Ketomimetic Medium Promotes Metastatic Disposition and Chemoresistance in Breast Cancer Cells through Hypersialylation and Lipid Synthesis.

Although metastasis accounts for the vast majority of cancer-related fatalities, the triggers for the metastatic transformation of breast cancer (BC) cells remain unknown. Recent evidence suggests that a common feature of invasive and resistant cells could be their metabolic state. However, attempts to control metabolic state via nutrient intake, e.g., ketogenic or low carbohydrate diets, have shown inconsistent results with respect to improving chemotherapy efficacy and curbing metastasis. Aiming to decode the molecular mechanisms that alter cell phenotype upon nutrient alteration, we study how a ketomimetic (ketone body-rich, low glucose) medium affects Doxorubicin (DOX) susceptibility and invasive disposition of BC cells. We quantified glycocalyx sialylation and found an inverse correlation with DOX-induced cytotoxicity and DOX internalization. These measurements were coupled with single-cell metabolic imaging, bulk migration studies, and transcriptomic and metabolomic analyses to map the mechanisms involved in ketone body-driven BC cell metabolic maneuvering. Our findings revealed that a ketomimetic medium enhances chemoresistance and invasive disposition of BC cells via two main oncogenic pathways: hypersialylation and lipid accumulation. We propose that the crosstalk between these pathways leads to synthesis of the glycan precursor UDP-GlcNAc, which leads to advancement of a metastatic phenotype in BC cells under ketomimetic conditions.

Enhanced dynamic covalent chemistry for the controlled release of small molecules and biologics from a nanofibrous peptide hydrogel platform.

Maintaining safe and potent pharmaceutical drug levels is often challenging. Multidomain peptides (MDPs) assemble into supramolecular hydrogels with a well-defined, highly porous nanostructure that makes them attractive for drug delivery, yet their ability to extend release is typically limited by rapid drug diffusion. To overcome this challenge, we developed self-assembling boronate ester release (SABER) MDPs capable of engaging in dynamic covalent bonding with payloads containing boronic acids (BAs). As examples, we demonstrate that SABER hydrogels can prolong the release of five BA-containing small-molecule drugs as well as BA-modified insulin and antibodies. Pharmacokinetic studies revealed that SABER hydrogels extended the therapeutic effect of ganfeborole from days to weeks, preventing Mycobacterium tuberculosis growth better than repeated oral administration in an infection model. Similarly, SABER hydrogels extended insulin activity, maintaining normoglycemia for six days in diabetic mice after a single injection. These results suggest that SABER hydrogels present broad potential for clinical translation.

In vitro evaluation of the percutaneous absorption of progesterone in anhydrous permeation-enhancing base using the Franz skin finite dose model and mass spectrometry.

Progesterone is used for hormone replacement therapy through various routes of administration. This study was conducted to (a) evaluate the stability of progesterone in a proprietary anhydrous permeation-enhancing base (APEB) and the efficiency of its skin permeation, and (b) determine the appropriateness of mass spectrometry as a method of analysis for permeated progesterone. Using a proven stability-indicating ultra-performance liquid chromatographic method, the compounded hormone (100 mg progesterone/g APEB gel) was determined to be physically and chemically stable at room temperature for six months. Skin permeation analysis using the Franz skin finite dose model and mass spectrometry imaging showed an optical density of 1699 for the permeated progesterone compounded in APEB and 550 for the permeated progesterone in a water containing VBC, which is a statistically significant different (P = 0.029). The study suggests that APEB can be used as a compounding base for effective skin permeation of progesterone, and mass spectrometry is a reliable method for visualization and quantitative analysis of permeated progesterone.

Molecular, Metabolic, and Subcellular Mapping of the Tumor Immune Microenvironment via 3D Targeted and Non-Targeted Multiplex Multi-Omics Analyses.

Most platforms used for the molecular reconstruction of the tumor-immune microenvironment (TIME) of a solid tumor fail to explore the spatial context of the three-dimensional (3D) space of the tumor at a single-cell resolution, and thus lack information about cell-cell or cell-extracellular matrix (ECM) interactions. To address this issue, a pipeline which integrated multiplex spatially resolved multi-omics platforms was developed to identify crosstalk signaling networks among various cell types and the ECM in the 3D TIME of two FFPE (formalin-fixed paraffin embedded) gynecologic tumor samples. These platforms include non-targeted mass spectrometry imaging (glycans, metabolites, and peptides) and Stereo-seq (spatial transcriptomics) and targeted seqIF (IHC proteomics). The spatially resolved imaging data in a two- and three-dimensional space demonstrated various cellular neighborhoods in both samples. The collection of spatially resolved analytes in a voxel (3D pixel) across serial sections of the tissue was also demonstrated. Data collected from this analytical pipeline were used to construct spatial 3D maps with single-cell resolution, which revealed cell identity, activation, and energized status. These maps will provide not only insights into the molecular basis of spatial cell heterogeneity in the TIME, but also novel predictive biomarkers and therapeutic targets, which can improve patient survival rates.

TNFR1 signaling converging on FGF14 controls neuronal hyperactivity and sickness behavior in experimental cerebral malaria.

BACKGROUND: Excess tumor necrosis factor (TNF) is implicated in the pathogenesis of hyperinflammatory experimental cerebral malaria (eCM), including gliosis, increased levels of fibrin(ogen) in the brain, behavioral changes, and mortality. However, the role of TNF in eCM within the brain parenchyma, particularly directly on neurons, remains underdefined. Here, we investigate electrophysiological consequences of eCM on neuronal excitability and cell signaling mechanisms that contribute to observed phenotypes. METHODS: The split-luciferase complementation assay (LCA) was used to investigate cell signaling mechanisms downstream of tumor necrosis factor receptor 1 (TNFR1) that could contribute to changes in neuronal excitability in eCM. Whole-cell patch-clamp electrophysiology was performed in brain slices from eCM mice to elucidate consequences of infection on CA1 pyramidal neuron excitability and cell signaling mechanisms that contribute to observed phenotypes. Involvement of identified signaling molecules in mediating behavioral changes and sickness behavior observed in eCM were investigated in vivo using genetic silencing. RESULTS: Exploring signaling mechanisms that underlie TNF-induced effects on neuronal excitability, we found that the complex assembly of fibroblast growth factor 14 (FGF14) and the voltage-gated Na+ (Nav) channel 1.6 (Nav1.6) is increased upon tumor necrosis factor receptor 1 (TNFR1) stimulation via Janus Kinase 2 (JAK2). On account of the dependency of hyperinflammatory experimental cerebral malaria (eCM) on TNF, we performed patch-clamp studies in slices from eCM mice and showed that Plasmodium chabaudi infection augments Nav1.6 channel conductance of CA1 pyramidal neurons through the TNFR1-JAK2-FGF14-Nav1.6 signaling network, which leads to hyperexcitability. Hyperexcitability of CA1 pyramidal neurons caused by infection was mitigated via an anti-TNF antibody and genetic silencing of FGF14 in CA1. Furthermore, knockdown of FGF14 in CA1 reduced sickness behavior caused by infection. CONCLUSIONS: FGF14 may represent a therapeutic target for mitigating consequences of TNF-mediated neuroinflammation.

Spatially Resolved Metabolites in Stable and Unstable Human Atherosclerotic Plaques Identified by Mass Spectrometry Imaging.

BACKGROUND: Impairments in carbohydrate, lipid, and amino acid metabolism drive features of plaque instability. However, where these impairments occur within the atheroma remains largely unknown. Therefore, we sought to characterize the spatial distribution of metabolites within stable and unstable atherosclerosis in both the fibrous cap and necrotic core. METHODS: Atherosclerotic tissue specimens from 9 unmatched individuals were scored based on the Stary classification scale and subdivided into stable and unstable atheromas. After performing mass spectrometry imaging on these samples, we identified over 850 metabolite-related peaks. Using MetaboScape, METASPACE, and Human Metabolome Database, we confidently annotated 170 of these metabolites and found over 60 of these were different between stable and unstable atheromas. We then integrated these results with an RNA-sequencing data set comparing stable and unstable human atherosclerosis. RESULTS: Upon integrating our mass spectrometry imaging results with the RNA-sequencing data set, we discovered that pathways related to lipid metabolism and long-chain fatty acids were enriched in stable plaques, whereas reactive oxygen species, aromatic amino acid, and tryptophan metabolism were increased in unstable plaques. In addition, acylcarnitines and acylglycines were increased in stable plaques whereas tryptophan metabolites were enriched in unstable plaques. Evaluating spatial differences in stable plaques revealed lactic acid in the necrotic core, whereas pyruvic acid was elevated in the fibrous cap. In unstable plaques, 5-hydroxyindoleacetic acid was enriched in the fibrous cap. CONCLUSIONS: Our work here represents the first step to defining an atlas of metabolic pathways involved in plaque destabilization in human atherosclerosis. We anticipate this will be a valuable resource and open new avenues of research in cardiovascular disease.

In Situ Imaging of O-Linked ß-N-Acetylglucosamine Using On-Tissue Hydrolysis and MALDI Mass Spectrometry.

Post-translational O-glycosylation of proteins via the addition of N-acetylglucosamine (O-GlcNAc) is a regulator of many aspects of cellular physiology. Processes driven by perturbed dynamics of O-GlcNAcylation modification have been implicated in cancer development. Variability in O-GlcNAcylation is emerging as a metabolic biomarker of many cancers. Here, we evaluate the use of MALDI-mass spectrometry imaging (MSI) to visualize the location of O-GlcNAcylated proteins in tissue sections by mapping GlcNAc that has been released by the enzymatic hydrolysis of glycoproteins using an O-GlcNAc hydrolase. We use this strategy to monitor O-GlcNAc within hepatic VX2 tumor tissue. We show that increased O-GlcNAc is found within both viable tumor and tumor margin regions, implicating GlcNAc in tumor progression.

Spatial intra-tumor heterogeneity is associated with survival of lung adenocarcinoma patients.

Intra-tumor heterogeneity (ITH) of human tumors is important for tumor progression, treatment response, and drug resistance. However, the spatial distribution of ITH remains incompletely understood. Here, we present spatial analysis of ITH in lung adenocarcinomas from 147 patients using multi-region mass spectrometry of >5,000 regions, single-cell copy number sequencing of ~2,000 single cells, and cyclic immunofluorescence of >10 million cells. We identified two distinct spatial patterns among tumors, termed clustered and random geographic diversification (GD). These patterns were observed in the same samples using both proteomic and genomic data. The random proteomic GD pattern, which is characterized by decreased cell adhesion and lower levels of tumor-interacting endothelial cells, was significantly associated with increased risk of recurrence or death in two independent patient cohorts. Our study presents comprehensive spatial mapping of ITH in lung adenocarcinoma and provides insights into the mechanisms and clinical consequences of GD.

Lactate is an epigenetic metabolite that drives survival in model systems of glioblastoma.

Lactate accumulates to a significant amount in glioblastomas (GBMs), the most common primary malignant brain tumor with an unfavorable prognosis. However, it remains unclear whether lactate is metabolized by GBMs. Here, we demonstrated that lactate rescued patient-derived xenograft (PDX) GBM cells from nutrient-deprivation-mediated cell death. Transcriptome analysis, ATAC-seq, and ChIP-seq showed that lactate entertained a signature of oxidative energy metabolism. LC/MS analysis demonstrated that U-13C-lactate elicited substantial labeling of TCA-cycle metabolites, acetyl-CoA, and histone protein acetyl-residues in GBM cells. Lactate enhanced chromatin accessibility and histone acetylation in a manner dependent on oxidative energy metabolism and the ATP-citrate lyase (ACLY). Utilizing orthotopic PDX models of GBM, a combined tracer experiment unraveled that lactate carbons were substantially labeling the TCA-cycle metabolites. Finally, pharmacological blockage of oxidative energy metabolism extended overall survival in two orthotopic PDX models in mice. These results establish lactate metabolism as a novel druggable pathway for GBM.

Are mass spectrometry imaging-based diagnostics becoming reality?

Traditional histological tissue-based diagnostics have been slow and often require large numbers of sections to interrogate for several different proteins with immunohistochemical stains. Often, due to small biopsy size, there is not sufficient material available to carry out all the desired tests on a patient sample. Mass Spectrometry Imaging (MSI) enables the simultaneous detection of hundreds to thousands of analytes from a single tissue section. In recent years, great strides have been made to standardize MSI workflows and data analysis to make it an accessible tool for clinicians to use in patient diagnoses. This commentary highlights the advances by Janßen et al. toward this goal that are discussed in this issue (Proteomics Clin Appl., https://doi.org/10.1002/prca.202100068).

Reduced Hemoglobin Signal and Improved Detection of Endogenous Proteins in Blood-Rich Tissues for MALDI Mass Spectrometry Imaging.

Mass spectrometry imaging provides a powerful approach for the direct analysis and spatial visualization of molecules in tissue sections. Using matrix-assisted laser desorption/ionization mass spectrometry, intact protein imaging has been widely investigated for biomarker analysis and diagnosis in a variety of tissue types and diseases. However, blood-rich or highly vascular tissues present a challenge in molecular imaging due to the high ionization efficiency of hemoglobin, which leads to ion suppression of endogenous proteins. Here, we describe a protocol to selectively reduce hemoglobin signal in blood-rich tissues that can easily be integrated into mass spectrometry imaging workflows.

Differentiation of lymphocytic-plasmacytic enteropathy and small cell lymphoma in cats using histology-guided mass spectrometry.

BACKGROUND: Differentiation of lymphocytic-plasmacytic enteropathy (LPE) from small cell lymphoma (SCL) in cats can be challenging. HYPOTHESIS/OBJECTIVE: Histology-guided mass spectrometry (HGMS) is a suitable method for the differentiation of LPE from SCL in cats. ANIMALS: Forty-one cats with LPE and 52 cats with SCL. METHODS: This is a retrospective clinicopathologic study. Duodenal tissue samples of 17 cats with LPE and 22 cats with SCL were subjected to HGMS, and the acquired data were used to develop a linear discriminate analysis (LDA) machine learning algorithm. The algorithm was subsequently validated using a separate set of 24 cats with LPE and 30 cats with SCL. Cases were classified as LPE or SCL based on a consensus by an expert panel consisting of 5-7 board-certified veterinary specialists. Histopathology, immunohistochemistry, and clonality testing were available for all cats. The panel consensus classification served as a reference for the calculation of test performance parameters. RESULTS: Relative sensitivity, specificity, and accuracy of HGMS were 86.7% (95% confidence interval [CI]: 74.5%-98.8%), 91.7% (95% CI: 80.6%-100%), and 88.9% (95% CI: 80.5%-97.3%), respectively. Comparatively, the clonality testing had a sensitivity, specificity, and accuracy of 85.7% (95% CI: 72.8%-98.7%), 33.3% (95% CI: 14.5%-52.2%), and 61.5% (95% CI: 48.3%-74.8%) relative to the panel decision. CONCLUSIONS AND CLINICAL IMPORTANCE: Histology-guided mass spectrometry was a reliable technique for the differentiation of LPE from SCL in duodenal formalin-fixed paraffin-embedded samples of cats and might have advantages over tests currently considered state of the art.

Combining Chemistry and Engineering for Hepatocellular Carcinoma: Nano-Scale and Smaller Therapies.

Primary liver cancer, or hepatocellular carcinoma (HCC), is a major worldwide cause of death from carcinoma. Most patients are not candidates for surgery and medical therapies, including new immunotherapies, have not shown major improvements since the modest benefit seen with the introduction of sorafenib over a decade ago. Locoregional therapies for intermediate stage disease are not curative but provide some benefit. However, upon close scrutiny, there is still residual disease in most cases. We review the current status for treatment of intermediate stage disease, summarize the literature on correlative histopathology, and discuss emerging methods at micro-, nano-, and pico-scales to improve therapy. These include transarterial hyperthermia methods and thermoembolization, along with microfluidics model systems and new applications of mass spectrometry imaging for label-free analysis of pharmacokinetics and pharmacodynamics.

Histopathology-guided mass spectrometry differentiates benign nevi from malignant melanoma.

PURPOSE: Distinguishing benign nevi from malignant melanoma using current histopathological criteria may be very challenging and is one the most difficult areas in dermatopathology. The goal of this study was to identify proteomic differences, which would more reliably differentiate between benign and malignant melanocytic lesions. METHODS: We performed histolpathology - guided mass spectrometry (HGMS) profiling analysis on formalin-fixed, paraffin embedded tissue samples to identify differences at the proteomic level between different types of benign nevi and melanomas. A total of 756 cases, of which 357 cases of melanoma and 399 benign nevi, were included in the study. The specimens originated from both biopsies (376 samples) and tissue microarray (TMA) cores (380 samples). After obtaining mass spectra from each sample, classification models were built using a training set of biopsy specimens from 111 nevi and 100 melanomas. The classification algorithm developed on the training data set was validated on an independent set of 288 nevi and 257 melanomas from both biopsies and TMA cores. RESULTS: In the melanoma cohort, 239/257 (93%) cases classified correctly in the validation set, 3/257 (1.2%) classified incorrectly, and 15/257 (5.8%) classified as indeterminate. In the cohort of nevi, 282/288 (98%) cases classified correctly, 1/288 (0.3%) classified incorrectly, and 5/288 (1.7%) were indeterminate. HGMS showed a sensitivity of 98.76% and specificity of 99.65% in determining benign vs malignant. CONCLUSION: HGMS proteomic analysis is an objective and reliable test with minimal tissue requirements, which can be a helpful ancillary test in the diagnosis of challenging melanocytic lesions.

Proteomic Mass Spectrometry Imaging for Skin Cancer Diagnosis.

Mass spectrometry imaging can be successfully used for skin cancer diagnosis, particularly for the diagnosis of challenging melanocytic lesions. This method analyzes proteins within benign and malignant melanocytic tumor cells and, based on their differences, which constitute a unique molecular signature of 5 to 20 proteins, can render a diagnosis of benign nevus versus malignant melanoma. Mass spectrometry imaging may assist in the differentiation between metastases and nevi as well as between proliferative nodules in nevi and melanoma arising in a nevus. In the difficult area of atypical Spitzoid neoplasms, mass spectrometry diagnosis can predict clinical outcome better than histopathology.

Mass Spectrometry Imaging Can Distinguish on a Proteomic Level Between Proliferative Nodules Within a Benign Congenital Nevus and Malignant Melanoma.

Histopathological interpretation of proliferative nodules occurring in association with congenital melanocytic nevi can be very challenging due to their similarities with congenital malignant melanoma and malignant melanoma arising in association with congenital nevi. We hereby report a diagnostically challenging case of congenital melanocytic nevus with proliferative nodules and ulcerations, which was originally misdiagnosed as congenital malignant melanoma. Subsequent histopathological examination in consultation by one of the authors (R.L.) and mass spectrometry imaging analysis rendered a diagnosis of congenital melanocytic nevus with proliferative nodules. In this case, mass spectrometry imaging, a novel method capable of distinguishing benign from malignant melanocytic lesions on a proteomic level, was instrumental in making the diagnosis of a benign nevus. We emphasize the importance of this method as an ancillary tool in the diagnosis of difficult melanocytic lesions.

Imaging mass spectrometry assists in the classification of diagnostically challenging atypical Spitzoid neoplasms.

BACKGROUND: Previously, using imaging mass spectrometry (IMS), we discovered proteomic differences between Spitz nevi and Spitzoid melanomas. OBJECTIVE: We sought to determine whether IMS can assist in the classification of diagnostically challenging atypical Spitzoid neoplasms (ASN), to compare and correlate the IMS and histopathological diagnoses with clinical behavior. METHODS: We conducted a retrospective collaborative study involving centers from 11 countries and 11 US institutions analyzing 102 ASNs by IMS. Patients were divided into clinical groups 1 to 4 representing best to worst clinical behavior. The association among IMS findings, histopathological diagnoses, and clinical groups was assessed. RESULTS: There was a strong association between a diagnosis of Spitzoid melanoma by IMS and lesions categorized as clinical groups 2, 3, and 4 (recurrence of disease, metastases, or death) compared with clinical group 1 (no recurrence or metastasis beyond a sentinel node) (P < .0001). Older age and greater tumor thickness were strongly associated with poorer outcome (P = .01). CONCLUSIONS: IMS diagnosis of ASN better predicted clinical outcome than histopathology. Diagnosis of Spitzoid melanoma by IMS was strongly associated with aggressive clinical behavior. IMS analysis using a proteomic signature may improve the diagnosis and prediction of outcome/risk stratification for patients with ASN.

Are clear cell carcinomas of the ovary and endometrium phenotypically identical? A proteomic analysis.

Phenotypic differences between otherwise similar tumors arising from different gynecologic locations may be highly significant in understanding the underlying driver molecular events at each site and may potentially offer insights into differential responses to treatment. In this study, the authors sought to identify and quantify phenotypic differences between ovarian clear cell carcinoma (OCCC) and endometrial clear cell carcinoma (ECCC) using a proteomic approach. Tissue microarrays were constructed from tumor samples of 108 patients (54 ECCCs and 54 OCCCs). Formalin-fixed samples on microarray slides were analyzed by matrix-assisted laser desorption/ionization mass spectrometry, and 730 spectral peaks were generated from the combined data set. A linear mixed-effect model with random intercept was used to generate 93 (12.7%) peaks that were significantly different between OCCCs and ECCCs at the fold cutoffs of 1.5 and 0.667 and an adjusted P value cutoff of 1.0 × 10(-10). Liquid chromatography-tandem mass spectrometry was performed on selected cores from each group, and peptides identified therefrom were compared with lists of statistically significant peaks from the aforementioned linear mixed-effects model to find matches within 0.2 Da. A total of 53 candidate proteins were thus identified as being differentially expressed in OCCCs and ECCCs, 45 (85%) of which were expressed at higher levels in ECCCs than OCCCs. These proteins were functionally diverse and did not highlight a clearly dominant cellular theme or molecular pathway. Although ECCCs and OCCCs are very similar, some phenotypic differences are demonstrable. Additional studies of these differentially expressed proteins may ultimately clarify the significance of these differences.