Selective capture of circulating metastatic cancer cell clusters from lung cancer patients reveals a unique genomic profile that identifies anti-metastatic molecular therapeutic targets.
Metastasis remains the leading cause of cancer deaths worldwide and lung cancer, known for its highly metastatic progression, remains among the most lethal of malignancies. The heterogeneous genomic profile of lung cancer metastases is often unknown. Since different metastatic events can selectively spread to multiple organs, strongly suggests more studies are needed to understand and target these different pathways. Unfortunately, access to the primary driver of metastases, the metastatic cancer cell clusters (MCCCs), remains difficult and limited. These metastatic clusters have been shown to be 100-fold more tumorigenic than individual cancer cells. Capturing and characterizing MCCCs is a key limiting factor in efforts to help treat and ultimately prevent cancer metastasis. Elucidating differentially regulated biological pathways in MCCCs will help uncover new therapeutic drug targets to help combat cancer metastases. We demonstrate a novel, proof of principle technology, to capture MCCCs directly from patients whole blood. Our platform can be readily tuned for different solid tumor types by combining a biomimicry-based margination effect coupled with immunoaffinity to isolate MCCCs. Adopting a selective capture approach based on overexpressed CD44 in MCCCs provides a methodology that preferentially isolates them from whole blood. Furthermore, we demonstrate a high capture efficiency of more than 90% when spiking MCCC-like model cell clusters into whole blood. Characterization of the captured MCCCs from lung cancer patients by immunofluorescence staining and genomic analyses, suggests highly differential morphologies and genomic profiles., This study lays the foundation to identify potential drug targets thus unlocking a new area of anti-metastatic therapeutics.