AI helps reveal how cells change in complex biological environments such as tumors

Tel Aviv University researchers have developed an artificial intelligence (AI) -based scNET system to gain insight into cell behavior changes in complex biological environments such as tumors, which is expected to provide a new approach to disease treatment research.

Xinhua News Agency reported that Tel Aviv University recently issued a communique saying that the current single-cell sequencing technology is becoming increasingly mature, enabling researchers to observe the gene expression characteristics of different cell populations in biological samples and explore its impact on individual cell function. Such studies are especially important in the tumor setting, both to observe the effects of treatment on the cancer cells themselves and to analyze the effects on cancer-promoting or anticancer cells around the tumor. However, the current sequencing technology has some problems, making it difficult for researchers to accurately capture changes in the genetic program that control cell function.

The scNET system integrates single-cell data with a network of gene interactions to map out possible paths of interaction between different genes, the researchers said. This system improves the accuracy of identifying the population of cells in a sample, can reveal the genetic behavior characteristics of cells under different conditions, and can help scientists understand the cellular mechanisms of healthy states and their response to drug treatment.

Focusing on populations of T cells with anti-cancer potential, the team used the new system to clearly observe for the first time how a drug activates the cytotoxic function of T cells to attack tumor cells more effectively, a finding that was previously difficult to identify in traditional analytical methods.

The communique said that scNET demonstrates the great potential of the integration of artificial intelligence and biomedicine, and is expected to reveal the underlying mechanisms of diseases and develop new treatment schemes in the future.

The results of the study have been published in the British scientific journal Nature Methods.