Measuring the effects of drugs on single cancer cell growth

Understanding the effectiveness of a drug therapy on halting disease progression is an essential aspect of cancer biology. Conventional assays that study cell behavior after a drug intervention report the average response of a cell population which can mask the heterogeneity and dynamics of seemingly identical cells. Recently, many single-cell techniques have been developed, but there are currently no methods that can fully characterize the long-term effects of drug treatment on cancer cell growth. To accomplish such, we developed an instrument to measure single-cell growth before and after drug treatment. In order to achieve femtogram-level mass resolution, we employed the suspended microchannel resonator (SMR), a vacuum-packaged cantilever with an embedded channel. Here, we describe three implementations that involve different technologies (optical trap, mechanical trap, and dynamic ow trapping) to capture a cell for repeated measurements and to perform drug delivery. Applying the technique we developed based on the dynamic ow trapping, we were able to monitor one or more generations of a cancer cell before and after drug treatment. We investigated the growth of mouse leukemia cells in response to drugs that inhibit the mammalian target of rapamycin (mTOR) pathway, induce apoptosis, or prevent translational activity directly at the ribosome. Our method was able to discern a particular growth signature for each drug investigated and to discover a new phenotype in cells following mTOR inhibition. Furthermore, our data demonstrates that the instantaneous growth rate changes following a drug treatment could potentially predict the long-term inhibitory effect on cellular biogenesis and mass accumulation.

Department dc:contributor.department

Massachusetts Institute of Technology. Computational and Systems Biology Program.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2012

Author dc:creator

• Weng, Yaochung

Advisor dc:contributor.advisor

• Scott R. Manalis.

• Computational and Systems Biology Program.

Statement dc:rights

• M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/72638

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/72638