Project 4: Modeling neoplastic progression and analyzing genomic data to characterize the load of driver and passenger mutations in cancer. The development ofcancer can be considered as an evolutionary process within an organism. During neoplastic progression, cells acquire mutations, compete for resources, and are subject of selection for ability to grow fast in a complex and dynamic environment. These processes of Darwinian evolution have been systematically studied and modeled mathematically by methods similar to those used in Statistical Mechanics and related fields of Physics. As a result of somatic micro-evolution a population of cancer cells harbors multiple mutations: a few driver mutations essential for neoplastic progression, and many more passenger mutations. Classical works in population genetics have demonstrated that accumulation of mutations lead to increased genetic load, i.e. reduction in the mean fitness, and can lead to population extinction. Our hypothesis is that increasing the genetic load of mutations present in the population of cancer cells can make the population shrink to extinction, a process that we call clonal extinction. This idea can pave a way to a potentially novel approach to cancer treatment by therapeutics that unleash the deleterious effects of harbored mutations. To the best of our knowledge the idea of exploiting accumulated mutations to push a population of cancer cells into extinction has not been put forward. We propose to test this hypothesis by a unique approach that combines development of a theory of neoplastic evolution, analysis of emerging massive cancer genomics data, and experimental study of passenger mutation and their impact of cancer development. The experiment will reproduce seminal Luria-Delbruck experiment applied to cancer cell. Our data-driven theoretical approach is rooted in fifty years of evolutionary genetic thought about the genetic load and its consequences for population extinction.

Public Health Relevance

Developed theory of cancer micro-evolution can help to elucidate several phenomena in cancer development. If successful, our study of passenger mutations can offer a potentially novel approach to cancer treatment. This approach use cancers'own internal weakness - numerous accumulated mutations - to bring the population of cancer cells down. Characterization of cancer mutations can provide avenues for dfivfilonment of new anti-cancer driins and heln eluddatina the of action of exciting ones

National Institute of Health (NIH)
National Cancer Institute (NCI)
Specialized Center--Cooperative Agreements (U54)
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Special Emphasis Panel (ZCA1-SRLB-9)
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Massachusetts Institute of Technology
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McFarland, Christopher D (2016) A modified ziggurat algorithm for generating exponentially- and normally-distributed pseudorandom numbers. J Stat Comput Simul 86:1281-1294
Cermak, Nathan; Olcum, Selim; Delgado, Francisco Feijó et al. (2016) High-throughput measurement of single-cell growth rates using serial microfluidic mass sensor arrays. Nat Biotechnol 34:1052-1059
Hosios, Aaron M; Hecht, Vivian C; Danai, Laura V et al. (2016) Amino Acids Rather than Glucose Account for the Majority of Cell Mass in Proliferating Mammalian Cells. Dev Cell 36:540-9
Stevens, Mark M; Maire, Cecile L; Chou, Nigel et al. (2016) Drug sensitivity of single cancer cells is predicted by changes in mass accumulation rate. Nat Biotechnol 34:1161-1167
Kimmerling, Robert J; Lee Szeto, Gregory; Li, Jennifer W et al. (2016) A microfluidic platform enabling single-cell RNA-seq of multigenerational lineages. Nat Commun 7:10220
Hecht, Vivian C; Sullivan, Lucas B; Kimmerling, Robert J et al. (2016) Biophysical changes reduce energetic demand in growth factor-deprived lymphocytes. J Cell Biol 212:439-47
Akutagawa, J; Huang, T Q; Epstein, I et al. (2016) Targeting the PI3K/Akt pathway in murine MDS/MPN driven by hyperactive Ras. Leukemia 30:1335-43
Shaw Bagnall, Josephine; Byun, Sangwon; Miyamoto, David T et al. (2016) Deformability-based cell selection with downstream immunofluorescence analysis. Integr Biol (Camb) 8:654-64
Ramanan, Vyas; Trehan, Kartik; Ong, Mei-Lyn et al. (2016) Viral genome imaging of hepatitis C virus to probe heterogeneous viral infection and responses to antiviral therapies. Virology 494:236-47
Shaw Bagnall, Josephine; Byun, Sangwon; Begum, Shahinoor et al. (2015) Deformability of Tumor Cells versus Blood Cells. Sci Rep 5:18542

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