; Amanda B. Spurdle; Peter A. Fasching; Fergus J. Couch; Javier Benitez; Jose Ignacio Arias Perez; M. Pilar Zamora; Núria Malats; Isabel dos Santos Silva; Lorna Gibson; Olivia Fletcher; Nichola Johnson; Hoda Anton-Culver; Argyrios Ziogas; Jonine D. Figueroa; Louise A. Brinton; Mark E. Sherman; Jolanta Lissowska; John L. Hopper; Gillian S. Dite; Carmel Apicella; Melissa C. Southey; Alice J. Sigurdson; Martha S. Linet; Sara J. Schonfeld; D. Michal Freedman; Arto Mannermaa; Veli-Matti Kosma; Vesa Kataja
IntroductionSeveral common breast cancer genetic susceptibility variants have recently been identified. We aimed to determine how these variants combine with a subset of other known risk factors to influence breast cancer risk in white women of European ancestry using case-control studies participating in the Breast Cancer Association Consortium.MethodsWe evaluated two-way interactions between each of age at menarche, ever having had a live birth, number of live births, age at first birth and body mass index (BMI) and each of 12 single nucleotide polymorphisms (SNPs) (10q26-rs2981582 (FGFR2), 8q24-rs13281615, 11p15-rs3817198 (LSP1), 5q11-rs889312 (MAP3K1), 16q12-rs3803662 (TOX3), 2q35-rs13387042, 5p12-rs10941679 (MRPS30), 17q23-rs6504950 (COX11), 3p24-rs4973768 (SLC4A7), CASP8-rs17468277, TGFB1-rs1982073 and ESR1-rs3020314). Interactions were tested for by fitting logistic regression models including per-allele and linear trend main effects for SNPs and risk factors, respectively, and single-parameter interaction terms for linear departure from independent multiplicative effects.ResultsThese analyses were applied to data for up to 26,349 invasive breast cancer cases and up to 32,208 controls from 21 case-control studies. No statistical evidence of interaction was observed beyond that expected by chance. Analyses were repeated using data from 11 population-based studies, and results were very similar.ConclusionsThe relative risks for breast cancer associated with the common susceptibility variants identified to date do not appear to vary across women with different reproductive histories or body mass index (BMI). The assumption of multiplicative combined effects for these established genetic and other risk factors in risk prediction models appears justified.
Human Molecular Genetics | 2012
Peter A. Fasching; Paul Pharoah; Angela Cox; Heli Nevanlinna; Stig E. Bojesen; Thomas Karn; Annegien Broeks; Flora E. van Leeuwen; Laura J. van't Veer; Renate Udo; Alison M. Dunning; Dario Greco; Kristiina Aittomäki; Carl Blomqvist; Mitul Shah; Børge G. Nordestgaard; Henrik Flyger; John L. Hopper; Melissa C. Southey; Carmel Apicella; Montserrat Garcia-Closas; Mark E. Sherman; Jolanta Lissowska; Caroline Seynaeve; Petra E A Huijts; Rob A. E. M. Tollenaar; Argyrios Ziogas; Arif B. Ekici; Claudia Rauh; Arto Mannermaa
Recent genome-wide association studies identified 11 single nucleotide polymorphisms (SNPs) associated with breast cancer (BC) risk. We investigated these and 62 other SNPs for their prognostic relevance. Confirmed BC risk SNPs rs17468277 (CASP8), rs1982073 (TGFB1), rs2981582 (FGFR2), rs13281615 (8q24), rs3817198 (LSP1), rs889312 (MAP3K1), rs3803662 (TOX3), rs13387042 (2q35), rs4973768 (SLC4A7), rs6504950 (COX11) and rs10941679 (5p12) were genotyped for 25 853 BC patients with the available follow-up; 62 other SNPs, which have been suggested as BC risk SNPs by a GWAS or as candidate SNPs from individual studies, were genotyped for replication purposes in subsets of these patients. Cox proportional hazard models were used to test the association of these SNPs with overall survival (OS) and BC-specific survival (BCS). For the confirmed loci, we performed an accessory analysis of publicly available gene expression data and the prognosis in a different patient group. One of the 11 SNPs, rs3803662 (TOX3) and none of the 62 candidate/GWAS SNPs were associated with OS and/or BCS at P<0.01. The genotypic-specific survival for rs3803662 suggested a recessive mode of action [hazard ratio (HR) of rare homozygous carriers=1.21; 95% CI: 1.09-1.35, P=0.0002 and HR=1.29; 95% CI: 1.12-1.47, P=0.0003 for OS and BCS, respectively]. This association was seen similarly in all analyzed tumor subgroups defined by nodal status, tumor size, grade and estrogen receptor. Breast tumor expression of these genes was not associated with prognosis. With the exception of rs3803662 (TOX3), there was no evidence that any of the SNPs associated with BC susceptibility were associated with the BC survival. Survival may be influenced by a distinct set of germline variants from those influencing susceptibility.
Cancer Genetics and Cytogenetics | 2011
Robert B. Jenkins; Margaret Wrensch; Derek R. Johnson; Brooke L. Fridley; Paul A. Decker; Yuanyuan Xiao; Thomas M. Kollmeyer; Amanda L. Rynearson; Stephanie R. Fink; Terri Rice; Lucie McCoy; Chandralekha Halder; Matthew L. Kosel; Caterina Giannini; Tarik Tihan; Brian Patrick O’Neill; Daniel H. Lachance; Ping Yang; Joseph L. Wiemels; John K. Wiencke
Two recent genome-wide association studies reported that single nucleotide polymorphisms (SNPs) in (or near) TERT (5p15), CCDC26 (8q24), CDKN2A/B (9p21), PHLDB1 (11q23), and RTEL1 (20q13) are associated with infiltrating glioma. From these reports, it was not clear whether the single nucleotide polymorphism associations predispose to glioma in general or whether they are specific to certain glioma grades or morphologic subtypes. To identify hypothesized associations between susceptibility loci and tumor subtype, we genotyped two case-control groups composed of the spectrum of infiltrating glioma subtypes and stratified the analyses by type. We report that specific germ line polymorphisms are associated with different glioma subtypes. CCDC26 (8q24) region polymorphisms are strongly associated with oligodendroglial tumor risk (rs4295627, odds ratio [OR] = 2.05, P = 8.3 × 10(-11)) but not glioblastoma risk. The opposite is true of RTEL (20q13) region polymorphisms, which are significantly associated with glioblastoma (rs2297440, OR = 0.56, P = 4.6 × 10(-10)) but not oligodendroglial tumor. The SNPs in or near CCDC26 (8q24) are associated with oligodendroglial tumors regardless of combined 1p and 19q deletion status; however, the association is greatest for those with combined deletion (rs4295627, OR = 2.77, P = 2.6 × 10(-9)). These observations generate hypotheses concerning the possible mechanisms by which specific SNPs (or alterations in linkage disequilibrium with such SNPs) are associated with glioma development.
Cancer | 2013
Lisa A. Kottschade; Vera J. Suman; Domingo G. Perez; Robert R. McWilliams; Judith S. Kaur; Thomas Amatruda; Francois J. Geoffroy; Howard M. Gross; Peter A. Cohen; Anthony J. Jaslowski; Matthew L. Kosel; Svetomir N. Markovic
Increasing evidence shows chemotherapy in combination with vascular endothelial growth factor (VEGF) inhibition is a clinically active therapy for patients with metastatic melanoma (MM).
Nature Genetics | 2017
Beatrice Melin; Jill S. Barnholtz-Sloan; Margaret Wrensch; Christoffer Johansen; Dora Il'yasova; Ben Kinnersley; Quinn T. Ostrom; Karim Labreche; Yanwen Chen; Georgina Armstrong; Yanhong Liu; Jeanette E. Eckel-Passow; Paul A. Decker; Marianne Labussière; Ahmed Idbaih; Khê Hoang-Xuan; Anna-Luisa Di Stefano; Karima Mokhtari; Jean-Yves Delattre; Peter Broderick; Pilar Galan; Konstantinos Gousias; Johannes Schramm; Minouk J. Schoemaker; Sarah Fleming; Stefan Herms; Stefanie Heilmann; Markus M. Nöthen; Heinz-Erich Wichmann; Stefan Schreiber
Genome-wide association studies (GWAS) have transformed our understanding of glioma susceptibility, but individual studies have had limited power to identify risk loci. We performed a meta-analysis of existing GWAS and two new GWAS, which totaled 12,496 cases and 18,190 controls. We identified five new loci for glioblastoma (GBM) at 1p31.3 (rs12752552; P = 2.04 × 10−9, odds ratio (OR) = 1.22), 11q14.1 (rs11233250; P = 9.95 × 10−10, OR = 1.24), 16p13.3 (rs2562152; P = 1.93 × 10−8, OR = 1.21), 16q12.1 (rs10852606; P = 1.29 × 10−11, OR = 1.18) and 22q13.1 (rs2235573; P = 1.76 × 10−10, OR = 1.15), as well as eight loci for non-GBM tumors at 1q32.1 (rs4252707; P = 3.34 × 10−9, OR = 1.19), 1q44 (rs12076373; P = 2.63 × 10−10, OR = 1.23), 2q33.3 (rs7572263; P = 2.18 × 10−10, OR = 1.20), 3p14.1 (rs11706832; P = 7.66 × 10−9, OR = 1.15), 10q24.33 (rs11598018; P = 3.39 × 10−8, OR = 1.14), 11q21 (rs7107785; P = 3.87 × 10−10, OR = 1.16), 14q12 (rs10131032; P = 5.07 × 10−11, OR = 1.33) and 16p13.3 (rs3751667; P = 2.61 × 10−9, OR = 1.18). These data substantiate that genetic susceptibility to GBM and non-GBM tumors are highly distinct, which likely reflects different etiology.
Carcinogenesis | 2010
Judith A. Schwartzbaum; Yuanyuan Xiao; Yanhong Liu; Spyros Tsavachidis; Mitchel S. Berger; Melissa L. Bondy; Jeffrey S. Chang; Susan M. Chang; Paul A. Decker; Bo Ding; Sarah J. Hepworth; Richard S. Houlston; Fay J. Hosking; Robert B. Jenkins; Matthew L. Kosel; Lucie McCoy; Patricia A. McKinney; Kenneth Muir; Joe Patoka; Michael D. Prados; Terri Rice; Lindsay B. Robertson; Minouk J. Schoemaker; Sanjay Shete; Anthony J. Swerdlow; Joseph L. Wiemels; John K. Wiencke; Ping Yang; Margaret Wrensch
To determine whether inherited variations in immune function single-nucleotide polymorphisms (SNPs), genes or pathways affect glioblastoma risk, we analyzed data from recent genome-wide association studies in conjunction with predefined immune function genes and pathways. Gene and pathway analyses were conducted on two independent data sets using 6629 SNPs in 911 genes on 17 immune pathways from 525 glioblastoma cases and 602 controls from the University of California, San Francisco (UCSF) and a subset of 6029 SNPs in 893 genes from 531 cases and 1782 controls from MD Anderson (MDA). To further assess consistency of SNP-level associations, we also compared data from the UK (266 cases and 2482 controls) and the Mayo Clinic (114 cases and 111 controls). Although three correlated epidermal growth factor receptor (EGFR) SNPs were consistently associated with glioblastoma in all four data sets (Mantel–Haenzel P values = 1 × 10−5 to 4 × 10−3), independent replication is required as genome-wide significance was not attained. In gene-level analyses, eight immune function genes were significantly (minP < 0.05) associated with glioblastoma; the IL-2RA (CD25) cytokine gene had the smallest minP values in both UCSF (minP = 0.01) and MDA (minP = 0.001) data sets. The IL-2RA receptor is found on the surface of regulatory T cells potentially contributing to immunosuppression characteristic of the glioblastoma microenvironment. In pathway correlation analyses, cytokine signaling and adhesion–extravasation–migration pathways showed similar associations with glioblastoma risk in both MDA and UCSF data sets. Our findings represent the first systematic description of immune genes and pathways that characterize glioblastoma risk.
Neuro-oncology | 2013
Terri Rice; Shichun Zheng; Paul A. Decker; Kyle M. Walsh; Paige M. Bracci; Yuanyuan Xiao; Lucie McCoy; Ivan Smirnov; Joseph S. Patoka; Helen M. Hansen; George Hsuang; Joseph L. Wiemels; Tarik Tihan; Alexander R. Pico; Michael D. Prados; Susan M. Chang; Mitchel S. Berger; Alissa Caron; Stephanie R. Fink; Thomas M. Kollmeyer; Amanda L. Rynearson; Jesse S. Voss; Matthew L. Kosel; Brooke L. Fridley; Daniel H. Lachance; Jeanette E. Eckel-Passow; Hugues Sicotte; Brian Patrick O'Neill; Caterina Giannini; John K. Wiencke
INTRODUCTION Recent discoveries of inherited glioma risk loci and acquired IDH mutations are providing new insights into glioma etiology. IDH mutations are common in lower grade gliomas and secondary glioblastomas and uncommon in primary glioblastomas. Because the inherited variant in 11q23 has been associated with risk of lower grade glioma and not with glioblastomas, we hypothesized that this variant increases susceptibility to IDH-mutated gliomas, but not to IDH-wild-type gliomas. METHODS We tested this hypothesis in patients with glioma and controls from the San Francisco Adult Glioma Study, the Mayo Clinic, and Illumina controls (1102 total patients, 5299 total controls). Case-control additive associations of 11q23 risk alleles (rs498872, T allele) were calculated using logistic regression, stratified by tumor IDH status (mutated or wild-type) and by histology and grade. We also adjusted for the recently discovered 8q24 glioma risk locus rs55705857 G allele. RESULTS The 11q23 glioma risk locus was associated with increased risk of IDH-mutated gliomas of all histologies and grades (odds ratio [OR] = 1.50; 95% confidence interval [CI] = 1.29-1.74; P = 1.3X10(-7)) but not with IDH-wild-type gliomas of any histology or grade (OR = 0.91; 95% CI = 0.81-1.03; P = 0.14). The associations were independent of the rs55705857 G allele. CONCLUSION A variant at the 11q23 locus increases risk for IDH-mutated but not IDH-wild-type gliomas, regardless of grade or histology.
Clinical Cancer Research | 2013
Celine M. Vachon; Vera J. Suman; Kathleen R. Brandt; Matthew L. Kosel; Aman U. Buzdar; Janet E. Olson; Fang Fang Wu; Lynn M. Flickinger; Giske Ursin; Catherine Elliott; Lois E. Shepherd; Richard M. Weinshilboum; Paul E. Goss; James N. Ingle
Purpose: Mammographic breast density (MBD) is decreased by tamoxifen, but the effect of aromatase inhibitors is less clear. Experimental Design: We enrolled early-stage postmenopausal patients with breast cancer initiating adjuvant aromatase inhibitor therapy and ascertained mammograms before and at an average 10 months of aromatase inhibitor therapy. We matched cases to healthy postmenopausal women (controls) from a large mammography screening cohort on age, baseline body mass index, baseline MBD, and interval between mammograms. We estimated change in MBD using a computer-assisted thresholding program (Cumulus) and compared differences between cases and matched controls. Results: In predominantly White women (96%), we found 14% of the 387 eligible cases had a MBD reduction of at least 5% after an average of 10 months of aromatase inhibitor therapy. MBD reductions were associated with higher baseline MBD, aromatase inhibitor use for more than 12 months, and prior postmenopausal hormone use. Comparing each case with her matched control, there was no evidence of an association of change in MBD with aromatase inhibitor therapy [median case–control difference among 369 pairs was −0.1% (10th and 90th percentile: −5.9%, 5.2%) P = 0.51]. Case–control differences were similar by type of aromatase inhibitor (Ps 0.41 and 0.56); prior use of postmenopausal hormones (P = 0.85); baseline MBD (P = 0.55); and length of aromatase inhibitor therapy (P = 0.08). Conclusions: In postmenopausal women treated with aromatase inhibitors, 14% of cases had a MBD reduction of more than 5%, but these decreases did not differ from matched controls. These data suggest that MBD is not a clinically useful biomarker for predicting the value of aromatase inhibitor therapy in White postmenopausal women. Clin Cancer Res; 19(8); 2144–53. ©2013 AACR.