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KAIST team develops smart immune system that can pin down on malignant tumors
A joint research team led by Professor Jung Kyoon Choi of the KAIST Department of Bio and Brain Engineering and Professor Jong-Eun Park of the KAIST Graduate School of Medical Science and Engineering (GSMSE) announced the development of the key technologies to treat cancers using smart immune cells designed based on AI and big data analysis. This technology is expected to be a next-generation immunotherapy that allows precision targeting of tumor cells by having the chimeric antigen receptors (CARs) operate through a logical circuit. Professor Hee Jung An of CHA Bundang Medical Center and Professor Hae-Ock Lee of the Catholic University of Korea also participated in this research to contribute joint effort. Professor Jung Kyoon Choi’s team built a gene expression database from millions of cells, and used this to successfully develop and verify a deep-learning algorithm that could detect the differences in gene expression patterns between tumor cells and normal cells through a logical circuit. CAR immune cells that were fitted with the logic circuits discovered through this methodology could distinguish between tumorous and normal cells as a computer would, and therefore showed potentials to strike only on tumor cells accurately without causing unwanted side effects. This research, conducted by co-first authors Dr. Joonha Kwon of the KAIST Department of Bio and Brain Engineering and Ph.D. candidate Junho Kang of KAIST GSMSE, was published by Nature Biotechnology on February 16, under the title Single-cell mapping of combinatorial target antigens for CAR switches using logic gates. An area in cancer research where the most attempts and advances have been made in recent years is immunotherapy. This field of treatment, which utilizes the patient’s own immune system in order to overcome cancer, has several methods including immune checkpoint inhibitors, cancer vaccines and cellular treatments. Immune cells like CAR-T or CAR-NK equipped with chimera antigen receptors, in particular, can recognize cancer antigens and directly destroy cancer cells. Starting with its success in blood cancer treatment, scientists have been trying to expand the application of CAR cell therapy to treat solid cancer. But there have been difficulties to develop CAR cells with effective killing abilities against solid cancer cells with minimized side effects. Accordingly, in recent years, the development of smarter CAR engineering technologies, i.e., computational logic gates such as AND, OR, and NOT, to effectively target cancer cells has been underway. At this point in time, the research team built a large-scale database for cancer and normal cells to discover the exact genes that are expressed only from cancer cells at a single-cell level. The team followed this up by developing an AI algorithm that could search for a combination of genes that best distinguishes cancer cells from normal cells. This algorithm, in particular, has been used to find a logic circuit that can specifically target cancer cells through cell-level simulations of all gene combinations. CAR-T cells equipped with logic circuits discovered through this methodology are expected to distinguish cancerous cells from normal cells like computers, thereby minimizing side effects and maximizing the effects of chemotherapy. Dr. Joonha Kwon, who is the first author of this paper, said, “this research suggests a new method that hasn’t been tried before. What’s particularly noteworthy is the process in which we found the optimal CAR cell circuit through simulations of millions of individual tumors and normal cells.” He added, “This is an innovative technology that can apply AI and computer logic circuits to immune cell engineering. It would contribute greatly to expanding CAR therapy, which is being successfully used for blood cancer, to solid cancers as well.” This research was funded by the Original Technology Development Project and Research Program for Next Generation Applied Omic of the Korea Research Foundation. Figure 1. A schematic diagram of manufacturing and administration process of CAR therapy and of cancer cell-specific dual targeting using CAR. Figure 2. Deep learning (convolutional neural networks, CNNs) algorithm for selection of dual targets based on gene combination (left) and algorithm for calculating expressing cell fractions by gene combination according to logical circuit (right).
DNA based semiconductor technology developed
Professor Park Hyun Gyu’s research team from the Department of Chemical and Biomolecular Engineering at KAIST has successfully implemented all logic gates using DNA, a feat that led the research to be published as the cover paper for the international nanotechnology paper "Small". Even with the latest technology, it was impossible to create a silicon based semiconductor smaller than 10nm, but because DNA has a thickness of only 2nm, this could lead to the creation of semiconductors with groundbreaking degrees of integration. A 2 nm semiconductor will be able to store 10,000 HD movies within a size of a postage stamp, at least 100 times more than the current 20nm semiconductors. DNAs are comprised of 4 bases which are continually connected: Adenine (A) with Thymine (T), and Guanine (G) with Cytosine (C). For this research, the team used the specific binding properties of DNA, which forms its helix-shape, and a circular molecular beacon that has fluorescent signaling properties under structural changes. The research team used input signals to open and close the circular DNA, the same principle that is applied to logic gates in digital circuits. The output signal was measured using the increase and decrease of the fluorescent signal from the molecular beacon due to the opening and closing of the circular DNA respectively. The team overcame the limited system problems of the existing logic gates and managed to implement all 8 logic gates (AND, OR, XOR, INHIBIT, NAND, NOR, XNOR, IMPlCATION). A multilevel circuit that connects different logic gates was also tested to show its regenerative properties. Professor Park said that “cheap bio-electric devices with high degrees of integration will be made possible by this research” and that “there will be a large difference in the field of molecular level electronic research” Mr. Park Gi Su, a doctoral candidate and the 1st author of this research, said that “a DNA sequence of 10 bases is only 3.4nm long and 2nm thick, which can be used to effectively increase the degree of integration of electronic devices” and that “a bio computer could materialize in the near future through DNA semiconductors with accurate logic gates”. XOR Gate: The output signal 1 comes through the open circular DNA when either input DNA A or input DNA B is present. When both inputs are not present, the flourescent signal does not come through
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