TY  - JOUR
A1  - Ferreira, Manuel A.
A1  - Gamazon, Eric R.
A1  - Al-Ejeh, Fares
A1  - Aittomäki, Kristiina
A1  - Andrulis, Irene L.
A1  - Anton-Culver, Hoda
A1  - Arason, Adalgeir
A1  - Arndt, Volker
A1  - Aronson, Kristan J.
A1  - Arun, Banu K.
A1  - Asseryanis, Ella
A1  - Azzollini, Jacopo
A1  - Balmaña, Judith
A1  - Barnes, Daniel R.
A1  - Barrowdale, Daniel
A1  - Beckmann, Matthias W.
A1  - Behrens, Sabine
A1  - Benitez, Javier
A1  - Bermisheva, Marina
A1  - Bialkowska, Katarzyna
A1  - Blomqvist, Carl
A1  - Bogdanova, Natalia V.
A1  - Bojesen, Stig E.
A1  - Bolla, Manjeet K.
A1  - Borg, Ake
A1  - Brauch, Hiltrud
A1  - Brenner, Hermann
A1  - Broeks, Annegien
A1  - Burwinkel, Barbara
A1  - Caldés, Trinidad
A1  - Caligo, Maria A.
A1  - Campa, Daniele
A1  - Campbell, Ian
A1  - Canzian, Federico
A1  - Carter, Jonathan
A1  - Carter, Brian D.
A1  - Castelao, Jose E.
A1  - Chang-Claude, Jenny
A1  - Chanock, Stephen J.
A1  - Christiansen, Hans
A1  - Chung, Wendy K.
A1  - Claes, Kathleen B. M.
A1  - Clarke, Christine L.
A1  - Couch, Fergus J.
A1  - Cox, Angela
A1  - Cross, Simon S.
A1  - Czene, Kamila
A1  - Daly, Mary B.
A1  - de la Hoya, Miguel
A1  - Dennis, Joe
A1  - Devilee, Peter
A1  - Diez, Orland
A1  - Dörk, Thilo
A1  - Dunning, Alison M.
A1  - Dwek, Miriam
A1  - Eccles, Diana M.
A1  - Ejlertsen, Bent
A1  - Ellberg, Carolina
A1  - Engel, Christoph
A1  - Eriksson, Mikael
A1  - Fasching, Peter A.
A1  - Fletcher, Olivia
A1  - Flyger, Henrik
A1  - Friedman, Eitan
A1  - Frost, Debra
A1  - Gabrielson, Marike
A1  - Gago-Dominguez, Manuela
A1  - Ganz, Patricia A.
A1  - Gapstur, Susan M.
A1  - Garber, Judy
A1  - García-Closas, Montserrat
A1  - García-Sáenz, José A.
A1  - Gaudet, Mia M.
A1  - Giles, Graham G.
A1  - Glendon, Gord
A1  - Godwin, Andrew K.
A1  - Goldberg, Mark S.
A1  - Goldgar, David E.
A1  - González-Neira, Anna
A1  - Greene, Mark H.
A1  - Gronwald, Jacek
A1  - Guenél, Pascal
A1  - Haimann, Christopher A.
A1  - Hall, Per
A1  - Hamann, Ute
A1  - He, Wei
A1  - Heyworth, Jane
A1  - Hogervorst, Frans B. L.
A1  - Hollestelle, Antoinette
A1  - Hoover, Robert N.
A1  - Hopper, John L.
A1  - Hulick, Peter J.
A1  - Humphreys, Keith
A1  - Imyanitov, Evgeny N.
A1  - Isaacs, Claudine
A1  - Jakimovska, Milena
A1  - Jakubowska, Anna
A1  - James, Paul A.
A1  - Janavicius, Ramunas
A1  - Jankowitz, Rachel C.
A1  - John, Esther M.
A1  - Johnson, Nichola
A1  - Joseph, Vijai
A1  - Karlan, Beth Y.
A1  - Khusnutdinova, Elza
A1  - Kiiski, Johanna I.
A1  - Ko, Yon-Dschun
A1  - Jones, Michael E.
A1  - Konstantopoulou, Irene
A1  - Kristensen, Vessela N.
A1  - Laitman, Yael
A1  - Lambrechts, Diether
A1  - Lazaro, Conxi
A1  - Leslie, Goska
A1  - Lester, Jenny
A1  - Lesueur, Fabienne
A1  - Lindström, Sara
A1  - Long, Jirong
A1  - Loud, Jennifer T.
A1  - Lubiński, Jan
A1  - Makalic, Enes
A1  - Mannermaa, Arto
A1  - Manoochehri, Mehdi
A1  - Margolin, Sara
A1  - Maurer, Tabea
A1  - Mavroudis, Dimitrios
A1  - McGuffog, Lesley
A1  - Meindl, Alfons
A1  - Menon, Usha
A1  - Michailidou, Kyriaki
A1  - Miller, Austin
A1  - Montagna, Marco
A1  - Moreno, Fernando
A1  - Moserle, Lidia
A1  - Mulligan, Anna Marie
A1  - Nathanson, Katherine L.
A1  - Neuhausen, Susan L.
A1  - Nevanlinna, Heli
A1  - Nevelsteen, Ines
A1  - Nielsen, Finn C.
A1  - Nikitina-Zake, Liene
A1  - Nussbaum, Robert L.
A1  - Offit, Kenneth
A1  - Olah, Edith
A1  - Olopade, Olufunmilayo I.
A1  - Olsson, Håkan
A1  - Osorio, Ana
A1  - Papp, Janos
A1  - Park-Simon, Tjoung-Won
A1  - Parsons, Michael T.
A1  - Pedersen, Inge Sokilde
A1  - Peixoto, Ana
A1  - Peterlongo, Paolo
A1  - Pharaoh, Paul D. P.
A1  - Plaseska-Karanfilska, Dijana
A1  - Poppe, Bruce
A1  - Presneau, Nadege
A1  - Radice, Paolo
A1  - Rantala, Johanna
A1  - Rennert, Gad
A1  - Risch, Harvey A.
A1  - Saloustros, Emmanouil
A1  - Sanden, Kristin
A1  - Sawyer, Elinor J.
A1  - Schmidt, Marjanka K.
A1  - Schmutzler, Rita K.
A1  - Sharma, Priyanka
A1  - Shu, Xiao-Ou
A1  - Simard, Jaques
A1  - Singer, Christian F.
A1  - Soucy, Penny
A1  - Southey, Melissa C.
A1  - Spinelli, John J.
A1  - Spurdle, Amanda B.
A1  - Stone, Jennifer
A1  - Swerdlow, Anthony J.
A1  - Tapper, William J.
A1  - Taylor, Jack A.
A1  - Teixeira, Manuel R.
A1  - Terry, Mary Beth
A1  - Teulé, Alex
A1  - Thomassen, Mads
A1  - Thöne, Kathrin
A1  - Thull, Darcy L.
A1  - Tischkowitz, Marc
A1  - Toland, Amanda E.
A1  - Torres, Diana
A1  - Truong, Thérèse
A1  - Tung, Nadine
A1  - Vachon, Celine M.
A1  - van Asperen, Christi J.
A1  - van den Ouweland, Ans M. W.
A1  - van Rensburg, Elizabeth J.
A1  - Vega, Ana
A1  - Viel, Alexandra
A1  - Wang, Qin
A1  - Wappenschmidt, Barbara
A1  - Weitzel, Jeffrey N.
A1  - Wendt, Camilla
A1  - Winqvist, Robert
A1  - Yang, Xiaohong R.
A1  - Yannoukakos, Drakoulis
A1  - Ziogas, Argyrios
A1  - Kraft, Peter
A1  - Antoniou, Antonis C.
A1  - Zheng, Wei
A1  - Easton, Douglas F.
A1  - Milne, Roger L.
A1  - Beesley, Jonathan
A1  - Chenevix-Trench, Georgia
T1  - Genome-wide association and transcriptome studies identify target genes and risk loci for breast cancer
JF  - Nature Communications
N2  - Genome-wide association studies (GWAS) have identified more than 170 breast cancer susceptibility loci. Here we hypothesize that some risk-associated variants might act in non-breast tissues, specifically adipose tissue and immune cells from blood and spleen. Using expression quantitative trait loci (eQTL) reported in these tissues, we identify 26 previously unreported, likely target genes of overall breast cancer risk variants, and 17 for estrogen receptor (ER)-negative breast cancer, several with a known immune function. We determine the directional effect of gene expression on disease risk measured based on single and multiple eQTL. In addition, using a gene-based test of association that considers eQTL from multiple tissues, we identify seven (and four) regions with variants associated with overall (and ER-negative) breast cancer risk, which were not reported in previous GWAS. Further investigation of the function of the implicated genes in breast and immune cells may provide insights into the etiology of breast cancer.
KW  - cancer
KW  - genetics
Y1  - 2019
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-228024
VL  - 10
ER  - 
TY  - JOUR
A1  - Arlt, Wiebke
A1  - Biehl, Michael
A1  - Taylor, Angela E.
A1  - Hahner, Stefanie
A1  - Libé, Rossella
A1  - Hughes, Beverly A.
A1  - Schneider, Petra
A1  - Smith, David J.
A1  - Stiekema, Han
A1  - Krone, Nils
A1  - Porfiri, Emilio
A1  - Opocher, Giuseppe
A1  - Bertherat, Jerôme
A1  - Mantero, Franco
A1  - Allolio, Bruno
A1  - Terzolo, Massimo
A1  - Nightingale, Peter
A1  - Shackleton, Cedric H. L.
A1  - Bertagna, Xavier
A1  - Fassnacht, Martin
A1  - Stewart, Paul M.
T1  - Urine Steroid Metabolomics as a Biomarker Tool for Detecting Malignancy in Adrenal Tumors
JF  - The Journal of Clinical Endocrinology & Metabolism
N2  - Context:
Adrenal tumors have a prevalence of around 2% in the general population. Adrenocortical carcinoma (ACC) is rare but accounts for 2–11% of incidentally discovered adrenal masses. Differentiating ACC from adrenocortical adenoma (ACA) represents a diagnostic challenge in patients with adrenal incidentalomas, with tumor size, imaging, and even histology all providing unsatisfactory predictive values.

Objective:
Here we developed a novel steroid metabolomic approach, mass spectrometry-based steroid profiling followed by machine learning analysis, and examined its diagnostic value for the detection of adrenal malignancy.

Design:
Quantification of 32 distinct adrenal derived steroids was carried out by gas chromatography/mass spectrometry in 24-h urine samples from 102 ACA patients (age range 19–84 yr) and 45 ACC patients (20–80 yr). Underlying diagnosis was ascertained by histology and metastasis in ACC and by clinical follow-up [median duration 52 (range 26–201) months] without evidence of metastasis in ACA. Steroid excretion data were subjected to generalized matrix learning vector quantization (GMLVQ) to identify the most discriminative steroids.

Results:
Steroid profiling revealed a pattern of predominantly immature, early-stage steroidogenesis in ACC. GMLVQ analysis identified a subset of nine steroids that performed best in differentiating ACA from ACC. Receiver-operating characteristics analysis of GMLVQ results demonstrated sensitivity = specificity = 90% (area under the curve = 0.97) employing all 32 steroids and sensitivity = specificity = 88% (area under the curve = 0.96) when using only the nine most differentiating markers.

Conclusions:
Urine steroid metabolomics is a novel, highly sensitive, and specific biomarker tool for discriminating benign from malignant adrenal tumors, with obvious promise for the diagnostic work-up of patients with adrenal incidentalomas.
KW  - adrenal cortex hormones
KW  - urine
KW  - adrenal cortex neoplasms
KW  - mass spectrometry
KW  - metabolomics
Y1  - 2011
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-154682
VL  - 96
IS  - 12
SP  - 3775
EP  - 3784
ER  -