Leukemia comprises a diverse group of bone marrow tumors marked by cell proliferation. Current diagnosis involves identifying leukemia subtypes through visual assessment of blood and bone marrow smears, a subjective and time-consuming method. Our study introduces the characterization of different leukemia subtypes using a global clustering approach of Raman hyperspectral maps of cells. We analyzed bone marrow samples from 19 patients, each presenting one of nine distinct leukemia subtypes, by conducting high spatial resolution Raman imaging on 319 cells, generating over 1.3 million spectra in total. An automated preprocessing pipeline followed by a single-step global clustering approach performed over the entire data set identified relevant cellular components (cytoplasm, nucleus, carotenoids, myeloperoxidase (MPO), and hemoglobin (HB)) enabling the unsupervised creation of high-quality pseudostained images at the single-cell level. Furthermore, this approach provided a semiquantitative analysis of cellular component distribution, and multivariate analysis of clustering results revealed the potential of Raman imaging in leukemia research, highlighting both advantages and challenges associated with global clustering.

Wild-type p53 cancer therapy-induced senescent cells frequently engulf and degrade neighboring ones inside a massive vacuole in their cytoplasm. After clearance of the internalized cell, the vacuole persists, seemingly empty, for several hours. Despite large vacuoles being associated with cell death, this process is known to confer a survival advantage to cancer engulfing cells, leading to therapy resistance and tumor relapse. Previous attempts to resolve the vacuolar structure and visualize their content using dyes were unsatisfying for lack of known targets and ineffective dye penetration and/or retention. Here, we overcame this problem by applying optical diffraction tomography and Raman spectroscopy to MCF7 doxorubicin-induced engulfing cells. We demonstrated a real ability of cell tomography and Raman to phenotype complex microstructures, such as cell-in-cells and vacuoles, and detect chemical species in extremely low concentrations within live cells in a completely label-free fashion. We show that vacuoles had a density indistinguishable to the medium, but were not empty, instead contained diluted cell-derived macromolecules, and we could discern vacuoles from medium and cells using their Raman fingerprint. Our approach is useful for the noninvasive investigation of senescent engulfing (and other peculiar) cells in unperturbed conditions, crucial for a better understanding of complex biological processes.

Wild-type p53 cancer therapy-induced senescent cells frequently engulf and degrade neighboring ones inside a massive vacuole in their cytoplasm. After clearance of the internalized cell, the vacuole persists, seemingly empty, for several hours. Despite large vacuoles being associated with cell death, this process is known to confer a survival advantage to cancer engulfing cells, leading to therapy resistance and tumor relapse. Previous attempts to resolve the vacuolar structure and visualize their content using dyes were unsatisfying for lack of known targets and ineffective dye penetration and/or retain. Here, we overcame this problem by applying optical diffraction tomography and Raman spectroscopy to MCF7 doxorubicin-induced engulfing cells. We demonstrated a real ability of cell tomography and Raman to phenotype complex microstructures, such as cell-in-cells and vacuoles, and detect chemical species in extremely low concentrations within live cells in a completely label-free fashion. We show that vacuoles had a density indistinguishable to the medium, but were not empty, instead contained diluted cell-derived macromolecules, and we could discern vacuoles from medium and cells using their Raman fingerprint. Our approach is useful for the non-invasive investigation of senescent engulfing (and other peculiar) cells in unperturbed conditions, crucial for a better understanding of complex biological processes.

Leukemia comprises a diverse group of bone marrow tumors marked by immature cell proliferation. Current diagnosis involves identifying leukemia subtypes through visual assessment of blood and bone marrow smears, a subjective and time-consuming method. Our study introduces the characterization of different leukemia subtypes using a global clustering approach of Raman hyperspectral maps of cells. We analyzed bone marrow samples from 19 patients, each presenting one of nine distinct leukemia subtypes, conducting high spatial resolution Raman imaging on 319 cells, generating over 1.3 million spectra in total. An automated pre-processing pipeline followed by a single-step global clustering approach performed over the entire dataset identified relevant cellular components (cytoplasm, nucleus, carotenoids, myeloperoxidase (MPO) and hemoglobin (HB)) enabling the unsupervised creation of high-quality pseudo-stained images at the single-cell level. Furthermore, this approach provided a semi-quantitative analysis of cellular component distribution, and multivariate analysis of clustering results revealed the potential of Raman imaging in leukemia research, highlighting both advantages and challenges associated with global clustering.

Cardio–oncology is a recent rapid–developing multidisciplinary approach created by oncologists in accordance with cardiologists with the objective to minimize the adverse cardiovascular effects of contemporary cancer therapy and to maximize the benefits that can be obtained from it. Pre–treatment cancer therapy–related cardiovascular toxicity (CTR–CVT) risk assessment can be performed using HFA–ICOS risk assessment tools, in addition to a careful clinical history analysis, physical examination, ECG, biomarkers, and echocardiography. In our study, the analysis of standard and advanced echocardiographic parameters (left atrial strain or LAS, left ventricular global longitudinal strain or GLS, and 3D echocardiography) were performed at baseline, at three, six, and 12 months timepoints. A number of 53 female patients with breast cancer, scheduled to receive chemotherapy, was enrolled. All patients had basal 3D LVEF values ≥ 50% and a basal GLS > –18,5%. Statistically significant reductions (p<0,001) in 3D LVEF at three, six, and 12 months compared to baseline were found, and in all cases 3D LVEF levels were within the reference values (3D LVEF ≥ 50%). GLS and atrial strain parameters (LASr and LASct) were significantly reduced compared to the baseline at 3 months (GLS p<0.01; LASr p<0,001; LASct p<0,001), 6 months (GLS p<0.05; LASr p<0,001; LASct p<0,001) and 12 months (GLS p<0.01; LASr p<0,05; LASct p15% of GLS reduction compared to baseline) after 12 months, and 17 out of 53 patients (32,08%) had atrial dysfunction (expressed by >15% of LASr reduction compared to baseline) after three months. Although atrial dysfunction was not statistically significant in predicting asymptomatic cardiotoxicity (p=0.12), patients with atrial dysfunction at three months have a 3,7 times greater risk of developing asymptomatic cardiotoxicity at 12 months. With our analysis, we found that HFA–ICOS risk score could be considered a predictor of cardiotoxicity at 12 months (p<001). Further studies will be conducted, in order to expand the population and to confirm our results. Open in new tab Download slide Open in new tab Download slide Open in new tab Download slide