**Abstract:** A cross-disciplinary team led by researchers from the Department of Mechanical Engineering at Tsinghua University, in collaboration with the Department of Automation at the same university and other institutions including Peking University Cancer Hospital, has developed a novel personalized lung cancer assembloid model (LCAs). This model leverages droplet microfluidic technology to rapidly and precisely construct a tumor microenvironment that exhibits heterogeneity, including immune microenvironment, which is crucial for tumor research and treatment evaluation. The model addresses key limitations of current tumor organoid models, such as the lack of a representative tumor microenvironment and poor batch-to-batch consistency. The team's innovation involves the use of a microfluidic droplet system and a biocompatible hydrogel material designed to maintain the viability of various primary cells during co-culture. By encapsulating patient-derived lung cancer organoids (LCOs) and multiple types of tumor microenvironment cells within the hydrogel, the researchers can form the LCAs through fluid shear, light curing, and rapid culture. This technique allows for the precise control of cell loading from clinical biopsy samples, which are often limited in quantity, and the LCAs can be directly cryopreserved and thawed for later use. The study comprehensively demonstrates the similarity of the LCAs to in vivo tumors at molecular, cellular, and tissue levels. Through drug screening experiments and clinical drug response prediction tests, the researchers have validated the LCAs as a precise model for personalized treatment and drug screening. This development holds significant potential for translational applications in cancer treatment, offering a more accurate and reliable tool for predicting patient responses to various drugs and for advancing the field of precision oncology. The research findings were published in the journal *Nature Communications* on April 20, 2024, under the title "A Patient-Specific Lung Cancer Assembloid Model with Heterogeneous Tumor Microenvironments." The paper's first authors are Dr. Yanmei Zhang, formerly a postdoctoral researcher at Tsinghua University's Department of Mechanical Engineering and now a researcher at the Beijing Academy of Science and Technology, and Qifan Hu, a doctoral student in the Department of Automation at Tsinghua University. Dr. Yukan Pei, a deputy chief physician at Peking University Cancer Hospital, is also a first author. The corresponding authors are Professor Zhuo Xiong from the Department of Mechanical Engineering and Associate Professor Jin Gu from the Department of Automation at Tsinghua University. The research was a collaborative effort involving researchers from Tsinghua University's Department of Mechanical Engineering and Department of Automation, the Beijing Academy of Science and Technology, Peking University Cancer Hospital, the PLA General Hospital, and the National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences. The project was supported by the Tsinghua-Toyota Joint Research Fund and the National Natural Science Foundation for Young Scientists. **Key Elements:** - **Date of Publication:** April 20, 2024 - **Journal:** *Nature Communications* - **Title of the Paper:** "A Patient-Specific Lung Cancer Assembloid Model with Heterogeneous Tumor Microenvironments" - **Lead Researchers:** Professor Zhuo Xiong (Department of Mechanical Engineering, Tsinghua University), Associate Professor Jin Gu (Department of Automation, Tsinghua University) - **First Authors:** Dr. Yanmei Zhang, Qifan Hu, Dr. Yukan Pei - **Collaborating Institutions:** Tsinghua University, Peking University Cancer Hospital, Beijing Academy of Science and Technology, PLA General Hospital, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences - **Funding:** Tsinghua-Toyota Joint Research Fund, National Natural Science Foundation for Young Scientists - **Technology:** Droplet microfluidics, biocompatible hydrogel - **Model:** Lung cancer assembloids (LCAs) - **Advantages:** Improved batch-to-batch consistency, ability to mimic tumor heterogeneity and microenvironment, potential for drug response prediction and personalized treatment This breakthrough in tumor modeling represents a significant step forward in the development of precision medicine for lung cancer, offering a new and more reliable approach to predict patient responses to treatments and to screen potential drugs.