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2. Large scale multifactorial likelihood quantitative analysis of BRCA1 and BRCA2 variants: An ENIGMA resource to support clinical variant classification.

Author

Feroce I., Schoenwiese U., Seggewiss J., Solanes A., Steinemann D., Stiller M., Stoppa-Lyonnet D., Sullivan K.J., Susman R., Sutter C., Tavtigian S.V., Teo S.H., Teule A., Thomassen M., Tibiletti M.G., Tischkowitz M., Tognazzo S., Toland A.E., Tornero E., Torngren T., Torres-Esquius S., Toss A., Trainer A.H., Tucker K.M., van Asperen C.J., van Mackelenbergh M.T., Varesco L., Vargas-Parra G., Varon R., Vega A., Velasco A., Vesper A.-S., Viel A., Vreeswijk M.P.G., Wagner S.A., Waha A., Walker L.C., Walters R.J., Wang-Gohrke S., Weber B.H.F., Weichert W., Wieland K., Wiesmuller L., Witzel I., Wockel A., Woodward E.R., Zachariae S., Zampiga V., Zeder-Goss C., Investigators K., Lazaro C., De Nicolo A., Radice P., Engel C., Schmutzler R.K., Goldgar D.E., Spurdle A.B., Harris M., Parsons M.T., Tudini E., Li H., Hahnen E., Wappenschmidt B., Feliubadalo L., Aalfs C.M., Agata S., Aittomaki K., Alducci E., Alonso-Cerezo M.C., Arnold N., Auber B., Austin R., Azzollini J., Balmana J., Barbieri E., Bartram C.R., Blanco A., Blumcke B., Bonache S., Bonanni B., Borg A., Bortesi B., Brunet J., Bruzzone C., Bucksch K., Cagnoli G., Caldes T., Caliebe A., Caligo M.A., Calvello M., Capone G.L., Caputo S.M., Carnevali I., Carrasco E., Caux-Moncoutier V., Cavalli P., Cini G., Clarke E.M., Concolino P., Cops E.J., Cortesi L., Couch F.J., Darder E., de la Hoya M., Dean M., Debatin I., Del Valle J., Delnatte C., Derive N., Diez O., Ditsch N., Domchek S.M., Dutrannoy V., Eccles D.M., Ehrencrona H., Enders U., Evans D.G., Farra C., Faust U., Felbor U., Fine M., Foulkes W.D., Galvao H.C.R., Gambino G., Gehrig A., Gensini F., Gerdes A.-M., Germani A., Giesecke J., Gismondi V., Gomez C., Gomez Garcia E.B., Gonzalez S., Grau E., Grill S., Gross E., Guerrieri-Gonzaga A., Guillaud-Bataille M., Gutierrez-Enriquez S., Haaf T., Hackmann K., Hansen T.V.O., Hauke J., Heinrich T., Hellebrand H., Herold K.N., Honisch E., Horvath J., Houdayer C., Hubbel V., Iglesias S., Izquierdo A., James P.A., Janssen L.A.M., Jeschke U., Kaulfuss S., Keupp K., Kiechle M., Kolbl A., Krieger S., Kruse T.A., Kvist A., Lalloo F., Larsen M., Lattimore V.L., Lautrup C., Ledig S., Leinert E., Lewis A.L., Lim J., Loeffler M., Lopez-Fernandez A., Lucci-Cordisco E., Maass N., Manoukian S., Marabelli M., Matricardi L., Meindl A., Michelli R.D., Moghadasi S., Moles-Fernandez A., Montagna M., Montalban G., Monteiro A.N., Montes E., Mori L., Moserle L., Muller C.R., Mundhenke C., Naldi N., Nathanson K.L., Navarro M., Nevanlinna H., Nichols C.B., Niederacher D., Nielsen H.R., Ong K.-R., Pachter N., Palmero E.I., Papi L., Pedersen I.S., Peissel B., Perez-Segura P., Pfeifer K., Pineda M., Pohl-Rescigno E., Poplawski N.K., Porfirio B., Quante A.S., Ramser J., Reis R.M., Revillion F., Rhiem K., Riboli B., Ritter J., Rivera D., Rofes P., Rump A., Salinas M., Sanchez de Abajo A.M., Schmidt G., Feroce I., Schoenwiese U., Seggewiss J., Solanes A., Steinemann D., Stiller M., Stoppa-Lyonnet D., Sullivan K.J., Susman R., Sutter C., Tavtigian S.V., Teo S.H., Teule A., Thomassen M., Tibiletti M.G., Tischkowitz M., Tognazzo S., Toland A.E., Tornero E., Torngren T., Torres-Esquius S., Toss A., Trainer A.H., Tucker K.M., van Asperen C.J., van Mackelenbergh M.T., Varesco L., Vargas-Parra G., Varon R., Vega A., Velasco A., Vesper A.-S., Viel A., Vreeswijk M.P.G., Wagner S.A., Waha A., Walker L.C., Walters R.J., Wang-Gohrke S., Weber B.H.F., Weichert W., Wieland K., Wiesmuller L., Witzel I., Wockel A., Woodward E.R., Zachariae S., Zampiga V., Zeder-Goss C., Investigators K., Lazaro C., De Nicolo A., Radice P., Engel C., Schmutzler R.K., Goldgar D.E., Spurdle A.B., Harris M., Parsons M.T., Tudini E., Li H., Hahnen E., Wappenschmidt B., Feliubadalo L., Aalfs C.M., Agata S., Aittomaki K., Alducci E., Alonso-Cerezo M.C., Arnold N., Auber B., Austin R., Azzollini J., Balmana J., Barbieri E., Bartram C.R., Blanco A., Blumcke B., Bonache S., Bonanni B., Borg A., Bortesi B., Brunet J., Bruzzone C., Bucksch K., Cagnoli G., Caldes T., Caliebe A., Caligo M.A., Calvello M., Capone G.L., Caputo S.M., Carnevali I., Carrasco E., Caux-Moncoutier V., Cavalli P., Cini G., Clarke E.M., Concolino P., Cops E.J., Cortesi L., Couch F.J., Darder E., de la Hoya M., Dean M., Debatin I., Del Valle J., Delnatte C., Derive N., Diez O., Ditsch N., Domchek S.M., Dutrannoy V., Eccles D.M., Ehrencrona H., Enders U., Evans D.G., Farra C., Faust U., Felbor U., Fine M., Foulkes W.D., Galvao H.C.R., Gambino G., Gehrig A., Gensini F., Gerdes A.-M., Germani A., Giesecke J., Gismondi V., Gomez C., Gomez Garcia E.B., Gonzalez S., Grau E., Grill S., Gross E., Guerrieri-Gonzaga A., Guillaud-Bataille M., Gutierrez-Enriquez S., Haaf T., Hackmann K., Hansen T.V.O., Hauke J., Heinrich T., Hellebrand H., Herold K.N., Honisch E., Horvath J., Houdayer C., Hubbel V., Iglesias S., Izquierdo A., James P.A., Janssen L.A.M., Jeschke U., Kaulfuss S., Keupp K., Kiechle M., Kolbl A., Krieger S., Kruse T.A., Kvist A., Lalloo F., Larsen M., Lattimore V.L., Lautrup C., Ledig S., Leinert E., Lewis A.L., Lim J., Loeffler M., Lopez-Fernandez A., Lucci-Cordisco E., Maass N., Manoukian S., Marabelli M., Matricardi L., Meindl A., Michelli R.D., Moghadasi S., Moles-Fernandez A., Montagna M., Montalban G., Monteiro A.N., Montes E., Mori L., Moserle L., Muller C.R., Mundhenke C., Naldi N., Nathanson K.L., Navarro M., Nevanlinna H., Nichols C.B., Niederacher D., Nielsen H.R., Ong K.-R., Pachter N., Palmero E.I., Papi L., Pedersen I.S., Peissel B., Perez-Segura P., Pfeifer K., Pineda M., Pohl-Rescigno E., Poplawski N.K., Porfirio B., Quante A.S., Ramser J., Reis R.M., Revillion F., Rhiem K., Riboli B., Ritter J., Rivera D., Rofes P., Rump A., Salinas M., Sanchez de Abajo A.M., and Schmidt G.

Abstract

The multifactorial likelihood analysis method has demonstrated utility for quantitative assessment of variant pathogenicity for multiple cancer syndrome genes. Independent data types currently incorporated in the model for assessing BRCA1 and BRCA2 variants include clinically calibrated prior probability of pathogenicity based on variant location and bioinformatic prediction of variant effect, co-segregation, family cancer history profile, co-occurrence with a pathogenic variant in the same gene, breast tumor pathology, and case-control information. Research and clinical data for multifactorial likelihood analysis were collated for 1,395 BRCA1/2 predominantly intronic and missense variants, enabling classification based on posterior probability of pathogenicity for 734 variants: 447 variants were classified as (likely) benign, and 94 as (likely) pathogenic; and 248 classifications were new or considerably altered relative to ClinVar submissions. Classifications were compared with information not yet included in the likelihood model, and evidence strengths aligned to those recommended for ACMG/AMP classification codes. Altered mRNA splicing or function relative to known nonpathogenic variant controls were moderately to strongly predictive of variant pathogenicity. Variant absence in population datasets provided supporting evidence for variant pathogenicity. These findings have direct relevance for BRCA1 and BRCA2 variant evaluation, and justify the need for gene-specific calibration of evidence types used for variant classification.Copyright © 2019 Wiley Periodicals, Inc.

Published
2019

3. Large scale multifactorial likelihood quantitative analysis of BRCA1 and BRCA2 variants: An ENIGMA resource to support clinical variant classification

Author

Parsons, MT, Tudini, E, Li, H, Hahnen, E, Wappenschmidt, B, Feliubadalo, L, Aalfs, CM, Agata, S, Aittomaki, K, Alducci, E, Concepcion Alonso-Cerezo, M, Arnold, N, Auber, B, Austin, R, Azzollini, J, Balmana, J, Barbieri, E, Bartram, CR, Blanco, A, Bluemcke, B, Bonache, S, Bonanni, B, Borg, A, Bortesi, B, Brunet, J, Bruzzone, C, Bucksch, K, Cagnoli, G, Caldes, T, Caliebe, A, Caligo, MA, Calvello, M, Capone, GL, Caputo, SM, Carnevali, I, Carrasco, E, Caux-Moncoutier, V, Cavalli, P, Cini, G, Clarke, EM, Concolino, P, Cops, EJ, Cortesi, L, Couch, FJ, Darder, E, de la Hoya, M, Dean, M, Debatin, I, Del Valle, J, Delnatte, C, Derive, N, Diez, O, Ditsch, N, Domchek, SM, Dutrannoy, V, Eccles, DM, Ehrencrona, H, Enders, U, Evans, DG, Farra, C, Faust, U, Felbor, U, Feroce, I, Fine, M, Foulkes, WD, Galvao, HC, Gambino, G, Gehrig, A, Gensini, F, Gerdes, A-M, Germani, A, Giesecke, J, Gismondi, V, Gomez, C, Garcia, EBG, Gonzalez, S, Grau, E, Grill, S, Gross, E, Guerrieri-Gonzaga, A, Guillaud-Bataille, M, Gutierrez-Enriquez, S, Haaf, T, Hackmann, K, Hansen, TV, Harris, M, Hauke, J, Heinrich, T, Hellebrand, H, Herold, KN, Honisch, E, Horvath, J, Houdayer, C, Huebbel, V, Iglesias, S, Izquierdo, A, James, PA, Janssen, LA, Jeschke, U, Kaulfuss, S, Keupp, K, Kiechle, M, Koelbl, A, Krieger, S, Kruse, TA, Kvist, A, Lalloo, F, Larsen, M, Lattimore, VL, Lautrup, C, Ledig, S, Leinert, E, Lewis, AL, Lim, J, Loeffler, M, Lopez-Fernandez, A, Lucci-Cordisco, E, Maass, N, Manoukian, S, Marabelli, M, Matricardi, L, Meindl, A, Michelli, RD, Moghadasi, S, Moles-Fernandez, A, Montagna, M, Montalban, G, Monteiro, AN, Montes, E, Mori, L, Moserle, L, Mueller, CR, Mundhenke, C, Naldi, N, Nathanson, KL, Navarro, M, Nevanlinna, H, Nichols, CB, Niederacher, D, Nielsen, HR, Ong, K-R, Pachter, N, Palmero, E, Papi, L, Pedersen, IS, Peissel, B, Perez-Segura, P, Pfeifer, K, Pineda, M, Pohl-Rescigno, E, Poplawski, NK, Porfirio, B, Quante, AS, Ramser, J, Reis, RM, Revillion, F, Rhiem, K, Riboli, B, Ritter, J, Rivera, D, Rofes, P, Rump, A, Salinas, M, Sanchez de Abajo, AM, Schmidt, G, Schoenwiese, U, Seggewiss, J, Solanes, A, Steinemann, D, Stiller, M, Stoppa-Lyonnet, D, Sullivan, KJ, Susman, R, Sutter, C, Tavtigian, S, Teo, SH, Teule, A, Thomassen, M, Tibiletti, MG, Tischkowitz, M, Tognazzo, S, Toland, AE, Tornero, E, Torngren, T, Torres-Esquius, S, Toss, A, Trainer, AH, Tucker, KM, van Asperen, CJ, van Mackelenbergh, MT, Varesco, L, Vargas-Parra, G, Varon, R, Vega, A, Velasco, A, Vesper, A-S, Viel, A, Vreeswijk, MPG, Wagner, SA, Waha, A, Walker, LC, Walters, RJ, Wang-Gohrke, S, Weber, BHF, Weichert, W, Wieland, K, Wiesmueller, L, Witzel, I, Woeckel, A, Woodward, ER, Zachariae, S, Zampiga, V, Zeder-Goss, C, Lazaro, C, De Nicolo, A, Radice, P, Engel, C, Schmutzler, RK, Goldgar, DE, Spurdle, AB, Parsons, MT, Tudini, E, Li, H, Hahnen, E, Wappenschmidt, B, Feliubadalo, L, Aalfs, CM, Agata, S, Aittomaki, K, Alducci, E, Concepcion Alonso-Cerezo, M, Arnold, N, Auber, B, Austin, R, Azzollini, J, Balmana, J, Barbieri, E, Bartram, CR, Blanco, A, Bluemcke, B, Bonache, S, Bonanni, B, Borg, A, Bortesi, B, Brunet, J, Bruzzone, C, Bucksch, K, Cagnoli, G, Caldes, T, Caliebe, A, Caligo, MA, Calvello, M, Capone, GL, Caputo, SM, Carnevali, I, Carrasco, E, Caux-Moncoutier, V, Cavalli, P, Cini, G, Clarke, EM, Concolino, P, Cops, EJ, Cortesi, L, Couch, FJ, Darder, E, de la Hoya, M, Dean, M, Debatin, I, Del Valle, J, Delnatte, C, Derive, N, Diez, O, Ditsch, N, Domchek, SM, Dutrannoy, V, Eccles, DM, Ehrencrona, H, Enders, U, Evans, DG, Farra, C, Faust, U, Felbor, U, Feroce, I, Fine, M, Foulkes, WD, Galvao, HC, Gambino, G, Gehrig, A, Gensini, F, Gerdes, A-M, Germani, A, Giesecke, J, Gismondi, V, Gomez, C, Garcia, EBG, Gonzalez, S, Grau, E, Grill, S, Gross, E, Guerrieri-Gonzaga, A, Guillaud-Bataille, M, Gutierrez-Enriquez, S, Haaf, T, Hackmann, K, Hansen, TV, Harris, M, Hauke, J, Heinrich, T, Hellebrand, H, Herold, KN, Honisch, E, Horvath, J, Houdayer, C, Huebbel, V, Iglesias, S, Izquierdo, A, James, PA, Janssen, LA, Jeschke, U, Kaulfuss, S, Keupp, K, Kiechle, M, Koelbl, A, Krieger, S, Kruse, TA, Kvist, A, Lalloo, F, Larsen, M, Lattimore, VL, Lautrup, C, Ledig, S, Leinert, E, Lewis, AL, Lim, J, Loeffler, M, Lopez-Fernandez, A, Lucci-Cordisco, E, Maass, N, Manoukian, S, Marabelli, M, Matricardi, L, Meindl, A, Michelli, RD, Moghadasi, S, Moles-Fernandez, A, Montagna, M, Montalban, G, Monteiro, AN, Montes, E, Mori, L, Moserle, L, Mueller, CR, Mundhenke, C, Naldi, N, Nathanson, KL, Navarro, M, Nevanlinna, H, Nichols, CB, Niederacher, D, Nielsen, HR, Ong, K-R, Pachter, N, Palmero, E, Papi, L, Pedersen, IS, Peissel, B, Perez-Segura, P, Pfeifer, K, Pineda, M, Pohl-Rescigno, E, Poplawski, NK, Porfirio, B, Quante, AS, Ramser, J, Reis, RM, Revillion, F, Rhiem, K, Riboli, B, Ritter, J, Rivera, D, Rofes, P, Rump, A, Salinas, M, Sanchez de Abajo, AM, Schmidt, G, Schoenwiese, U, Seggewiss, J, Solanes, A, Steinemann, D, Stiller, M, Stoppa-Lyonnet, D, Sullivan, KJ, Susman, R, Sutter, C, Tavtigian, S, Teo, SH, Teule, A, Thomassen, M, Tibiletti, MG, Tischkowitz, M, Tognazzo, S, Toland, AE, Tornero, E, Torngren, T, Torres-Esquius, S, Toss, A, Trainer, AH, Tucker, KM, van Asperen, CJ, van Mackelenbergh, MT, Varesco, L, Vargas-Parra, G, Varon, R, Vega, A, Velasco, A, Vesper, A-S, Viel, A, Vreeswijk, MPG, Wagner, SA, Waha, A, Walker, LC, Walters, RJ, Wang-Gohrke, S, Weber, BHF, Weichert, W, Wieland, K, Wiesmueller, L, Witzel, I, Woeckel, A, Woodward, ER, Zachariae, S, Zampiga, V, Zeder-Goss, C, Lazaro, C, De Nicolo, A, Radice, P, Engel, C, Schmutzler, RK, Goldgar, DE, and Spurdle, AB

Abstract

The multifactorial likelihood analysis method has demonstrated utility for quantitative assessment of variant pathogenicity for multiple cancer syndrome genes. Independent data types currently incorporated in the model for assessing BRCA1 and BRCA2 variants include clinically calibrated prior probability of pathogenicity based on variant location and bioinformatic prediction of variant effect, co-segregation, family cancer history profile, co-occurrence with a pathogenic variant in the same gene, breast tumor pathology, and case-control information. Research and clinical data for multifactorial likelihood analysis were collated for 1,395 BRCA1/2 predominantly intronic and missense variants, enabling classification based on posterior probability of pathogenicity for 734 variants: 447 variants were classified as (likely) benign, and 94 as (likely) pathogenic; and 248 classifications were new or considerably altered relative to ClinVar submissions. Classifications were compared with information not yet included in the likelihood model, and evidence strengths aligned to those recommended for ACMG/AMP classification codes. Altered mRNA splicing or function relative to known nonpathogenic variant controls were moderately to strongly predictive of variant pathogenicity. Variant absence in population datasets provided supporting evidence for variant pathogenicity. These findings have direct relevance for BRCA1 and BRCA2 variant evaluation, and justify the need for gene-specific calibration of evidence types used for variant classification.

Published
2019

4. Large scale multifactorial likelihood quantitative analysis of BRCA1 and BRCA2 variants: An ENIGMA resource to support clinical variant classification

Author

Parsons, M. T., Tudini, E., Li, H., Hahnen, E., Wappenschmidt, B., Feliubadalo, L., Aalfs, C. M., Agata, S., Aittomaki, K., Alducci, E., Alonso-Cerezo, M. C., Arnold, N., Auber, B., Austin, R., Azzollini, J., Balmana, J., Barbieri, E., Bartram, C. R., Blanco, A., Blumcke, B., Bonache, S., Bonanni, B., Borg, A., Bortesi, B., Brunet, J., Bruzzone, C., Bucksch, K., Cagnoli, G., Caldes, T., Caliebe, A., Caligo, M. A., Calvello, M., Capone, G. L., Caputo, S. M., Carnevali, I., Carrasco, E., Caux-Moncoutier, V., Cavalli, P., Cini, G., Clarke, E. M., Concolino, Paola, Cops, E. J., Cortesi, L., Couch, F. J., Darder, E., de la Hoya, M., Dean, M., Debatin, I., Del Valle, J., Delnatte, C., Derive, N., Diez, O., Ditsch, N., Domchek, S. M., Dutrannoy, V., Eccles, D. M., Ehrencrona, H., Enders, U., Evans, D. G., Farra, C., Faust, U., Felbor, U., Feroce, I., Fine, M., Foulkes, W. D., Galvao, H. C. R., Gambino, G., Gehrig, A., Gensini, F., Gerdes, A. -M., Germani, A., Giesecke, J., Gismondi, V., Gomez, C., Gomez Garcia, E. B., Gonzalez, S., Grau, E., Grill, S., Gross, E., Guerrieri-Gonzaga, A., Guillaud-Bataille, M., Gutierrez-Enriquez, S., Haaf, T., Hackmann, K., Hansen, T. V. O., Harris, M., Hauke, J., Heinrich, T., Hellebrand, H., Herold, K. N., Honisch, E., Horvath, J., Houdayer, C., Hubbel, V., Iglesias, S., Izquierdo, A., James, P. A., Janssen, L. A. M., Jeschke, U., Kaulfuss, S., Keupp, K., Kiechle, M., Kolbl, A., Krieger, S., Kruse, T. A., Kvist, A., Lalloo, F., Larsen, M., Lattimore, V. L., Lautrup, C., Ledig, S., Leinert, E., Lewis, A. L., Lim, J., Loeffler, M., Lopez-Fernandez, A., Lucci Cordisco, Emanuela, Maass, N., Manoukian, S., Marabelli, M., Matricardi, L., Meindl, A., Michelli, R. D., Moghadasi, S., Moles-Fernandez, A., Montagna, M., Montalban, G., Monteiro, A. N., Montes, E., Mori, L., Moserle, L., Muller, C. R., Mundhenke, C., Naldi, N., Nathanson, K. L., Navarro, M., Nevanlinna, H., Nichols, C. B., Niederacher, D., Nielsen, H. R., Ong, K. -R., Pachter, N., Palmero, E. I., Papi, L., Pedersen, I. S., Peissel, B., Perez-Segura, P., Pfeifer, K., Pineda, M., Pohl-Rescigno, E., Poplawski, N. K., Porfirio, B., Quante, A. S., Ramser, J., Reis, R. M., Revillion, F., Rhiem, K., Riboli, B., Ritter, J., Rivera, D., Rofes, P., Rump, A., Salinas, M., Sanchez de Abajo, A. M., Schmidt, G., Schoenwiese, U., Seggewiss, J., Solanes, A., Steinemann, D., Stiller, M., Stoppa-Lyonnet, D., Sullivan, K. J., Susman, R., Sutter, C., Tavtigian, S. V., Teo, S. H., Teule, A., Thomassen, M., Tibiletti, M. G., Tischkowitz, M., Tognazzo, S., Toland, A. E., Tornero, E., Torngren, T., Torres-Esquius, S., Toss, A., Trainer, A. H., Tucker, K. M., van Asperen, C. J., van Mackelenbergh, M. T., Varesco, L., Vargas-Parra, G., Varon, R., Vega, A., Velasco, A., Vesper, A. -S., Viel, A., Vreeswijk, M. P. G., Wagner, S. A., Waha, A., Walker, L. C., Walters, R. J., Wang-Gohrke, S., Weber, B. H. F., Weichert, W., Wieland, K., Wiesmuller, L., Witzel, I., Wockel, A., Woodward, E. R., Zachariae, S., Zampiga, V., Zeder-Goss, C., Investigators, K., Lazaro, C., De Nicolo, A., Radice, P., Engel, C., Schmutzler, R. K., Goldgar, D. E., Spurdle, A. B., Concolino P., Lucci Cordisco E. (ORCID:0000-0002-6279-7604), Parsons, M. T., Tudini, E., Li, H., Hahnen, E., Wappenschmidt, B., Feliubadalo, L., Aalfs, C. M., Agata, S., Aittomaki, K., Alducci, E., Alonso-Cerezo, M. C., Arnold, N., Auber, B., Austin, R., Azzollini, J., Balmana, J., Barbieri, E., Bartram, C. R., Blanco, A., Blumcke, B., Bonache, S., Bonanni, B., Borg, A., Bortesi, B., Brunet, J., Bruzzone, C., Bucksch, K., Cagnoli, G., Caldes, T., Caliebe, A., Caligo, M. A., Calvello, M., Capone, G. L., Caputo, S. M., Carnevali, I., Carrasco, E., Caux-Moncoutier, V., Cavalli, P., Cini, G., Clarke, E. M., Concolino, Paola, Cops, E. J., Cortesi, L., Couch, F. J., Darder, E., de la Hoya, M., Dean, M., Debatin, I., Del Valle, J., Delnatte, C., Derive, N., Diez, O., Ditsch, N., Domchek, S. M., Dutrannoy, V., Eccles, D. M., Ehrencrona, H., Enders, U., Evans, D. G., Farra, C., Faust, U., Felbor, U., Feroce, I., Fine, M., Foulkes, W. D., Galvao, H. C. R., Gambino, G., Gehrig, A., Gensini, F., Gerdes, A. -M., Germani, A., Giesecke, J., Gismondi, V., Gomez, C., Gomez Garcia, E. B., Gonzalez, S., Grau, E., Grill, S., Gross, E., Guerrieri-Gonzaga, A., Guillaud-Bataille, M., Gutierrez-Enriquez, S., Haaf, T., Hackmann, K., Hansen, T. V. O., Harris, M., Hauke, J., Heinrich, T., Hellebrand, H., Herold, K. N., Honisch, E., Horvath, J., Houdayer, C., Hubbel, V., Iglesias, S., Izquierdo, A., James, P. A., Janssen, L. A. M., Jeschke, U., Kaulfuss, S., Keupp, K., Kiechle, M., Kolbl, A., Krieger, S., Kruse, T. A., Kvist, A., Lalloo, F., Larsen, M., Lattimore, V. L., Lautrup, C., Ledig, S., Leinert, E., Lewis, A. L., Lim, J., Loeffler, M., Lopez-Fernandez, A., Lucci Cordisco, Emanuela, Maass, N., Manoukian, S., Marabelli, M., Matricardi, L., Meindl, A., Michelli, R. D., Moghadasi, S., Moles-Fernandez, A., Montagna, M., Montalban, G., Monteiro, A. N., Montes, E., Mori, L., Moserle, L., Muller, C. R., Mundhenke, C., Naldi, N., Nathanson, K. L., Navarro, M., Nevanlinna, H., Nichols, C. B., Niederacher, D., Nielsen, H. R., Ong, K. -R., Pachter, N., Palmero, E. I., Papi, L., Pedersen, I. S., Peissel, B., Perez-Segura, P., Pfeifer, K., Pineda, M., Pohl-Rescigno, E., Poplawski, N. K., Porfirio, B., Quante, A. S., Ramser, J., Reis, R. M., Revillion, F., Rhiem, K., Riboli, B., Ritter, J., Rivera, D., Rofes, P., Rump, A., Salinas, M., Sanchez de Abajo, A. M., Schmidt, G., Schoenwiese, U., Seggewiss, J., Solanes, A., Steinemann, D., Stiller, M., Stoppa-Lyonnet, D., Sullivan, K. J., Susman, R., Sutter, C., Tavtigian, S. V., Teo, S. H., Teule, A., Thomassen, M., Tibiletti, M. G., Tischkowitz, M., Tognazzo, S., Toland, A. E., Tornero, E., Torngren, T., Torres-Esquius, S., Toss, A., Trainer, A. H., Tucker, K. M., van Asperen, C. J., van Mackelenbergh, M. T., Varesco, L., Vargas-Parra, G., Varon, R., Vega, A., Velasco, A., Vesper, A. -S., Viel, A., Vreeswijk, M. P. G., Wagner, S. A., Waha, A., Walker, L. C., Walters, R. J., Wang-Gohrke, S., Weber, B. H. F., Weichert, W., Wieland, K., Wiesmuller, L., Witzel, I., Wockel, A., Woodward, E. R., Zachariae, S., Zampiga, V., Zeder-Goss, C., Investigators, K., Lazaro, C., De Nicolo, A., Radice, P., Engel, C., Schmutzler, R. K., Goldgar, D. E., Spurdle, A. B., Concolino P., and Lucci Cordisco E. (ORCID:0000-0002-6279-7604)

Abstract

The multifactorial likelihood analysis method has demonstrated utility for quantitative assessment of variant pathogenicity for multiple cancer syndrome genes. Independent data types currently incorporated in the model for assessing BRCA1 and BRCA2 variants include clinically calibrated prior probability of pathogenicity based on variant location and bioinformatic prediction of variant effect, co-segregation, family cancer history profile, co-occurrence with a pathogenic variant in the same gene, breast tumor pathology, and case-control information. Research and clinical data for multifactorial likelihood analysis were collated for 1,395 BRCA1/2 predominantly intronic and missense variants, enabling classification based on posterior probability of pathogenicity for 734 variants: 447 variants were classified as (likely) benign, and 94 as (likely) pathogenic; and 248 classifications were new or considerably altered relative to ClinVar submissions. Classifications were compared with information not yet included in the likelihood model, and evidence strengths aligned to those recommended for ACMG/AMP classification codes. Altered mRNA splicing or function relative to known nonpathogenic variant controls were moderately to strongly predictive of variant pathogenicity. Variant absence in population datasets provided supporting evidence for variant pathogenicity. These findings have direct relevance for BRCA1 and BRCA2 variant evaluation, and justify the need for gene-specific calibration of evidence types used for variant classification.

Published
2019

5. Endogenous sex hormones and endometrial cancer risk in women in the European Prospective Investigation into Cancer and Nutrition (EPIC)

Author

Allen, N.E. Key, T.J. Dossus, L. Rinaldi, S. Cust, A. Lukanova, A. Peeters, P.H. Onland-Moret, N.C. Lahmann, P.H. Berrino, F. Panico, S. Larrahaga, N. Pera, G. Tormo, M.-J. Sánchez, M.-J. Quirós, J.R. Ardanaz, E. Tjønneland, A. Olsen, A. Chang-Claude, J. Linseisen, J. Schulz, M. Boeing, H. Lundin, E. Palli, D. Overvad, K. Clavel-Chapelon, F. Boutron-Ruault, M.-C. Bingham, S. Khaw, K.-T. Bueno-De-Mesquita, H.B. Trichopoulou, A. Trichopoulos, D. Naska, A. Tumino, R. Riboli, B. Kaaks, R.

Abstract

Epidemiological data show that reproductive and hormonal factors are involved in the etiology of endometrial cancer, but there is little data on the association with endogenous sex hormone levels. We analyzed the association between prediagnostic serum concentrations of sex steroids and endometrial cancer risk in the European Prospective Investigation into Cancer and Nutrition using a nested case-control design of 247 incident endometrial cancer cases and 481 controls, matched on center, menopausal status, age, variables relating to blood collection, and, for premenopausal women, phase of menstrual cycle. Using conditional regression analysis, endometrial cancer risk among postmenopausal women was positively associated with increasing levels of total testosterone, free testosterone, estrone, total estradiol, and free estradiol. The odds ratios (ORs) for the highest versus lowest fertile were 2.66 (95% confidence interval (CI) 1.50-4.72; P=0.002 for a continuous linear trend) for estrone, 2.07 (95% CI 1.20-3.60; P = 0.001) for estradiol, and 1.66 (95% CI 0.98-2.82; P = 0.001) for free estradiol. For total and free testosterone, ORs for the highest versus lowest fertile were 1.44 (95% CI 0.88-2.36; P = 0.05) and 2.05 (95% CI 1.23-3.42; P = 0.005) respectively. Androstenedione and dehydroepiandrosterone sulfate were not associated with risk. Sex hormone-binding globulin was significantly inversely associated with risk (OR for the highest versus lowest fertile was 0.57, 95% CI 0.34-0.95; P = 0.004). In premenopausal women, serum sex hormone concentrations were not clearly associated with endometrial cancer risk, but numbers were too small to draw firm conclusions. In conclusion, relatively high blood concentrations of estrogens and free testosterone are associated with an increased endometrial cancer risk in postmenopausal women. © 2008 Society for Endocrinology.

Published
2008

6. Role of nurses in the evaluation of septic patients

Author

Moraschini, F, Vitali, V, Togni, I, Riboli, B, Marchesi, G, Fumagalli, R, FUMAGALLI, ROBERTO, Moraschini, F, Vitali, V, Togni, I, Riboli, B, Marchesi, G, Fumagalli, R, and FUMAGALLI, ROBERTO

Abstract

ICU nurses hold an important role in the management of septic patients underlining with their ability to recognize SIRS that is the first step in the proinflammatory and procoagulant cascade following an infection. Early and timely approach to organ dysfunction can indeed modify the damages due to hypoperfusion. The ability to recognize organ dysfunction using different monitoring devices available should be part of the nursing attitudes

Published
2003

10. Cloning of a novel pilin-like gene from Bordetella pertussis: homology to the fim2 gene.

Author

Pedroni, P., Riboli, B., de Ferra, F., Grandi, G., Toma, S., Aricò, B., and Rappuoli, R.

Subjects
BORDETELLA pertussis, MOLECULAR cloning, CLONING, GENETIC engineering, MOLECULAR genetics, HOMOLOGY (Biology), BORDETELLA, GENETICS
Abstract

A search for pilin genes in a Bordetella pertussis (Bp) genomic library has led to the identification of several clones which hybridize to synthetic oligonucleotides with sequences derived from amino acid sequences of Bp fimbrial subunits. One of these clones (corresponding to a gene we have named fimX) contains an open reading frame encoding a protein with a molecular weight of about 20 kD and a sequence similar but not identical to the fimbrial subunit fim2 and to other fimbrial protein sequences. In this communication we present the cloning and nucleotide sequence of the fimX gene and its homology to the fim2 gene. A genomic analysis on the positional relationship between the two genes is also presented. [ABSTRACT FROM AUTHOR]

Published
1988
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11. E. coli recA protein possesses a strand separating activity on short duplex DNAs.

Author

Bianchi, M., Riboli, B., and Magni, G.

Abstract

RecA protein was found to catalyze the dissociation of the strands of a DNA substrate consisting of a 20‐nucleotide primer annealed to circular single‐stranded M13mp DNA. The strand separation reaction requires ATP hydrolysis and the presence of single‐stranded DNA flanking the duplex DNA region to be unwound. RecA‐catalyzed strand separation is effective only for very short duplexes, not exceeding 30 bp, and is not stimulated by single‐stranded DNA‐binding protein. These results are consistent with the ability of recA protein to disrupt regions of secondary structure in single‐stranded DNA and to incorporate large non‐homologies into heteroduplex DNA.

Published
1985
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12. Bordetella pertussis pilin and pilin-like genes

Author

de Ferra F, Pedroni P, Riboli B, Cuzzoni A, and Guido Grandi

Subjects
Virulence, Genes, Bacterial, Fimbriae, Bacterial, Molecular Sequence Data, Amino Acid Sequence, Fimbriae Proteins, Gene Expression Regulation, Bacterial, Bordetella pertussis, Bacterial Outer Membrane Proteins
Abstract

Bordetella pertussis fimbriae, which mediate the adherence of the microorganism to the epithelium of the respiratory tract, elicit a protective immunogenic response which could be taken advantage of for the creation of an acellular vaccine against pertussis. A few of the fimbrial proteins have been partially characterized by immunological means which recently the cloning and characterization of pilin and pilin-like genes are allowing us to study their structure, regulation of expression during the infectious cycle of Bordetella pertussis, and the basis for antigenic variation. In this communication we will review recent data on Bordetella pertussis pilin and pilin-like genes and their products, with particular emphasis on data most relevant to the design of an acellular vaccine.

Published
1988

14. DNA repair deficiency as circulating biomarker in prostate cancer.

Author

Catalano M, Generali D, Gatti M, Riboli B, Paganini L, Nesi G, and Roviello G

Abstract

Deleterious aberrations in DNA repair genes are actionable in approximately 25% of metastatic castration-resistant prostate cancers (mCRPC) patients. Homology recombination repair (HRR) is the DNA damage repair (DDR) mechanism most frequently altered in prostate cancer; of note BRCA2 is the most frequently altered DDR gene in this tumor. Poly ADP-ribose polymerase inhibitors showed antitumor activity with a improvement in overall survival in mCRPC carrying somatic and/or germline alterations of HHR. Germline mutations are tested on peripheral blood samples using DNA extracted from peripheral blood leukocytes, while the somatic alterations are assessed by extracting DNA from a tumor tissue sample. However, each of these genetic tests have some limitations: the somatic tests are related to the sample availability and tumor heterogeneity, while the germline testing are mainly related to the inability to detect somatic HRR mutations. Therefore, the liquid biopsy, a non-invasive and easily repeatable test compared to tissue test, could identified somatic mutation detected on the circulating tumor DNA (ctDNA) extracted from a plasma. This approach should better represent the heterogeneity of the tumor compared to the primary biopsy and maybe helpful in monitoring the onset of potential mutations involved in treatment resistance. Furthermore, ctDNA may inform about timing and potential cooperation of multiple driver genes aberration guiding the treatment options in patients with mCRPC. However, the clinical use of ctDNA test in prostate cancer compared to blood and tissue testing are currently very limited. In this review, we summarize the current therapeutic indications in prostate cancer patients with DDR deficiency, the recommendation for germline and somatic-genomic testing in advanced PC and the advantages of the use liquid biopsy in clinical routine for mCRPC., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Catalano, Generali, Gatti, Riboli, Paganini, Nesi and Roviello.)

Published
2023
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15. Large scale multifactorial likelihood quantitative analysis of BRCA1 and BRCA2 variants: An ENIGMA resource to support clinical variant classification.

Author

Parsons MT, Tudini E, Li H, Hahnen E, Wappenschmidt B, Feliubadaló L, Aalfs CM, Agata S, Aittomäki K, Alducci E, Alonso-Cerezo MC, Arnold N, Auber B, Austin R, Azzollini J, Balmaña J, Barbieri E, Bartram CR, Blanco A, Blümcke B, Bonache S, Bonanni B, Borg Å, Bortesi B, Brunet J, Bruzzone C, Bucksch K, Cagnoli G, Caldés T, Caliebe A, Caligo MA, Calvello M, Capone GL, Caputo SM, Carnevali I, Carrasco E, Caux-Moncoutier V, Cavalli P, Cini G, Clarke EM, Concolino P, Cops EJ, Cortesi L, Couch FJ, Darder E, de la Hoya M, Dean M, Debatin I, Del Valle J, Delnatte C, Derive N, Diez O, Ditsch N, Domchek SM, Dutrannoy V, Eccles DM, Ehrencrona H, Enders U, Evans DG, Farra C, Faust U, Felbor U, Feroce I, Fine M, Foulkes WD, Galvao HCR, Gambino G, Gehrig A, Gensini F, Gerdes AM, Germani A, Giesecke J, Gismondi V, Gómez C, Gómez Garcia EB, González S, Grau E, Grill S, Gross E, Guerrieri-Gonzaga A, Guillaud-Bataille M, Gutiérrez-Enríquez S, Haaf T, Hackmann K, Hansen TVO, Harris M, Hauke J, Heinrich T, Hellebrand H, Herold KN, Honisch E, Horvath J, Houdayer C, Hübbel V, Iglesias S, Izquierdo A, James PA, Janssen LAM, Jeschke U, Kaulfuß S, Keupp K, Kiechle M, Kölbl A, Krieger S, Kruse TA, Kvist A, Lalloo F, Larsen M, Lattimore VL, Lautrup C, Ledig S, Leinert E, Lewis AL, Lim J, Loeffler M, López-Fernández A, Lucci-Cordisco E, Maass N, Manoukian S, Marabelli M, Matricardi L, Meindl A, Michelli RD, Moghadasi S, Moles-Fernández A, Montagna M, Montalban G, Monteiro AN, Montes E, Mori L, Moserle L, Müller CR, Mundhenke C, Naldi N, Nathanson KL, Navarro M, Nevanlinna H, Nichols CB, Niederacher D, Nielsen HR, Ong KR, Pachter N, Palmero EI, Papi L, Pedersen IS, Peissel B, Perez-Segura P, Pfeifer K, Pineda M, Pohl-Rescigno E, Poplawski NK, Porfirio B, Quante AS, Ramser J, Reis RM, Revillion F, Rhiem K, Riboli B, Ritter J, Rivera D, Rofes P, Rump A, Salinas M, Sánchez de Abajo AM, Schmidt G, Schoenwiese U, Seggewiß J, Solanes A, Steinemann D, Stiller M, Stoppa-Lyonnet D, Sullivan KJ, Susman R, Sutter C, Tavtigian SV, Teo SH, Teulé A, Thomassen M, Tibiletti MG, Tischkowitz M, Tognazzo S, Toland AE, Tornero E, Törngren T, Torres-Esquius S, Toss A, Trainer AH, Tucker KM, van Asperen CJ, van Mackelenbergh MT, Varesco L, Vargas-Parra G, Varon R, Vega A, Velasco Á, Vesper AS, Viel A, Vreeswijk MPG, Wagner SA, Waha A, Walker LC, Walters RJ, Wang-Gohrke S, Weber BHF, Weichert W, Wieland K, Wiesmüller L, Witzel I, Wöckel A, Woodward ER, Zachariae S, Zampiga V, Zeder-Göß C, Lázaro C, De Nicolo A, Radice P, Engel C, Schmutzler RK, Goldgar DE, and Spurdle AB

Subjects
Alternative Splicing, Early Detection of Cancer, Female, Genetic Predisposition to Disease, Humans, Likelihood Functions, Male, Multifactorial Inheritance, Neoplasms genetics, BRCA1 Protein genetics, BRCA2 Protein genetics, Computational Biology methods, Mutation, Missense, Neoplasms diagnosis
Abstract

The multifactorial likelihood analysis method has demonstrated utility for quantitative assessment of variant pathogenicity for multiple cancer syndrome genes. Independent data types currently incorporated in the model for assessing BRCA1 and BRCA2 variants include clinically calibrated prior probability of pathogenicity based on variant location and bioinformatic prediction of variant effect, co-segregation, family cancer history profile, co-occurrence with a pathogenic variant in the same gene, breast tumor pathology, and case-control information. Research and clinical data for multifactorial likelihood analysis were collated for 1,395 BRCA1/2 predominantly intronic and missense variants, enabling classification based on posterior probability of pathogenicity for 734 variants: 447 variants were classified as (likely) benign, and 94 as (likely) pathogenic; and 248 classifications were new or considerably altered relative to ClinVar submissions. Classifications were compared with information not yet included in the likelihood model, and evidence strengths aligned to those recommended for ACMG/AMP classification codes. Altered mRNA splicing or function relative to known nonpathogenic variant controls were moderately to strongly predictive of variant pathogenicity. Variant absence in population datasets provided supporting evidence for variant pathogenicity. These findings have direct relevance for BRCA1 and BRCA2 variant evaluation, and justify the need for gene-specific calibration of evidence types used for variant classification., (© 2019 Wiley Periodicals, Inc.)

Published
2019
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16. Inositol supplementation in pregnancies at risk of apparently folate-resistant NTDs.

Author

Cavalli P, Tedoldi S, and Riboli B

Subjects
5,10-Methylenetetrahydrofolate Reductase (FADH2) genetics, Adult, Cystathionine beta-Synthase genetics, Female, Ferredoxin-NADP Reductase genetics, Folic Acid administration & dosage, Folic Acid therapeutic use, Humans, Infant, Low Birth Weight, Infant, Newborn, Infant, Premature, Male, Neural Tube Defects etiology, Polymorphism, Genetic, Pregnancy, Risk Factors, Drug Resistance, Folic Acid pharmacology, Inositol administration & dosage, Inositol therapeutic use, Neural Tube Defects prevention & control, Pregnancy Outcome
Published
2008
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18. Prenatal diagnosis of X chromosome monosomy.

Author

Cavalli P, Riboli B, Torresani P, and Poggiani C

Subjects
Adult, Diagnosis, Differential, Female, Humans, In Situ Hybridization, Fluorescence, Monosomy genetics, Polymerase Chain Reaction, Pregnancy, Prenatal Diagnosis, Chromosomes, Human, X, Genes, sry, Monosomy diagnosis
Published
2006
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19. [Role of nurses in the evaluation of septic patients].

Author

Moraschini F, Vitali V, Togni I, Riboli B, Marchesi G, and Fumagalli R

Subjects
Central Nervous System physiopathology, Humans, Monitoring, Physiologic, Sepsis physiopathology, Critical Care methods, Sepsis diagnosis, Sepsis nursing
Abstract

ICU nurses hold an important role in the management of septic patients underlining with their ability to recognize SIRS that is the first step in the proinflammatory and procoagulant cascade following an infection. Early and timely approach to organ dysfunction can indeed modify the damages due to hypoperfusion. The ability to recognize organ dysfunction using different monitoring devices available should be part of the nursing attitudes.

Published
2003

20. The S-layer gene of Lactobacillus helveticus CNRZ 892: cloning, sequence and heterologous expression.

Author

Callegari ML, Riboli B, Sanders JW, Cocconcelli PS, Kok J, Venema G, and Morelli L

Subjects
Amino Acid Sequence, Bacterial Proteins chemistry, Bacterial Proteins metabolism, Base Sequence, Blotting, Northern, Blotting, Western, Electrophoresis, Polyacrylamide Gel, Escherichia coli genetics, Immunoblotting, Lactobacillus metabolism, Lactococcus lactis genetics, Membrane Proteins chemistry, Membrane Proteins metabolism, Microscopy, Electron, Molecular Sequence Data, RNA, Messenger genetics, Recombinant Proteins biosynthesis, Sequence Alignment, Sequence Analysis, Transcription, Genetic, Bacterial Proteins genetics, Cloning, Molecular, Gene Expression, Genes, Bacterial, Lactobacillus genetics, Membrane Glycoproteins, Membrane Proteins genetics
Abstract

Lactobacillus helveticus CNRZ 892 contains a surface layer (S-layer) composed of protein monomers of 43 kDa organized in regular arrays. The gene encoding this protein (slpH) has been cloned in Escherichia coli and sequenced. slpH consists of 440 codons and is preceded by a ribosome-binding site (RBS) and followed by a putative rho-independent terminator. Indeed, Northern analysis revealed that slpH is a monocistronic gene. The gene is preceded by a possible promotor of which the -35 and -10 hexanucleotides are separated by 17 nt. By primer extension analysis the transcription start site was mapped at 7 nt downstream of the -10 sequence while the deduced amino acid sequence of SlpH shows a leader peptide of 30 aa. The slpH gene has been amplified by PCR and the fragment, carrying the complete gene from the RBS to the stop codon, has been cloned in a lactococcal gene expression vector downstream of promoter P32. Lactococcus lactis MG1363 carrying the resulting plasmid produced and secreted an S-layer monomer with the same molecular mass as the authentic L. helveticus CNRZ 892 SlpH, as judged by SDS-PAGE. Immunoelectron microscopy revealed that SlpH was bound to the lactococcal cell walls in small clumps and accumulated in the growth medium as small sheets.

Published
1998
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