Label-free imaging and identification of typical cells of acute myeloid leukaemia and myelodysplastic syndrome by Raman microspectroscopy.

In clinical practice, the diagnosis and classification of acute myeloid leukaemia (AML) and myelodysplastic syndrome (MDS) start from the manual examination of stained smears of bone marrow (BM) and peripheral blood (PB) by using an optical microscope. This step is subjective and scarcely reproducible. Therefore, the development of subjective and potentially automatable methods for the recognition of typical AML/MDS cells is necessary. Here we have used Raman spectroscopy for distinguishing myeloblasts, promyelocytes, abnormal promyelocytes and erhytroblasts, which have to be counted for a correct diagnosis and morphological classification of AML and MDS. BM samples from patients affected by four different AML subtypes, mostly characterized by the presence of the four subpopulations selected for this study, were analyzed. First, each cell was scanned by acquiring 4096 spectra, thus obtaining Raman images which demonstrate an accurate description of morphological features characteristic of each subpopulation. Raman imaging coupled with hierarchical cluster analysis permitted the automatic discrimination and localization of the nucleus, the cytoplasm, myeloperoxidase containing granules and haemoglobin. Second, the averaged Raman fingerprint of each cell was analysed by multivariate analysis (principal component analysis and linear discriminant analysis) in order to study the typical vibrational features of each subpopulation and also for the automatic recognition of cells. The leave-one-out cross validation of a Raman-based classification model demonstrated the correct classification of myeloblasts, promyelocytes (normal/abnormal) and erhytroblasts with an accuracy of 100%. Normal and abnormal promyelocytes were distinguished with 95% accuracy. The overall classification accuracy considering the four subpopulations was 98%. This proof-of-concept study shows that Raman micro-spectroscopy could be a valid approach for developing label-free, objective and automatic methods for the morphological classification and counting of cells from AML/MDS patients, in substitution of the manual examination of BM and PB stained smears.

Distinct Chk2 activation pathways are triggered by genistein and DNA-damaging agents in human melanoma cells.

Genistein, a natural isoflavone found in soybeans, exerts a number of biological actions suggesting that it may have a role in cancer prevention. We have previously shown that it potently inhibits OCM-1 melanoma cell proliferation by inducing a G(2) cell cycle arrest. Here we show that genistein exerts this effect by impairing the Cdc25C-dependent Tyr-15 dephosphorylation of Cdk1, as the overexpression of this phosphatase allows the cells to escape G(2) arrest and enter an abnormal chromatin condensation stage. Caffeine totally overrides the genistein-induced G(2) arrest, whereas the block caused by etoposide is not bypassed and that caused by adriamycin is only partially abolished. We also report that genistein activates the checkpoint kinase Chk2 as efficiently as the two genotoxic agents and that caffeine may counteract the activation of Chk2 by genistein but not by etoposide. In contrast, caffeine abolishes the accumulation of p53 caused by all the compounds. Wortmannin does not suppress the Chk2 activation in any situation, suggesting that the ataxia telangiectasia-mutated kinase is not involved in this regulation. Finally, unlike etoposide and adriamycin, genistein induces only a weak response in terms of DNA damage in OCM-1 cells. Taken together, these results suggest that the G(2) checkpoints activated by genistein and the two genotoxic agents involve different pathways.