It’s well known that the engine room of cells, the mitochondria, have a key role in fueling cancer growth. Treatments have targeted these microscopic organelles in many ways, including by blocking their food source to inhibit energy production, knocking them out with a cocktail of drugs and using their output as an early sign of cancer.
Mitochondria are back under the microscope, with scientists capturing their networks in two types of lung cancer tumors, showing their distinct structural organization and its relationship with their energy activity across the region. These detailed, complete maps hold great promise for finding better strategies to target lung cancers.
Researchers from the University of California, Los Angeles’ (UCLA) Jonsson Comprehensive Cancer Center used positron emission tomography and electron microscopy to generate three-dimensional ultra-resolution maps of mitochondrial networks. Using an artificial intelligence technique called deep learning, they measured the architecture across hundreds of cells and thousands of mitochondria within the tumor.
“Our study represents a first step towards generating highly detailed three-dimensional maps of lung tumors using genetically engineered mouse models,” said David Shackelford, associate professor of medicine at UCLA and co-author of the study. “Using these maps, we have begun to create a structural and functional atlas of lung tumors, which has provided us valuable insight into how tumor cells structurally organize their cellular architecture in response to the high metabolic demands of tumor growth. Our findings hold promise to inform and improve current treatment strategies while illuminating new directions from which to target lung cancer.”
Mitochondria are the tiny organelles within cells that process food to release as energy, or cellular respiration, which is essentially the power supply. A better understanding on overall cellular activity within a tumor is vital, given than cancer cells rely heavily on the energy they receive through mitochondrial respiration.
Two main subtypes of cancer were examined, adenocarcinomas LUAD) and squamous-cell carcinomas (LUSC), and the researchers found distinct subpopulations of mitochondrial networks. They also found that mitochondria frequently aligned with organelles such as lipid droplets (fat) to create subcellular structures to support tumor cell metabolism.
"Our study has uncovered a novel finding in the metabolic flux of lung tumors, revealing that their nutrient preference may be determined by the compartmentalization of their mitochondria with other organelles, either relying on glucose (sugar) or free fatty acids (fat),” said Mingqi Han, researcher at UCLA and co-author.
What this means for treatment is that by identifying the architecture of the mitochondria networks, researchers may be better positioned to develop targeted therapies that challenge the structure and the preferred nutrients the cells are requiring at the time.
“This discovery has important implications for developing effective anti-cancer therapies that target tumor-specific nutrient preferences," said Dr. Han. "Our multi-modality imaging approach has enabled us to uncover this previously unknown aspect of cancer metabolism, and we believe that it can be applied to other types of cancer, paving the way for further research in this area."
The researchers believe that their mice study will be the foundation for developing a similar window into the complex world of mitochondrial architecture within human lung tumors.
See the team's 3D ultra-resolution map of the LUAD cancer subtype mitochondrial network in the video below.
The study was published in the journal Nature.
Source: UCLA Health
