Researchers pinpoint hierarchy of breast cancer cells as potential cause
for treatment resistance

Date:
August 25, 2020
Source:
University of Cincinnati
Summary:
Researchers say it can take cells in different forms or 'life
stages' to cause cancer to grow and spread.



FULL STORY ==========================================================================
You might have heard the old proverb, "It takes a village to raise
a child."

========================================================================== University of Cincinnati instructor Syn Yeo, PhD, thinks the same analogy applies when it comes to cells and the growth of cancer, particularly
breast cancer.

In his recent study, published in the journal eLife, Yeo, research
instructor in the department of cancer biology at the UC College of
Medicine and co-lead author, says it can take cells in different forms or
"life stages" to cause cancer to grow and spread.

"Our recent findings emphasize the need to account for the specific cell
states that are present within a tumor," says Yeo, who is a member in
the lab of Jun- Lin Guan, PhD, the Francis Brunning Endowed Chair and
professor of cancer biology. "This could potentially help determine
the combination of drugs that are required to eliminate all the cell
states that are present to eliminate treatment resistance." Yeo says
that when it comes to breast cancers, it is known that cells within a
tumor are varied.

"This diversity poses a problem to treating patients because particular
subsets of tumor cells may be drug resistant and eventually lead to
disease recurrence," he says. "One of the factors contributing to this diversity is the fact that tumor cells can exist in different cellular
states, ranging from more stem-like cells that can become other cell types
to more differentiated cells that have been coded to serve a purpose,
or do a certain 'job' within the system.

"Cancer cells with stem-like properties are known to cause drug
resistance, and they are generally seen as being at the top of the
tumor hierarchy, like the kKing or queen of the village, with more differentiated tumor cells towards the bottom of the hierarchy, like
the common townspeople." In this study, researchers used breast cancer
animal models to determine tumor hierarchies beyond "ruler" and "common
people" cells, Yeo says. They identified and categorized singular cells
which helped them understand each, individual cell's purpose. Yeo adds
that bulk tumor cell analysis would have masked the cellular details.

"We were able to find a complex spectrum of cell states between different
tumor types that can range from stem-cells to the 'beginner cells' to more differentiated cells," he says. "In our village [scenario], these would be
the governors and mayors, followed by the common townspeople. Furthermore, depending on the lineage of the tumor, some may show a spectrum of cell
states that are higher up in the hierarchy and vice versa.

"These findings are important because they show we need to know more
about how these specific cell states contribute to tumor growth so we
can target them with combination drug therapies, potentially helping more people who may otherwise experience drug resistance." Funding for this research was provided by the National Institutes of Health (R01-CA211066, R01-HL073394 and R01-NS094144). Xiaoting Zhu was the other co- lead
author who was partially supported by R01-HL111829. Other contributors
include Takako Okamoto, Mingang Hao, Cailian Wang, Peixin Lu, Long Jason
Lu and Jun-Lin Guan. Researchers cite no conflict of interest.


========================================================================== Story Source: Materials provided by University_of_Cincinnati. Original
written by Katie Pence. Note: Content may be edited for style and length.


========================================================================== Journal Reference:
1. Syn Kok Yeo, Xiaoting Zhu, Takako Okamoto, Mingang Hao, Cailian
Wang,
Peixin Lu, Long Jason Lu, Jun-Lin Guan. Single-cell RNA-sequencing
reveals distinct patterns of cell state heterogeneity in mouse
models of breast cancer. eLife, 2020; 9 DOI: 10.7554/eLife.58810 ==========================================================================

Link to news story: https://www.sciencedaily.com/releases/2020/08/200825110633.htm

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