The Łuksza Lab develops predictive models of immune-driven evolution to understand how tumors and viruses adapt under immune pressure. By integrating concepts from information theory, machine learning, statistical physics, and quantitative immunology, the lab builds computational frameworks to quantify immunogenicity, forecast therapy response, and optimize vaccine design. Led by Marta Łuksza, Ph.D., Associate Attending Member in the Computational Oncology Service at Memorial Sloan Kettering Cancer Center and affiliate of the Olayan Center for Cancer Vaccines, the group aims to anticipate evolutionary trajectories that inform precision immunotherapy and vaccine development. Dr. Łuksza is recognized for co-developing the influenza fitness model, which informs global vaccine strain selection, and for pioneering the neoantigen fitness model, which captures immunogenicity features of tumor mutations to predict patient response to checkpoint blockade therapy. At MSK, the lab’s interdisciplinary research bridges evolutionary modeling and translational oncology to guide data-driven decision-making in cancer immunotherapy and global public health.
Meijers, M., D. Ruchnewitz, J. Eberhardt, M. Karmakar, M. Łuksza*, and M. Lässig*, Concepts and Methods for Predicting Viral Evolution. Methods Mol Biol, 2025. 2890: p. 253-290 10.1007/978-1-0716-4326-6_14
Łuksza, M., Z.M. Sethna, L.A. Rojas, J. Lihm, B. Bravi, Y. Elhanati, K. Soares, M. Amisaki, A. Dobrin, D. Hoyos, P. Guasp, A. Zebboudj, R. Yu, A.K. Chandra, T. Waters, Z. Odgerel, J. Leung, R. Kappagantula, A. Makohon-Moore, A. Johns, A. Gill, M. Gigoux, J. Wolchok, T. Merghoub, M. Sadelain, E. Patterson, R. Monasson, T. Mora, A.M. Walczak, S. Cocco, C. Iacobuzio-Donahue, B.D. Greenbaum, and V.P. Balachandran, Neoantigen quality predicts immunoediting in survivors of pancreatic cancer. Nature, 2022. 606(7913): p. 389-395 10.1038/s41586-022-04735-9.
Hoyos, D., R. Zappasodi, I. Schulze, Z. Sethna, K.C. de Andrade, D.F. Bajorin, C. Bandlamudi, M.K. Callahan, S.A. Funt, S.R. Hadrup, J.S. Holm, J.E. Rosenberg, S.P. Shah, I. Vazquez-Garcia, B. Weigelt, M. Wu, D. Zamarin, L.F. Campitelli, E.J. Osborne, M. Klinger, H.S. Robins, P.P. Khincha, S.A. Savage, V.P. Balachandran, J.D. Wolchok, M.D. Hellmann, T. Merghoub*, A.J. Levine*, M. Łuksza*, and B.D. Greenbaum*, Fundamental immune-oncogenicity trade-offs define driver mutation fitness. Nature, 2022. 606(7912): p. 172-179 10.1038/s41586-022-04696-z.
Łuksza, M., N. Riaz, V. Makarov, V.P. Balachandran, M.D. Hellmann, A. Solovyov, N.A. Rizvi, T. Merghoub, A.J. Levine, T.A. Chan, J.D. Wolchok, and B.D. Greenbaum, A neoantigen fitness model predicts tumour response to checkpoint blockade immunotherapy. Nature, 2017. 551(7681): p. 517-520 10.1038/nature24473
Please visit Dr. Łuksza’s faculty page, or Google Scholar for more publications.
Selected projects in progress. Details coming soon.
