Mitochondria (mitochondrion) is the "energy factory" of the cell. The mitochondria contains a set of genetic material, -- mitochondrial DNA (mtDNA), which is independent of the nucleus. Due to the important role of mitochondria in energy homeostasis, mitochondrial disorders can lead to multiple 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, so far, little is known about the relationship between the structural organization of the mitochondrial network and its functional bioenergetic activity at the overall tumor level.
Researchers at the University of California, Los Angeles, recently published a research paper in the Nature journal, entitled: Spatial mapping of mitochondrial networks and bioenergetics in lung cancer.
This study uses positron emission tomography (PET) coupled with electron microscopy to generate a 3-dimensional super-resolution map of the mitochondrial network in genetically engineered mouse lung tumors. The research team used deep learning (Deep Learning) technology to classify tumors based on mitochondrial activity and other factors to quantify the mitochondrial structure of hundreds of cells and thousands of mitochondria in the entire tumor.
The team examined two major subtypes of -- lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) in non-small cell lung cancer (NSCLC) and identified different subsets of mitochondrial networks in these tumors. Importantly, they found that mitochondria are often organized with lipid droplets to create unique subcellular structures that support tumor cell metabolism and mitochondrial activity.
Mitochondria are essential for the control of metabolism and bioenergetics in cancer cells, forming highly organized networks in which their inner and outer membrane structures determine their bioenergetic capacity. However, studies describing the structural organization of mitochondrial networks and their bioenergetic activity in vivo remain limited.
In this study, the research team used an integrated platform consisting of positron emission tomography imaging, respirometry and three-dimensional scanning block surface electron microscopy to perform in vivo structural and functional analysis of the mitochondrial network and bioenergetic phenotype of non-small cell lung cancer (NSCLC).
The different bioenergy phenotypes and metabolic dependency identified by the research team in NSCLC tumors are consistent with the distinct structural organization of the mitochondrial network present. Furthermore, the study revealed that the mitochondrial network is organized into distinct regions in tumor cells.
A mitochondrial network surrounding droplets that contact and surround lipid droplets was found in tumors with high oxidative phosphorylation and rates of fatty acid oxidation. Whereas in tumors with low oxidative phosphorylation rates, high glucose flux regulates the perinuclear localization of mitochondria, cristae structural remodeling, and mitochondrial respiratory capacity. These results suggest that the mitochondrial network is divided into distinct subpopulations that control the bioenergetic capacity of tumors.
The team says the study represents the first step in generating a high-resolution three-dimensional map of lung cancer using a genetically engineered mouse model. Using these maps, the research team has begun to further create structural and functional maps of lung tumors, which can help to understand how tumor cells structurally organize their cellular structures in response to the high metabolic requirements of tumor growth. These findings also provide key information about mitochondrial function in cancer cells, promising to provide new information and improved approaches for current cancer treatment strategies, while pointing a new direction for targeting lung cancer.
Dr Han Mingqi, the lead author of the paper, said the study found new in the metabolic flux of lung cancer, revealing that the nutritional preferences of lung cancer cells may be determined by the subcellular compartmentalization of their mitochondria and other organelles, either glucose or free fatty acids. This finding has important implications for the development of effective anticancer therapies that target tumor-specific nutritional preferences. The multimodal imaging approach allows us to reveal this previously unknown aspect of cancer metabolism, and we believe it can also be applied to other cancer types, paving the way for further research in this field.
