Current trends in targeted therapy of leukaemia and lymphoma

Abstract

Decades of cancer and leukaemia research have provided priceless insight into the molecular mechanisms underlying the development and maintenance of malignancies. The ultimate goal of these findings was, and still is, discovering discriminating factors enabling detection or treatment of tumour cells. An important achievement in this field has been the integration of protein chemistry, fluorescence detectors, nanoparticles, optical devices and computational devolvement integrated in the field of flow cytometry, fluorescence activated cell sorting FACS, data analysis and visualisation. Especially important is the onset of computational data mining tools like T-distributed Stochastic Neighbor Embedding (t- SNE), developed by van der Maatenand Hinton and further continuous progress of the machine learning algorithms for visualization of the huge amount of data produced from single cell FACS or mass cytometry analysis.