FANCM missense variants and breast cancer risk

Autor: Figlioli, G., Billaud, A., Ahearn, T.U., Antonenkova, N.N., Becher, H., Beckmann, M.W., Behrens, S., Benitez, J., Bermisheva, M., Blok, M.J., Bogdanova, N.V., Bonanni, B., Burwinkel, B., Camp, N.J., Campbell, A., Castelao, J.E., Cessna, M.H., Chanock, S.J., Czene, K., Devilee, P., Dork, T., Engel, C., Eriksson, M., Fasching, P.A., Figueroa, J.D., Gabrielson, M., Gago-Dominguez, M., Garcia-Closas, M., Gonzalez-Neira, A., Grassmann, F., Guenel, P., Gundert, M., Hadjisavvas, A., Hahnen, E., Hall, P., Hamann, U., Harrington, P.A., He, W., Hillemanns, P., Hollestelle, A., Hooning, M.J., Hoppe, R., Howell, A., Humphreys, K., Jager, A., Jakubowska, A., Khusnutdinova, E.K., Ko, Y.D., Kristensen, V.N., Lindblom, A., Peterlongo, Paolo

Publikováno v: European Journal of Human Genetics, 31, 578-587. Nature Publishing Group
European Journal of Human Genetics, 31(5), 578-587. Nature Publishing Group
NBCS Collaborators 2023, ' FANCM missense variants and breast cancer risk: a case-control association study of 75,156 European women ', European journal of human genetics : EJHG, pp. 1-10 . https://doi.org/10.1038/s41431-022-01257-w

Evidence from literature, including the BRIDGES study, indicates that germline protein truncating variants (PTVs) in FANCM confer moderately increased risk of ER-negative and triple-negative breast cancer (TNBC), especially for women with a family hi

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http://www.scopus.com/inward/record.url?scp=85159201147&partnerID=8YFLogxK

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PredictCBC-2.0: a contralateral breast cancer risk prediction model developed and validated in ~ 200,000 patients

Autor: Giardiello, D., Hooning, M.J., Hauptmann, M., Keeman, R., Heemskerk-Gerritsen, B.A.M., Becher, H., Blomqvist, C., Bojesen, S.E., Bolla, M.K., Camp, N.J., Czene, K., Devilee, P., Eccles, D.M., Fasching, P.A., Figueroa, J.D., Flyger, H., Garcia-Closas, M., Haiman, C.A., Hamann, U., Hopper, J.L., Jakubowska, A., Leeuwen, F.E., Lindblom, A., Lubinski, J., Margolin, S., Martinez, M.E., Nevanlinna, H., Nevelsteen, I., Pelders, S., Pharoah, P.D.P., Siesling, S., Southey, M.C., Hout, A.H. van der, Hest, L.P. van, Chang-Claude, J., Hall, P., Easton, D.F., Steyerberg, E.W., Schmidt, M.K.

Publikováno v: Breast Cancer Research, 24(1). BMC
Giardiello, D, Hooning, M J, Hauptmann, M, Keeman, R, Heemskerk-Gerritsen, B A M, Becher, H, Blomqvist, C, Bojesen, S E, Bolla, M K, Camp, N J, Czene, K, Devilee, P, Eccles, D M, Fasching, P A, Figueroa, J D, Flyger, H, García-Closas, M, Haiman, C A, Hamann, U, Hopper, J L, Jakubowska, A, Leeuwen, F E, Lindblom, A, Lubiński, J, Margolin, S, Martinez, M E, Nevanlinna, H, Nevelsteen, I, Pelders, S, Pharoah, P D P, Siesling, S, Southey, M C, van der Hout, A H, van Hest, L P, Chang-Claude, J, Hall, P, Easton, D F, Steyerberg, E W & Schmidt, M K 2022, ' PredictCBC-2.0 : a contralateral breast cancer risk prediction model developed and validated in ~ 200,000 patients ', Breast Cancer Research, vol. 24, no. 1, 69 . https://doi.org/10.1186/s13058-022-01567-3
Breast Cancer Research, 24(1):69. BioMed Central Ltd.
Giardiello, D, Hooning, M J, Hauptmann, M, Keeman, R, Heemskerk-Gerritsen, B A M, Becher, H, Blomqvist, C, Bojesen, S E, Bolla, M K, Camp, N J, Czene, K, Devilee, P, Eccles, D M, Fasching, P A, Figueroa, J D, Flyger, H, García-Closas, M, Haiman, C A, Hamann, U, Hopper, J L, Jakubowska, A, Leeuwen, F E, Lindblom, A, Lubiński, J, Margolin, S, Martinez, M E, Nevanlinna, H, Nevelsteen, I, Pelders, S, Pharoah, P D P, Siesling, S, Southey, M C, van der Hout, A H, van Hest, L P, Chang-Claude, J, Hall, P, Easton, D F, Steyerberg, E W & Schmidt, M K 2022, ' PredictCBC-2.0 : a contralateral breast cancer risk prediction model developed and validated in ~ 200,000 patients ', Breast Cancer Research, vol. 24, no. 1, 69, pp. 69 . https://doi.org/10.1186/s13058-022-01567-3
Breast Cancer Research, 24(1):69. BioMed Central
Breast cancer research : BCR, vol 24, iss 1
Breast cancer research, 24:69. BioMed Central Ltd.

Background Prediction of contralateral breast cancer (CBC) risk is challenging due to moderate performances of the known risk factors. We aimed to improve our previous risk prediction model (PredictCBC) by updated follow-up and including additional r

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