Patients Lung Derived Tumoroids (PLDTs) to model therapeutic response

[Mechanisms of cancer drug resistance]

Despite decades of research into the molecular mechanisms of cancer and the development of new treatments, drug resistance persists as a major problem. This is in part due to the heterogeneity of cancer, including the diversity of tumor cell lineage and cell plasticity, the spectrum of somatic mutations, the complexity of microenvironments, and immunosuppressive characteristic, then necessitating the use of many different therapeutic approaches. We summarize here the biological causes of resistance, thus offering new perspectives for tackle drug resistance.

In vitro vascularized immunocompetent patient-derived model to test cancer therapies

This work describes a patient-derived tumoroid model (PDTs) to support precision medicine in lung oncology. The use of human adipose tissue-derived microvasculature and patient-derived peripheral blood mononuclear cells (PBMCs) permits to achieve a physiologically relevant tumor microenvironment. This study involved ten patients at various stages of tumor progression. The vascularized, immune-infiltrated PDT model could be obtained within two weeks, matching the requirements of the therapeutic decision. Histological and transcriptomic analyses confirmed that the main features from the original tumor were reproduced. The 3D tumor model could be used to determine the dynamics of response to antiangiogenic therapy and platinum-based chemotherapy. Antiangiogenic therapy showed a significant decrease in vascular endothelial growth factor (VEGF)-A expression, reflecting its therapeutic effect in the model. In an immune-infiltrated PDT model, chemotherapy showed the ability to decrease the levels of lymphocyte activation gene-3 protein (LAG-3), B and T lymphocyte attenuator (BTLA), and inhibitory receptors of T cells functions.

Patient-Derived Tumoroid for the Prediction of Radiotherapy and Chemotherapy Responses in Non-Small-Cell Lung Cancer

Radiation therapy and platinum-based chemotherapy are common treatments for lung cancer patients. Several factors are considered for the low overall survival rate of lung cancer, such as the patient's physical state and the complex heterogeneity of the tumor, which leads to resistance to the treatment. Consequently, precision medicines are needed for the patients to improve their survival and their quality of life. Until now, no patient-derived tumoroid model has been reported to predict the efficiency of radiation therapy in non-small-cell lung cancer. Using our patient-derived tumoroid model, we report that this model could be used to evaluate the efficiency of radiation therapy and cisplatin-based chemotherapy in non-small-cell lung cancer. In addition, these results can be correlated to clinical outcomes of patients, indicating that this patient-derived tumoroid model can predict the response to radiotherapy and chemotherapy in non-small-cell lung cancer.

Advances in the Lung Cancer Immunotherapy Approaches

Despite the progress in the comprehension of LC progression, risk, immunologic control, and treatment choices, it is still the primary cause of cancer-related death. LC cells possess a very low and heterogeneous antigenicity, which allows them to passively evade the anticancer defense of the immune system by educating cytotoxic lymphocytes (CTLs), tumor-infiltrating lymphocytes (TILs), regulatory T cells (Treg), immune checkpoint inhibitors (ICIs), and myeloid-derived suppressor cells (MDSCs). Though ICIs are an important candidate in first-line therapy, consolidation therapy, adjuvant therapy, and other combination therapies involving traditional therapies, the need for new predictive immunotherapy biomarkers remains. Furthermore, ICI-induced resistance after an initial response makes it vital to seek and exploit new targets to benefit greatly from immunotherapy. As ICIs, tumor mutation burden (TMB), and microsatellite instability (MSI) are not ideal LC predictive markers, a multi-parameter analysis of the immune system considering tumor, stroma, and beyond can be the future-oriented predictive marker. The optimal patient selection with a proper adjuvant agent in immunotherapy approaches needs to be still revised. Here, we summarize advances in LC immunotherapy approaches with their clinical and preclinical trials considering cancer models and vaccines and the potential of employing immunology to predict immunotherapy effectiveness in cancer patients and address the viewpoints on future directions. We conclude that the field of lung cancer therapeutics can benefit from the use of combination strategies but with comprehension of their limitations and improvements.

Patient-Derived Lung Tumoroids—An Emerging Technology in Drug Development and Precision Medicine

Synthetic 3D multicellular systems derived from patient tumors, or tumoroids, have been developed to complete the cancer research arsenal and overcome the limits of current preclinical models. They aim to represent the molecular and structural heterogeneity of the tumor micro-environment, and its complex network of interactions, with greater accuracy. They are more predictive of clinical outcomes, of adverse events, and of resistance mechanisms. Thus, they increase the success rate of drug development, and help clinicians in their decision-making process. Lung cancer remains amongst the deadliest of diseases, and still requires intensive research. In this review, we analyze the merits and drawbacks of the current preclinical models used in lung cancer research, and the position of tumoroids. The introduction of immune cells and healthy regulatory cells in autologous tumoroid models has enabled their application to most recent therapeutic concepts. The possibility of deriving tumoroids from primary tumors within reasonable time has opened a direct approach to patient-specific features, supporting their future role in precision medicine.