Nanocytometer for smart analysis of peripheral blood and acute myeloid leukemia: a pilot study

• Published in: Nano letters Vol. 20; no. 9; pp. 6572 - 6581
• Main Authors: Schütt, Julian, Sandoval Bojorquez, Diana Isabel, Avitabile, Elisabetta, Oliveros Mata, Eduardo Sergio, Milyukov, Gleb, Colditz, Juliane, Delogu, Lucia Gemma, Rauner, Martina, Feldmann, Anja, Koristka, Stefanie, Middeke, Jan Moritz, Sockel, Katja, Fassbender, Jürgen, Bachmann, Michael, Bornhäuser, Martin, Cuniberti, Gianaurelio, Baraban, Larysa
• Format: Journal Article
• Language: English
• Published: American Chemical Society 09.09.2020
• Subjects: POC diagnostics; acute myeloid leukemia (AML); machine learning for data treatment; PBMCs; impedance cytometer; nanosensor
• ISSN: 1530-6984; 1530-6992; 1530-6992
• DOI: 10.1021/acs.nanolett.0c02300

We realize an ultracompact nanocytometer for real-time impedimetric detection and classification of subpopulations of living cells. Nanoscopic nanowires in a microfluidic channel act as nanocapacitors and measure in real time the change of the amplitude and phase of the output voltage and, thus, the electrical properties of living cells. We perform the cell classification in the human peripheral blood (PBMC) and demonstrate for the first time the possibility to discriminate monocytes and subpopulations of lymphocytes in a label-free format. Further, we demonstrate that the PBMC of acute myeloid leukemia and healthy samples grant the label free identification of the disease. Using the algorithm based on machine learning, we generated specific data patterns to discriminate healthy donors and leukemia patients. Such a solution has the potential to improve the traditional diagnostics approaches with respect to the overall cost and time effort, in a label-free format, and restrictions of the complex data analysis.