Cataloging Breast Cells To Find Cancer Origins (Medicine)

CSHL scientists genetically profiled thousands of cells in normal breast tissue to establish what types of cells tend to become cancerous. This catalog can help researchers develop preventive therapies.

What if you could predict which cells might become cancerous? Breast tissue changes dramatically throughout a woman’s life, so finding markers for sudden changes that can lead to cancer is especially difficult. Cold Spring Harbor Laboratory (CSHL) Associate Professor Camila dos Santos and her team identified and cataloged thousands of normal human and mouse breast cell types. The new catalog redefines healthy breast tissue so that when something goes awry, scientists can pinpoint its origin.

Any breast cell could become cancerous. Dos Santos says:

“In order to understand breast cancer risk, you have to understand normal breast cells first, so when we think about preventive and even targeting therapies, you would be preventing the right cell types from developing to cancer cells.”

A traditional way to catalog cells is by tracking a few signature genes related to the cell’s function. To classify cells more extensively, dos Santos’ team turned to a technique known as single-cell RNA sequencing. They tracked the activity of several genes in over 15,000 cells in mouse and human breast tissue. Samantha Henry, a Stony Brook University graduate student-in-residence in dos Santos’ lab, says:

“We really created a whole catalog of many genes for each cell population to better define them. And when I say there was a lot of genes, there was a lot of genes and it took a long time to get through.”

Camila dos Santos, Associate Professor, Cancer Center Member, Ph.D., Universidade Estadual de Campinas © CHSL

One cell group included estrogen receptor-positive cells, which are generally amenable to treatment. But dos Santos’ team found that this group could be split into several subpopulations, where each one might have different responses to therapies.

The team, in collaboration with computational biologist CSHL Professor Adam Siepel and his team, learned that mice and human breast cells had similar genetic profiles, demonstrating why studies in mice are likely to be relevant to humans. Marygrace Trousdell, a computational science developer in the dos Santos lab, says:

“We’re always finding ourselves struggling with definitive classifications of certain cell types. Sometimes I think I’ve seen every gene out there, and then something else will pop up.”

Currently, the lab is trying to distinguish normal genetic shifts from those associated with cancer. Dos Santos hopes that her catalog of breast cell types will point to which kinds of cells to monitor and point researchers toward treatment options in the future.

Funding

The CSHL and Northwell Health affiliation, the CSHL and Simons Foundation Award, the Rita Allen Scholar Award, the Pershing Square Sohn Prize for Cancer Research, the National Cancer Institute, and the National Institute on Aging

Citation

Henry, S., et al., “Characterization of gene expression signatures for the identification of cellular heterogeneity in the developing mammary gland”, Journal of Mammary Gland Biology and Neoplasia, May 14, 2021. DOI: 10.1007/s10911-021-09486-3

Featured image: Mammary tissue is made up of a variety of cells, including epithelial (pink), immune (cyan), and fat (black) cells visible in this cross-section of a mouse mammary gland. CSHL Associate Professor Camila dos Santos’ team identified and cataloged thousands of human and mouse breast cells to understand the origins of breast cancer. Image: Camila dos Santos/dos Santos lab


Provided by Cold Spring Harbor Laboratory

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out /  Change )

Google photo

You are commenting using your Google account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s