Silvia Ghislanzoni

Dr. Silvia Ghislanzoni


Research Focus & Metrics

Academic Career Length

5Years (2022-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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15 September 2023 in Science Advances
Verified
Journal Article
Open access
Arianna BresciArianna Bresci
Arianna Bresci
Jeong Hee KimJeong Hee Kim
Jeong Hee Kim
SGSilvia Ghislanzoni
Silvia Ghislanzoni
FMFrancesco Manetti
Francesco Manetti
LWLintong Wu
Lintong Wu
Dario PolliDario Polli
Dario Polli
Anticancer therapy screening in vitro identifies additional treatments and improves clinical outcomes. Systematically, although most tested cells respond to cues with apoptosis, an appreciable portion enters a senescent state, a critical condition potentially driving tumor resistance and relapse. Conventional screening protocols would strongly benefit from prompt identification and monitoring of therapy-induced senescent (TIS) cells in their native form. We combined complementary all-optical, label-free, and quantitative microscopy techniques, based on coherent Raman scattering, multiphoton absorption, and interferometry, to explore the early onset and progression of this phenotype, which has been understudied in unperturbed conditions. We identified TIS manifestations as early as 24 hours following treatment, consisting of substantial mitochondrial rearrangement and increase of volume and dry mass, followed by accumulation of lipid vesicles starting at 72 hours. This work holds the potential to affect anticancer treatment research, by offering a label-free, rapid, and accurate method to identify initial TIS in tumor cells.

7 November 2023 in Biosensors
Verified
Journal Article
Open access
PDF file
SGSilvia Ghislanzoni
Silvia Ghislanzoni
JKJeon Woong Kang
Jeon Woong Kang
Arianna BresciArianna Bresci
Arianna Bresci
AMAndrea Masella
Andrea Masella
KKKoseki J. Kobayashi-Kirschvink
Koseki J. Kobayashi-Kirschvink
PSPeter T. C. So
Peter T. C. So
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.

21 April 2023 in The International Journal of Biochemistry & Cell Biology
Verified
Journal Article
Open access
SGSilvia Ghislanzoni
Silvia Ghislanzoni
GSGaia Martina Sarcinelli
Gaia Martina Sarcinelli
Arianna BresciArianna Bresci
Arianna Bresci
FMFrancesco Manetti
Francesco Manetti
DPDario Polli
Dario Polli
IBItalia Bongarzone
Italia Bongarzone
Iron chelators, such as deferoxamine, exert an anticancer effect by altering the activity of biomolecules critical for regulation of the cell cycle, cell metabolism, and apoptotic processes. Thus, iron chelators are sometimes used in combination with radio- and/or chemotherapy in the treatment of cancer. The possibility that deferoxamine could induce a program of senescence similar to radio- and/or chemotherapy, fostering adaptation in the treatment of cancer cells, is not fully understood. Using established biochemical techniques, biomarkers linked to lipid composition, and coherent anti-Stokes Raman scattering microscopy, we demonstrated that hepatocellular carcinoma-derived HepG2 cells survive after deferoxamine treatment, acquiring phenotypic traits and representative hallmarks of senescent cells. The results support the view that deferoxamine acts in HepG2 cells to produce oxidative stress-induced senescence by triggering sequential mitochondrial and lysosomal dysfunction accompanied by autophagy blockade. We also focused on the lipidome of senescent cells after deferoxamine treatment. Using mass spectrometry, we found that the deferoxamine-induced senescent cells presented marked remodeling of the phosphoinositol, sulfatide, and cardiolipin profiles, which all play a central role in cell signaling cascades, intracellular membrane trafficking, and mitochondria functions. Detection of alterations in glycosphingolipid sulfate species suggested modifications in ceramide generation, and turnover is frequently described in cancer cell survival and resistance to chemotherapy. Blockade of ceramide generation may explain autophagic default, resistance to apoptosis, and the onset of senescence.

15 July 2024 in The Analyst
Verified
Journal Article
Open access
PDF file
RJRajendhar Junjuri
Rajendhar Junjuri
MCMatteo Calvarese
Matteo Calvarese
MVMohammadSadegh Vafaeinezhad
MohammadSadegh Vafaeinezhad
FVFederico Vernuccio
Federico Vernuccio
MVMarco Ventura
Marco Ventura
Thomas W. BocklitzThomas W. Bocklitz
Thomas W. Bocklitz
Broadband Coherent Anti-Stokes Raman Scattering (BCARS) is a valuable spectroscopic imaging tool for visualizing cellular structures and lipid distributions in biomedical applications. However, the inevitable biological changes in the samples (cells/tissues/lipids) introduce spectral variations in BCARS data and make analysis challenging. In this work, we conducted a systematic study to estimate the biological variance in BCARS data of two commonly used cell lines (HEK293 and HepG2) in biomedical research. The BCARS data were acquired from two different experimental setups (Leibniz Institute of Photonics Technology (IPHT) in Jena and Politecnico di Milano (POLIMI) in Milano) to evaluate the reproducibility of results. Also, spontaneous Raman data were independently acquired at POLIMI to validate those results. First, Kramers–Kronig (KK) algorithm was utilized to retrieve Raman-like signals from the BCARS data, and a pre-processing pipeline was subsequently used to standardize the data. Principal component analysis – Linear discriminant analysis (PCA-LDA) was performed using two cross-validation (CV) methods: batch-out CV and 10-fold CV. Additionally, the analysis was repeated, considering different spectral regions of the data as input to the PCA-LDA. Finally, the classification accuracies of the two BCARS datasets were compared with the results of spontaneous Raman data. The results demonstrated that the CH band region (2770–3070 cm−1) and spectral data in the 1500–1800 cm−1 region have significantly contributed to the classification. A maximum of 100% balanced accuracies were obtained for the 10-fold CV for both BCARS setups. However, in the case of batch-out CV, it is 92.4% for the IPHT dataset and 98.8% for the POLIMI dataset. This study offers a comprehensive overview for estimating biological variance in biomedical applications. The insights gained from this analysis hold promise for improving the reliability of BCARS measurements in biomedical applications, paving the way for more accurate and meaningful spectroscopic analyses in the study of biological systems.

1 January 2022
Verified
Conference Paper
Closed access
PDF file
Arianna BresciArianna Bresci
Arianna Bresci
FMFrancesco Manetti
Francesco Manetti
SGSilvia Ghislanzoni
Silvia Ghislanzoni
BTBenedetta Talone
Benedetta Talone
FVFederico Vernuccio
Federico Vernuccio
Dario PolliDario Polli
Dario Polli
We introduce label-free multimodal nonlinear optical microscopy, based on different coherent Raman and multi-photon ultrafast light-matter interactions, as a noninvasive, quantitative and chemically selective tool to assess chemotherapy-induced senescence in human cancer cells.

10 October 2023 in Preprints.org
Verified
Preprint
Open access
PDF file
SGSilvia Ghislanzoni
Silvia Ghislanzoni
JKJeon Woong Kang
Jeon Woong Kang
ABArianna Bresci
Arianna Bresci
AMAndrea Masella
Andrea Masella
KKKoseki J. Kobayashi-Kirschvink
Koseki J. Kobayashi-Kirschvink
PSPeter T. C. So
Peter T. C. So
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.