High-Throughput Complex Disease Modeling for Ethical Drug Discovery: Clinical Relevance of a NAM Platform for Cancer Biomarker Development
The development of tumor biomarkers derived from blood, or its components, has become pivotal in advancing early cancer diagnosis. Malignant transformations induce cancer-specific alterations in the transcriptome, proteome, and secretome of tumor cells. Recent studies highlighted similar alterations in peripheral blood mononuclear cells (PBMCs) in cancer patients, which appear to mirror the state of transformation in tumor cells. These findings suggest an intercellular communication–driven mechanism rather than a systemic inflammatory response and, in addition to current ctDNA-based liquid biopsy biomarkers, point to a novel, simple, and highly robust approach for the early detection of cancer. Using this phenomenon to advance PBMC-based biomarker development, it will be essential to achieve 3D in vitro tumor models that reproduce a highly physiological tumor microenvironment (TME). Likewise, more enhanced 3D ex vivo models are required to enable the replication of cell-to-cell and organ-to-organ communication. These systems will guide the self-organization of mixed microenvironments derived from different tissues and enable them to accurately reproduce the molecular connections underlying these alterations. In this study, an innovative new modular 3D co-culturing approach was used to expose PBMCs to lung tumoroids, under physiologically relevant conditions. Changes in DNA fragmentation of PBMCs in the presence of lung cancer were quantified and used as a biomarker. To validate the predictiveness of this biomarker, our results were compared with clinical data from a clinical evaluation study. Similar to the clinical trial observations, PBMCs, when exposed to lung tumoroids, showed a significantly lower level of DNA fragmentation (37%). This modular 3D co-culturing model showed a predictiveness of the clinical data of > 90%, demonstrating its power to monitoring cell-to-cell communication effects and support the development of blood-based biomarkers.