Enhancing Precision Oncology: Preclinical Assessment of Individual Drug Treatment Susceptibility Using Patient-Derived 3D Microtumor and Immune Cell Co-cultures

Abstract

Despite 50 years of dedicated efforts in the "War on Cancer", the results achieved in treating cancer have been regrettably unsatisfactory. Particularly challenging are tumors characterized by high inter- and intratumoral heterogeneity and an advanced stage. These complex cancers, including ovarian, breast and glioblastoma, present significant barriers to effective therapy. Nowadays, the healthcare system faces two major issues in cancer treatment: low success rates of newly approved anti-cancer drugs and ineffective treatments leading to adverse side effects in patients. The ability to pre-select and pre-determine individualized treatment options prior to clinical care, as envisioned in the context of personalized medicine, could thus facilitate therapeutic decision making and ultimately improve patient outcomes. This will require advances in the implementation of diagnostic tools for detailed and accurate patient stratification, and advances in the prediction of patient-specific response to treatment. To enable preclinical validation of anticancer drug efficacy in personalized cancer therapy, it is crucial to develop patient-derived tumor models that mirror the unique complexity of individual tumors and account for the significant impact of the tumor microenvironment and cellular diversity on drug response. In this context, this study presents an ex vivo tumor model composed of patient-derived 3D microtumors (PDM) and autologous tumor-infiltrating immune cells (TIL), established and validated for ovarian cancer, breast cancer, and glioblastoma patients to identify individual tumor vulnerabilities. By limited digestion and subsequent culture in defined media, PDM and TIL cultures with high viability were successfully generated from freshly resected primary tumors. In- depth histopathological, immunohistological and proteomic analyses of PDM and corresponding primary tumors were performed and confirmed conserved subtype- specific histology, tumor marker expression, and the presence of tumor microenvironment components including extracellular matrix, tumor-associated macrophages, and cancer-associated fibroblasts. Comprehensive protein profiling of up to 200 analytes was performed in both primary tumors and PDM with limited sample material using advanced technologies such as DigiWest® and RPPA immunoassay screening. The preservation of molecular protein signatures and molecular heterogeneity of the original primary tumor in PDM was confirmed by the extensive protein data obtained. Functional drug testing on PDM and PDM-TIL co-cultures with small molecules, chemotherapeutic as well as immunotherapeutic agents identified tumors sensitive to specific treatments, enabling the prediction of individual therapeutic susceptibility. In combination with the collected proteomic data, molecular protein signatures have been revealed that correlate with treatment response and resistance. The clinical utility of PDM is based on their efficient isolation process, time-saving generation, ethical non-animal culture conditions, patient-specific representation, preservation of tissue architecture and TME components, and compatibility with various downstream readout technologies. These combined advantages position PDM as a powerful and versatile tool that holds great promise for drug mode of action analyses, biomarker identification and personalized therapeutic sensitivity prediction.