Rapid and Short-term Extracellular Matrix-mediated In Vitro Culturing of Tumor and Nontumor Human Primary Prostate Cells From Fresh Radical Prostatectomy Tissue

Live-cell phenotypic-biomarker microfluidic assay for the risk stratification of cancer patients via machine learning

“…A successful risk stratification test needs to mitigate the complexities of tumour heterogeneity and of the tumour microenvironment, and be able to predict post-surgical adverse pathologies. STRAT-AP includes five distinct components: a defined extracellular-matrix formulation designed for primary-cell adhesion, survival and for the measurement of relevant biomarkers 19 (Supplementary Methods), a suite of dynamic and static molecular and cellular phenotypic biomarkers (Supplementary Methods), a microfluidic device for high-throughput live-cell and fixed-cell imaging (Methods and Supplementary Methods), machine-vision software to objectively measure biomarkers (Supplementary Methods) and machine-learning algorithms (Supplementary Methods) to generate clinically relevant scores that predict postsurgery adverse pathology states related to the local growth and metastatic behaviour of single, tumour-derived, primary biopsied cells 19–23 , and ultimately to the patient tumour samples.…”

“…The assay has been designed as a clinically relevant and actionable laboratory-developed test 24 . Sample-handling and rapid-culturing conditions were established to develop, from tumour samples, single-cell suspensions and short-term cell cultures (<72 h) enriched with epithelial cells 19 (see Methods). Cells derived from patient biopsies were placed on an ECMf-coated microfluidic device (Fig.…”

“…Phenotypic biomarkers can be used in cancer diagnosis and in risk stratification because of the inherent genetic heterogeneity of cancer 15–17 . Direct evaluation of the dynamic phenotypic behaviour of single, living tumour cells grown in a controlled microenvironment could provide deeper insights into multiple and coordinated signalling pathways, and offer an improved risk stratification and diagnostic tool 18,19 . Previous attempts to analyse dynamic biomarkers from single cells derived from primary biopsy tissue have been limited by inherent difficulties in culturing primary tumour cells (particularly prostate cells).…”

“…1). The assay uses live-cell phenotypic biomarkers—including protein localization, protein dynamics, protein modification state, cytoskeletal dynamics, membrane dynamics, cell morphology and cell motility—and leverages machine vision and machine learning to overcome the limitations of traditional, static, formalin-fixed histochemical biomarker analysis and also genomic tests that measure a small number of selected genes 19–23 from bulk and static formalin-fixed tissue samples. The assay requires an extracellular-matrix formulation (ECMf; ref.…”

“…The assay requires an extracellular-matrix formulation (ECMf; ref. 19 and Supplementary Methods) that enables rapid culture (<72 h) of primary cancer cells and the measurement of previously inaccessible live-cell phenotypic biomarkers, as well as custom machine-vision software and machine-learning algorithms (Supplementary Methods) that quantify both live-cell and fixed-cell molecular and cellular phenotypic biomarkers from single cells to generate predictive scores via specific machine-learning algorithms for a given prediction 18 .…”