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19 results on '"Hovig, E."'

1. The population genomic legacy of the second plague pandemic

Author

Gopalakrishnan, S., Ebenesersdóttir, S., Lundstrøm, I., Turner-Walker, G., Moore, K., Luisi, P., Margaryan, A., Martin, M., Ellegaard, M., Magnússon, Ó., Sigurðsson, Á., Snorradóttir, S., Magnúsdóttir, D., Laffoon, J., van Dorp, L., Liu, X., Moltke, I., Ávila-Arcos, M., Schraiber, J., Rasmussen, S., Juan, D., Gelabert, P., de-Dios, T., Fotakis, A., Iraeta-Orbegozo, M., Vågene, Å., Denham, S., Christophersen, A., Stenøien, H., Vieira, F., Liu, S., Günther, T., Kivisild, T., Moseng, O., Skar, B., Cheung, C., Sandoval-Velasco, M., Wales, N., Schroeder, H., Campos, P., Guðmundsdóttir, V., Sicheritz-Ponten, T., Petersen, B., Halgunset, J., Gilbert, E., Cavalleri, G., Hovig, E., Kockum, I., Olsson, T., Alfredsson, L., Hansen, T., Werge, T., Willerslev, E., Balloux, F., Marques-Bonet, T., Lalueza-Fox, C., Nielsen, R., Stefánsson, K., Helgason, A., and Gilbert, M.

Abstract

SummaryHuman populations have been shaped by catastrophes that may have left long-lasting signatures in their genomes. One notable example is the second plague pandemic that entered Europe in ca. 1,347 CE and repeatedly returned for over 300 years, with typical village and town mortality estimated at 10%–40%.1 It is assumed that this high mortality affected the gene pools of these populations. First, local population crashes reduced genetic diversity. Second, a change in frequency is expected for sequence variants that may have affected survival or susceptibility to the etiologic agent (Yersinia pestis).2 Third, mass mortality might alter the local gene pools through its impact on subsequent migration patterns. We explored these factors using the Norwegian city of Trondheim as a model, by sequencing 54 genomes spanning three time periods: (1) prior to the plague striking Trondheim in 1,349 CE, (2) the 17th–19th century, and (3) the present. We find that the pandemic period shaped the gene pool by reducing long distance immigration, in particular from the British Isles, and inducing a bottleneck that reduced genetic diversity. Although we also observe an excess of large FST values at multiple loci in the genome, these are shaped by reference biases introduced by mapping our relatively low genome coverage degraded DNA to the reference genome. This implies that attempts to detect selection using ancient DNA (aDNA) datasets that vary by read length and depth of sequencing coverage may be particularly challenging until methods have been developed to account for the impact of differential reference bias on test statistics. Results and discussion STAR★Methods

Published
2022

2. Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen

Author

Menden M, Wang D, Mason M, Szalai B, Bulusu K, Guan Y, Yu T, Kang J, Jeon M, Wolfinger R, Nguyen T, Zaslavskiy M, Jang I, Ghazoui Z, Ahsen M, Vogel R, Neto E, Norman T, Tang E, Garnett M, Di Veroli G, Fawell S, Stolovitzky G, Guinney J, Dry J, Saez-Rodriguez J, Abante J, Abecassis B, Aben N, Aghamirzaie D, Aittokallio T, Akhtari F, Al-lazikani B, Alam T, Allam A, Allen C, de Almeida M, Altarawy D, Alves V, Amadoz A, Anchang B, Antolin A, Ash J, Aznar V, Ba-alawi W, Bagheri M, Bajic V, Ball G, Ballester P, Baptista D, Bare C, Bateson M, Bender A, Bertrand D, Wijayawardena B, Boroevich K, Bosdriesz E, Bougouffa S, Bounova G, Brouwer T, Bryant B, Calaza M, Calderone A, Calza S, Capuzzi S, Carbonell-Caballero J, Carlin D, Carter H, Castagnoli L, Celebi R, Cesareni G, Chang H, Chen G, Chen H, Cheng L, Chernomoretz A, Chicco D, Cho K, Cho S, Choi D, Choi J, Choi K, Choi M, De Cock M, Coker E, Cortes-Ciriano I, Cserzo M, Cubuk C, Curtis C, Van Daele D, Dang C, Dijkstra T, Dopazo J, Draghici S, Drosou A, Dumontier M, Ehrhart F, Eid F, ElHefnawi M, Elmarakeby H, van Engelen B, Engin H, de Esch I, Evelo C, Falcao A, Farag S, Fernandez-Lozano C, Fisch K, Flobak A, Fornari C, Foroushani A, Fotso D, Fourches D, Friend S, Frigessi A, Gao F, Gao X, Gerold J, Gestraud P, Ghosh S, Gillberg J, Godoy-Lorite A, Godynyuk L, Godzik A, Goldenberg A, Gomez-Cabrero D, Gonen M, de Graaf C, Gray H, Grechkin M, Guimera R, Guney E, Haibe-Kains B, Han Y, Hase T, He D, He L, Heath L, Hellton K, Helmer-Citterich M, Hidalgo M, Hidru D, Hill S, Hochreiter S, Hong S, Hovig E, Hsueh Y, Hu Z, Huang J, Huang R, Hunyady L, Hwang J, Hwang T, Hwang W, Hwang Y, Isayev O, Walk O, Jack J, Jahandideh S, Ji J, Jo Y, Kamola P, Kanev G, Karacosta L, Karimi M, Kaski S, Kazanov M, Khamis A, Khan S, Kiani N, Kim A, Kim J, Kim K, Kim S, Kim Y, Kirk P, Kitano H, Klambauer G, Knowles D, Ko M, Kohn-Luque A, Kooistra A, Kuenemann M, Kuiper M, Kurz C, Kwon M, van Laarhoven T, Laegreid A, Lederer S, Lee H, Lee J, Lee Y, Leppaho E, Lewis R, Li J, Li L, Liley J, Lim W, Lin C, Liu Y, Lopez Y, Low J, Lysenko A, Machado D, Madhukar N, De Maeyer D, Malpartida A, Mamitsuka H, Marabita F, Marchal K, Marttinen P, Mason D, Mazaheri A, Mehmood A, Mehreen A, Michaut M, Miller R, Mitsopoulos C, Modos D, Van Moerbeke M, Moo K, Motsinger-Reif A, Movva R, Muraru S, Muratov E, Mushthofa M, Nagarajan N, Nakken S, Nath A, Neuvial P, Newton R, Ning Z, De Niz C, Oliva B, Olsen C, Palmeri A, Panesar B, Papadopoulos S, Park J, Park S, Pawitan Y, Peluso D, Pendyala S, Peng J, Perfetto L, Pirro S, Plevritis S, Politi R, Poon H, Porta E, Prellner I, Preuer K, Pujana M, Ramnarine R, Reid J, Reyal F, Richardson S, Ricketts C, Rieswijk L, Rocha M, Rodriguez-Gonzalvez C, Roell K, Rotroff D, de Ruiter J, Rukawa P, Sadacca B, Safikhani Z, Safitri F, Sales-Pardo M, Sauer S, Schlichting M, Seoane J, Serra J, Shang M, Sharma A, Sharma H, Shen Y, Shiga M, Shin M, Shkedy Z, Shopsowitz K, Sinai S, Skola D, Smirnov P, Soerensen I, Soerensen P, Song J, Song S, Soufan O, Spitzmueller A, Steipe B, Suphavilai C, Tamayo S, Tamborero D, Tang J, Tanoli Z, Tarres-Deulofeu M, Tegner J, Thommesen L, Tonekaboni S, Tran H, De Troyer E, Truong A, Tsunoda T, Turu G, Tzeng G, Verbeke L, Videla S, Vis D, Voronkov A, Votis K, Wang A, Wang H, Wang P, Wang S, Wang W, Wang X, Wennerberg K, Wernisch L, Wessels L, van Westen G, Westerman B, White S, Willighagen E, Wurdinger T, Xie L, Xie S, Xu H, Yadav B, Yau C, Yeerna H, Yin J, Yu M, Yun S, Zakharov A, Zamichos A, Zanin M, Zeng L, Zenil H, Zhang F, Zhang P, Zhang W, Zhao H, Zhao L, Zheng W, Zoufir A, Zucknick M, AstraZeneca-Sanger Drug Combinatio, Ege Üniversitesi, Gönen, Mehmet (ORCID 0000-0002-2483-075X & YÖK ID 237468), Menden, Michael P., Wang, Dennis, Mason, Mike J., Szalai, Bence, Bulusu, Krishna C., Guan, Yuanfang, Yu, Thomas, Kang, Jaewoo, Jeon, Minji, Wolfinger, Russ, Nguyen, Tin, Zaslavskiy, Mikhail, Jang, In Sock, Ghazoui, Zara, Ahsen, Mehmet Eren, Vogel, Robert, Neto, Elias Chaibub, Norman, Thea, Tang, Eric K. Y., Garnett, Mathew J., Di Veroli, Giovanni Y., Fawell, Stephen, Stolovitzky, Gustavo, Guinney, Justin, Dry, Jonathan R., Saez-Rodriguez, Julio, Abante, Jordi, Abecassis, Barbara Schmitz, Aben, Nanne, Aghamirzaie, Delasa, Aittokallio, Tero, Akhtari, Farida S., Al-lazikani, Bissan, Alam, Tanvir, Allam, Amin, Allen, Chad, de Almeida, Mariana Pelicano, Altarawy, Doaa, Alves, Vinicius, Amadoz, Alicia, Anchang, Benedict, Antolin, Albert A., Ash, Jeremy R., Romeo Aznar, Victoria, Ba-alawi, Wail, Bagheri, Moeen, Bajic, Vladimir, Ball, Gordon, Ballester, Pedro J., Baptista, Delora, Bare, Christopher, Bateson, Mathilde, Bender, Andreas, Bertrand, Denis, Wijayawardena, Bhagya, Boroevich, Keith A., Bosdriesz, Evert, Bougouffa, Salim, Bounova, Gergana, Brouwer, Thomas, Bryant, Barbara, Calaza, Manuel, Calderone, Alberto, Calza, Stefano, Capuzzi, Stephen, Carbonell-Caballero, Jose, Carlin, Daniel, Carter, Hannah, Castagnoli, Luisa, Celebi, Remzi, Cesareni, Gianni, Chang, Hyeokyoon, Chen, Guocai, Chen, Haoran, Chen, Huiyuan, Cheng, Lijun, Chernomoretz, Ariel, Chicco, Davide, Cho, Kwang-Hyun, Cho, Sunghwan, Choi, Daeseon, Choi, Jaejoon, Choi, Kwanghun, Choi, Minsoo, De Cock, Martine, Coker, Elizabeth, Cortes-Ciriano, Isidro, Cserzo, Miklos, Cubuk, Cankut, Curtis, Christina, Van Daele, Dries, Dang, Cuong C., Dijkstra, Tjeerd, Dopazo, Joaquin, Draghici, Sorin, Drosou, Anastasios, Dumontier, Michel, Ehrhart, Friederike, Eid, Fatma-Elzahraa, ElHefnawi, Mahmoud, Elmarakeby, Haitham, van Engelen, Bo, Engin, Hatice Billur, de Esch, Iwan, Evelo, Chris, Falcao, Andre O., Farag, Sherif, Fernandez-Lozano, Carlos, Fisch, Kathleen, Flobak, Asmund, Fornari, Chiara, Foroushani, Amir B. K., Fotso, Donatien Chedom, Fourches, Denis, Friend, Stephen, Frigessi, Arnoldo, Gao, Feng, Gao, Xiaoting, Gerold, Jeffrey M., Gestraud, Pierre, Ghosh, Samik, Gillberg, Jussi, Godoy-Lorite, Antonia, Godynyuk, Lizzy, Godzik, Adam, Goldenberg, Anna, Gomez-Cabrero, David, de Graaf, Chris, Gray, Harry, Grechkin, Maxim, Guimera, Roger, Guney, Emre, Haibe-Kains, Benjamin, Han, Younghyun, Hase, Takeshi, He, Di, He, Liye, Heath, Lenwood S., Hellton, Kristoffer H., Helmer-Citterich, Manuela, Hidalgo, Marta R., Hidru, Daniel, Hill, Steven M., Hochreiter, Sepp, Hong, Seungpyo, Hovig, Eivind, Hsueh, Ya-Chih, Hu, Zhiyuan, Huang, Justin K., Huang, R. Stephanie, Hunyady, Laszlo, Hwang, Jinseub, Hwang, Tae Hyun, Hwang, Woochang, Hwang, Yongdeuk, Isayev, Olexandr, Walk, Oliver Bear Don't, Jack, John, Jahandideh, Samad, Ji, Jiadong, Jo, Yousang, Kamola, Piotr J., Kanev, Georgi K., Karacosta, Loukia, Karimi, Mostafa, Kaski, Samuel, Kazanov, Marat, Khamis, Abdullah M., Khan, Suleiman Ali, Kiani, Narsis A., Kim, Allen, Kim, Jinhan, Kim, Juntae, Kim, Kiseong, Kim, Kyung, Kim, Sunkyu, Kim, Yongsoo, Kim, Yunseong, Kirk, Paul D. W., Kitano, Hiroaki, Klambauer, Gunter, Knowles, David, Ko, Melissa, Kohn-Luque, Alvaro, Kooistra, Albert J., Kuenemann, Melaine A., Kuiper, Martin, Kurz, Christoph, Kwon, Mijin, van Laarhoven, Twan, Laegreid, Astrid, Lederer, Simone, Lee, Heewon, Lee, Jeon, Lee, Yun Woo, Leppaho, Eemeli, Lewis, Richard, Li, Jing, Li, Lang, Liley, James, Lim, Weng Khong, Lin, Chieh, Liu, Yiyi, Lopez, Yosvany, Low, Joshua, Lysenko, Artem, Machado, Daniel, Madhukar, Neel, De Maeyer, Dries, Malpartida, Ana Belen, Mamitsuka, Hiroshi, Marabita, Francesco, Marchal, Kathleen, Marttinen, Pekka, Mason, Daniel, Mazaheri, Alireza, Mehmood, Arfa, Mehreen, Ali, Michaut, Magali, Miller, Ryan A., Mitsopoulos, Costas, Modos, Dezso, Van Moerbeke, Marijke, Moo, Keagan, Motsinger-Reif, Alison, Movva, Rajiv, Muraru, Sebastian, Muratov, Eugene, Mushthofa, Mushthofa, Nagarajan, Niranjan, Nakken, Sigve, Nath, Aritro, Neuvial, Pierre, Newton, Richard, Ning, Zheng, De Niz, Carlos, Oliva, Baldo, Olsen, Catharina, Palmeri, Antonio, Panesar, Bhawan, Papadopoulos, Stavros, Park, Jaesub, Park, Seonyeong, Park, Sungjoon, Pawitan, Yudi, Peluso, Daniele, Pendyala, Sriram, Peng, Jian, Perfetto, Livia, Pirro, Stefano, Plevritis, Sylvia, Politi, Regina, Poon, Hoifung, Porta, Eduard, Prellner, Isak, Preuer, Kristina, Angel Pujana, Miguel, Ramnarine, Ricardo, Reid, John E., Reyal, Fabien, Richardson, Sylvia, Ricketts, Camir, Rieswijk, Linda, Rocha, Miguel, Rodriguez-Gonzalvez, Carmen, Roell, Kyle, Rotroff, Daniel, de Ruiter, Julian R., Rukawa, Ploy, Sadacca, Benjamin, Safikhani, Zhaleh, Safitri, Fita, Sales-Pardo, Marta, Sauer, Sebastian, Schlichting, Moritz, Seoane, Jose A., Serra, Jordi, Shang, Ming-Mei, Sharma, Alok, Sharma, Hari, Shen, Yang, Shiga, Motoki, Shin, Moonshik, Shkedy, Ziv, Shopsowitz, Kevin, Sinai, Sam, Skola, Dylan, Smirnov, Petr, Soerensen, Izel Fourie, Soerensen, Peter, Song, Je-Hoon, Song, Sang Ok, Soufan, Othman, Spitzmueller, Andreas, Steipe, Boris, Suphavilai, Chayaporn, Tamayo, Sergio Pulido, Tamborero, David, Tang, Jing, Tanoli, Zia-ur-Rehman, Tarres-Deulofeu, Marc, Tegner, Jesper, Thommesen, Liv, Tonekaboni, Seyed Ali Madani, Tran, Hong, De Troyer, Ewoud, Truong, Amy, Tsunoda, Tatsuhiko, Turu, Gabor, Tzeng, Guang-Yo, Verbeke, Lieven, Videla, Santiago, Vis, Daniel, Voronkov, Andrey, Votis, Konstantinos, Wang, Ashley, Wang, Hong-Qiang Horace, Wang, Po-Wei, Wang, Sheng, Wang, Wei, Wang, Xiaochen, Wang, Xin, Wennerberg, Krister, Wernisch, Lorenz, Wessels, Lodewyk, van Westen, Gerard J. P., Westerman, Bart A., White, Simon Richard, Willighagen, Egon, Wurdinger, Tom, Xie, Lei, Xie, Shuilian, Xu, Hua, Yadav, Bhagwan, Yau, Christopher, Yeerna, Huwate, Yin, Jia Wei, Yu, Michael, Yu, MinHwan, Yun, So Jeong, Zakharov, Alexey, Zamichos, Alexandros, Zanin, Massimiliano, Zeng, Li, Zenil, Hector, Zhang, Frederick, Zhang, Pengyue, Zhang, Wei, Zhao, Hongyu, Zhao, Lan, Zheng, Wenjin, Zoufir, Azedine, Zucknick, Manuela, College of Engineering, Department of Industrial Engineering, Institute of Data Science, RS: FSE DACS IDS, Bioinformatica, RS: NUTRIM - R1 - Obesity, diabetes and cardiovascular health, RS: FHML MaCSBio, Promovendi NTM, Tero Aittokallio / Principal Investigator, Bioinformatics, Institute for Molecular Medicine Finland, Hu, Z, Fotso, DC, Menden, M, Wang, D, Mason, M, Szalai, B, Bulusu, K, Guan, Y, Yu, T, Kang, J, Jeon, M, Wolfinger, R, Nguyen, T, Zaslavskiy, M, Abante, J, Abecassis, B, Aben, N, Aghamirzaie, D, Aittokallio, T, Akhtari, F, Al-lazikani, B, Alam, T, Allam, A, Allen, C, de Almeida, M, Altarawy, D, Alves, V, Amadoz, A, Anchang, B, Antolin, A, Ash, J, Aznar, V, Ba-alawi, W, Bagheri, M, Bajic, V, Ball, G, Ballester, P, Baptista, D, Bare, C, Bateson, M, Bender, A, Bertrand, D, Wijayawardena, B, Boroevich, K, Bosdriesz, E, Bougouffa, S, Bounova, G, Brouwer, T, Bryant, B, Calaza, M, Calderone, A, Calza, S, Capuzzi, S, Carbonell-Caballero, J, Carlin, D, Carter, H, Castagnoli, L, Celebi, R, Cesareni, G, Chang, H, Chen, G, Chen, H, Cheng, L, Chernomoretz, A, Chicco, D, Cho, K, Cho, S, Choi, D, Choi, J, Choi, K, Choi, M, Cock, M, Coker, E, Cortes-Ciriano, I, Cserzo, M, Cubuk, C, Curtis, C, Daele, D, Dang, C, Dijkstra, T, Dopazo, J, Draghici, S, Drosou, A, Dumontier, M, Ehrhart, F, Eid, F, Elhefnawi, M, Elmarakeby, H, van Engelen, B, Engin, H, de Esch, I, Evelo, C, Falcao, A, Farag, S, Fernandez-Lozano, C, Fisch, K, Flobak, A, Fornari, C, Foroushani, A, Fotso, D, Fourches, D, Friend, S, Frigessi, A, Gao, F, Gao, X, Gerold, J, Gestraud, P, Ghosh, S, Gillberg, J, Godoy-Lorite, A, Godynyuk, L, Godzik, A, Goldenberg, A, Gomez-Cabrero, D, Gonen, M, de Graaf, C, Gray, H, Grechkin, M, Guimera, R, Guney, E, Haibe-Kains, B, Han, Y, Hase, T, He, D, He, L, Heath, L, Hellton, K, Helmer-Citterich, M, Hidalgo, M, Hidru, D, Hill, S, Hochreiter, S, Hong, S, Hovig, E, Hsueh, Y, Huang, J, Huang, R, Hunyady, L, Hwang, J, Hwang, T, Hwang, W, Hwang, Y, Isayev, O, Don't Walk, O, Jack, J, Jahandideh, S, Ji, J, Jo, Y, Kamola, P, Kanev, G, Karacosta, L, Karimi, M, Kaski, S, Kazanov, M, Khamis, A, Khan, S, Kiani, N, Kim, A, Kim, J, Kim, K, Kim, S, Kim, Y, Kirk, P, Kitano, H, Klambauer, G, Knowles, D, Ko, M, Kohn-Luque, A, Kooistra, A, Kuenemann, M, Kuiper, M, Kurz, C, Kwon, M, van Laarhoven, T, Laegreid, A, Lederer, S, Lee, H, Lee, J, Lee, Y, Lepp_aho, E, Lewis, R, Li, J, Li, L, Liley, J, Lim, W, Lin, C, Liu, Y, Lopez, Y, Low, J, Lysenko, A, Machado, D, Madhukar, N, Maeyer, D, Malpartida, A, Mamitsuka, H, Marabita, F, Marchal, K, Marttinen, P, Mason, D, Mazaheri, A, Mehmood, A, Mehreen, A, Michaut, M, Miller, R, Mitsopoulos, C, Modos, D, Moerbeke, M, Moo, K, Motsinger-Reif, A, Movva, R, Muraru, S, Muratov, E, Mushthofa, M, Nagarajan, N, Nakken, S, Nath, A, Neuvial, P, Newton, R, Ning, Z, Niz, C, Oliva, B, Olsen, C, Palmeri, A, Panesar, B, Papadopoulos, S, Park, J, Park, S, Pawitan, Y, Peluso, D, Pendyala, S, Peng, J, Perfetto, L, Pirro, S, Plevritis, S, Politi, R, Poon, H, Porta, E, Prellner, I, Preuer, K, Pujana, M, Ramnarine, R, Reid, J, Reyal, F, Richardson, S, Ricketts, C, Rieswijk, L, Rocha, M, Rodriguez-Gonzalvez, C, Roell, K, Rotroff, D, de Ruiter, J, Rukawa, P, Sadacca, B, Safikhani, Z, Safitri, F, Sales-Pardo, M, Sauer, S, Schlichting, M, Seoane, J, Serra, J, Shang, M, Sharma, A, Sharma, H, Shen, Y, Shiga, M, Shin, M, Shkedy, Z, Shopsowitz, K, Sinai, S, Skola, D, Smirnov, P, Soerensen, I, Soerensen, P, Song, J, Song, S, Soufan, O, Spitzmueller, A, Steipe, B, Suphavilai, C, Tamayo, S, Tamborero, D, Tang, J, Tanoli, Z, Tarres-Deulofeu, M, Tegner, J, Thommesen, L, Tonekaboni, S, Tran, H, Troyer, E, Truong, A, Tsunoda, T, Turu, G, Tzeng, G, Verbeke, L, Videla, S, Vis, D, Voronkov, A, Votis, K, Wang, A, Wang, H, Wang, P, Wang, S, Wang, W, Wang, X, Wennerberg, K, Wernisch, L, Wessels, L, van Westen, G, Westerman, B, White, S, Willighagen, E, Wurdinger, T, Xie, L, Xie, S, Xu, H, Yadav, B, Yau, C, Yeerna, H, Yin, J, Yu, M, Yun, S, Zakharov, A, Zamichos, A, Zanin, M, Zeng, L, Zenil, H, Zhang, F, Zhang, P, Zhang, W, Zhao, H, Zhao, L, Zheng, W, Zoufir, A, Zucknick, M, Jang, I, Ghazoui, Z, Ahsen, M, Vogel, R, Neto, E, Norman, T, Tang, E, Garnett, M, Veroli, G, Fawell, S, Stolovitzky, G, Guinney, J, Dry, J, Saez-Rodriguez, J, Menden, Michael P. [0000-0003-0267-5792], Mason, Mike J. [0000-0002-5652-7739], Yu, Thomas [0000-0002-5841-0198], Kang, Jaewoo [0000-0001-6798-9106], Nguyen, Tin [0000-0001-8001-9470], Ahsen, Mehmet Eren [0000-0002-4907-0427], Stolovitzky, Gustavo [0000-0002-9618-2819], Guinney, Justin [0000-0003-1477-1888], Saez-Rodriguez, Julio [0000-0002-8552-8976], Apollo - University of Cambridge Repository, Menden, Michael P [0000-0003-0267-5792], Mason, Mike J [0000-0002-5652-7739], Pathology, CCA - Cancer biology and immunology, Medical oncology laboratory, Neurosurgery, Chemistry and Pharmaceutical Sciences, AIMMS, Medicinal chemistry, Universidade do Minho, Department of Computer Science, Professorship Marttinen P., Aalto-yliopisto, and Aalto University

Subjects
Drug Resistance, 02 engineering and technology, 13, PATHWAY, Antineoplastic Combined Chemotherapy Protocols, Molecular Targeted Therapy, Càncer, lcsh:Science, media_common, Cancer, Tumor, Settore BIO/18, Settore BIO/11, Drug combinations, High-throughput screening, Drug Synergism, purl.org/becyt/ford/1.2 [https], Genomics, Machine Learning, predictions, 3. Good health, ddc, Technologie de l'environnement, contrôle de la pollution, Benchmarking, 5.1 Pharmaceuticals, Cancer treatment, Farmacogenètica, Science & Technology - Other Topics, Development of treatments and therapeutic interventions, 0210 nano-technology, Human, Drug, media_common.quotation_subject, Science, 49/23, ADAM17 Protein, General Biochemistry, Genetics and Molecular Biology, 03 medical and health sciences, SDG 3 - Good Health and Well-being, RESOURCE, Machine learning, Genetics, Chimie, Humans, BREAST-CANCER, CELL, 49/98, Science & Technology, Antineoplastic Combined Chemotherapy Protocol, 45, MUTATIONS, Computational Biology, Androgen receptor, Breast-cancer, Gene, Cell, Inhibition, Resistance, Pathway, Mutations, Landscape, Resource, 631/114/1305, medicine.disease, Drug synergy, 49, 030104 developmental biology, Pharmacogenetics, Mutation, Ciências Médicas::Biotecnologia Médica, lcsh:Q, 631/154/1435/2163, Biomarkers, RESISTANCE, 0301 basic medicine, ING-INF/06 - BIOINGEGNERIA ELETTRONICA E INFORMATICA, Statistical methods, Computer science, General Physics and Astronomy, Datasets as Topic, Drug resistance, purl.org/becyt/ford/1 [https], Phosphatidylinositol 3-Kinases, Biotecnologia Médica [Ciências Médicas], Neoplasms, Science and technology, Phosphoinositide-3 Kinase Inhibitors, Multidisciplinary, Biomarkers, Tumor, Cell Line, Tumor, Drug Antagonism, Drug Resistance, Neoplasm, Treatment Outcome, Pharmacogenetic, article, ANDROGEN RECEPTOR, 49/39, 631/114/2415, 021001 nanoscience & nanotechnology, 692/4028/67, Multidisciplinary Sciences, 317 Pharmacy, Patient Safety, Systems biology, 3122 Cancers, INHIBITION, Computational biology, Cell Line, medicine, LANDSCAPE, Physique, Human Genome, Data Science, General Chemistry, AstraZeneca-Sanger Drug Combination DREAM Consortium, Astronomie, GENE, Good Health and Well Being, Pharmacogenomics, Genomic, Neoplasm, 631/553, Phosphatidylinositol 3-Kinase
Abstract

PubMed: 31209238, The effectiveness of most cancer targeted therapies is short-lived. Tumors often develop resistance that might be overcome with drug combinations. However, the number of possible combinations is vast, necessitating data-driven approaches to find optimal patient-specific treatments. Here we report AstraZeneca’s large drug combination dataset, consisting of 11,576 experiments from 910 combinations across 85 molecularly characterized cancer cell lines, and results of a DREAM Challenge to evaluate computational strategies for predicting synergistic drug pairs and biomarkers. 160 teams participated to provide a comprehensive methodological development and benchmarking. Winning methods incorporate prior knowledge of drug-target interactions. Synergy is predicted with an accuracy matching biological replicates for >60% of combinations. However, 20% of drug combinations are poorly predicted by all methods. Genomic rationale for synergy predictions are identified, including ADAM17 inhibitor antagonism when combined with PIK3CB/D inhibition contrasting to synergy when combined with other PI3K-pathway inhibitors in PIK3CA mutant cells. © 2019, The Author(s)., National Institute for Health Research, NIHR Wellcome Trust, WT: 102696, 206194 Magyar Tudományos Akadémia, MTA Bayer 668858 PrECISE AstraZeneca, We thank the Genomics of Drug Sensitivity in Cancer and COSMIC teams at the Wellcome Trust Sanger Institute for help with the preparation of the molecular data, Denes Turei for help with Omnipath, and Katjusa Koler for help with matching drug names across combination screens. We thank AstraZeneca for funding and provision of data to the DREAM Consortium to run the challenge, and funding from the European Union Horizon 2020 research (under grant agreement No 668858 PrECISE to J.S.R.), the Joint Research Center for Computational Biomedicine (which is partially funded by Bayer AG) to J.S.R., National Institute for Health Research (NIHR) Sheffield Biomedical Research Center, Premium Postdoctoral Fellowship Program of the Hungarian Academy of Sciences. M.G lab is supported by Wellcome Trust (102696 and 206194)., Competing interests: K.C.B., Z.G., G.Y.D., E.K.Y.T., S.F., and J.R.D. are AstraZeneca employees. K.C.B., Z.G., E.K.Y.T., S.F., and J.R.D. are AstraZeneca shareholders. Y.G. receives personal compensation from Eli Lilly and Company, is a shareholder of Cleerly, Inc., and Ann Arbor Algorithms, Inc. M.G. receives research funding from AstraZeneca and has performed consultancy for Sanofi. The remaining authors declare no competing interests.

Published
2019

3. Correction: Cancer risks by gene, age, and gender in 6350 carriers of pathogenic mismatch repair variants: findings from the Prospective Lynch Syndrome Database (Genetics in Medicine, (2020), 22, 1, (15-25), 10.1038/s41436-019-0596-9)

Author

Dominguez-Valentin M., Sampson J. R., Seppala T. T., ten Broeke S. W., Plazzer J. -P., Nakken S., Engel C., Aretz S., Jenkins M. A., Sunde L., Bernstein I., Capella G., Balaguer F., Thomas H., Evans D. G., Burn J., Greenblatt M., Hovig E., de Vos tot Nederveen Cappel W. H., Sijmons R. H., Bertario L., Tibiletti M. G., Cavestro G. M., Lindblom A., Della Valle A., Lopez-Kostner F., Gluck N., Katz L. H., Heinimann K., Vaccaro C. A., Buttner R., Gorgens H., Holinski-Feder E., Morak M., Holzapfel S., Huneburg R., Knebel Doeberitz M., Loeffler M., Rahner N., Schackert H. K., Steinke-Lange V., Schmiegel W., Vangala D., Pylvanainen K., Renkonen-Sinisalo L., Hopper J. L., Win A. K., Haile R. W., Lindor N. M., Gallinger S., Le Marchand L., Newcomb P. A., Figueiredo J. C., Thibodeau S. N., Wadt K., Therkildsen C., Okkels H., Ketabi Z., Moreira L., Sanchez A., Serra-Burriel M., Pineda M., Navarro M., Blanco I., Green K., Lalloo F., Crosbie E. J., Hill J., Denton O. G., Frayling I. M., Rodland E. A., Vasen H., Mints M., Neffa F., Esperon P., Alvarez K., Kariv R., Rosner G., Pinero T. A., Gonzalez M. L., Kalfayan P., Tjandra D., Winship I. M., Macrae F., Moslein G., Mecklin J. -P., Nielsen M., Moller P., Dominguez-Valentin, M., Sampson, J. R., Seppala, T. T., ten Broeke, S. W., Plazzer, J. -P., Nakken, S., Engel, C., Aretz, S., Jenkins, M. A., Sunde, L., Bernstein, I., Capella, G., Balaguer, F., Thomas, H., Evans, D. G., Burn, J., Greenblatt, M., Hovig, E., de Vos tot Nederveen Cappel, W. H., Sijmons, R. H., Bertario, L., Tibiletti, M. G., Cavestro, G. M., Lindblom, A., Della Valle, A., Lopez-Kostner, F., Gluck, N., Katz, L. H., Heinimann, K., Vaccaro, C. A., Buttner, R., Gorgens, H., Holinski-Feder, E., Morak, M., Holzapfel, S., Huneburg, R., Knebel Doeberitz, M., Loeffler, M., Rahner, N., Schackert, H. K., Steinke-Lange, V., Schmiegel, W., Vangala, D., Pylvanainen, K., Renkonen-Sinisalo, L., Hopper, J. L., Win, A. K., Haile, R. W., Lindor, N. M., Gallinger, S., Le Marchand, L., Newcomb, P. A., Figueiredo, J. C., Thibodeau, S. N., Wadt, K., Therkildsen, C., Okkels, H., Ketabi, Z., Moreira, L., Sanchez, A., Serra-Burriel, M., Pineda, M., Navarro, M., Blanco, I., Green, K., Lalloo, F., Crosbie, E. J., Hill, J., Denton, O. G., Frayling, I. M., Rodland, E. A., Vasen, H., Mints, M., Neffa, F., Esperon, P., Alvarez, K., Kariv, R., Rosner, G., Pinero, T. A., Gonzalez, M. L., Kalfayan, P., Tjandra, D., Winship, I. M., Macrae, F., Moslein, G., Mecklin, J. -P., Nielsen, M., and Moller, P.

Abstract

The original version of this Article did not contain details of Dutch Cancer Society (DCS) funding (grant number UL 2017-8223) in the Acknowledgements section. This has now been corrected in both the PDF and HTML versions of the Article.

Published
2020

4. Analysis in the Prospective Lynch Syndrome Database identifies sarcoma as part of the Lynch syndrome tumor spectrum

Author

Dominguez-Valentin M., Sampson J. R., Moller P., Seppala T. T., Plazzer J. -P., Nakken S., Engel C., Aretz S., Jenkins M. A., Sunde L., Bernstein I., Capella G., Balaguer F., Thomas H., Evans D. G., Burn J., Greenblatt M., Hovig E., Nielsen M., de Vos tot Nederveen Cappel W. H., Sijmons R. H., Bertario L., Tibiletti M. G., Cavestro G. M., Lindblom A., Valle A. D., Lopez-Kostner F., Gluck N., Katz L. H., Heinimann K., Vaccaro C. A., Buttner R., Gorgens H., Holinski-Feder E., Morak M., Holzapfel S., Huneburg R., von Knebel Doeberitz M., Loeffler M., Rahner N., Weitz J., Steinke-Lange V., ten Broeke S. W., Schmiegel W., Vangala D., Pylvanainen K., Renkonen-Sinisalo L., Hopper J. L., Win A. K., Haile R. W., Lindor N. M., Gallinger S., Le Marchand L., Newcomb P. A., Figueiredo J. C., Thibodeau S. N., Jensen L. H., Madsen M. B., Kroldrup L., Nilbert M., Moreira L., Sanchez A., Serra-Burriel M., Pineda M., Navarro M., Vidal J. B., Blanco I., Green K., Lalloo F., Crosbie E. J., Hill J., Denton O. G., Rodland E. A., Vasen H., Mints M., Neffa F., Esperon P., Alvarez K., Kariv R., Rosner G., Pinero T. A., Gonzalez M. L., Kalfayan P., Tjandra D., Winship I. M., Macrae F., Moslein G., Mecklin J. -P., Dominguez-Valentin, M., Sampson, J. R., Moller, P., Seppala, T. T., Plazzer, J. -P., Nakken, S., Engel, C., Aretz, S., Jenkins, M. A., Sunde, L., Bernstein, I., Capella, G., Balaguer, F., Thomas, H., Evans, D. G., Burn, J., Greenblatt, M., Hovig, E., Nielsen, M., de Vos tot Nederveen Cappel, W. H., Sijmons, R. H., Bertario, L., Tibiletti, M. G., Cavestro, G. M., Lindblom, A., Valle, A. D., Lopez-Kostner, F., Gluck, N., Katz, L. H., Heinimann, K., Vaccaro, C. A., Buttner, R., Gorgens, H., Holinski-Feder, E., Morak, M., Holzapfel, S., Huneburg, R., von Knebel Doeberitz, M., Loeffler, M., Rahner, N., Weitz, J., Steinke-Lange, V., ten Broeke, S. W., Schmiegel, W., Vangala, D., Pylvanainen, K., Renkonen-Sinisalo, L., Hopper, J. L., Win, A. K., Haile, R. W., Lindor, N. M., Gallinger, S., Le Marchand, L., Newcomb, P. A., Figueiredo, J. C., Thibodeau, S. N., Jensen, L. H., Madsen, M. B., Kroldrup, L., Nilbert, M., Moreira, L., Sanchez, A., Serra-Burriel, M., Pineda, M., Navarro, M., Vidal, J. B., Blanco, I., Green, K., Lalloo, F., Crosbie, E. J., Hill, J., Denton, O. G., Rodland, E. A., Vasen, H., Mints, M., Neffa, F., Esperon, P., Alvarez, K., Kariv, R., Rosner, G., Pinero, T. A., Gonzalez, M. L., Kalfayan, P., Tjandra, D., Winship, I. M., Macrae, F., Moslein, G., and Mecklin, J. -P.

Subjects
Male, Adult, Oncology, Cancer Research, 2019-20 coronavirus outbreak, medicine.medical_specialty, sarcoma, Databases, Factual, Coronavirus disease 2019 (COVID-19), Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), Sarcoma/diagnosis, 03 medical and health sciences, 0302 clinical medicine, Internal medicine, Humans, Medicine, Aged, business.industry, Sarcoma, Syndrome, Middle Aged, medicine.disease, Colorectal Neoplasms, Hereditary Nonpolyposis, Lynch syndrome, MSH2, 030220 oncology & carcinogenesis, Colorectal Neoplasms, Hereditary Nonpolyposis/diagnosis, Female, 030211 gastroenterology & hepatology, business
Published
2020

5. Computational approaches in cancer multidrug resistance research: Identification of potential biomarkers, drug targets and drug-target interactions

Author

Tolios, A. De Las Rivas, J. Hovig, E. Trouillas, P. Scorilas, A. Mohr, T.

Abstract

Like physics in the 19th century, biology and molecular biology in particular, has been fertilized and enhanced like few other scientific fields, by the incorporation of mathematical methods. In the last decades, a whole new scientific field, bioinformatics, has developed with an output of over 30,000 papers a year (Pubmed search using the keyword “bioinformatics”). Huge databases of mass throughput data have been established, with ArrayExpress alone containing more than 2.7 million assays (October 2019). Computational methods have become indispensable tools in molecular biology, particularly in one of the most challenging areas of cancer research, multidrug resistance (MDR). However, confronted with a plethora of different algorithms, approaches, and methods, the average researcher faces key questions: Which methods do exist? Which methods can be used to tackle the aims of a given study? Or, more generally, how do I use computational biology/bioinformatics to bolster my research? The current review is aimed at providing guidance to existing methods with relevance to MDR research. In particular, we provide an overview on: a) the identification of potential biomarkers using expression data; b) the prediction of treatment response by machine learning methods; c) the employment of network approaches to identify gene/protein regulatory networks and potential key players; d) the identification of drug-target interactions; e) the use of bipartite networks to identify multidrug targets; f) the identification of cellular subpopulations with the MDR phenotype; and, finally, g) the use of molecular modeling methods to guide and enhance drug discovery. This review shall serve as a guide through some of the basic concepts useful in MDR research. It shall give the reader some ideas about the possibilities in MDR research by using computational tools, and, finally, it shall provide a short overview of relevant literature. © 2019

Published
2020

6. High number of kinome‐mutations in non‐small cell lung cancer is associated with reduced immune response and poor relapse‐free survival

Author

Helland, Å., Brustugun, O. T., Nakken, S., Halvorsen, A. R., Dønnem, T., Bremnes, R., Busund, L. T., Sun, J., Lorenz, S., Solberg, S. K., Jørgensen, L. H., Vodak, D., Myklebost, O., Hovig, E., and Meza‐Zepeda, L. A.

Subjects
Adult, Male, Immunity, Cellular, Genome, Human, Phosphotransferases, Short Report, High-Throughput Nucleotide Sequencing, kinome, Tumor Immunology and Microenvironment, sequencing, Middle Aged, mutations, Prognosis, Disease-Free Survival, Neoplasm Proteins, lung cancer, Carcinoma, Non-Small-Cell Lung, Mutation, Humans, Female, Neoplasm Recurrence, Local, Protein Kinase Inhibitors, Aged
Abstract

Lung cancer is the leading cause of cancer related death, and the past years’ improved insight into underlying molecular events has significantly improved outcome for specific subsets of patients. In particular, several new therapies that target protein kinases have been implemented, and many more are becoming available. We have investigated lung cancer specimens for somatic mutations in a targeted panel of 612 human genes, the majority being protein kinases. The somatic mutation profiles were correlated to profiles of immune cell infiltration as well as relapse‐free survival. Targeted deep sequencing was performed on 117 tumour/normal pairs using the SureSelect Human Kinome kit (Agilent Technologies), with capture probes targeting 3.2 Mb of the human genome, including exons and untranslated regions of all known kinases, kinase receptors and selected cancer‐related genes (612 genes in total). CD8 staining was determined using Ventana Benchmark. Survival analyses were performed using SPSS. The number of mutations per sample ranged from 0 to 50 (within the 612 genes tested), with a median of nine. The prognosis was worse for patients with more than the median number of mutations. A significant correlation was found between mutations in one of selected DNA‐repair genes and the total number of mutations in that tumour (p, What's new? Lung carcinomas are among the tumours with highest mutation frequency. Here, the authors performed mutational analyses of 612 genes–including all known kinases and kinase receptors–in 117 non‐small cell lung cancer (NSCLC) tumours. They also investigated the relationship of mutation rate to number of infiltrating lymphocytes and to the clinical course of the disease. The number of mutations per sample varied, and the relapse‐free survival was worse for patients with more than the median number of mutations. Also, there was a significant inverse correlation between the number of infiltrating stromal CD8+ lymphocytes and the presence of EGFR mutations.

Published
2017

8. Speed-Up of DNA Melting Algorithm with Complete Nearest Neighbor Properties

Author

Tostesen, E., Liu, F., Jenssen, T. -K., and Hovig, E.

Subjects
Quantitative Biology::Biomolecules, Quantitative Biology - Biomolecules, FOS: Biological sciences, Biomolecules (q-bio.BM)
Abstract

We describe a faster and more accurate algorithm for computing the statistical mechanics of DNA denaturation according to the Poland-Scheraga type. Nearest neighbor thermodynamics is included in a complete and general way. The algorithm represents an optimization with respect to algorithmic complexity of the partition function algorithm of Yeramian et al.: We reduce the computation time for a base-pairing probability profile from O(N2) to O(N). This speed-up comes in addition to the speed-up due to a multiexponential approximation of the loop entropy factor as introduced by Fixman and Freire. The speed-up, however, is independent of the multiexponential approximation and reduces time from O(N3) to O(N2) in the exact case. In addition to calculating the standard base-pairing probability profiles, we propose to use the algorithm to calculate various other probabilities (loops, helices, tails) for a more direct view of the melting regions and their positions and sizes., 20 pages, 4 figures

Published
2004

9. Ectopic expression of target genes may represent an inherent limitation of RT-PCR assays used for micrometastasis detection: Studies on the epithelial glycoprotein gene EGP-2

Author

deGraaf, H, Maelandsmo, GM, Ruud, P, Forus, A, Oyjord, T, Fodstad, O, and Hovig, E

Subjects
REVERSE-TRANSCRIPTASE, MOLECULAR-CLONING, BONE-MARROW, BREAST-CANCER, POLYMERASE CHAIN-REACTION, PERIPHERAL-BLOOD, MONOCLONAL-ANTIBODIES, MESSENGER-RNA, CIRCULATING TUMOR-CELLS, ILLEGITIMATE TRANSCRIPTION
Abstract

Our objective was to develop and study the feasibility of a quantitative, nested reverse-transcription polymerase chain reaction (RT-PCR) assay for detection of micrometastatic, epithelial tumor cells using the epithelial glycoprotein EGP-2 gene as a target, Several carcinoma cell lines and peripheral blood samples of 10 healthy volunteers were screened for levels of EGP-2 mRNA, The assay included EGP-2, competitor molecules, carrying an internal deletion, that had been titrated by limiting dilution. Seven carcinoma cell lines showed a wide spectrum of EGP-2 mRNA expression levels, with the highest values (20-100 molecules/cell) seen in 3 breast-cancer cell lines. Unexpectedly, a consistent low level of EGP-2 mRNA expression (0.0004 molecules/cell) was observed in peripheral blood mononuclear cells, probably representing ectopic non-functional expression, Because of this background level, spiking experiments with T47D breast-carcinoma cells added to blood mononuclear cells exhibited a detection limit that was not better than approximately one tumor cell in 2 x 10(4) normal cells, Together with the considerable variation of EGP-2 transcript levels that is observed in different carcinoma cell lines, the extent of expression in normal blood cells would prevent a reliable estimation of low numbers of carcinoma cells in clinical samples. A similar situation might well apply for other target genes, This emphasizes the need for a critical evaluation of the different steps involved in the methods used for RT-PCR detection of micrometastatic tumor cells. (C) 1997 Wiley-Liss, Inc.

Published
1997

12. Database of p53 gene somatic mutations in human tumors and cell lines

Author

Hollstein, M., Rice, K., Greenblatt, M. S., thierry soussi, Fuchs, R., Sørlie, T., Hovig, E., Smith-Sørensen, B., Montesano, R., and Harris, C. C.

Subjects
Databases, Factual, Neoplasms, DNA Mutational Analysis, Mutation, Tumor Cells, Cultured, Humans, Genes, p53
Abstract

A data base is described in which over 2,500 mutations in the p53 gene of human tumors and tumor cell lines are compiled from a systematic search of reports published before 1 January 1994. Data from 1994 are being added intermittently, with a systematic search and update scheduled for December, 1994. The compilation has been deposited with the EMBL Data Library and is available in electronic form free of charge. This report contains a rationale for the compilation, a brief summary of the major findings and a description of the data base.

13. Mortality by age, gene and gender in carriers of pathogenic mismatch repair gene variants receiving surveillance for early cancer diagnosis and treatment:a report from the prospective Lynch syndrome database

Author

Mev Dominguez-Valentin, Saskia Haupt, Toni T. Seppälä, Julian R. Sampson, Lone Sunde, Inge Bernstein, Mark A. Jenkins, Christoph Engel, Stefan Aretz, Maartje Nielsen, Gabriel Capella, Francesc Balaguer, Dafydd Gareth Evans, John Burn, Elke Holinski-Feder, Lucio Bertario, Bernardo Bonanni, Annika Lindblom, Zohar Levi, Finlay Macrae, Ingrid Winship, John-Paul Plazzer, Rolf Sijmons, Luigi Laghi, Adriana Della Valle, Karl Heinimann, Tadeusz Dębniak, Robert Fruscio, Francisco Lopez-Koestner, Karin Alvarez-Valenzuela, Lior H. Katz, Ido Laish, Elez Vainer, Carlos Vaccaro, Dirce Maria Carraro, Kevin Monahan, Elizabeth Half, Aine Stakelum, Des Winter, Rory Kennelly, Nathan Gluck, Harsh Sheth, Naim Abu-Freha, Marc Greenblatt, Benedito Mauro Rossi, Mabel Bohorquez, Giulia Martina Cavestro, Leonardo S. Lino-Silva, Karoline Horisberger, Maria Grazia Tibiletti, Ivana do Nascimento, Huw Thomas, Norma Teresa Rossi, Leandro Apolinário da Silva, Attila Zaránd, Juan Ruiz-Bañobre, Vincent Heuveline, Jukka-Pekka Mecklin, Kirsi Pylvänäinen, Laura Renkonen-Sinisalo, Anna Lepistö, Päivi Peltomäki, Christina Therkildsen, Mia Gebauer Madsen, Stefan Kobbelgaard Burgdorf, John L. Hopper, Aung Ko Win, Robert W. Haile, Noralane Lindor, Steven Gallinger, Loïc Le Marchand, Polly A. Newcomb, Jane Figueiredo, Daniel D. Buchanan, Stephen N. Thibodeau, Magnus von Knebel Doeberitz, Markus Loeffler, Nils Rahner, Evelin Schröck, Verena Steinke-Lange, Wolff Schmiegel, Deepak Vangala, Claudia Perne, Robert Hüneburg, Silke Redler, Reinhard Büttner, Jürgen Weitz, Marta Pineda, Nuria Duenas, Joan Brunet Vidal, Leticia Moreira, Ariadna Sánchez, Eivind Hovig, Sigve Nakken, Kate Green, Fiona Lalloo, James Hill, Emma Crosbie, Miriam Mints, Yael Goldberg, Douglas Tjandra, Sanne W. ten Broeke, Revital Kariv, Guy Rosner, Suresh H. Advani, Lidiya Thomas, Pankaj Shah, Mithun Shah, Florencia Neffa, Patricia Esperon, Walter Pavicic, Giovana Tardin Torrezan, Thiago Bassaneze, Claudia Alejandra Martin, Gabriela Moslein, Pål Moller, Dominguez-Valentin, M, Haupt, S, Seppälä, T, Sampson, J, Sunde, L, Bernstein, I, Jenkins, M, Engel, C, Aretz, S, Nielsen, M, Capella, G, Balaguer, F, Evans, D, Burn, J, Holinski-Feder, E, Bertario, L, Bonanni, B, Lindblom, A, Levi, Z, Macrae, F, Winship, I, Plazzer, J, Sijmons, R, Laghi, L, Della Valle, A, Heinimann, K, Dębniak, T, Fruscio, R, Lopez-Koestner, F, Alvarez-Valenzuela, K, Katz, L, Laish, I, Vainer, E, Vaccaro, C, Carraro, D, Monahan, K, Half, E, Stakelum, A, Winter, D, Kennelly, R, Gluck, N, Sheth, H, Abu-Freha, N, Greenblatt, M, Rossi, B, Bohorquez, M, Cavestro, G, Lino-Silva, L, Horisberger, K, Tibiletti, M, Nascimento, I, Thomas, H, Rossi, N, Apolinário da Silva, L, Zaránd, A, Ruiz-Bañobre, J, Heuveline, V, Mecklin, J, Pylvänäinen, K, Renkonen-Sinisalo, L, Lepistö, A, Peltomäki, P, Therkildsen, C, Madsen, M, Burgdorf, S, Hopper, J, Win, A, Haile, R, Lindor, N, Gallinger, S, Le Marchand, L, Newcomb, P, Figueiredo, J, Buchanan, D, Thibodeau, S, von Knebel Doeberitz, M, Loeffler, M, Rahner, N, Schröck, E, Steinke-Lange, V, Schmiegel, W, Vangala, D, Perne, C, Hüneburg, R, Redler, S, Büttner, R, Weitz, J, Pineda, M, Duenas, N, Vidal, J, Moreira, L, Sánchez, A, Hovig, E, Nakken, S, Green, K, Lalloo, F, Hill, J, Crosbie, E, Mints, M, and Goldberg, Y

Subjects
kuolleisuus, perinnölliset taudit, Survival, MLH1, riskitekijät, General Medicine, MSH6, sukupuoli, MSH2, Cancer risk, Lynch syndrome, PMS2, syöpägeenit, syöpätaudit, Lynchin oireyhtymä, Mortality, Prospective study, ilmaantuvuus, ikä, henkiinjääminen, kohorttitutkimus
Abstract

Background: The Prospective Lynch Syndrome Database (PLSD) collates information on carriers of pathogenic or likely pathogenic MMR variants (path_MMR) who are receiving medical follow-up, including colonoscopy surveillance, which aims to the achieve early diagnosis and treatment of cancers. Here we use the most recent PLSD cohort that is larger and has wider geographical representation than previous versions, allowing us to present mortality as an outcome, and median ages at cancer diagnoses for the first time.Methods: The PLSD is a prospective observational study without a control group that was designed in 2012 and updated up to October 2022. Data for 8500 carriers of path_MMR variants from 25 countries were included, providing 71,713 years of follow up. Cumulative cancer incidences at 65 years of age were combined with 10-year crude survival following cancer, to derive estimates of mortality up to 75 years of age by organ, gene, and gender.Findings: Gynaecological cancers were more frequent than colorectal cancers in path_MSH2, path_MSH6 and path_PMS2 carriers [cumulative incidence: 53.3%, 49.6% and 23.3% at 75 years, respectively]. Endometrial, colon and ovarian cancer had low mortality [8%, 13% and 15%, respectively] and prostate cancers were frequent in male path_MSH2 carriers [cumulative incidence: 39.7% at 75 years]. Pancreatic, brain, biliary tract and ureter and kidney and urinary bladder cancers were associated with high mortality [83%, 66%, 58%, 27%, and 29%, respectively]. Among path_MMR carriers undergoing colonoscopy surveillance, particularly path_MSH2 carriers, more deaths followed non-colorectal Lynch syndrome cancers than colorectal cancers.Interpretation: In path_MMR carriers undergoing colonoscopy surveillance, non-colorectal Lynch syndrome cancers were associated with more deaths than were colorectal cancers. Reducing deaths from non-colorectal cancers presents a key challenge in contemporary medical care in Lynch syndrome. Background: The Prospective Lynch Syndrome Database (PLSD) collates information on carriers of pathogenic or likely pathogenic MMR variants (path_MMR) who are receiving medical follow-up, including colonoscopy surveillance, which aims to the achieve early diagnosis and treatment of cancers. Here we use the most recent PLSD cohort that is larger and has wider geographical representation than previous versions, allowing us to present mortality as an outcome, and median ages at cancer diagnoses for the first time. Methods: The PLSD is a prospective observational study without a control group that was designed in 2012 and updated up to October 2022. Data for 8500 carriers of path_MMR variants from 25 countries were included, providing 71,713 years of follow up. Cumulative cancer incidences at 65 years of age were combined with 10-year crude survival following cancer, to derive estimates of mortality up to 75 years of age by organ, gene, and gender. Findings: Gynaecological cancers were more frequent than colorectal cancers in path_MSH2, path_MSH6 and path_PMS2 carriers [cumulative incidence: 53.3%, 49.6% and 23.3% at 75 years, respectively]. Endometrial, colon and ovarian cancer had low mortality [8%, 13% and 15%, respectively] and prostate cancers were frequent in male path_MSH2 carriers [cumulative incidence: 39.7% at 75 years]. Pancreatic, brain, biliary tract and ureter and kidney and urinary bladder cancers were associated with high mortality [83%, 66%, 58%, 27%, and 29%, respectively]. Among path_MMR carriers undergoing colonoscopy surveillance, particularly path_MSH2 carriers, more deaths followed non-colorectal Lynch syndrome cancers than colorectal cancers. Interpretation: In path_MMR carriers undergoing colonoscopy surveillance, non-colorectal Lynch syndrome cancers were associated with more deaths than were colorectal cancers. Reducing deaths from non-colorectal cancers presents a key challenge in contemporary medical care in Lynch syndrome. Funding: We acknowledge funding from the Norwegian Cancer Society, contract 194751-2017.

Published
2023

14. No Difference in Penetrance between Truncating and Missense/Aberrant Splicing Pathogenic Variants in MLH1 and MSH2: A Prospective Lynch Syndrome Database Study

Author

Guy Rosner, Walter Hernán Pavicic, Claudia Perne, Carlos A. Vaccaro, Elke Holinski-Feder, Leticia Moreira, Wouter H. de Vos tot Nederveen Cappel, Stefan Aretz, Einar Andreas Rødland, Polly A. Newcomb, Karin Alvarez, Ariadna Sánchez, Lone Sunde, Wolff Schmiegel, Joan Brunet, Marc S. Greenblatt, Christina Therkildsen, Karl Heinimann, Lior H. Katz, Fiona Lalloo, Jürgen Weitz, Anna Lepistö, Rolf H. Sijmons, Maartje Nielsen, Hans F. A. Vasen, Deepak Vangala, Monika Morak, Jukka-Pekka Mecklin, Toni T. Seppälä, Sigve Nakken, Stefanie Holzapfel, Douglas Tjandra, Finlay A. Macrae, Päivi Peltomäki, Daniel D. Buchanan, Stephen N. Thibodeau, Adriana Della Valle, James Hill, Annika Lindblom, Bernardo Bonanni, Reinhard Büttner, Francisco López-Köstner, Giulia Martina Cavestro, John Burn, Emma J Crosbie, Lucio Bertario, Sanne W. ten Broeke, D. G. R. Evans, Kate Green, Verena Steinke-Lange, Eivind Hovig, Miquel Serra-Burriel, Francesc Balaguer, Kirsi Pylvänäinen, Gabriela Möslein, Revital Kariv, Thomas Hansen, Maria Grazia Tibiletti, Tamara Alejandra Piñero, Nils Rahner, Magnus von Knebel Doeberitz, Ingrid Winship, Nathan Gluck, Lars Joachim Lindberg, Christoph Engel, Mev Dominguez-Valentin, John-Paul Plazzer, Julian R. Sampson, Marta Pineda, John L. Hopper, Pablo Kalfayan, Heike Görgens, Aung Ko Win, Steven Gallinger, Loic Le Marchand, Mark A. Jenkins, Markus Loeffler, Noralane M. Lindor, Inge Bernstein, Pål Møller, Laura Renkonen-Sinisalo, Florencia Neffa, Huw Thomas, Gabriel Capellá, Jane C. Figueiredo, Miriam Mints, Patricia Esperon, Matilde Navarro, Robert Hüneburg, Guided Treatment in Optimal Selected Cancer Patients (GUTS), HUS Abdominal Center, Department of Surgery, Genome-Scale Biology (GSB) Research Program, II kirurgian klinikka, ATG - Applied Tumor Genomics, Research Programs Unit, Clinicum, Department of Medical and Clinical Genetics, Dominguez-Valentin, M., Plazzer, J. -P., Sampson, J. R., Engel, C., Aretz, S., Jenkins, M. A., Sunde, L., Bernstein, I., Capella, G., Balaguer, F., Macrae, F., Winship, I. M., Thomas, H., Evans, D. G., Burn, J., Greenblatt, M., de Vos tot Nederveen Cappel, W. H., Sijmons, R. H., Nielsen, M., Bertario, L., Bonanni, B., Tibiletti, M. G., Cavestro, G. M., Lindblom, A., Della Valle, A., Lopez-Kostner, F., Alvarez, K., Gluck, N., Katz, L., Heinimann, K., Vaccaro, C. A., Nakken, S., Hovig, E., Green, K., Lalloo, F., Hill, J., Vasen, H. F. A., Perne, C., Buttner, R., Gorgens, H., Holinski-Feder, E., Morak, M., Holzapfel, S., Huneburg, R., Doeberitz, M. V. K., Loeffler, M., Rahner, N., Weitz, J., Steinke-Lange, V., Schmiegel, W., Vangala, D., Crosbie, E. J., Pineda, M., Navarro, M., Brunet, J., Moreira, L., Sanchez, A., Serra-Burriel, M., Mints, M., Kariv, R., Rosner, G., Pinero, T. A., Pavicic, W. H., Kalfayan, P., Ten Broeke, S. W., Mecklin, J. -P., Pylvanainen, K., Renkonen-Sinisalo, L., Lepisto, A., Peltomaki, P., Hopper, J. L., Win, A. K., Buchanan, D. D., Lindor, N. M., Gallinger, S., Marchand, L. L., Newcomb, P. A., Figueiredo, J. C., Thibodeau, S. N., Therkildsen, C., Hansen, T. V. O., Lindberg, L., Rodland, E. A., Neffa, F., Esperon, P., Tjandra, D., Moslein, G., Seppala, T. T., and Moller, P.

Subjects
cancer incidence, 0302 clinical medicine, Malalties hereditàries, Missense mutation, 8Q23.3, Càncer, Cancer, Genetics, 0303 health sciences, medicine.diagnostic_test, Factors de risc en les malalties, MISMATCH REPAIR GENES, MLH1, General Medicine, Penetrance, Lynch syndrome, 3. Good health, syöpägeenit, 030220 oncology & carcinogenesis, Medicine, syöpätaudit, ilmaantuvuus, Genetic diseases, congenital, hereditary, and neonatal diseases and abnormalities, missense, 11Q23.1, Risk factors in diseases, CANCER-RISK, Article, aberrant splicing, 03 medical and health sciences, AGE, medicine, Genetic predisposition, ddc:610, MSH2, Lynchin oireyhtymä, penetrance, 030304 developmental biology, Genetic testing, truncating, perinnölliset taudit, business.industry, MUTATIONS, HMSH2, nutritional and metabolic diseases, medicine.disease, digestive system diseases, 3121 General medicine, internal medicine and other clinical medicine, business
Abstract

Background. Lynch syndrome is the most common genetic predisposition for hereditary cancer. Carriers of pathogenic changes in mismatch repair (MMR) genes have an increased risk of developing colorectal (CRC), endometrial, ovarian, urinary tract, prostate, and other cancers, depending on which gene is malfunctioning. In Lynch syndrome, differences in cancer incidence (penetrance) according to the gene involved have led to the stratification of cancer surveillance. By contrast, any differences in penetrance determined by the type of pathogenic variant remain unknown. Objective. To determine cumulative incidences of cancer in carriers of truncating and missense or aberrant splicing pathogenic variants of the MLH1 and MSH2 genes. Methods. Carriers of pathogenic variants of MLH1 (path_MLH1) and MSH2 (path_MSH2) genes filed in the Prospective Lynch Syndrome Database (PLSD) were categorized as truncating or missense/aberrant splicing according to the InSiGHT criteria for pathogenicity. Results. Among 5199 carriers, 1045 had missense or aberrant splicing variants, and 3930 had truncating variants. Prospective observation years for the two groups were 8205 and 34,141 years, respectively, after which there were no significant differences in incidences for cancer overall or for colorectal cancer or endometrial cancers separately. Conclusion. Truncating and missense or aberrant splicing pathogenic variants were associated with similar average cumulative incidences of cancer in carriers of path MLH1 and path_MSH2.

Published
2021

15. Uptake of hysterectomy and bilateral salpingo-oophorectomy in carriers of pathogenic mismatch repair variants:a Prospective Lynch Syndrome Database report

Author

Einar Andreas Rødland, Joan B. Vida, Heike Görgens, Eivind Hovig, Kirsi Pylvänäinen, Monika Morak, Wouter H. de Vos tot Nederveen Cappel, Lone Sunde, Mark A. Jenkins, Lucio Bertario, Patricia Esperon, Reinhard Büttner, Finlay A. Macrae, Inge Bernstein, Marc S. Greenblatt, Wolff Schmiegel, Giulia Martina Cavestro, Maria Grazia Tibiletti, Silke Redler, Zohreh Ketabi, Karl Heinimann, Fiona Lalloo, Huw Thomas, Christina Therkildsen, Deepak Vangala, Magnus von Knebel Doeberitz, Matilde Navarro, Erik Rokkones, Douglas Tjandra, D. G. Evans, Marta Pineda, Marian J.E. Mourits, Lior H. Katz, Bernardo Bonanni, Pablo Kalfayan, Stephen N. Thibodeau, Loic Le Marchand, Revital Kariv, Maartje Nielsen, Emma J Crosbie, Oliver G. Denton, Stefanie Holzapfel, Guy Rosner, Mev Dominguez-Valentin, John Burn, Verena Steinke-Lange, Carlos A. Vaccaro, Gabriela Möslein, Elke Holinski-Feder, Gabriel Capellá, Johanna Tecklenburg, Karin Wadt, Kate Green, Christoph Engel, Miriam Mints, Anna Lepistö, Tamara Alejandra Piñero, Jukka-Pekka Mecklin, John L. Hopper, Robert Hüneburg, Markus Loeffler, Florencia Neffa, Toni T. Seppälä, Claudia Perne, Polly A. Newcomb, Karin Alvarez, Adriana Della Valle, Julian R. Sampson, Sanne W. ten Broeke, Francisco Lopez-Koestner, John-Paul Plazzer, James Hill, Hans Georg Strauß, Ingrid Winship, Nathan Gluck, Aung Ko Win, Jane C. Figueiredo, Jürgen Weitz, Hans F. A. Vasen, Rolf H. Sijmons, Walter Hernán Pavicic, Stefan Aretz, Steven Gallinger, Noralane M. Lindor, Pål Møller, Laura Renkonen-Sinisalo, Guided Treatment in Optimal Selected Cancer Patients (GUTS), Damage and Repair in Cancer Development and Cancer Treatment (DARE), Targeted Gynaecologic Oncology (TARGON), Seppala, T. T., Dominguez-Valentin, M., Crosbie, E. J., Engel, C., Aretz, S., Macrae, F., Winship, I., Capella, G., Thomas, H., Hovig, E., Nielsen, M., Sijmons, R. H., Bertario, L., Bonanni, B., Tibiletti, M. G., Cavestro, G. M., Mints, M., Gluck, N., Katz, L., Heinimann, K., Vaccaro, C. A., Green, K., Lalloo, F., Hill, J., Schmiegel, W., Vangala, D., Perne, C., Strauss, H. -G., Tecklenburg, J., Holinski-Feder, E., Steinke-Lange, V., Mecklin, J. -P., Plazzer, J. -P., Pineda, M., Navarro, M., Vida, J. B., Kariv, R., Rosner, G., Pinero, T. A., Pavicic, W., Kalfayan, P., ten Broeke, S. W., Jenkins, M. A., Sunde, L., Bernstein, I., Burn, J., Greenblatt, M., de Vos tot Nederveen Cappel, W. H., Della Valle, A., Lopez-Koestner, F., Alvarez, K., Buttner, R., Gorgens, H., Morak, M., Holzapfel, S., Huneburg, R., von Knebel Doeberitz, M., Loeffler, M., Redler, S., Weitz, J., Pylvanainen, K., Renkonen-Sinisalo, L., Lepisto, A., Hopper, J. L., Win, A. K., Lindor, N. M., Gallinger, S., Le Marchand, L., Newcomb, P. A., Figueiredo, J. C., Thibodeau, S. N., Therkildsen, C., Wadt, K. A. W., Mourits, M. J. E., Ketabi, Z., Denton, O. G., Rodland, E. A., Vasen, H., Neffa, F., Esperon, P., Tjandra, D., Moslein, G., Rokkones, E., Sampson, J. R., Evans, D. G., Moller, P., Genome-Scale Biology (GSB) Research Program, HUS Abdominal Center, Clinicum, II kirurgian klinikka, Department of Surgery, and Doctoral Programme in Clinical Research

Subjects
0301 basic medicine, Cancer Research, Oophorectomy, Databases, Factual, Colorectal cancer, SURGERY, medicine.medical_treatment, Càncer d'ovari, computer.software_genre, DNA Mismatch Repair, 0302 clinical medicine, Endometrial cancer, munasarjasyöpä, Medicine, Prospective Studies, Colectomy, Salpingo-oophorectomy/methods, Database, Manchester Cancer Research Centre, COLON-CANCER, MLH1, WOMEN, Middle Aged, Prognosis, Lynch syndrome, 3. Good health, kohdunrungon syöpä, Oncology, COLECTOMY, 030220 oncology & carcinogenesis, Female, Biomarkers, Tumor/genetics, Adult, Heterozygote, Genital Neoplasms, Female, Salpingo-oophorectomy, Hysterectomy, 03 medical and health sciences, Genital Neoplasms, Female/prevention & control, Ovarian cancer, Colorectal Neoplasms, Hereditary Nonpolyposis/genetics, Biomarkers, Tumor, Mortalitat, Humans, Hysterectomy/methods, Mortality, Lynchin oireyhtymä, Risk-reducing surgery, Aged, business.industry, ResearchInstitutes_Networks_Beacons/mcrc, Cancer, MSH6, 3126 Surgery, anesthesiology, intensive care, radiology, medicine.disease, Colorectal Neoplasms, Hereditary Nonpolyposis, MSH2, 030104 developmental biology, Cross-Sectional Studies, PMS2, Càncer d'endometri, Mutation, kohdunpoisto, business, computer, Follow-Up Studies
Abstract

Purpose: This study aimed to report the uptake of hysterectomy and/or bilateral salpingo-oophorectomy (BSO) to prevent gynaecological cancers (risk-reducing surgery [RRS]) in carriers of pathogenic MMR (path_MMR) variants.Methods: The Prospective Lynch Syndrome Database (PLSD) was used to investigate RRS by a cross-sectional study in 2292 female path_MMR carriers aged 30-69 years.Results: Overall, 144, 79, and 517 carriers underwent risk-reducing hysterectomy, BSO, or both combined, respectively. Two-thirds of procedures before 50 years of age were combined hysterectomy and BSO, and 81% of all procedures included BSO. Risk-reducing hysterectomy was performed before age 50 years in 28%, 25%, 15%, and 9%, and BSO in 26%, 25%, 14% and 13% of path_MLH1, path_MSH2, path_MSH6, and path_PMS2 carriers, respectively. Before 50 years of age, 107 of 188 (57%) BSO and 126 of 204 (62%) hysterectomies were performed in women without any prior cancer, and only 5% (20/392) were performed simultaneously with colorectal cancer (CRC) surgery.Conclusion: Uptake of RRS before 50 years of age was low, and RRS was rarely undertaken in association with surgical treatment of CRC. Uptake of RRS aligned poorly with gene-and age-associated risk estimates for endometrial or ovarian cancer that were published recently from PLSD and did not correspond well with current clinical guidelines. The reasons should be clarified. Decision-making on opting for or against RRS and its timing should be better aligned with predicted risk and mortality for endometrial and ovarian cancer in Lynch syn-drome to improve outcomes. (C) 2021 The Author(s). Published by Elsevier Ltd.

Published
2021

16. Risk-reducing hysterectomy and bilateral salpingo-oophorectomy in female heterozygotes of pathogenic mismatch repair variants: a Prospective Lynch Syndrome Database report

Author

Eivind Hovig, Bernardo Bonanni, Monika Morak, Mark A. Jenkins, Patricia Esperon, Toni T. Seppälä, Lone Sunde, Pablo Kalfayan, Gabriel Capellá, Inge Bernstein, Matilde Navarro, Marc S. Greenblatt, John Burn, Zohreh Ketabi, Johanna Tecklenburg, Francisco Lopez-Koestner, Miriam Mints, Heike Görgens, Neil A J Ryan, Kate Green, Annika Auranen, Douglas Tjandra, Robert W. Haile, Marta Pineda, Tamara Alejandra Piñero, Stefan Aretz, Robert Hüneburg, Verena Steinke-Lange, Markus Loeffler, Christina Therkildsen, John L. Hopper, Deepak Vangala, Huw Thomas, Reinhard Büttner, James Hill, Einar Andreas Rødland, Revital Kariv, Maria Grazia Tibiletti, Sigve Nakken, Stefanie Holzapfel, D. Gareth Evans, Oliver G. Denton, Julian R. Sampson, Henrik Okkels, Joan Vidal, Loic Le Marchand, Hans Georg Strauß, Gabriela Möslein, Claudia Perne, Ingrid Winship, Nathan Gluck, Jane C. Figueiredo, Mev Dominguez-Valentin, Wolff Schmiegel, Karl Heinimann, Kirsi Pylvänäinen, Karin Alvarez, Maartje Nielsen, Wouter H. de Vos tot Nederveen Cappel, Fiona Lalloo, Aung Ko Win, Guy Rosner, Carlos A. Vaccaro, Polly A. Newcomb, Elke Holinski-Feder, John-Paul Plazzer, Lior H. Katz, Christoph Engel, Anna Lepistö, Jukka-Pekka Mecklin, Giulia Martina Cavestro, Adriana Della Valle, Finlay A. Macrae, Sanne W. ten Broeke, Florencia Neffa, Rolf H. Sijmons, María Laura Gonzalez, Nils Rahner, Jürgen Weitz, Hans F. A. Vasen, Stephen N. Thibodeau, Emma J Crosbie, Lucio Bertario, Steven Gallinger, Noralane M. Lindor, Pål Møller, Laura Renkonen-Sinisalo, Magnus von Knebel Doeberitz, Dominguez-Valentin, M., Crosbie, E. J., Engel, C., Aretz, S., Macrae, F., Winship, I., Capella, G., Thomas, H., Nakken, S., Hovig, E., Nielsen, M., Sijmons, R. H., Bertario, L., Bonanni, B., Tibiletti, M. G., Cavestro, G. M., Mints, M., Gluck, N., Katz, L., Heinimann, K., Vaccaro, C. A., Green, K., Lalloo, F., Hill, J., Schmiegel, W., Vangala, D., Perne, C., Strauss, H. -G., Tecklenburg, J., Holinski-Feder, E., Steinke-Lange, V., Mecklin, J. -P., Plazzer, J. -P., Pineda, M., Navarro, M., Vidal, J. B., Kariv, R., Rosner, G., Pinero, T. A., Gonzalez, M. L., Kalfayan, P., Ryan, N., ten Broeke, S. W., Jenkins, M. A., Sunde, L., Bernstein, I., Burn, J., Greenblatt, M., de Vos tot Nederveen Cappel, W. H., Della Valle, A., Lopez-Koestner, F., Alvarez, K., Buttner, R., Gorgens, H., Morak, M., Holzapfel, S., Huneburg, R., von Knebel Doeberitz, M., Loeffler, M., Rahner, N., Weitz, J., Pylvanainen, K., Renkonen-Sinisalo, L., Lepisto, A., Auranen, A., Hopper, J. L., Win, A. K., Haile, R. W., Lindor, N. M., Gallinger, S., Le Marchand, L., Newcomb, P. A., Figueiredo, J. C., Thibodeau, S. N., Therkildsen, C., Okkels, H., Ketabi, Z., Denton, O. G., Rodland, E. A., Vasen, H., Neffa, F., Esperon, P., Tjandra, D., Moslein, G., Sampson, J. R., Evans, D. G., Seppala, T. T., Moller, P., ATG - Applied Tumor Genomics, HUS Abdominal Center, II kirurgian klinikka, Department of Surgery, Clinicum, Helsinki University Hospital Area, and University of Helsinki

Subjects
0301 basic medicine, medicine.medical_treatment, DNA Mismatch Repair, Gynecologic surgery, 0302 clinical medicine, Malalties hereditàries, Prospective Studies, Prospective cohort study, Genetics (clinical), Mismatch Repair Endonuclease PMS2, Incidence (epidemiology), Middle Aged, 16. Peace & justice, Lynch syndrome, 3. Good health, 030220 oncology & carcinogenesis, Female, syöpätaudit, MutL Protein Homolog 1, Genetic diseases, Heterozygote, medicine.medical_specialty, Salpingo-oophorectomy, Cirurgia ginecològica, Hysterectomy, Article, 03 medical and health sciences, Càncer colorectal, CAPP2, medicine, Humans, Lynchin oireyhtymä, Gynecology, perinnölliset taudit, HEREDITARY COLORECTAL-CANCER, business.industry, Endometrial cancer, Cancer, medicine.disease, Colorectal Neoplasms, Hereditary Nonpolyposis, Colorectal cancer, ASPIRIN, 030104 developmental biology, Clinical research, 3121 General medicine, internal medicine and other clinical medicine, kohdunpoisto, 3111 Biomedicine, Ovarian cancer, business
Abstract

Purpose To determine impact of risk-reducing hysterectomy and bilateral salpingo-oophorectomy (BSO) on gynecological cancer incidence and death in heterozygotes of pathogenic MMR ( path_MMR ) variants. Methods The Prospective Lynch Syndrome Database was used to investigate the effects of gynecological risk-reducing surgery (RRS) at different ages. Results Risk-reducing hysterectomy at 25 years of age prevents endometrial cancer before 50 years in 15%, 18%, 13%, and 0% of path_MLH1 , path_MSH2 , path_MSH6 , and path_PMS2 heterozygotes and death in 2%, 2%, 1%, and 0%, respectively. Risk-reducing BSO at 25 years of age prevents ovarian cancer before 50 years in 6%, 11%, 2%, and 0% and death in 1%, 2%, 0%, and 0%, respectively. Risk-reducing hysterectomy at 40 years prevents endometrial cancer by 50 years in 13%, 16%, 11%, and 0% and death in 1%, 2%, 1%, and 0%, respectively. BSO at 40 years prevents ovarian cancer before 50 years in 4%, 8%, 0%, and 0%, and death in 1%, 1%, 0%, and 0%, respectively. Conclusion Little benefit is gained by performing RRS before 40 years of age and premenopausal BSO in path_MSH6 and path_PMS2 heterozygotes has no measurable benefit for mortality. These findings may aid decision making for women with LS who are considering RRS.

Published
2021

17. Correction:Cancer risks by gene, age, and gender in 6350 carriers of pathogenic mismatch repair variants: findings from the Prospective Lynch Syndrome Database

Author

Gabriel Capellá, Patricia Esperon, Christoph Engel, Rolf H. Sijmons, María Laura Gonzalez, Matilde Navarro, Francisco López-Köstner, Julian R. Sampson, Miquel Serra-Burriel, Karin Alvarez, Ingrid Winship, Nathan Gluck, Lone Sunde, Reinhard Büttner, Giulia Martina Cavestro, Wouter H. de Vos tot Nederveen Cappel, Jukka-Pekka Mecklin, Marc S. Greenblatt, Kate Green, Robert Hüneburg, Markus Loeffler, Maria Grazia Tibiletti, Tamara Alejandra Piñero, Florencia Neffa, Lucio Bertario, Ariadna Sánchez, Verena Steinke-Lange, Christina Therkildsen, Jane C. Figueiredo, Douglas Tjandra, Magnus von Knebel Doeberitz, Lior H. Katz, Steven Gallinger, Noralane M. Lindor, Gabriela Möslein, Adriana Della Valle, John L. Hopper, Einar Andreas Rødland, Miriam Mints, Annika Lindblom, Ian M. Frayling, Polly A. Newcomb, Pål Møller, Sanne W. ten Broeke, Laura Renkonen-Sinisalo, Sigve Nakken, Stefanie Holzapfel, Finlay A. Macrae, Stefan Aretz, Nils Rahner, Karin Wadt, Robert W. Haile, Francesc Balaguer, Revital Kariv, Stephen N. Thibodeau, Huw D. Thomas, Emma J Crosbie, Deepak Vangala, Monika Morak, Ignacio Blanco, Hans K. Schackert, Henrik Okkels, Mev Dominguez-Valentin, Oliver G. Denton, John-Paul Plazzer, Zohreh Ketabi, James Hill, Loic Le Marchand, Mark A. Jenkins, Inge Bernstein, D. Gareth Evans, Heike Görgens, Marta Pineda, John Burn, Kirsi Pylvänäinen, Eivind Hovig, Hans F. A. Vasen, Pablo Kalfayan, Toni T. Seppälä, Aung Ko Win, Maartje Nielsen, Wolff Schmiegel, Guy Rosner, Karl Heinimann, Fiona Lalloo, Carlos A. Vaccaro, Elke Holinski-Feder, Leticia Moreira, HUS Abdominal Center, Clinicum, II kirurgian klinikka, University of Helsinki, Department of Surgery, ATG - Applied Tumor Genomics, Research Programs Unit, Dominguez-Valentin, M., Sampson, J. R., Seppala, T. T., ten Broeke, S. W., Plazzer, J. -P., Nakken, S., Engel, C., Aretz, S., Jenkins, M. A., Sunde, L., Bernstein, I., Capella, G., Balaguer, F., Thomas, H., Evans, D. G., Burn, J., Greenblatt, M., Hovig, E., de Vos tot Nederveen Cappel, W. H., Sijmons, R. H., Bertario, L., Tibiletti, M. G., Cavestro, G. M., Lindblom, A., Della Valle, A., Lopez-Kostner, F., Gluck, N., Katz, L. H., Heinimann, K., Vaccaro, C. A., Buttner, R., Gorgens, H., Holinski-Feder, E., Morak, M., Holzapfel, S., Huneburg, R., Knebel Doeberitz, M., Loeffler, M., Rahner, N., Schackert, H. K., Steinke-Lange, V., Schmiegel, W., Vangala, D., Pylvanainen, K., Renkonen-Sinisalo, L., Hopper, J. L., Win, A. K., Haile, R. W., Lindor, N. M., Gallinger, S., Le Marchand, L., Newcomb, P. A., Figueiredo, J. C., Thibodeau, S. N., Wadt, K., Therkildsen, C., Okkels, H., Ketabi, Z., Moreira, L., Sanchez, A., Serra-Burriel, M., Pineda, M., Navarro, M., Blanco, I., Green, K., Lalloo, F., Crosbie, E. J., Hill, J., Denton, O. G., Frayling, I. M., Rodland, E. A., Vasen, H., Mints, M., Neffa, F., Esperon, P., Alvarez, K., Kariv, R., Rosner, G., Pinero, T. A., Gonzalez, M. L., Kalfayan, P., Tjandra, D., Winship, I. M., Macrae, F., Moslein, G., Mecklin, J. -P., Nielsen, M., Moller, P., and Guided Treatment in Optimal Selected Cancer Patients (GUTS)

Subjects
Oncology, Male, Colorectal cancer, Lynch syndrome, Penetrance, DNA Mismatch Repair, 0302 clinical medicine, Databases, Genetic, Malalties hereditàries, Prospective Studies, Càncer, PMS2, Genetics (clinical), Mismatch Repair Endonuclease PMS2, Cancer, 0303 health sciences, Sex Characteristics, Factors de risc en les malalties, 1184 Genetics, developmental biology, physiology, MLH1, Middle Aged, 16. Peace & justice, 3. Good health, DNA-Binding Proteins, MutS Homolog 2 Protein, syöpägeenit, MSH2, 030220 oncology & carcinogenesis, MSH6, 030211 gastroenterology & hepatology, DNA mismatch repair, Female, geneettiset tekijät, MutL Protein Homolog 1, Genetic diseases, Adult, medicine.medical_specialty, congenital, hereditary, and neonatal diseases and abnormalities, Risk factors in diseases, suolistosyövät, MUTATION CARRIERS, Risk Assessment, Article, sukupuoli, Age and gender, 03 medical and health sciences, Internal medicine, medicine, Humans, Genetic Predisposition to Disease, Lynchin oireyhtymä, Gene, 030304 developmental biology, Aged, business.industry, Endometrial cancer, Correction, nutritional and metabolic diseases, medicine.disease, Colorectal Neoplasms, Hereditary Nonpolyposis, Survival Analysis, digestive system diseases, Mutation, 3111 Biomedicine, ikä, business, Ovarian cancer
Abstract

Lynch syndrome (LS) results from pathogenic variants in the mismatch repair (MMR) genes and is the most common hereditary cancer syndrome, affecting an estimated 1 in 300 individuals. Pathogenic variants in each of the MMR genes path_MLH1, path_MSH2, path_MSH6, and path_PMS2 result in different risks for cancers in organs including the colorectum, endometrium, ovaries, stomach, small bowel, bile duct, pancreas, and upper urinary tract. Accurate estimates of these risks are essential for planning appropriate approaches to the prevention or early diagnosis of cancers but the robustness of previous studies has been limited by factors including retrospective design,1,2 lack of validation in independent cohorts,3-5 and inconsistent classification of genetic variants. Unexpected findings from previous studies have included path_MLH1 and path_MSH2 carriers appearing to have a lifetime risk of colorectal cancer (CRC) of approximately 50%, despite surveillance colonoscopy,6-8 and that shorter intervals between colonoscopies do not seem to reduce the incidence of CRC in LS.9,10 These findings challenge the assumptions that CRC in LS usually develops from a noninfiltrative adenoma precursor and that CRC can be prevented by colonoscopic detection and removal of adenomas in the colon and rectum. Additionally, previous studies in the Prospective Lynch Syndrome Database (PLSD) have shown no increase in cancer risk in path_PMS2 carriers before 40 years of age and, although observation years were limited in older path_PMS2 carriers, LS-associated cancers other than endometrial and prostate were not observed.6-8 In this study we collected prospective data from a new large cohort of path_MMR carriers to validate previous findings from PLSD. We also updated information on the original cohort to ensure consistent classification of pathogenicity of MMR gene variants. We then combined both data sets, providing larger numbers that allowed us to derive more precise risk estimates for cancers in LS categorized by gene and gender.

Published
2020

18. Immunological network signatures of cancer progression and survival

Author

Trevor Clancy1, Marco Pedicini2, Filippo Castiglione2, Daniele Santoni2, Vegard Nygaard1, Timothy J Lavelle1, Mikael Benson3, Eivind Hovig4, 1, 5, Clancy, T, Pedicini, Marco, Castiglione, Filippo, Santoni, Daniele, Nygaard, V, LAVELLE T., J, Benson, M, and Hovig, E.

Subjects
lcsh:Internal medicine, lcsh:QH426-470, animal diseases, chemical and pharmacologic phenomena, Biology, Bioinformatics, Interactome, 03 medical and health sciences, 0302 clinical medicine, Immune system, Human interactome, Immunity, Neoplasms, Genetics, Humans, Genetics(clinical), lcsh:RC31-1245, Melanoma, Genetics (clinical), 030304 developmental biology, 0303 health sciences, Tumor microenvironment, Gene Expression Profiling, Computational Biology, biochemical phenomena, metabolism, and nutrition, Acquired immune system, Prognosis, Human genetics, 3. Good health, Gene expression profiling, Survival Rate, Benchmarking, lcsh:Genetics, Organ Specificity, 030220 oncology & carcinogenesis, Immune System, Disease Progression, bacteria, Genes, Neoplasm, Research Article
Abstract

Background The immune contribution to cancer progression is complex and difficult to characterize. For example in tumors, immune gene expression is detected from the combination of normal, tumor and immune cells in the tumor microenvironment. Profiling the immune component of tumors may facilitate the characterization of the poorly understood roles immunity plays in cancer progression. However, the current approaches to analyze the immune component of a tumor rely on incomplete identification of immune factors. Methods To facilitate a more comprehensive approach, we created a ranked immunological relevance score for all human genes, developed using a novel strategy that combines text mining and information theory. We used this score to assign an immunological grade to gene expression profiles, and thereby quantify the immunological component of tumors. This immunological relevance score was benchmarked against existing manually curated immune resources as well as high-throughput studies. To further characterize immunological relevance for genes, the relevance score was charted against both the human interactome and cancer information, forming an expanded interactome landscape of tumor immunity. We applied this approach to expression profiles in melanomas, thus identifying and grading their immunological components, followed by identification of their associated protein interactions. Results The power of this strategy was demonstrated by the observation of early activation of the adaptive immune response and the diversity of the immune component during melanoma progression. Furthermore, the genome-wide immunological relevance score classified melanoma patient groups, whose immunological grade correlated with clinical features, such as immune phenotypes and survival. Conclusions The assignment of a ranked immunological relevance score to all human genes extends the content of existing immune gene resources and enriches our understanding of immune involvement in complex biological networks. The application of this approach to tumor immunity represents an automated systems strategy that quantifies the immunological component in complex disease. In so doing, it stratifies patients according to their immune profiles, which may lead to effective computational prognostic and clinical guides.

Published
2011

19. Combining Network Modeling and Gene Expression Microarray Analysis to Explore the Dynamics of Th1 and Th2 Cell Regulation

Author

Filippo Castiglione, Daniele Santoni, Eivind Hovig, Mikael Benson, Trevor Clancy, Kartiek Kanduri, Fredrik Barrenäs, Marco Pedicini, Pedicini, Marco, Barrenäs, F, Clancy, T, Castiglione, F, Hovig, E, Kanduri, K, Santoni, D, and Benson, M.

Subjects
In silico, Gene regulatory network, Biology, Transcriptome, Gene Knockout Techniques, 03 medical and health sciences, Cellular and Molecular Neuroscience, Th2 Cells, Databases, Genetic, Genetics, Humans, Computer Simulation, Gene Regulatory Networks, lcsh:QH301-705.5, Molecular Biology, Gene, Ecology, Evolution, Behavior and Systematics, Gene knockout, Oligonucleotide Array Sequence Analysis, 030304 developmental biology, 0303 health sciences, Computational Biology/Systems Biology, Ecology, Gene Expression Profiling, 030302 biochemistry & molecular biology, Computational Biology, Th1 Cells, Phenotype, Gene expression profiling, lcsh:Biology (General), Computational Theory and Mathematics, Modeling and Simulation, Immunology/Genetics of the Immune System, Mathematics, Algorithms, Research Article
Abstract

Two T helper (Th) cell subsets, namely Th1 and Th2 cells, play an important role in inflammatory diseases. The two subsets are thought to counter-regulate each other, and alterations in their balance result in different diseases. This paradigm has been challenged by recent clinical and experimental data. Because of the large number of genes involved in regulating Th1 and Th2 cells, assessment of this paradigm by modeling or experiments is difficult. Novel algorithms based on formal methods now permit the analysis of large gene regulatory networks. By combining these algorithms with in silico knockouts and gene expression microarray data from human T cells, we examined if the results were compatible with a counter-regulatory role of Th1 and Th2 cells. We constructed a directed network model of genes regulating Th1 and Th2 cells through text mining and manual curation. We identified four attractors in the network, three of which included genes that corresponded to Th0, Th1 and Th2 cells. The fourth attractor contained a mixture of Th1 and Th2 genes. We found that neither in silico knockouts of the Th1 and Th2 attractor genes nor gene expression microarray data from patients with immunological disorders and healthy subjects supported a counter-regulatory role of Th1 and Th2 cells. By combining network modeling with transcriptomic data analysis and in silico knockouts, we have devised a practical way to help unravel complex regulatory network topology and to increase our understanding of how network actions may differ in health and disease., Author Summary Different T helper (Th) cell subsets have an important role in regulating the immune response in inflammatory diseases. Th1 and Th2 cells are thought to counter-regulate each other, and alterations in their balance result in different diseases.This paradigm has been challenged by recent clinical and experimental data. Because of the large number of genes involved in regulating Th1 and Th2 cells, assessment of this paradigm by experiments or modelling is difficult. In this study, we combined novel algorithms for network analysis, in silico knockouts, and gene expression microarrays to examine if Th1 and Th2 cells had counter-regulatory roles. We constructed a directed network model of genes that regulated Th1 and Th2 cells through text mining and manual curation. We identified four cycles in the gene expression dynamics, three of which expressed genes that corresponded to Th0 (Th1/Th2 precursor), Th1 and Th2 cells. The fourth cycle contained the expression of a mixture of Th1 and Th2 genes. We found that neither in silico knockouts of the Th1 and Th2 attractor genes nor gene expression microarray data from patients and healthy subjects supported a counter-regulatory role of Th1 and Th2 cells.

Published
2010
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