Research Interests

Purpose: We are driven by finding unifying theories of nature. With an aim towards transdisciplinarity, we achieve this by developing and applying rigorous mathematics and conceptual reasoning to probe fundamental biological questions at an abstract level and, in doing so, uncover hidden connections between fields. We then work with empirical colleagues to further refine and reify these ideas iteratively.

Scientific Philosophy: We are strong proponents of qualitative and hypothesis-generating modeling, "Figure 1 theory", theory building, consilience, and intellectual nomadism. More pragmatically, if you want to know where we (currently) place our conceptual flags, check out these papers:

Modeling: here and here
Cancer Social Science: here and here
Cancer Evolutionary Ecology: here

Methods: Eco-evolutionary dynamics, game theory, matrix and integral population models, stochastic simulation, and philosophical deliberation. If you'd like to play around with G functions, check out our software tool here and the corresponding pedagogical website here.

See below for the main projects and research themes our lab is actively working on. For a full list of publications, see our Google Scholar page.

Cancer Evolutionary Ecology

In this research line, we draw on ideas from evolutionary ecology to devise novel treatment strategies for cancer with a focus on evolutionary double binds. Notably, via a tight integration of mathematical modeling, computational biology, and experimental work, we developed the idea of life history enlightened treatments that led to an approved clinical trial (NCT05574712). We are currently applying concepts from community ecology and modern coexistence theory to understand and disrupt intratumoral heterogeneity with the aim of designing first-strike, second-strike extinction therapies.

Relevant Publications

Cunningham, J., Bukkuri, A., Brown, J.S., Gillies, R.J., Gatenby, R.A. (2021). Coupled Source-Sink Habitats Produce Spatial and Temporal Variation of Cancer Cell Molecular Properties as an Alternative to Branched Clonal Evolution and Stem Cell Paradigms. Frontiers in Ecology and Evolution, 9(676071), 1-15. PDF.

Bukkuri, A., Gatenby, R.A., Brown, J.S. (2022). GLUT1 Production in Cancer Cells: A Tragedy of the Commons. Nature Project Journal Systems Biology and Applications, 8(22), 1-13. PDF.

Bukkuri, A., Pienta, K.J., Austin, R.H., Hammarlund, E.U., Amend, S.R., Brown, J.S. (2022). A Life History Model of the Ecological and Evolutionary Dynamics of Polyaneuploid Cancer Cells. Nature Scientific Reports, 12(13713), 1-12. PDF.

Bukkuri, A., Pienta, K.J., Austin, R.H., Hammarlund, E.U., Amend, S.R., Brown, J.S. (2022). Stochastic Models of Mendelian and Reverse Transcriptional Inheritance in State-Structured Cancer Populations. Nature Scientific Reports, 12(13079), 1-13. PDF.

Bukkuri, A., Pienta, K.J., Austin, R.H., Hammarlund, E.U., Amend, S.R., Brown, J.S. (2023). A Mathematical Investigation of Polyaneuploid Cancer Cell Memory and Cross-Resistance in State-Structured Cancer Populations. Scientific Reports, 13(15027), 1-11. PDF.

Bukkuri, A. (2024). Modeling Stress-Induced Responses: Plasticity in Continuous State Space and Gradualistic Clonal Evolution. Theory in Biosciences, 143(1), 1-15. Link. PDF Link.

Carroll, C.P., Manaprasertsak, A., Castro, A.B., van den Bos, H., Spierings, D., Wardenaar, R. Bukkuri, A., Engström, N., Baratchart, E., Yang, M., Biloglav, A., Cornwallis, C., Johansson, B., Hagerling, C., Arsenian-Henriksson, M., Paulsson, K, Amend, S., Mohlin, S., Foijer, F., McIntyre, A., Pienta, K.J., Hammarlund, E.U. (2024). Drug-resilient cancer cell phenotype is acquired via polyploidization associated with early stress response coupled to HIF-2α transcriptional regulation. Cancer Research Communications, 4(3), 691–705. Link.

Bukkuri, A., Andersson, S., Brown, J.S., Hammarlund, E.U., Mohlin, S. (2024). Cell Types or Cell States? An Investigation of Adrenergic and Mesenchymal Cell Phenotypes in Neuroblastoma. iScience, 27(111433), 1-9. PDF.

Cancer Social Science

Many aspects of oncogenesis, from signaling and resource acquisition to division of labor and mutualisms, can be viewed through the lens of social science. In this research program, we draw on linguistics, economics, criminology, political science, anthropology, and sociology to develop a novel research paradigm for understanding and treating cancer. The main question we seek to address is: "How do deviant actors arise and interact with external factors to promote the collapse of communication networks in their society, thereby facilitating their expansion?"

Relevant Publications

Bukkuri, A., Adler, F.R. (2021). Viewing Cancer Through the Lens of Corruption: Using Behavioral Ecology to Understand Cancer. Frontiers in Ecology and Evolution, 9(678533), 1-14. PDF.

Bukkuri, A., Gatenby, R.A., Brown, J.S. (2022). GLUT1 Production in Cancer Cells: A Tragedy of the Commons. Nature Project Journal Systems Biology and Applications, 8(22), 1-13. PDF.

Bukkuri, A., Adler, F.R. (2023). Biomarkers or Biotargets? Using Competition to Lure Cancer Cells into Evolutionary Traps. Evolution, Medicine, and Public Health, 11(1), 264-276. PDF.

Bukkuri, A., Adler, F.R. (2024). Of Criminals and Cancer: The Importance of Social Bonds and Innate Morality on Cellular Societies. Cells & Development, 180(203964), 1-6. Link.

Bukkuri, A., Adler, F.R. Mathematical Modeling of Field Cancerization through the Lens of Cancer Behavioral Ecology. Under Review, 1-12. Preprint.

Eco-Evolutionary Theory

Alongside our applied work, we also advance the theory of evolutionary games. Our efforts have primarily focused on developing methods to model eco-evolutionary dynamics in structured populations, but we are also interested in evolution in linked multi-trait systems, multi-level selection, and multi-agent evolutionary signaling games.

Relevant Publications

Bukkuri, A., Brown, J.S. (2023). Integrating Eco-Evolutionary Dynamics into Matrix Population Models for Structured Populations: Discrete and Continuous Frameworks. Methods in Ecology and Evolution, 14(6), 1475-1488. PDF.

Bukkuri, A. (2024). Modeling Stress-Induced Responses: Plasticity in Continuous State Space and Gradualistic Clonal Evolution. Theory in Biosciences, 143(1), 1-15. Link. PDF Link.

Bukkuri, A. (2024). Eco-Evolutionary Dynamics of Structured Populations in Periodically Fluctuating Environments: A G Function Approach. Theory in Biosciences, 143, 293-299. Link. PDF Link.

"I am not a donkey, I don't have a field" - Max Weber

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