Image Source: Kateryna Kon | Shutterstock
The study used positron emission tomography (PET) combined with electron microscopy to generate three-dimensional super-resolution maps of mitochondrial networks in lung tumors of genetically engineered mice. The research team used deep learning (Deep Learning) technology to classify tumors according to mitochondrial activity and other factors.
Mitochondria (mitochondrion) is the “energy factory” of the cell. There is a set of genetic materials independent of the nucleus in the mitochondria – mitochondrial DNA (mtDNA). Due to the important role of mitochondria in energy homeostasis, mitochondrial dysfunction contributes to the occurrence of a variety of diseases, including developmental disorders, neuromuscular diseases, metabolic diseases, cancer progression, and so on.
Although scientists have long known that mitochondria play a crucial role in the metabolism and energy production of cancer cells. However, until now, little is known about the relationship between the structural organization of the mitochondrial network and its functional bioenergetic activity at the whole tumor level.
Recently, researchers from UCLA published a research paper entitled: Spatial mapping of mitochondrial networks and bioenergetics in lung cancer in the journal Nature.
The study used positron emission tomography (PET) combined with electron microscopy to generate three-dimensional super-resolution maps of mitochondrial networks in lung tumors of genetically engineered mice. Using deep learning techniques to classify tumors based on mitochondrial activity and other factors, the research team quantified the mitochondrial structure of hundreds of thousands of cells and thousands of mitochondria throughout the tumor.
The research team examined two major subtypes of non-small cell lung cancer ( NSCLC ) — lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) — and found distinct subsets of mitochondrial networks in these tumors. Importantly, they found that mitochondria often organize with lipid droplets to create unique subcellular structures that support tumor cell metabolism and mitochondrial activity.
Mitochondria, which are critical to the control of the metabolism and bioenergetics of cancer cells, form highly organized networks in which the structure of their inner and outer membranes determines their bioenergetic capacity. However, studies describing the relationship between the structural organization of the mitochondrial network and its bioenergetic activity in vivo remain limited.
In this study, the research team used an integrated platform consisting of positron emission tomography imaging, respirometry, and 3D scanning block electron microscopy to perform in vivo studies of mitochondrial networks and bioenergetic phenotypes in non-small cell lung cancer (NSCLC). Structural and functional analysis.
The different bioenergetic phenotypes and metabolic dependencies that the research team found in NSCLC tumors are consistent with the different structural organization of the mitochondrial network that exists. In addition, the study found that the mitochondrial network is organized into distinct regions in tumor cells.
In tumors with high rates of oxidative phosphorylation and fatty acid oxidation, a mitochondrial network in which mitochondria contact and surround lipid droplets is found. Whereas, in tumors with low oxidative phosphorylation rates, high glucose flux modulates perinuclear localization of mitochondria, cristae remodeling, and mitochondrial respiratory capacity. These findings suggest that in non-small cell lung cancer (NSCLC), the mitochondrial network is divided into distinct subpopulations that control the bioenergetic capacity of the tumor.
According to the research team, this study represents the first step in generating a high-resolution, three-dimensional atlas of lung cancer using a genetically engineered mouse model. Using these maps, the research team has begun to further create a structural and functional map of lung tumors, which helps to understand how tumor cells structurally organize their cellular structure in response to the high metabolic demands of tumor growth. These findings also provide critical information about mitochondrial function in cancer cells, which are expected to provide new information and improved methods for current cancer treatment strategies, while pointing a new direction for targeting lung cancer.
Dr. Han Mingqi, the first author of the paper, said that this study found new findings in the metabolic flux of lung cancer, revealing that the nutritional preference of lung cancer cells may be determined by the subcellular compartmentation of their mitochondria and other organelles, either on glucose or on free fatty acids. This finding has important implications for the development of effective anticancer therapies targeting tumor-specific nutritional preferences. The multimodal imaging approach has allowed us to reveal this previously unknown aspect of cancer metabolism, which we believe can also be applied to other types of cancer, paving the way for further research in this area.
Reference:
Spatial mapping of mitochondrial networks and bioenergetics in lung cancer. Nature, 2023 Mar 15. doi: 10.1038/s41586-023-05793-3.
