Mariarosaria Boccellino, Mario Santini, Andrea Ballini, Domenico Rossi, Alfonso Fiorelli, Marina Di Domenico, Bianca Maria Nastri, Paolo A. Netti, David Dannhauser, Maria Michela Marino, Salvatore Scacco, Filippo Causa, Rossi, Domenico, Dannhauser, David, Nastri, Bianca Maria, Ballini, Andrea, Fiorelli, Alfonso, Santini, Mario, Netti, Paolo Antonio, Scacco, Salvatore, Marino, Maria Michela, Causa, Filippo, Boccellino, Mariarosaria, Di Domenico, Marina, Rossi, D., Dannhauser, D., Nastri, B. M., Ballini, A., Fiorelli, A., Santini, M., Netti, P. A., Scacco, S., Marino, M. M., Causa, F., Boccellino, M., and Di Domenico, M.
Simple Summary A reliable method for a fast diagnosis of non-small cell lung cancer (NSCLC) would greatly help in improving therapeutic success in personalized medicine approaches. Thus, in the present study, a new idea was proposed: a morphological single-cell analysis approach combined with a microfluidic device for liquid biopsy. The investigation of the NSCLC sample at different culturing times created the possibility of understanding the evolution of different cell types and their morphological changes, making the Circulating Tumour Cells (CTC) predominance against all other cell classes visible. Abstract Background: To date, in personalized medicine approaches, single-cell analyses such as circulating tumour cells (CTC) are able to reveal small structural cell modifications, and therefore can retrieve several biophysical cell properties, such as the cell dimension, the dimensional relationship between the nucleus and the cytoplasm and the optical density of cellular sub-compartments. On this basis, we present in this study a new morphological measurement approach for the detection of vital CTC from pleural washing in individual non-small cell lung cancer (NSCLC) patients. Materials and methods: After a diagnosis of pulmonary malignancy, pleural washing was collected from nine NSCLC patients. The collected samples were processed with a density gradient separation process. Light scattering analysis was performed on a single cell. The results of this analysis were used to obtain the cell’s biophysical pattern and, later on, as basis for Machine Learning (ML) on unknown samples. Results: Morphological single-cell analysis followed by ML show a predictive picture for an NSCLC patient, screening that it is possible to distinguish CTC from other cells. Moreover, we find that the proposed measurement approach was fast, reliable, label-free, identifying and count CTC in a biological fluid. Conclusions: Our findings demonstrate that CTC Biophysical Profile by Pure Light Scattering in NSCLC could be used as a promising diagnostic candidate in NSCLC patients.