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A single biopsy from a metastatic breast cancer tumor contains hundreds of thousands of cells—some cancerous and others part of the complex web of immune cells, blood vessels, and supportive tissue that surround a tumor. Researchers have typically analyzed these cells as a mixed-together group, but this approach can miss rare cell types, and makes it difficult to draw conclusions about how cells interact to drive the disease. Now, a team of researchers at the Broad Institute of MIT and Harvard, Dana-Farber Cancer Institute, MIT, Harvard, Stanford, and the Ludwig-Maximilians-University Munich has shown that state-of-the-art methods that analyze cells individually or within intact tissue can reveal new insight into the diversity of cells that make up metastatic breast cancers.
Their study, published in Nature Medicine , also provides a resource for scientists to help guide future experiments. The team compared six different high-resolution gene expression analysis methods, including four spatial profiling approaches, which map the location of cells within a tissue and reveal new details about which cells interact with each other and how. The researchers reported how well the methods worked to capture different cellular characteristics of the tumors and surrounding tissue.
The results pave the way for future single-cell or spatially resolved studies that look at how cells surrounding a metastatic tumor impact its progression or treatment outcomes. "Methods that analyze each single cell within a tissue have become incredibly powerful, especially for the study of tumors, but until now no one had explored what is possible when it comes to applying these methods to metastatic breast cancer biopsies," said Aviv Regev, a former Broad core institute member who co-led the work and is now at Genentech. "One of our goals here was to show that these single-cell and spatial methods can provide important biological insights into metastatic breast cancer," added Nikhil Wagle, also a former Broad scientist and co-senior author of the research who is also at Genentech.
"Eventually, we hope that these methods can help inform the development of drugs or even guide patients' individual treatments." This work is part of the Human Tumor Atlas Network, a consortium tasked with building three-dimensional cellular and molecular atlases of human cancers. Ten other papers from consortium members were published today in Nature , Nature Medicine , and other journals.
Methods matchup Metastatic breast cancer, which has spread from the breast to other areas of the body, remains incurable and is less well understood than breast cancer that hasn't spread. In particular, there are many questions about the role of surrounding immune cells in a metastatic tumor's progression. In the new work, the team used two single-cell RNA sequencing methods to analyze 67 metastatic breast cancer biopsies collected from 60 different patients.
They also applied four spatial transcriptomics methods, including Slide-Seq and MERFISH, to a subset of the biopsies. The biopsies were from a variety of metastatic breast cancer subtypes, taken from different sites of disease including lymph nodes, liver, bone, skin, and lung, and were collected at different points during the patients' treatment course. While all the methods were effective at capturing information on the cells, some excelled at profiling certain cell types over others, and some were better at gauging expression levels of small sets of genes, while others came out on top for profiling all the genes across the genome.
"We don't think we can nominate one universal winner that can satisfy all the possible needs that a researcher might have when wanting to generate this kind of data," explained Johanna Klughammer, a former postdoctoral research fellow at the Broad, now a group leader at the Ludwig-Maximilians-University Munich in Germany, and co-first author of the new study. "But by comparing the methods in this way, our results can help researchers draw their own conclusions about which method to use in their own work." Cell profiles While the study was not designed to make new biological conclusions about metastatic breast tumors, the researchers noted that they were surprised by how stable RNA patterns were within patients during disease progression, even over long periods of time and across sites in the body.
They also found three distinct spatial patterns of an important cancer program, and observed specific changes in gene expression in cancer cells when immune cells physically infiltrated metastatic tumors. "Because we selected samples to span the clinical diversity of metastatic breast cancer, we had limited statistical power to draw definite conclusions on biological questions regarding specific biologic subtypes or clinical scenarios," said co-first author Daniel Abravanel, an associate member of the Broad, a physician-scientist at Dana-Farber Cancer Institute, and an instructor at Harvard Medical School. "However, this heterogeneity enabled the evaluation of the impact of these variables on metastatic breast cancer and contributed exciting new evidence for emerging hypotheses.
" Using the methods that they validated in the study, the researchers now hope to begin asking more pointed biomedical questions, such as how cells within a biopsy change before and after immunotherapy, which could help explain why some metastatic breast cancers respond better than others to this treatment. They also say that while their work was limited to metastatic breast cancers, it could have implications for researchers studying other tumor types. More information: Johanna Klughammer et al, A multi-modal single-cell and spatial expression map of metastatic breast cancer biopsies across clinicopathological features, Nature Medicine (2024).
DOI: 10.1038/s41591-024-03215-z.
