[Advances in three-dimensional tumor models for colorectal cancer]

Conventional tumor culture models include two-dimensional tumor cell cultures and xenograft models. The former has disadvantages including lack of tumor heterogeneity and poor clinical relevance, while the latter are limited by the slow growth, low engraftment successful rate, and high cost. In recent years, in vitro three-dimensional (3D) tumor models have emerged as the tool to better recapitulate the spatial structure and the in vivo environment of tumors. In addition, they preserve the pathological and genetic features of tumor cells and reflect the complex intracellular and extracellular interactions of tumors, which have become a powerful tool for investigating the tumor mechanism, drug screening, and personalized cancer treatment. 3D tumor model technologies such as spheroids, organoids, and microfluidic devices are maturing. Application of new technologies such as co-culture, 3D bioprinting, and air-liquid interface has further improved the clinical relevance of the models. Some models recapitulate the tumor microenvironment, and some can even reconstitute endogenous immune components and microvasculature. In recent years, some scholars have combined xenograft models with organoid technology to develop matched in vivo/in vitro model biobanks, giving full play to the advantages of the two technologies, and providing an ideal research platform for individualized precision therapy for specific molecular targets in certain subtypes of tumors. So far, the above technologies have been widely applied in the field of colorectal cancer research. Our research team is currently studying upon the application of patient-derived tumor cell-like clusters, a self-assembly 3D tumor model, in guiding the selection of postoperative chemotherapy regimens for colorectal cancer. A high modeling success rate and satisfactory results in the drug screening experiments have been achieved. There is no doubt that with the advancement of related technologies, 3D tumor models will play an increasingly important role in the research and clinical practice of colorectal cancer.