Stimulated Raman Scattering Microscopy Reveals Aberrant Triglyceride Accumulation in Lymphatic Metastasis of Papillary Thyroid Carcinoma.

Lipid metabolic alterations are known to play a crucial role in cancer metastasis. As a key hub in lipid metabolism, intracellular neutral lipid accumulation in lipid droplets (LDs) has become a signature of aggressive human cancers. Nevertheless, it remains unclear whether lipid accumulation displays distinctive features in metastatic lesions compared to the primary ones. Here, we integrated multicolor stimulated Raman scattering (SRS) imaging with confocal Raman spectroscopy on the same platform to quantitatively analyze the amount and composition of LDs in intact human thyroid tissues in situ without any processing or labeling. Inspiringly, we found aberrant accumulation of triglycerides (TGs) in lymphatic metastases but not in normal thyroid, primary papillary thyroid carcinoma (PTC), or normal lymph node. In addition, the unsaturation degree of unsaturated TGs was significantly higher in the lymphatic metastases from patients diagnosed with late-stage (T3/T4) PTC compared to those of patients diagnosed with early-stage (T1/T2) PTC. Furthermore, both public sequencing data analysis and our RNA-seq transcriptomic experiment showed significantly higher expression of alcohol dehydrogenase-1B (ADH1B), which is critical to lipid uptake and transport, in lymphatic metastases relative to the primary ones. In summary, these findings unravel the lipid accumulation as a novel marker and therapeutic target for PTC lymphatic metastasis that has a poor response to the regular radioactive iodine therapy.

Applications of Data Characteristic AI-Assisted Raman Spectroscopy in Pathological Classification.

Raman spectroscopy has been widely used for label-free biomolecular analysis of cells and tissues for pathological diagnosis in vitro and in vivo. AI technology facilitates disease diagnosis based on Raman spectroscopy, including machine learning (PCA and SVM), manifold learning (UMAP), and deep learning (ResNet and AlexNet). However, it is not clear how to optimize the appropriate AI classification model for different types of Raman spectral data. Here, we selected five representative Raman spectral data sets, including endometrial carcinoma, hepatoma extracellular vesicles, bacteria, melanoma cell, diabetic skin, with different characteristics regarding sample size, spectral data size, Raman shift range, tissue sites, Kullback-Leibler (KL) divergence, and significant Raman shifts (i.e., wavenumbers with significant differences between groups), to explore the performance of different AI models (e.g., PCA-SVM, SVM, UMAP-SVM, ResNet or AlexNet). For data set of large spectral data size, Resnet performed better than PCA-SVM and UMAP. By building data characteristic-assisted AI classification model, we optimized the network parameters (e.g., principal components, activation function, and loss function) of AI model based on data size and KL divergence etc. The accuracy improved from 85.1 to 94.6% for endometrial carcinoma grading, from 77.1 to 90.7% for hepatoma extracellular vesicles detection, from 89.3 to 99.7% for melanoma cell detection, from 88.1 to 97.9% for bacterial identification, from 53.7 to 85.5% for diabetic skin screening, and mean time expense of 5 s.

VHL mutation drives human clear cell renal cell carcinoma progression through PI3K/AKT-dependent cholesteryl ester accumulation.

BACKGROUND: Cholesteryl ester (CE) accumulation in intracellular lipid droplets (LDs) is an essential signature of clear cell renal cell carcinoma (ccRCC), but its molecular mechanism and pathological significance remain elusive. METHODS: Enabled by the label-free Raman spectromicroscopy, which integrated stimulated Raman scattering microscopy with confocal Raman spectroscopy on the same platform, we quantitatively analyzed LD distribution and composition at the single cell level in intact ccRCC cell and tissue specimens in situ without any processing or exogenous labeling. Since we found that commonly used ccRCC cell lines actually did not show the CE-rich signature, primary cancer cells were isolated from human tissues to retain the lipid signature of ccRCC with CE level as high as the original tissue, which offers a preferable cell model for the study of cholesterol metabolism in ccRCC. Moreover, we established a patient-derived xenograft (PDX) mouse model that retained the CE-rich phenotype of human ccRCC. FINDINGS: Surprisingly, our results revealed that CE accumulation was induced by tumor suppressor VHL mutation, the most common mutation of ccRCC. Moreover, VHL mutation was found to promote CE accumulation by upregulating HIFα and subsequent PI3K/AKT/mTOR/SREBPs pathway. Inspiringly, inhibition of cholesterol esterification remarkably suppressed ccRCC aggressiveness in vitro and in vivo with negligible toxicity, through the reduced membrane cholesterol-mediated downregulations of integrin and MAPK signaling pathways. INTERPRETATION: Collectively, our study improves current understanding of the role of CE accumulation in ccRCC and opens up new opportunities for treatment. FUNDING: This work was supported by National Natural Science Foundation of China (No. U23B2046 and No. 62027824), National Key R&D Program of China (No. 2023YFC2415500), Fundamental Research Funds for the Central Universities (No. YWF-22-L-547), PKU-Baidu Fund (No. 2020BD033), Peking University First Hospital Scientific and Technological Achievement Transformation Incubation Guidance Fund (No. 2022CX02), and Beijing Municipal Health Commission (No. 2020-2Z-40713).

Coupling of Perinuclear Actin Cap and Nuclear Mechanics in Regulating Flow-Induced Yap Spatiotemporal Nucleocytoplasmic Transport.

Mechanical forces, including flow shear stress, govern fundamental cellular processes by modulating nucleocytoplasmic transport of transcription factors like Yes-associated Protein (YAP). However, the underlying mechanical mechanism remains elusive. In this study, it is reported that unidirectional flow induces biphasic YAP transport with initial nuclear import, followed by nuclear export as actin cap formation and nuclear stiffening. Conversely, pathological oscillatory flow induces slight actin cap formation, nuclear softening, and sustained YAP nuclear localization. To elucidate the disparately YAP spatiotemporal distribution, a 3D mechanochemical model is developed, which integrates flow sensing, cytoskeleton organization, nucleus mechanotransduction, and YAP transport. The results unveiled that despite the significant localized nuclear stress imposed by the actin cap, its inherent stiffness counteracts the dispersed contractile stress exerted by conventional fibers on the nuclear membrane. Moreover, alterations in nuclear stiffness synergistically regulate nuclear deformation, thereby governing YAP transport. Furthermore, by expanding the single-cell model to a collective vertex framework, it is revealed that the irregularities in actin cap formation within individual cells have the potential to induce topological defects and spatially heterogeneous YAP distribution in the cellular monolayer. This work unveils a unified mechanism of flow-induced nucleocytoplasmic transport, providing a linkage between transcription factor localization and mechanical stimulation.

Label-Free Raman Spectromicroscopy Unravels the Relationship between MGMT Methylation and Intracellular Lipid Accumulation in Glioblastoma.

Temozolomide (TMZ) is considered a first line chemotherapy drug for glioblastoma (GBM). Unfortunately, the GBM without methylation of O6-methylguanine-DNA methyltransferase (MGMT), accounting for about 70% of all GBM, shows an inherent resistance to TMZ treatment. Aberrant accumulation of neutral lipids, primarily triglycerides (TGs) and cholesteryl esters (CEs), in lipid droplets (LDs) has been recognized as metabolic vulnerability for GBM therapy. However, it is not known whether MGMT methylation affects lipid accumulation in GBM. Herein, we employed label-free Raman spectromicroscopy, which integrated stimulated Raman scattering (SRS) microscopy and confocal Raman spectroscopy, to quantitatively analyze both the amount and composition of intracellular LDs in intact GBM tissues obtained from patients who had undergone resection surgery. Our results showed significant reductions in both the LD amount and the CE percentage in MGMT unmethylated GBMs (MGMT methylation < 15%) compared to MGMT methylated ones (MGMT methylation ≥ 15%). Due to a big variation of lipid accumulation in the MGMT methylated GBMs, these patients were further divided into hypermethylated group (MGMT methylation ≥ 50%) and intermediate-methylated group (MGMT methylation 15∼50%), according to the significantly different median survival rates of these two groups. Remarkable differences in LD amount, CE percentage, and also lipid saturation degree were found between the hypermethylated group and the other two groups, but not between the unmethylated and intermediate-methylated groups. To elucidate the possible underlying mechanism, we analyzed the differential expression of lipid metabolism-related genes in GBM with different levels of MGMT methylation using The Cancer Genome Atlas Program (TCGA) dataset. It was shown that the genes related to lipid oxidation and lipid efflux were upregulated, and the genes related to lipid synthesis were downregulated in unmethylated group. These findings unravel the relationship between MGMT methylation and lipid accumulation in GBM, which may offer new opportunities for the diagnosis and treatment of TMZ-resistant GBM.

Insights into asynchronous changes of cell wall polymers accumulated in different cell types during conifer xylem differentiation.

An improved understanding of the events involved in cell wall polymers deposition during xylem development could provide new scientific ways for molecular regulation and biomass utilization. Axial and radial cells are spatially heterogeneous and have highly cross-correlated developmental behavior, whereas the deposition of corresponding cell wall polymers during xylem differentiation is less studied. To clarify our hypothesis that cell wall polymers of two cell types accumulated asynchronously, we performed hierarchical visualization, including label-free in situ spectral imaging of different polymer compositions during the development of Pinus bungeana. In axial tracheids, the deposition of cellulose and glucomannan was observed on earlier stages of secondary wall thickening than that of xylan and lignin, while xylan distribution was strongly related to spatial distribution of lignin during differentiation. The content of lignin and polysaccharides increased by over 130 % and 60 % respectively when the S3 layer was formed, compared to the S2 stage. In ray cells, the deposition of crystalline cellulose, xylan, and lignin was generally lagged compared to that in corresponding axial tracheids, although the process followed a similar order. The concentration of lignin and polysaccharides in ray cells was only approximately 50 % of that in the axial tracheids during secondary wall thickening.

Accurate and Rapid Detection of Peritoneal Metastasis from Gastric Cancer by AI-Assisted Stimulated Raman Molecular Cytology.

Peritoneal metastasis (PM) is the mostcommon form of distant metastasis and one of the leading causes of death in gastriccancer (GC). For locally advanced GC, clinical guidelines recommend peritoneal lavage cytology for intraoperative PM detection. Unfortunately, current peritoneal lavage cytology is limited by low sensitivity (<60%). Here the authors established the stimulated Raman molecular cytology (SRMC), a chemical microscopy-based intelligent cytology. The authors firstly imaged 53 951 exfoliated cells in ascites obtained from 80 GC patients (27 PM positive, 53 PM negative). Then, the authors revealed 12 single cell features of morphology and composition that are significantly different between PM positive and negative specimens, including cellular area, lipid protein ratio, etc. Importantly, the authors developed a single cell phenotyping algorithm to further transform the above raw features to feature matrix. Such matrix is crucial to identify the significant marker cell cluster, the divergence of which is finally used to differentiate the PM positive and negative. Compared with histopathology, the gold standard of PM detection, their SRMC method could reach 81.5% sensitivity, 84.9% specificity, and the AUC of 0.85, within 20 minutes for each patient. Together, their SRMC method shows great potential for accurate and rapid detection of PM from GC.

Stimulated Raman Scattering Imaging Sheds New Light on Lipid Droplet Biology.

A lipid droplet (LD) is a dynamic organelle closely associated with cellular functions and energy homeostasis. Dysregulated LD biology underlies an increasing number of human diseases, including metabolic disease, cancer, and neurodegenerative disorder. Commonly used lipid staining and analytical tools have difficulty providing the information regarding LD distribution and composition at the same time. To address this problem, stimulated Raman scattering (SRS) microscopy uses the intrinsic chemical contrast of biomolecules to achieve both direct visualization of LD dynamics and quantitative analysis of LD composition with high molecular selectivity at the subcellular level. Recent developments of Raman tags have further enhanced sensitivity and specificity of SRS imaging without perturbing molecular activity. With these advantages, SRS microscopy has offered great promise for deciphering LD metabolism in single live cells. This article overviews and discusses the latest applications of SRS microscopy as an emerging platform to dissect LD biology in health and disease.

The role of altered lipid composition and distribution in liver fibrosis revealed by multimodal nonlinear optical microscopy.

Intracellular lipid accumulation is commonly seen in fibrotic livers, but its exact role in liver fibrosis remains elusive. Here, we established a multimodal nonlinear optical microscopy to quantitatively map distribution of biomolecules in fibrotic livers. Our data revealed that unsaturated triglycerides were predominantly accumulated in central vein area during liver fibrosis but not in portal vein area. Moreover, the lipid homeostasis was remarkably dysregulated in the late-stage compared to the early-stage fibrosis, including increased unsaturated triglycerides with decreased lipid unsaturation degree and decreased membrane fluidity. Such alterations were likely due to up-regulated lipogenesis, desaturation, and peroxidation, which consequently led to endoplasmic reticulum stress and cell death. Inspiringly, injured hepatocyte could be rescued by remodeling lipid homeostasis via either supply of unsaturated fatty acids or enhancement of membrane fluidity. Collectively, our study improves current understanding of the role of lipid homeostasis in fibrosis and open opportunities for treatment.

Cytosolic peptides encoding CaV1 C-termini downregulate the calcium channel activity-neuritogenesis coupling.

L-type Ca2+ (CaV1) channels transduce channel activities into nuclear signals critical to neuritogenesis. Also, standalone peptides encoded by CaV1 DCT (distal carboxyl-terminus) act as nuclear transcription factors reportedly promoting neuritogenesis. Here, by focusing on exemplary CaV1.3 and cortical neurons under basal conditions, we discover that cytosolic DCT peptides downregulate neurite outgrowth by the interactions with CaV1's apo-calmodulin binding motif. Distinct from nuclear DCT, various cytosolic peptides exert a gradient of inhibitory effects on Ca2+ influx via CaV1 channels and neurite extension and arborization, and also the intermediate events including CREB activation and c-Fos expression. The inhibition efficacies of DCT are quantitatively correlated with its binding affinities. Meanwhile, cytosolic inhibition tends to facilitate neuritogenesis indirectly by favoring Ca2+-sensitive nuclear retention of DCT. In summary, DCT peptides as a class of CaV1 inhibitors specifically regulate the channel activity-neuritogenesis coupling in a variant-, affinity-, and localization-dependent manner.

Fiber-optic large-depth 3D chromatic confocal endomicroscopy.

Current endoscopy techniques have difficulties to provide both high resolution and large imaging depth, which significantly hinders the early diagnosis of gastric cancer. Here, we developed a label-free, large-depth, three-dimensional (3D) chromatic reflectance confocal endomicroscopy. In order to solve the problem of insufficient imaging depth of traditional chromatic confocal microscopy, a customized miniature objective lens both with large chromatic focal shift and correction for spherical aberration was used to focus light of different wavelengths at different depths of the sample simultaneously, and a fiber bundle containing 50000 single-mode cores was used to collect the confocal reflectance signal. To acquire detailed information along the axial direction at a faster speed, a high-speed multi-pixel spectrometer was used to realize simultaneous detection of multi-depth signals. Specifically, we have built up a label-free fiber-optic 3D chromatic reflectance confocal endomicroscopy, with 2.3 µm lateral resolution, imaging depth of 570 µm in 3D phantom and 220 µm in tissue, and 1.5 Hz 3D volumetric frame rate. We have demonstrated that the fiber-optic 3D chromatic confocal endomicroscopy can be used to image human gastric tissues ex vivo, and provide important morphological information for diagnosis without labeling. These results show the great potential of the fiber-optic 3D chromatic confocal endomicroscopy for gastric cancer diagnosis.

A rapid procedure for bacterial identification and antimicrobial susceptibility testing directly from positive blood cultures.

There is an urgent need to develop a rapid procedure that can rapidly identify and obtain antimicrobial susceptibility testing (AST) results directly from positive blood cultures. Here, we report a semi-automatic bacterial diagnosis procedure, which includes (1) a bacterial concentration process to isolate bacteria from a positive blood culture bottle (PBCB), (2) an identification process using matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS), and (3) a rapid AST process based on stimulated Raman scattering imaging of deuterium oxide (D2O) incorporation in bacteria. A total of 105 samples were tested for bacterial identification, and a bacterial identification accuracy of 92.3% was achieved. AST takes about 2.5 h after identification. This semi-automatic procedure only takes 3.5 h, which is demonstrated to be the fastest process to obtain identification and AST results starting from PBCBs.

Distinct BTK inhibitors differentially induce apoptosis but similarly suppress chemotaxis and lipid accumulation in mantle cell lymphoma.

BACKGROUND: The more selective second-generation BTK inhibitors (BTKi) Acalabrutinib and Zanubrutinib and the first-generation BTKi Ibrutinib are highlighted by their clinical effectiveness in mantle cell lymphoma (MCL), however, similarities and differences of their biological and molecular effects on anti-survival of MCL cells induced by these BTKi with distinct binding selectivity against BTK remain largely unknown. METHODS: AlamarBlue assays were performed to define cytotoxicity of BTKi against MCL cells, Jeko-1 and Mino. Cleaved PARP and caspase-3 levels were examined by immunoblot analysis to study BTKi-induced apoptotic effects. Biological effects of BTKi on MCL-cell chemotaxis and lipid droplet (LD) accumulation were examined in Jeko-1, Mino and primary MCL cells via Transwell and Stimulated Raman scattering imaging analysis respectively. Enzyme-linked immunoassays were used to determine CCL3 and CCL4 levels in MCL-cell culture supernatants. RNA-seq analyses identified BTKi targets which were validated by quantitative RT-PCR (qRT-PCR) and immunoblot analysis. RESULTS: Acalabrutinib and Zanubrutinib induced moderate apoptosis in Ibrutinib high-sensitive JeKo-1 cells and Ibrutinib low-sensitive Mino cells, which was accompanied by cleaved PARP and caspase-3. Such effects might be caused by the stronger ability of Ibrutinib to upregulate the expression of pro-apoptotic genes, such as HRK, GADD45A, and ATM, in JeKo-1 cells than in Mino cells, and the expression of such apoptotic genes was slightly changed by Acalabrutinib and Zanubrutinib in both JeKo-1 and Mino cells. Further, Acalabrutinib, Zanubrutinib and Ibrutinib reduced MCL-cell chemotaxis with similar efficiency, due to their similar abilities to downmodulate chemokines, such as CCL3 and CCL4. Also, these three BTKi similarly suppressed MCL-cell LD accumulation via downregulating lipogenic factors, DGAT2, SCD, ENPP2 and ACACA without significant differences. CONCLUSION: BTKi demonstrated differential capacities to induce MCL-cell apoptosis due to their distinct capabilities to regulate the expression of apoptosis-related genes, and similar biological and molecular inhibitory effects on MCL-cell chemotaxis and LD accumulation.

Direct mapping from diffuse reflectance to chromophore concentrations in multi-fx spatial frequency domain imaging (SFDI) with a deep residual network (DRN).

Spatial frequency domain imaging (SFDI) is an emerging technology that enables label-free, non-contact, and wide-field mapping of tissue chromophore contents, such as oxy- and deoxy-hemoglobin concentrations. It has been shown that the use of more than two spatial frequencies (multi-fx ) can vastly improve measurement accuracy and reduce chromophore estimation uncertainties, but real-time multi-fx SFDI for chromophore monitoring has been limited in practice due to the slow speed of available chromophore inversion algorithms. Existing inversion algorithms have to first convert the multi-fx diffuse reflectance to optical absorptions, and then solve a set of linear equations to estimate chromophore concentrations. In this work, we present a deep learning framework, noted as a deep residual network (DRN), that is able to directly map from diffuse reflectance to chromophore concentrations. The proposed DRN is over 10x faster than the state-of-the-art method for chromophore inversion and enables 25x improvement on the frame rate for in vivo real-time oxygenation mapping. The proposed deep learning model will help enable real-time and highly accurate chromophore monitoring with multi-fx SFDI.

Coherent Raman Scattering Microscopy in Oncology Pharmacokinetic Research.

The high attrition rates of anti-cancer drugs during clinical development remains a bottleneck problem in pharmaceutical industry. This is partially due to the lack of quantitative, selective, and rapid readouts of anti-cancer drug activity in situ with high resolution. Although fluorescence microscopy has been commonly used in oncology pharmacological research, fluorescent labels are often too large in size for small drug molecules, and thus may disturb the function or metabolism of these molecules. Such challenge can be overcome by coherent Raman scattering microscopy, which is capable of chemically selective, highly sensitive, high spatial resolution, and high-speed imaging, without the need of any labeling. Coherent Raman scattering microscopy has tremendously improved the understanding of pharmaceutical materials in the solid state, pharmacokinetics of anti-cancer drugs and nanocarriers in vitro and in vivo. This review focuses on the latest applications of coherent Raman scattering microscopy as a new emerging platform to facilitate oncology pharmacokinetic research.

Clear cell renal cell carcinoma detection by multimodal photoacoustic tomography.

There is a need for accurate and rapid detection of renal cancer in clinic. Here, we integrated photoacoustic tomography (PAT) with ultrasound imaging in a single system, which achieved tissue imaging depth about 3 mm and imaging speed about 3.5 cm2/min. We used the wavelength at 1197 nm to map lipid distribution in normal renal tissues and clear cell renal cell carcinoma (ccRCC) tissues collected from 19 patients undergone nephrectomy. Our results indicated that the photoacoustic signal from lipids was significantly higher in ccRCC tissues than that in normal tissues. Moreover, based on the quantification of lipid area ratio, we were able to differentiate normal and ccRCC with 100 % sensitivity, 80 % specificity, and area under receiver operating characteristic curve of 0.95. Our findings demonstrate that multimodal PAT can differentiate normal and ccRCC by integrating the morphologic information from ultrasound and lipid amount information from vibrational PAT.

Antibody-Based Immunotherapeutic Strategies for the Treatment of Hematological Malignancies.

As the most common type of cancer in the world, hematological malignancies (HM) account for 10% of all annual cancer deaths and have attracted more attention. Conventional treatments, such as chemotherapy, radiotherapy, and hematopoietic stem cell transplantation (HSCT), could relieve patients suffering HM. However, serious side effects and high costs bring patients both physical complaints and mental pressure. Recently, compared with conventional therapeutic strategies for HM patients, antibody-based immunotherapies, including cancer vaccines, oncolytic virus therapies, monoclonal antibody treatments, and CAR-T cell therapies, have displayed longer survival time and fewer adverse reactions, even though specific efficacy and safety of these antibody-based immunotherapies still need to be evaluated and improved. This review summarized the advantages of antibody-based immunotherapies over conventional treatments, as well as its existing difficulties and solutions, thereby enhancing the understanding and applications of antibody-based immunotherapies in HM treatment.

Facile Fabrication of Magnetic Microrobots Based on Spirulina Templates for Targeted Delivery and Synergistic Chemo-Photothermal Therapy.

Magnetic microrobots can be actuated in fuel-free conditions and are envisioned for biomedical applications related to targeted delivery and therapy in a minimally invasive manner. However, mass fabrication of microrobots with precise propulsion performance and excellent therapeutic efficacy is still challenging, especially in a predictable and controllable manner. Herein, we propose a facile technique for mass production of magnetic microrobots with multiple functions using Spirulina ( Sp.) as biotemplate. Core-shell-structured Pd@Au nanoparticles (NPs) were synthesized in Sp. cells by electroless deposition, working as photothermal conversion agents. Subsequently, the Fe3O4 NPs were deposited onto the surface of the obtained (Pd@Au)@ Sp. particles via a sol-gel process, enabling them to be magnetically actuated. Moreover, the anticancer drug doxorubicin (DOX) was loaded on the (Pd@Au)/Fe3O4@ Sp. microrobots, which endows them with additional chemotherapeutic efficacy. The as-prepared biohybrid (Pd@Au)/Fe3O4@ Sp.-DOX microrobots not only possess efficient propulsion performance with the highest speed of 526.2 µm/s under a rotating magnetic field but also have enhanced synergistic chemo-photothermal therapeutic efficacy. Furthermore, they can be structurally disassembled into individual particles under near-infrared (NIR) laser irradiation and exhibit pH- and NIR-triggered drug release. These intriguing properties enable the microrobots to be a very promising and efficient platform for drug loading, targeted delivery, and chemo-photothermal therapy.

Raman Spectroscopy and Imaging for Cancer Diagnosis.

Raman scattering has long been used to analyze chemical compositions in biological systems. Owing to its high chemical specificity and noninvasive detection capability, Raman scattering has been widely employed in cancer screening, diagnosis, and intraoperative surgical guidance in the past ten years. In order to overcome the weak signal of spontaneous Raman scattering, coherent Raman scattering and surface-enhanced Raman scattering have been developed and recently applied in the field of cancer research. This review focuses on innovative studies of the use of Raman scattering in cancer diagnosis and their potential to transition from bench to bedside.

Hyperspectral Stimulated Raman Scattering Microscopy Unravels Aberrant Accumulation of Saturated Fat in Human Liver Cancer.

Lipid metabolism is dysregulated in human cancers. The analytical tools that could identify and quantitatively map metabolites in unprocessed human tissues with submicrometer resolution are highly desired. Here, we implemented analytical hyperspectral stimulated Raman scattering microscopy to map the lipid metabolites in situ in normal and cancerous liver tissues from 24 patients. In contrast to the conventional wisdom that unsaturated lipid accumulation enhances tumor cell survival and proliferation, we unexpectedly visualized substantial amount of saturated fat accumulated in cancerous liver tissues, which was not seen in majority of their adjacent normal tissues. Further analysis by mass spectrometry confirmed significant high levels of glyceryl tripalmitate specifically in cancerous liver. These findings suggest that the aberrantly accumulated saturated fat may have great potential to be a metabolic biomarker for liver cancer.