Non-genetic tumor diversity contributes to treatment failure in cancer patients

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Non-genetic tumor diversity contributes to treatment failure in cancer patients

The above figure summarizes the team’s findings in terms of genetic, epigenetic and stochastic differences between the EGFR mutant lung cancer cells studied. Credit: University of Arkansas

Leonard Harris, assistant professor of biomedical engineering, led a team of researchers at Vanderbilt University that has demonstrated how an in vitro model of tumor heterogeneity, or diversity, resolves three different sources of cell state variability in cancer cells. The article was published in PLOS Biology.

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a heterogeneous tumor is a tumor that consists of many different types cancer cells. Often the cells have different types genetic mutations and coexist in a tumor. The diversity of the tumor is what makes cancer difficult to treat.

“It’s like the success of a diverse team,” explains Harris. “A team made up of people from different backgrounds, ages, career stages, etc. are often better at tackling problems because the team members offer different perspectives.”

In a tumor, different cells respond to medicine treatments differently. Some cells are able to survive and allow the tumor to grow and spread. That’s why Harris and his team continue to investigate how surviving cancer cells differ from one another. tumor cells.

But genetic mutations aren’t the only way cancer cells can differ from one another. Cells with exactly the same DNA can exist in very different states. For example your skin cells and your liver cells have exactly the same DNA, but they function very differently; that is an example of epigenetic heterogeneity. In addition, when one skin cell divides, it produces two skin cells. The cells do not inherit the skin cell state from the DNA; it has to come by another route. It is this non-genetic form of inheritance that makes the process epigenetic.

Cancer cells also differ by random fluctuations in the number of molecules in each cell: molecules interact randomly with each other, are broken down, synthesized by the cell, secrete in and out of the cell, etc. This type of non-genetic heterogeneity is called stochastic. variability and is not heritable, unlike epigenetic processes. It may not seem like a big deal, but researchers have shown that stochastic variability can have major effects.

The experimental and computational work reported in the paper was performed at Vanderbilt University in collaboration with Corey E. Hayford, Darren R. Tyson, C. Jack Robbins III, Peter L. Frick and Vito Quaranta and has motivated many additional research projects. . It is now the base for Harris’ U of A laboratory.

“Cancer is commonly referred to as a ‘genetic disease,’ meaning it is caused by mutations in critical parts of DNA that cause cells to grow out of control,” Harris said. β€œThis has led to decades of research into the genetics of cancer, which has resulted in significant advances, including the development of numerous therapeutic drugs targeting so-called ‘driver oncogenes’. This has led many researchers to think on the role of non-genetic processes in the response of tumors to drugs.”

Modeling and experimental techniques were used to distinguish the three different sources of variability between lung cancer cells: genetic, epigenetic and stochastic. As mentioned above, epigenetic and stochastic variability are different types of non-genetic variability. Epigenetically different cells look different, like the skin and liver cells from the example above, while stochastically different cells look almost identical, but can act completely differently.

“Distinguishing genetic from non-genetic and epigenetic from stochastic factors in drug response is critical to developing new therapies that can kill tumor cells before they have a chance to acquire genetic resistance mutations,” Harris said. “They all contribute to tumor drug response in different ways.”

A framework for distinguishing genetic and non-genetic sources of heterogeneity in tumors has been proposed previously, but has not yet been widely accepted within the cancer research community due to a lack of strong experimental evidence. The team’s paper provides strong support for this framework.

The analysis presented in the article was specifically applied to EGFR mutant non-small cell lung cancer. Harris’ lab is currently applying these ideas to other cancer types, including small cell lung cancer, melanoma, and bone metastatic breast cancer.

“In my lab, we’re building computer models of the molecular networks in cancer cells that give rise to the different epigenetic states over which cells can transition to survive drug treatments,” Harris said. “The long-term goal of my lab’s research is to extend these models until they are detailed enough to act as virtual platforms for testing the effects of different drugs and identifying new drug targets.”

By constructing these so-called “digital twins,” the hope is to one day use them to run virtual drug screens on models made from samples of real patient tumors and then design personalized treatment options for those patients. This requires collaborations with bioinformatics, experimenters, and clinicians here at U of A, the Winthrop P. Rockefeller Cancer Institute at the University of Arkansas for Medical Sciences in Little Rock, and elsewhere. “Hopefully the publication of this article will help kick-start some of those collaborations,” Harris said.

Preventing unwanted recurrence of lung cancer

More information:
Corey E. Hayford et al, An in vitro model of tumor heterogeneity resolves genetic, epigenetic and stochastic sources of cell state variability, PLOS Biology (2021). DOI: 10.1371/journal.pbio.3000797

Quote: Non-genetic tumor diversity contributes to treatment failure in cancer patients (2021, July 15) retrieved July 17, 2021 from . html

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