New tumor cell tracking system aims to understand cancer treatment
resistance

Date:
August 13, 2021
Source:
University of Texas at Austin
Summary:
A team of researchers have developed a new way to tag tumor cells
to figure out how they evolve and change over time to resist
cancer treatments.



FULL STORY ========================================================================== Despite tremendous advances in medicine, tumors are challenging to
cure because they are made up of heterogeneous cells. Like human
families, the individual cells of a tumor share some common traits
and characteristics, but as the tumor expands, the cells also develop
their own identities. And, as a result, some cells are more resistant
to therapy than others and quicker to adapt and change.


==========================================================================
A team of researchers at The University of Texas at Austin developed a new
way to tag tumor cells to figure out how they evolve and change over time
to resist cancer treatments. They studied chronic lymphocytic leukemia
(CLL) primarily, but these findings could help researchers learn more
about the entire spectrum of cancerous tumors.

"This is a technology that lets you replay the evolutionary history
of the tumor," said Amy Brock, an associate professor in the Cockrell
School's Department of Biomedical Engineering and co-lead author on a new
paper published in Nature Cancer. "We can collect those pre-resistant
cells and go back and look at what happened to them. We can try many
parallel treatments and measure how specific cells respond and which
ones persist." The ability to essentially "tag" nucleic acids -- the
genetic information of the cell such as RNA or DNA -- to monitor them
is not a brand-new technology.

However, current capabilities don't paint a full picture of how tumor
cells evolve. What this platform, known as ClonMapper, can do that wasn't possible before is look backward and trace how tumor cells change over
time. That gives researchers the ability to look at which cells "win out"
over less resistant cells, continue to clone themselves and make the
tumor more dangerous. By isolating these cells, researchers can better
test which treatments do and don't work against them.

Monitoring changes over time is key to successful transfer
treatments. Tumor cells adjust to treatments and become resistant. That's
why patients can go into remission, but later experience relapse.

"This is one of reasons cancer treatment is so challenging -- we don't
have very good ways of predicting ahead of time which cells will be
sensitive to a type of drug and which ones will be resistant," Brock
said. "This acquired resistance is a leading cause of treatment failure
for many patients with cancer." CLL is a low-grade B-cell malignancy that
is often monitored for months or even years before it requires active treatment. This "watch and wait" style of treatment relies heavily on
accurate monitoring of the patient. In the study, ClonMapper focused on identifying which cells were cloning themselves, how fast this process
happened and how it influences the growth rate of surrounding cells over
time. This allowed a much more accurate analysis of the cell population
and may enable more customized treatment plans for patients.

The ClonMapper study was led by researchers from UT Austin and the
Dana-Farber Cancer Institute, Harvard Medical School and the Broad
Institute. The UT Austin team includes from the Cockrell School and
College of Natural Sciences Aziz M.

Al'Khafaji, Eric Brenner, Kaitlyn E. Johnson and Russell E. Durrett.

The UT Austin team is now deploying ClonMapper to study several different cancer types. Brock's lab recently received funding from the National
Cancer Institute to study breast cancer and has an ongoing collaboration
with Dell Medical School working on colorectal carcinoma treatments.

========================================================================== Story Source: Materials provided by University_of_Texas_at_Austin. Note: Content may be edited for style and length.


========================================================================== Journal Reference:
1. Catherine Gutierrez, Aziz M. Al'Khafaji, Eric Brenner, Kaitlyn E.

Johnson, Satyen H. Gohil, Ziao Lin, Binyamin A. Knisbacher,
Russell E.

Durrett, Shuqiang Li, Salma Parvin, Anat Biran, Wandi Zhang,
Laura Rassenti, Thomas J. Kipps, Kenneth J. Livak, Donna Neuberg,
Anthony Letai, Gad Getz, Catherine J. Wu, Amy Brock. Multifunctional
barcoding with ClonMapper enables high-resolution study of clonal
dynamics during tumor evolution and treatment. Nature Cancer,
2021; 2 (7): 758 DOI: 10.1038/s43018-021-00222-8 ==========================================================================

Link to news story: https://www.sciencedaily.com/releases/2021/08/210813105536.htm

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