Researchers analyze the significance of cellular interactions for lung cancer

A new Cleveland Clinic study has uncovered vital information about the cellular interaction of tumor cells and normal tissue, leading to a better understanding of how therapeutic resistance evolves.

Researchers analyze the significance of cellular interactions for lung cancer
Jacob Scott, M.D., D.Phil. Image Credit: Cleveland Clinic

In the study of drug resistance, researchers often try to understand the fitness of cells that have specific mutations in the presence of a drug in a laboratory setting.”

Jacob Scott, M.D., D.Phil., Radiation Oncologist and Head, Lerner Research Institute Department of Translational Hematology and Oncology Research, Cleveland Clinic

But the reality is more complex because tumor cells don’t exist in a vacuum; instead, they co-exist in a complex, heterogeneous mixture of other tumor cells and normal tissues — an interacting ecology.”

With treatment-resistant disease accounting for approximately 90% of cancer deaths, these cellular interactions, also recognized as “evolutionary games,” have high stakes.

Dr Scott and his colleagues used an originally developed assay to directly measure those interactions in a simple tumor environment comprised of drug-resistant non-small cell lung cancer cells and drug-sensitive precursor (ancestor) cells in their newest study released on July 1st, 2022, in Science Advances.

Cells resistant to the metastatic non-small cell lung cancer treatment gefitinib were sourced from current lung cancer cells after six months of continuous gefitinib treatment and grown in vitro with their sensitive ancestors. The dynamics of cell expansion were studied with and without gefitinib.

We cultured the two groups of cells together in different starting fractions and we measured how their growth changed depending on how much of each group was mixed together.”

Jeff Maltas, PhD, Study Co-Lead Author and Postdoctoral Researcher, Cleveland Clinic

The scientists found that the fitness of the resistant type of cell varies dramatically based on the mixture’s composition.

Tests demonstrated that in the lack of therapy, the resistant population was outcompeted by the ancestral line at all researched population frequency ranges, indicating the comprehensive competitive exclusion of the resistant population and a cost of resistance. When gefitinib was incorporated, the effect was completely reversed, allowing the resistant clone to outcompete the sensitive ancestor.

This difference in growth dynamics between treatment-resistant and treatment-sensitive cells could not be identified using current standard assays, implying a new method by which resistant cells remain in the absence of treatment.

This paper highlights the need to understand and directly measure those ecological interactions that come from being around other cell types,” Dr Scott said. “That’s something we’re doing here that’s fundamentally different.”

Dr Scott points out that, while these preliminary discoveries cannot be immediately extrapolated to clinical settings, they do raise important questions that could have a significant impact on clinical research and trial design. In a broader sense, could patients benefit from a medication break to enable the survival of a critical treatment-sensitive population of tumor cells?

Furthermore, could treatment regimens that alternate between on- and off-treatment periods lead to improved regulation of cancer cell growth and, in the long, extended patient lives?

One of the most exciting parts of this paper is the opportunity for clinical advances that it highlights,” Dr Scott said.  The next translational application of these key results could be the design and testing of vibrant treatment regimens that could maintain cancer cells “in check” over time.

The Theory Division at Cleveland Clinic performs cancer research to establish and grant access to novel diagnostic tools, targeted therapies, and clinical trials for immediate use in patient care.

Source:
Journal reference:

Farrokhian, N., et al. (2022) Measuring competitive exclusion in non–small cell lung cancer. Science Advances. doi.org/10.1126/sciadv.abm7212.

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