Unveiling a Detailed Timeline and Spatial Depiction of Tumor Development: Innovative Tool Reveals Intricate History of Tumor Expansion
In a significant breakthrough, researchers at MIT have developed an innovative lineage tracing tool called PEtracer, which has the potential to revolutionise our understanding of cellular relationships and dynamics in complex tissues. The tool was recently used to study the growth of metastatic tumors in mice, offering deeper insights into the factors influencing tumor evolution in vivo.
The data collected from the study will be invaluable for training AI models of cellular behaviour. PEtracer captures an accurate family tree of cell divisions, combining it with spatial information, enabling detailed analysis of how both intrinsic properties of cancer cells and their microenvironment impact tumor development and progression.
The tumor under investigation was found to be made up of four distinct modules, or neighbourhoods, of cells. The cells at the leading edge of the tumor were more diverse and less fit, while the cells closest to the lung were the most fit, indicating the highest rate of cell division over time. Interestingly, the expression of certain fitness-related genes, such as Fgf1/Fgfbp1, correlated to a cell's location, rather than its ancestry.
Below the leading edge was a low-oxygen neighbourhood of cells that might once have been leading edge cells. Each piece of code in PEtracer is made up of five bases, the building blocks of DNA. The researchers used a gene editing technology called prime editing to insert these marks into the cells' DNA.
The researchers collected tissues from a tumor growing in the lung of a mouse and used advanced imaging approaches to analyse each cell's lineage relationship and spatial position. The findings demonstrate how cancer growth is influenced by both factors intrinsic to certain lineages of cancer cells and by environmental factors that shape the behaviour of cancer cells.
The tumor was also found to have inherited traits that gave the lung-adjacent cells an edge, including expression of the fitness-related gene Cldn4. The researchers plan to apply the PEtracer tool to look at various questions in health and disease, embryonic development, and across other model species.
The researchers are excited to share this technology with other researchers and see what they can discover. They have published their findings in the journal Science on July 24, and the future of cellular research seems to be shining brighter with the advent of PEtracer.
- The innovative lineage tracing tool, PEtracer, developed by MIT researchers, has been published in the journal Science, offering a potential revolution in our understanding of complex tissues.
- The PEtracer tool, when used to study metastatic tumors in mice, provides deep insights into the factors influencing tumor evolution in vivo.
- The data collected from the PEtracer study will be crucial for training AI models of cellular behavior, offering detailed analysis of tumor development and progression.
- PEtracer captures an accurate family tree of cell divisions, combining it with spatial information, making it possible to analyze how both intrinsic properties of cancer cells and their microenvironment impact tumor growth.
- The tumor under investigation was found to have four distinct modules or neighboring areas of cells, with cells closest to the lung being the most fit, indicating the highest rate of cell division.
- Interestingly, the expression of certain fitness-related genes correlated to a cell's location, rather than its ancestry, suggesting that environmental factors play a significant role in cancer cells' behavior.
- PEtracer uses gene editing technology like prime editing to insert marks into the cells' DNA, allowing for precise modifications during the research process.
- The researchers plan to apply the PEtracer tool to various questions in health and disease, embryonic development, and across other model species, expanding the horizons of scientific research in multiple fields.
- The advent of PEtracer in technology promises to shed light on various medical-conditions, health-and-wellness concerns, and advance our understanding of data-and-cloud-computing applications in the field of science and medicine.
