Rapidly quantifying drug sensitivity of dispersed and clumped breast cancer cells by mass profiling

Jennifer Chun1, Thomas A Zangle, Theodora Kolarova

  • 1Bioengineering Interdepartmental Program, Los Angeles, California, USA.

The Analyst
|October 12, 2012
PubMed

Insights

Automated Live Cell Interferometry (LCI) rapidly quantifies cancer cell sensitivity to therapies, even in cell clusters. This breakthrough enables faster drug response testing for patient-derived tumor samples.

Area of Science:

  • Biotechnology
  • Cell Biology
  • Cancer Research

Background:

  • Live cell mass profiling offers rapid quantification of cellular responses to therapeutics by measuring minute changes in cell mass.
  • Existing mass profiling methods struggle with pleomorphic cellular clusters common in patient-derived samples.
  • There is a need for faster, more accurate methods to assess drug sensitivity in complex cell populations.

Purpose of the Study:

  • To demonstrate automated Live Cell Interferometry (LCI) as a rapid and accurate method for quantifying drug sensitivity.
  • To assess the sensitivity of human breast cancer cell lines to trastuzumab using LCI.
  • To evaluate LCI's capability in handling clustered and single-cell samples.

Main Methods:

  • Development and application of automated Live Cell Interferometry (LCI).
  • Testing of four human breast cancer cell lines, including single cells and colony-forming clusters.
  • Quantification of cellular response to the HER2-directed antibody, trastuzumab (Herceptin).

Main Results:

  • LCI accurately quantified the sensitivity of breast cancer cell lines to trastuzumab.
  • Relative sensitivities of small cell samples (<500 cells) were determined significantly faster than traditional assays.
  • LCI demonstrated efficacy in assessing both single cells and clustered cell populations.

Conclusions:

  • Automated LCI provides a rapid and accurate method for assessing therapeutic agent sensitivity.
  • LCI overcomes limitations of existing methods by effectively analyzing clustered cells.
  • This technology holds promise for expedited therapeutic response testing of patient-derived solid tumor samples.

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