A method to determine the metabolic activity of thousands of individual cells per hour in vitro has been demonstrated by researchers in the US. The team used photoacoustic spectroscopy, in which laser pulses generate an ultrasound signal upon absorption by specific molecules, to measure the degree of oxygen saturation in haemoglobin. Improving significantly on the throughput rate of existing measurement techniques, the new method could give clinicians a more complete picture of tumour heterogeneity, leading to more accurate diagnoses and personalized cancer therapies (Nature Biomed. Eng. 10.1038/s41551-019-0376-5).
One way in which cancer cells differ from healthy cells is in their rate of oxygen consumption. Fast-growing cancers are sustained by correspondingly fast metabolisms, prompting treatments that target cellular metabolic processes. There is a challenge in the fact that cancers, although originating from a single mutated cell, acquire further mutations as they proliferate and can differentiate into a variety of cell types. This means that a typical tumour comprises a diversity of genotypes and phenotypes, and it cannot be assumed that a given treatment will affect the whole tumour equally. Oncologists, then, need a way to determine in detail the range of metabolic characteristics present in a tumour.
Addressing this issue, two collaborating teams led by Jun Zou at Texas A&M University and Lihong Wang at California Institute of Technology have described a way to profile several thousand tumour cells at a time. First, the researchers created an array of microwells, each of which was large enough to hold a single cell and some blood to supply oxygen. The team populated some of these microwells with non-cancerous cells derived from a mouse, some with cells from a human lung-cancer culture, and others with cells from tumours excised from breast-cancer patients.
When the researchers illuminated the microwells with 532 and 559 nm lasers, the energy absorbed by the cells was converted into a pulse of ultrasound that was picked up by an ultrasonic transducer. Oxygenated and deoxygenated haemoglobin have distinct absorption profiles at the two frequencies used, so the team could translate the ultrasound signal into a measure of oxygen saturation. Making one measurement at the start of the experiment and another 15 minutes later, the researchers determined the rate of oxygen consumption for each individual cell.
As predicted, the healthy cells exhibited lower metabolic rates on the whole than the cancer cells. And while the healthy cells showed a near-normal distribution, the metabolic rates of the cancer cells were more chaotically distributed, indicating a high degree of heterogeneity.
The cells also differed in how they responded to hypoxia, which the researchers investigated by supplying healthy and lung-cancer cells with relatively deoxygenated blood. The metabolic rates of both cultures decreased when starved of oxygen, but the effect was more pronounced in the healthy cells. This might seem paradoxical given cancer cells’ usual metabolic profligacy, but Zou has an explanation.
“Because cancer cells consume more oxygen, cells buried deep inside a tumour can sometimes face an insufficient supply, and tend to develop a better adaptation to hypoxia,” says Zou. “This is just like weeds. When dry, they don’t die. When wet, they grow like crazy.”
Hypoxia within tumours is associated with resistance to chemotherapy and radiotherapy, so a better understanding of cancer cells’ behaviour under such conditions is vital. Characterizing the metabolic rate of large numbers of individual cells could also yield information about treatment progress and likely success. Measuring tumour cells’ activity after an initial round of therapy, for example, could indicate whether a tumour is resistant or sensitive to treatment, informing subsequent clinical decisions. Focusing on cancer cells circulating in blood, meanwhile, can help predict a tumour’s metastatic potential, which is linked to cellular metabolic rate.
“We expect the work could have a huge impact on personalized cancer treatment and the development of new cancer drugs,” says Zou. “Furthermore, the entry barrier entry for this technology is low, so it could be used widely.”
