Marta Luksza, PhD
- ASSISTANT PROFESSOR | Oncological Sciences
- ASSISTANT PROFESSOR | Genetics and Genomic Sciences
Research Topics:Bioinformatics, Biophysics, Cancer, Infectious Disease, Influenza Virus, Viruses and Virology
I am a computer scientist working on topics at the interface of evolutionary biology and immunology. We apply approaches from information theory, statistical mechanics and machine learning to understand how the immune system and other biophysical phenotypes affect the evolution of viruses and cancer. Understanding their evolutionary dynamics and ways of adaptation is crucial for the design of treatments and vaccine selection.
Previously, we have developed computational methods for inference of fitness effects from genetic, phenotypic and epidemiological data for predicting the evolution of the influenza virus. The model is currently used to consult the World Health Organization vaccine strain selection. We also proposed a predictive model for therapy response of tumors evolving under strong selection from the immunotherapy. These studies have laid the groundwork for investigating personalized neoantigen vaccines for patients with various cancer types.
We are looking for highly motivated students and postdocs to join our lab and conduct research in the area of cancer or virus evolution.
Multi-Disciplinary Training AreaGenetics and Genomic Sciences [GGS]
PhD, Free University & Max Planck Institute for Molecular Genetics
The Dr. Harold and Golden Lamport Clinical Research Award
Łuksza M, Riaz N, Makarov V, Balachandran VP, Hellmann MD, Solovyov A, Rizvi NA, Merghoub T, Levine AJ, Chan TA, Wolchok JD, Greenbaum BD. A neoantigen fitness model predicts tumour response to checkpoint blockade immunotherapy. Nature 2017 11; 551(7681).
Balachandran VP, Łuksza M, Zhao JN, Makarov V, Moral JA, Remark R, Herbst B, Askan G, Bhanot U, Senbabaoglu Y, Wells DK, Cary CI, Grbovic-Huezo O, Attiyeh M, Medina B, Zhang J, Loo J, Saglimbeni J, Abu-Akeel M, Zappasodi R, Riaz N, Smoragiewicz M, Kelley ZL, Basturk O, Gönen M, Levine AJ, Allen PJ, Fearon DT, Merad M, Gnjatic S, Iacobuzio-Donahue CA, Wolchok JD, DeMatteo RP, Chan TA, Greenbaum BD, Merghoub T, Leach SD. Identification of unique neoantigen qualities in long-term survivors of pancreatic cancer. Nature 2017 11; 551(7681).
Morris DH, Gostic KM, Pompei S, Bedford T, Łuksza M, Neher RA, Grenfell BT, Lässig M, McCauley JW. Predictive Modeling of Influenza Shows the Promise of Applied Evolutionary Biology. Trends in microbiology 2018 Feb; 26(2).
Luksza M, Lässig M. A predictive fitness model for influenza. Nature 2014 Mar; 507(7490).
Łuksza M, Lässig M, Berg J. Significance analysis and statistical mechanics: an application to clustering. Physical review letters 2010 Nov; 105(22).
Łuksza M, Kluge B, Ostrowski J, Karczmarski J, Gambin A. Two-stage model-based clustering for liquid chromatography mass spectrometry data analysis. Statistical applications in genetics and molecular biology 2009; 8.
Physicians and scientists on the faculty of the Icahn School of Medicine at Mount Sinai often interact with pharmaceutical, device and biotechnology companies to improve patient care, develop new therapies and achieve scientific breakthroughs. In order to promote an ethical and transparent environment for conducting research, providing clinical care and teaching, Mount Sinai requires that salaried faculty inform the School of their relationships with such companies.
Below are financial relationships with industry reported by Dr. Luksza during 2022 and/or 2023. Please note that this information may differ from information posted on corporate sites due to timing or classification differences.
Other Activities: Examples include, but are not limited to, committee participation, data safety monitoring board (DSMB) membership.
- Hector Labs
Mount Sinai's faculty policies relating to faculty collaboration with industry are posted on our website. Patients may wish to ask their physician about the activities they perform for companies.