Italia Bongarzone

Background: Lipids represent a significant component of the human brain, exerting crucial functions in both physiological and pathological conditions. Mapping brain lipids distribution is an emerging area of research, with mass spectrometry imaging allowing the detection of lipid species and their localization within tissue sections. However, comprehensive spatial mapping of lipids in the human brain remains to be achieved. This systematic review addresses this gap by critically synthesizing the available literature in the field. Methods: A bibliographic search on PubMed, Scopus and Web of Science for original articles employing mass spectrometry imaging to analyze lipids and their distribution in the human brain was performed. The included articles were grouped according to the clinical characteristics of the studied populations, including healthy subjects and selected neurological and psychiatric disorders. Studies on human brain tissue from tumoral specimens, animals, or in vitro models such as organoids were excluded to maintain focus on translational findings directly applicable to human neurological and psychiatric diseases. Results: Following the inclusion criteria, 34 articles were selected. Alzheimer’s disease, schizophrenia and multiple sclerosis were the most frequently investigated conditions, alongside studies in healthy subjects describing lipid distribution under physiological conditions. We observed considerable heterogeneity across studies in terms of research questions and methodological approaches. Nevertheless, our critical synthesis allowed us to identify both consistencies and discrepancies in experimental strategies and in the lipid signatures reported. Conclusions: Studying lipids by mass spectrometry imaging enables the identification of spatially defined profiles in distinct brain areas, providing valuable insights into both human neurobiology and brain disorders’ pathophysiology. In this context, spatial information is crucial for linking lipid alterations to specific structures or lesions, thereby supporting translational applications. Finally, we identified key methodological issues that must be addressed to advance this emerging field.

Despite advances in cancer therapies, treatment failure from resistance and recurrence remains a major clinical challenge. Therapy-induced senescence (TIS), a state of stable cell cycle arrest with sustained metabolic activity, has emerged as a driver of inflammation, tumor persistence, and relapse. However, the heterogeneity of TIS complicates its detection and targeting. Here, we applied a multi-modal strategy to characterize metabolic alterations in senescent cancer cells induced by doxorubicin or γ-irradiation across three tumor cell lines: MCF7, HeLa, and TPC-1. Mitochondrial dysfunction was assessed using MitoTracker and JC-1 staining, while two-photon excitation fluorescence (TPEF) microscopy enabled label-free visualization of intracellular NAD(P)H and FAD distribution. Lipid remodeling was evaluated by MALDI mass spectrometry imaging, and RNA sequencing was performed on control, senescent, and engulfing-senescent MCF7 cells to identify differentially expressed genes and enriched pathways. Senescent cells displayed mitochondrial dysfunction, with altered NAD(P)H/FAD distribution and decreased membrane potential. TPEF confirmed redistribution of coenzymes, reflecting redox changes. Lipidomics revealed consistent remodeling, notably involving cardiolipin precursors. Transcriptomic profiling showed engulfing-senescent MCF7 cells possess a distinct signature marked by increased lipid metabolism, endocrine signaling, and cell–cell communication. Overall, our findings reveal conserved and cell type–specific metabolic traits of TIS, highlighting metabolic vulnerabilities for senolytic intervention.

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.

Even with systemic chemotherapy, cytoreductive surgery (CRS), and hyperthermic intraperitoneal chemotherapy (HIPEC), peritoneal metastases (PM) remain a common site of disease progression for colorectal cancer (CRC) and are frequently associated with a poor prognosis. The mass spectrometry (MS) method known as Matrix-Assisted Laser Desorption/Ionization – Time of Flight (MALDI-TOF) is frequently used in medicine to identify structural compounds and biomarkers. It has been demonstrated that lipids are crucial in mediating the aggressive growth of tumors. In order to investigate the lipid profiles, particularly with regard to histological distribution, we used MALDI-TOF MS (MALDI-MS) and MALDI-TOF imaging MS (MALDI-IMS) on patient-derived tumor organoids (PDOs) and PM clinical samples. According to the MALDI-IMS research shown here, the predominant lipid signature of PDOs in PM tissues, glycosphingolipid (GSL) sulfates or sulfatides, or STs, is unique to the areas containing tumor cells and absent from the surrounding stromal compartments. Bioactive lipids are derived from arachidonic acid (AA), and AA-containing phosphatidylinositol (PI), or PI (18:0–20:4), is shown to be highly expressed in the stromal components. On the other hand, the tumor components contained a higher abundance of PI species with shorter and more saturated acyl chains (C34 and C36 carbons). The cellular subversion of PI and ST species may alter in ways that promote the growth, aggressiveness, and metastasis of tumor cells. Together, these findings suggest that the GSL/ST metabolic programming of PM may contain novel therapeutic targets to impede or halt PM progression.

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.

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.

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.