Cancer cells exert a corrupting influence, drawing otherwise innocent cells into nefarious schemes. To bring the schemes to light, scientists based at the Francis Crick Institute have developed a labeling system for the metastatic niche. By inducing metastatic cells to release a cell-penetrating fluorescent protein, the system can localize corrupting influences that are ordinarily hidden in the crowds of cells that constitute bulk tissue.

Already, the system has been used to identify healthy cells that respond to cancer cells by regressing to a stem-cell-like state. Once they acquire multilineage differentiation potential, the once-innocent cells may participate in various forms of corruption, helping cancer thrive.

The system—which resulted from a project led by Ilaria Malanchi, PhD, senior group leader at the Francis Crick Institute and Joo-Hyeon Lee, PhD, research group leader at the Cambridge Stem Cell Institue—may serve as a research tool, characterizing the spread of cancer, or as a clinical tool, assessing patient responses to cancer treatments.

“Our new technique allows us to study changes to cells in the tumor microenvironment with unprecedented precision,” asserted Malanchi. “This helps us to understand how these changes relate to tumor growth and metastasis, allowing us to develop better strategies to treat the disease.

“We discovered that noncancerous cells in the tumor microenvironment regress back into a stem-cell like state, and actually support cancer growth. By corrupting its neighbors, cancer transforms its local environment to support its own survival.”

Details about the new system appeared August 28 in Nature, in an article titled, “Metastatic-niche labeling reveals parenchymal cells with stem features.” The article describes how cancer cells may be engineered to release a marker that gets taken up by healthy cells that happen to be in the cancer cells’ proximity. Cells that acquire the marker from the cancer cells can be identified and compared to “uncorrupted” cells, that is, cells that remain free of the marker, perhaps because they are not quite close enough to any cancer cells.

“[We used the system] to study the cellular environment of metastatic breast cancer cells in the lung,” the article’s authors wrote. “We report the presence of cancer-associated parenchymal cells, which exhibit stem-cell-like features, expression of lung progenitor markers, multi-lineage differentiation potential, and self-renewal activity. In ex vivo assays, lung epithelial cells acquire a cancer-associated parenchymal-cell-like phenotype when co-cultured with cancer cells and support their growth.”

Researchers in Malanchi’s lab used the system to identify tissue cells with low representation in the metastatic niche. Data collected by colleagues at the Fritz Lipmann Institute in Germany confirmed that the labeled cells produced proteins different from those produced by unlabeled cells.

The results showed that those cells from the mouse lungs supported tumor growth when mixed with tumor cells in 3D culture in the lab, suggesting that they help the cancer to survive and grow. To further test the potential of the stem-cell-like cells in the tumor microenvironment, Malanchi teamed up with Lee, who used them to grow lung organoids.

The unlabeled healthy lung cells formed lung organoids that largely consisted of alveolar epithelial cells. By comparison, the labeled cells taken from the tumor microenvironment unexpectedly formed lung organoids with a wider range of cell types.

“To our amazement, we found that cells receiving proteins from adjacent cancer cells obtained stem-cell-like features,” Lee noted. “They could change their fate to become different cell types. It demonstrates the powerful influence that cancer exerts over its neighboring cells, making them liable to change easily.”

The researchers hope that their approach will be used by other scientists looking to gain a deeper understanding of the local changes triggered by cancer which help it to survive, spread, and develop resistance to treatments. The potential applications are not confined to cancer—a similar approach could enable scientists to study interactions between different cell types in the body.

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