The replication and segregation of the genome (the cell cycle) and the increase in bio-mass of individual cells (cell growth) must be coordinated in all cells. But the mechanism(s) underlying this coordination are very poorly understood, particularly in mammalian cells. The goal of Project 1 is to deconvolve cell growth and the cell division cycle, determine the molecular basis for the coordination of these two processes, and determine how these two processes and their coordination are altered in cancer. The proposed measurement platform will be developed by the Manalis lab in close collaboration with the Amon and Kirschner labs and will consist of separate modules for: obtaining synchronous populations of new-born daughter cells, measuring single cell growth rate, fixing cells, sequential storage of cells with known identity, staining these cell in parallel with probes against mRNAs, proteins, and protein phosphorylation sites, and high-resolution fluorescent Imaging of the stained cells. Our investigations will be focused on white blood cells that proliferate without adhesion in culture, as these cells can be easily manipulated within our measurement platform and are inherently tolerant of fluid flow and shear stress. Similarly, we will begin our investigations using common lines of cultured cells, but we are cognizant of the danger of being seriously misled by transformed cells. Once our technologies are established, we will progress to studying primary lymphocytes derived from mice as well as untransformed epithelial cells. Finally, we will begin to directly apply our technologies to cancer by characterizing the cell growth and the cell cycles of rare cells isolated from a human lymphoma in collaboration with the Nolan lab at Stanford.

Public Health Relevance

The relationship between the cell cycle and cell growth is fundamental to cell proliferation and needs to be understood if we are to understand how cell proliferation is altered in cancers. The rational design of cancer therapies would greatly benefit from understanding how oncogenes and tumor suppressors actually drive and/or permit proliferation.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Specialized Center--Cooperative Agreements (U54)
Project #
5U54CA143874-05
Application #
8535656
Study Section
Special Emphasis Panel (ZCA1-SRLB-9)
Project Start
Project End
Budget Start
2013-08-01
Budget End
2014-07-31
Support Year
5
Fiscal Year
2013
Total Cost
$354,845
Indirect Cost
Name
Massachusetts Institute of Technology
Department
Type
DUNS #
001425594
City
Cambridge
State
MA
Country
United States
Zip Code
02139
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

Showing the most recent 10 out of 81 publications