دورية أكاديمية
Patient-specific cancer genes contribute to recurrently perturbed pathways and establish therapeutic vulnerabilities in esophageal adenocarcinoma
| العنوان: | Patient-specific cancer genes contribute to recurrently perturbed pathways and establish therapeutic vulnerabilities in esophageal adenocarcinoma |
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| المؤلفون: | Mourikis, TP, Benedetti, L, Foxall, E, Temelkovski, D, Nulsen, J, Perner, J, Cereda, M, Lagergren, J, Howell, M, Yau, C, Fitzgerald, RC, Scaffidi, P, Noorani, A, Edwards, PAW, Elliott, RF, Grehan, N, Nutzinger, B, Hughes, C, Fidziukiewicz, E, Bornschein, J, MacRae, S, Crawte, J, Northrop, A, Contino, G, Li, X, De la Rue, R, Katz-Summercorn, A, Abbas, S, Loureda, D, O'Donovan, M, Miremadi, A, Malhotra, S, Tripathi, M, Tavare, S, Lynch, AG, Eldridge, M, Secrier, M, Bower, L, Devonshire, G, Jammula, S, Davies, J, Crichton, C, Carroll, N, Safranek, P, Hindmarsh, A, Sujendran, V, Hayes, SJ, Ang, Y, Sharrocks, A, Preston, SR, Oakes, S, Bagwan, I, Save, V, Skipworth, RJE, Hupp, TR, O'Neill, JR, Tucker, O, Beggs, A, Taniere, P, Puig, S, Underwood, TJ, Walker, RC, Grace, BL, Barr, H, Shepherd, N, Old, O, Gossage, J, Davies, A, Chang, F, Zylstra, J, Mahadeva, U, Goh, V, Sanders, G, Berrisford, R, Harden, C, Lewis, M, Cheong, E, Kumar, B, Parsons, SL, Soomro, I, Kaye, P, Saunders, J, Lovat, L, Haidry, R, Igali, L, Scott, M, Sothi, S, Suortamo, S, Lishman, S, Hanna, GB, Peters, CJ, Moorthy, K, Grabowska, A, Turkington, R, McManus, D, Khoo, D, Fickling, W, Ciccarelli, FD |
| المصدر: | 17 ; 1 |
| بيانات النشر: | Nature Research (part of Springer Nature) |
| سنة النشر: | 2019 |
| المجموعة: | Imperial College London: Spiral |
| مصطلحات موضوعية: | Science & Technology, Multidisciplinary Sciences, Science & Technology - Other Topics, BARRETTS-ESOPHAGUS, PROTEIN, EXPRESSION, DATABASE, REPLICATION, SELECTION, GERMLINE, VARIANTS, PATTERNS, UPDATE, Oesophageal Cancer Clinical and Molecular Stratification (OCCAMS) Consortium, MD Multidisciplinary |
| الوصف: | The identification of cancer-promoting genetic alterations is challenging particularly in highly unstable and heterogeneous cancers, such as esophageal adenocarcinoma (EAC). Here we describe a machine learning algorithm to identify cancer genes in individual patients considering all types of damaging alterations simultaneously. Analysing 261 EACs from the OCCAMS Consortium, we discover helper genes that, alongside well-known drivers, promote cancer. We confirm the robustness of our approach in 107 additional EACs. Unlike recurrent alterations of known drivers, these cancer helper genes are rare or patient-specific. However, they converge towards perturbations of well-known cancer processes. Recurrence of the same process perturbations, rather than individual genes, divides EACs into six clusters differing in their molecular and clinical features. Experimentally mimicking the alterations of predicted helper genes in cancer and pre-cancer cells validates their contribution to disease progression, while reverting their alterations reveals EAC acquired dependencies that can be exploited in therapy. |
| نوع الوثيقة: | article in journal/newspaper |
| اللغة: | English |
| تدمد: | 2041-1723 |
| العلاقة: | Nature Communications; http://hdl.handle.net/10044/1/72482Test; https://doi.org/10.1038/s41467-019-10898-3Test |
| DOI: | 10.1038/s41467-019-10898-3 |
| الإتاحة: | https://doi.org/10.1038/s41467-019-10898-3Test http://hdl.handle.net/10044/1/72482Test |
| حقوق: | © Crown 2019. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0Test/. |
| رقم الانضمام: | edsbas.20671115 |
| قاعدة البيانات: | BASE |
Full Text Finder | تدمد: | 20411723 |
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| DOI: | 10.1038/s41467-019-10898-3 |