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A tumour-derived organoid biobank maps cancer gene dependencies

Research Medical/Healthcare AI

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TL;DR - A Nature study presents a clinically annotated, multi-omic tumour-derived organoid biobank spanning 256 patients and five cancers. It maps cancer gene dependencies to support mechanistic research and precision oncology.

  • Organoids are paired with matched tumour samples and clinical annotations.
  • The resource identifies cancer subtype-specific genetic vulnerabilities.
  • It captures treatment-driven changes in gene dependencies.
  • The biobank expands experimental models for studying and targeting cancer.

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A tumour-derived organoid biobank maps cancer gene dependencies

Nature C. Herranz-Ors, S. G. Bhosle, A. E. Beck, J. G. R. Gilbert, G. Picco, J. Espejo Valle-Inclan, F. Muyas, S. Valentini, A. E. Andres, R. Ansari, S. Barthorpe, G. Battarbee, C. M. Beaver, S. Brocklesby, J. Cantwell, C. A. Collins, J. Davis, H. G. Dimitrova, J. Doran, E. Efendi, K. Evans, M. Fekry, T. A. Fowler, M. Garcia-Casado, J. A. T. Griffiths, C. Hall, R. Hamer, C. Hardy, Z. Hewitson, E. Hitch, L. Holland, D. A. Jackson, N. Joshi, A. Kavasakali, L. Letchford, H. B. Lightfoot, H. Lingala, I. Mali, K. May, T. Mironenko, J. Morris, C. Pacini, S. Price, G. Robert-Tissot, H. A. Rogers, J. V. Smith, K. Smith, E. Souster, W. J. Spence, F. Thomas, S. F. Vieira, S. Walker, G. Alfonsin, H. Bermingham, H. Coles, D. P. Ennis, A. Freeman, G. Giannone, N. Grehan, E. A. Griffiths, J. Hall, S. L. Lee, E. Y. L. Leung, C. Loreno, C. Millington, A. Mirnezami, B. Nutzinger, K. Orzechowska, C. M. A. Pinna, A. M. Redmond, K. Roberts, S. Roy, D. A. Sanders, P. Taniere, M. Vias, K. Wanigasooriya, P. A. W. Edwards, S. Abbas, E. C. Smyth, M. O’Donovan, A. Miremadi, S. Malhotra, M. Tripathi, C. Cheah, M. Eldridge, M. Secrier, G. Devonshire, S. Jammula, J. Davies, C. Crichton, N. Carroll, R. H. Hardwick, P. Safranek, A. Hindmarsh, V. Sujendran, S. J. Hayes, Y. Ang, A. Sharrocks, S. R. Preston, I. Bagwan, V. Save, R. J. E. Skipworth, J. R. O’Neill, O. Tucker, A. Beggs, S. Puig, G. Contino, B. L. Grace, J. Lagergren, J. Gossage, A. Davies, F. Chang, U. Mahadeva, V. Goh, F. D. Ciccarelli, G. Sanders, D. Chan, E. Cheong, B. Kumar, L. Sreedharan, S. L. Parsons, I. Soomro, P. Kaye, J. Saunders, L. Lovat, R. Haidry, M. Scott, S. Sothi, G. B. Hanna, C. J. Peters, K. Moorthy, A. Grabowska, R. Turkington, D. McManus, H. Coleman, R. D. Petty, F. Bartlett, T. D. L. Crosby, M. R. Stratton, L. M. Staudt, U. McDermott, J. D. Brenton, I. A. McNeish, A. Biankin, O. J. Sansom, I. Cortes-Ciriano, T. J. Underwood, R. C. Fitzgerald, A. D. Beggs, H. E. Francies, M. J. Garnett 2026-08-05 doi:10.1038/s41586-026-10830-y
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Providers: Hugging Face · N/A OpenAlex · Citations 2 Publisher · N/A Semantic Scholar · N/A X · N/A Fetched 2026-09-03 14:32:23.988412 UTC

TL;DR - A Nature study presents a clinically annotated, multi-omic tumour-derived organoid biobank spanning 256 patients and five cancers. It maps cancer gene dependencies to support mechanistic research and precision oncology.

  • Organoids are paired with matched tumour samples and clinical annotations.
  • The resource identifies cancer subtype-specific genetic vulnerabilities.
  • It captures treatment-driven changes in gene dependencies.
  • The biobank expands experimental models for studying and targeting cancer.
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