Meijun He, Ying Wu, Furong Du, Jingrui Wang, H Zhang, Jian Han
Cancer remains a major cause of death worldwide. In 2023, 18.5 million incident cases of cancer and 10.4 million deaths were estimated, excluding non-melanoma skin cancers [ 1 ]. As a significant contributor to the global disease burden, cancer is expected to have increased incidence and mortality rates by 2050. Tumorigenesis is a complex process involving the interaction of multiple factors, and the tumor microenvironment (TME) plays a crucial role in tumor initiation, progression, and metastasis [ 2 ]. Cells in the TME can both inhibit tumor growth and support tumor progression [ 3 ]. Tumor-suppressive cells can recognize and eliminate cancer cells, thereby boosting therapeutic efficacy. In contrast, tumor-promoting cells create an immunosuppressive microenvironment that allows cancer cells to escape immune surveillance, fosters tumor proliferation and invasion, reduces drug penetration, and ultimately leads to drug resistance [ 4 ]. In addition to the TME, tumor heterogeneity, defined as the molecular or genetic variations that arise in tumor daughter cells after repeated division and proliferation during tumor growth, is also a key factor affecting drug response and resistance in cancer treatment [ 5 ]. Owing to tumor heterogeneity, patients with the same type of cancer may experience significantly divergent therapeutic responses to the same anticancer drug [ 6 ]. The dynamic interactions between cancer cells and the TME and the presence of tumor heterogeneity underscore the pressing requirement for the establishment of preclinical models that can accurately predict drug response and resistance.