Advances in mass spectrometry imaging for plant metabolomics-Expanding the analytical toolbox.

Mass spectrometry imaging (MSI) has become increasingly popular in plant science due to its ability to characterize complex chemical, spatial, and temporal aspects of plant metabolism. Over the past decade, as the emerging and unique features of various MSI techniques have continued to support new discoveries in studies of plant metabolism closely associated with various aspects of plant function and physiology, spatial metabolomics based on MSI techniques has positioned it at the forefront of plant metabolic studies, providing the opportunity for far higher resolution than was previously available. Despite these efforts, profound challenges at the levels of spatial resolution, sensitivity, quantitative ability, chemical confidence, isomer discrimination, and spatial multi-omics integration, undoubtedly remain. In this Perspective, we provide a contemporary overview of the emergent MSI techniques widely used in the plant sciences, with particular emphasis on recent advances in methodological breakthroughs. Having established the detailed context of MSI, we outline both the golden opportunities and key challenges currently facing plant metabolomics, presenting our vision as to how the enormous potential of MSI technologies will contribute to progress in plant science in the coming years.

Protein analysis by desorption electrospray ionization mass spectrometry.

This review presents progress made in the ambient analysis of proteins, in particular by desorption electrospray ionization-mass spectrometry (DESI-MS). Related ambient ionization techniques are discussed in comparison to DESI-MS only to illustrate the larger context of protein analysis by ambient ionization mass spectrometry. The review describes early and current approaches for the analysis of undigested proteins, native proteins, tryptic digests, and indirect protein determination through reporter molecules. Applications to mass spectrometry imaging for protein spatial distributions, the identification of posttranslational modifications, determination of binding stoichiometries, and enzymatic transformations are discussed. The analytical capabilities of other ambient ionization techniques such as LESA and nano-DESI currently exceed those of DESI-MS for in situ surface sampling of intact proteins from tissues. This review shows, however, that despite its many limitations, DESI-MS is making valuable contributions to protein analysis. The challenges in sensitivity, spatial resolution, and mass range are surmountable obstacles and further development and improvements to DESI-MS is justified.

Single Cell Analysis of Proteoforms.

We introduce single cell Proteoform imaging Mass Spectrometry (scPiMS), which realizes the benefit of direct solvent extraction and MS detection of intact proteins from single cells dropcast onto glass slides. Sampling and detection of whole proteoforms by individual ion mass spectrometry enable a scalable approach to single cell proteomics. This new scPiMS platform addresses the throughput bottleneck in single cell proteomics and boosts the cell processing rate by several fold while accessing protein composition with higher coverage.

Advances in mass spectrometry imaging for toxicological analysis and safety evaluation of pharmaceuticals.

Safety issues caused by pharmaceuticals have frequently occurred worldwide, posing a tremendous threat to human health. As an essential part of drug development, the toxicological analysis and safety evaluation is of great significance. In addition, the risk of pharmaceuticals accumulation in the environment and the monitoring of the toxicity from natural medicines have also received ongoing concerns. Due to a lack of spatial distribution information provided by common analytical methods, analyses that provide spatial dimensions could serve as complementary safety evaluation methods for better prediction and evaluation of drug toxicity. With advances in technical solutions and software algorithms, mass spectrometry imaging (MSI) has received increasing attention as a popular analytical tool that enables the simultaneous implementation of qualitative, quantitative, and localization without complex sample pretreatment and labeling steps. In recent years, MSI has become more attractive, powerful, and sensitive and has been applied in several scientific fields that can meet the safety assessment requirements. This review aims to cover a detailed summary of the various MSI technologies utilized in the biomedical and pharmaceutical area, including technical principles, advantages, current status, and future trends. Representative applications and developments in the safety-related issues of different pharmaceuticals and natural medicines are also described to provide a reference for pharmaceutical research, improve rational clinical medicine use, and ensure public safety.

Imaging plant metabolism in situ.

Mass spectrometry imaging (MSI) has emerged as an invaluable analytical technique for investigating the spatial distribution of molecules within biological systems. In the realm of plant science, MSI is increasingly employed to explore metabolic processes across a wide array of plant tissues, including those in leaves, fruits, stems, roots, and seeds, spanning various plant systems such as model species, staple and energy crops, and medicinal plants. By generating spatial maps of metabolites, MSI has elucidated the distribution patterns of diverse metabolites and phytochemicals, encompassing lipids, carbohydrates, amino acids, organic acids, phenolics, terpenes, alkaloids, vitamins, pigments, and others, thereby providing insights into their metabolic pathways and functional roles. In this review, we present recent MSI studies that demonstrate the advances made in visualizing the plant spatial metabolome. Moreover, we emphasize the technical progress that enhances the identification and interpretation of spatial metabolite maps. Within a mere decade since the inception of plant MSI studies, this robust technology is poised to continue as a vital tool for tackling complex challenges in plant metabolism.

Unmasking Spatial Heterogeneity in Phytotoxicology Mechanisms Induced by Carbamazepine by Mass Spectrometry Imaging and Multiomics Analyses.

Previous studies have highlighted the toxicity of pharmaceuticals and personal care products (PPCPs) in plants, yet understanding their spatial distribution within plant tissues and specific toxic effects remains limited. This study investigates the spatial-specific toxic effects of carbamazepine (CBZ), a prevalent PPCP, in plants. Utilizing desorption electrospray ionization mass spectrometry imaging (DESI-MSI), CBZ and its transformation products were observed predominantly at the leaf edges, with 2.3-fold higher concentrations than inner regions, which was confirmed by LC-MS. Transcriptomic and metabolic analyses revealed significant differences in gene expression and metabolite levels between the inner and outer leaf regions, emphasizing the spatial location's role in CBZ response. Notably, photosynthesis-related genes were markedly downregulated, and photosynthetic efficiency was reduced at leaf edges. Additionally, elevated oxidative stress at leaf edges was indicated by higher antioxidant enzyme activity, cell membrane impairment, and increased free fatty acids. Given the increased oxidative stress at the leaf margins, the study suggests using in situ Raman spectroscopy for early detection of CBZ-induced damage by monitoring reactive oxygen species levels. These findings provide crucial insights into the spatial toxicological mechanisms of CBZ in plants, forming a basis for future spatial toxicology research of PPCPs.

DESI-MSI-guided exploration of metabolic-phenotypic relationships reveals a correlation between PI 38:3 and proliferating cells in clear cell renal cell carcinoma via single-section co-registration of multimodal imaging.

A workflow has been evaluated that utilizes a single tissue section to obtain spatially co-registered, molecular, and phenotypical information suitable for AI-enabled image analysis. Desorption electrospray ionization mass spectrometry imaging (DESI-MSI) was used to obtain molecular information followed by conventional histological staining and immunolabelling. The impact of varying DESI-MSI conditions (e.g., heated transfer line (HTL) temperature, scan rate, acquisition time) on the detection of small molecules and lipids as well as on tissue integrity crucial for integration into typical clinical pathology workflows was assessed in human kidney. Increasing the heated transfer line temperature from 150 to 450 °C resulted in a 1.8-fold enhancement in lipid signal at a scan rate of 10 scans/s, while preserving histological features. Moreover, increasing the acquisition speed to 30 scans/s yielded superior lipid signal when compared to 10 scans/s at 150 °C. Tissue morphology and protein epitopes remained intact allowing full histological assessment and further multiplex phenotyping by immunofluorescence (mIF) and immunohistochemistry (mIHC) of the same section. The successful integration of the workflow incorporating DESI-MSI, H&E, and immunolabelling on a single tissue section revealed an accumulation of ascorbic acid in regions of focal chronic inflammatory cell infiltrate within non-cancerous kidney tissue. Additionally, a strong positive correlation between PI 38:3 and proliferating cells was observed in clear cell renal cell carcinoma (ccRCC) showing the utility of this approach in uncovering molecular associations in disease pathology.

Tissue distribution of metabolites in Cordyceps cicadae determined by DESI-MSI analysis.

In this paper, we establish an in situ visualization analysis method to image the spatial distribution of metabolites in different parts (sclerotium, coremium) and different microregions of Cordyceps cicadae (C. cicadae) to achieve the in situ visual characterization of tissues for a variety of metabolites such as nucleosides, amino acids, polysaccharides, organic acids, fatty acids, and so on. The study included LC-MS chemical composition identification, preparation of C. cicadae tissue sections, DEDI-MSI analysis, DESI combined with Q-TOF/MS to obtain high-resolution imaging of mass-to-charge ratio and space, imaging of C. cicadae in positive-negative ion mode with a spatial resolution of 100 µm, and localizing and identifying its chemical compositions based on its precise mass. A total of 62 compounds were identified; nucleosides were mainly distributed in the coremium, L-threonine and DL-isoleucine, and other essential amino acids; peptides were mainly distributed in the sclerotium of C. cicadae; and the rest of the amino acids did not have a clear pattern; sugars and sugar alcohols were mainly distributed in the coremium of C. cicadae; organic acids and fatty acids were distributed in the nucleus of C. cicadae more than in the sclerotium, and the mass spectrometry imaging method is established in the research. The mass spectrometry imaging method established in this study is simple and fast and can visualize and analyse the spatial distribution of metabolites of C. cicadae, which is of great significance in characterizing the metabolic network of C. cicadae, and provides support for the quality evaluation of C. cicadae and the study of the temporal and spatial metabolic network of chemical compounds.

Accelerating strain phenotyping with desorption electrospray ionization-imaging mass spectrometry and untargeted analysis of intact microbial colonies.

Reading and writing DNA were once the rate-limiting step in synthetic biology workflows. This has been replaced by the search for the optimal target sequences to produce systems with desired properties. Directed evolution and screening mutant libraries are proven technologies for isolating strains with enhanced performance whenever specialized assays are available for rapidly detecting a phenotype of interest. Armed with technologies such as CRISPR-Cas9, these experiments are capable of generating libraries of up to 1010 genetic variants. At a rate of 102 samples per day, standard analytical methods for assessing metabolic phenotypes represent a major bottleneck to modern synthetic biology workflows. To address this issue, we have developed a desorption electrospray ionization-imaging mass spectrometry screening assay that directly samples microorganisms. This technology increases the throughput of metabolic measurements by reducing sample preparation and analyzing organisms in a multiplexed fashion. To further accelerate synthetic biology workflows, we utilized untargeted acquisitions and unsupervised analytics to assess multiple targets for future engineering strategies within a single acquisition. We demonstrate the utility of the developed method using Escherichia coli strains engineered to overproduce free fatty acids. We determined discrete metabolic phenotypes associated with each strain, which include the primary fatty acid product, secondary products, and additional metabolites outside the engineered product pathway. Furthermore, we measured changes in amino acid levels and membrane lipid composition, which affect cell viability. In sum, we present an analytical method to accelerate synthetic biology workflows through rapid, untargeted, and multiplexed metabolomic analyses.

Disaster preparedness among Asian, Pacific Islander, and Desi American communities.

Disaster experiences and explorations of preparedness among Asian, Pacific Islander, and Desi Americans (APIDA) in the United States are often overlooked owing to their relatively smaller population share. APIDA are not homogenous, and their disaster experiences warrant further examination. This paper does so by investigating disaster preparedness using disaggregated information about APIDA. The study utilises nationally representative data from the 2017 American Housing Survey, analysing sociodemographic covariates. The disaster preparedness score among APIDA communities was approximately 4.81 on a zero to nine scale. APIDA renters and non-US citizens were less prepared than homeowners and US citizens. Among subgroups, Korean, Chinese, and Vietnamese respondents who were non-US citizens were less prepared than those who were US citizens. Marital status was significantly and positively associated with preparedness among Indians, Japanese, Vietnamese, and multiracial respondents. The findings underscore the importance of data disaggregation and tailored preparedness information and resources to address specific challenges APIDA communities face instead of a one-size-fits-all approach.

Spatial metabolomics method to reveal the differences in chemical composition of raw and honey-fried Stemona tuberosa Lour. by using UPLC-Orbitrap Fusion MS and desorption electrospray ionization mass spectrometry imaging.

INTRODUCTION: Stemona tuberosa Lour. (ST) is a significant traditional Chinese medicine (TCM) renowned for its antitussive and insecticidal properties. ST is commonly subjected to processing in clinical practice before being utilized as a medicinal substance. Currently, the customary technique for processing ST is honey-fried. Nevertheless, the specific variations in chemical constituents of ST before and after honey-fried remain unclear. OBJECTIVE: This work aimed to analyze the variations in chemical constituents of ST before and after honey-fried and to study the distribution of differential markers in the roots. METHODS: UPLC-Orbitrap Fusion MS combined with molecular network analysis was used to analyze the metabolome of ST and honey-fried ST (HST) and to screen the differential metabolites by multivariate statistical analysis. Spatial metabolomics was applied to study the distribution of differential metabolites by desorption electrospray ionization mass spectrometry imaging (DESI-MSI). RESULTS: The ST and HST exhibited notable disparities, with 56 and 61 chemical constituents found from each, respectively. After processing, the types of alkaloids decreased, and 12 differential metabolites were screened from the common compounds. The notable component variations were epibisdehydro-tuberostemonine J, neostenine, tuberostemonine, croomine, neotuberostemonine, and so forth. MSI visualized the spatial distribution of differential metabolites. CONCLUSIONS: Our research provided a rapid and effective visualization method for the identification and spatial distribution of metabolites in ST. Compared with the traditional method, this method offered more convincing data supporting the processing mechanism investigations of Stemona tuberosa from a macroscopic perspective.

Interleukin-13 Treatment of Living Lung Tissue Model Alters the Metabolome and Proteome-A Nano-DESI MS Metabolomics and Shotgun Proteomics Study.

Asthma is a chronic respiratory disease with one of the largest numbers of cases in the world; thus, constant investigation and technical development are needed to unravel the underlying biochemical mechanisms. In this study, we aimed to develop a nano-DESI MS method for the in vivo characterization of the cellular metabolome. Using air-liquid interface (ALI) cell layers, we studied the role of Interleukin-13 (IL-13) on differentiated lung epithelial cells acting as a lung tissue model. We demonstrate the feasibility of nano-DESI MS for the in vivo monitoring of basal-apical molecular transport, and the subsequent endogenous metabolic response, for the first time. Conserving the integrity of the ALI lung-cell layer enabled us to perform temporally resolved metabolomic characterization followed by "bottom-up" proteomics on the same population of cells. Metabolic remodeling was observed upon histamine and corticosteroid treatment of the IL-13-exposed lung cell monolayers, in correlation with alterations in the proteomic profile. This proof of principle study demonstrates the utility of in vivo nano-DESI MS for characterizing ALI tissue layers, and the new markers identified in our study provide a good starting point for future, larger-scale studies.

Advances in mass spectrometry imaging for spatial cancer metabolomics.

Mass spectrometry (MS) has become a central technique in cancer research. The ability to analyze various types of biomolecules in complex biological matrices makes it well suited for understanding biochemical alterations associated with disease progression. Different biological samples, including serum, urine, saliva, and tissues have been successfully analyzed using mass spectrometry. In particular, spatial metabolomics using MS imaging (MSI) allows the direct visualization of metabolite distributions in tissues, thus enabling in-depth understanding of cancer-associated biochemical changes within specific structures. In recent years, MSI studies have been increasingly used to uncover metabolic reprogramming associated with cancer development, enabling the discovery of key biomarkers with potential for cancer diagnostics. In this review, we aim to cover the basic principles of MSI experiments for the nonspecialists, including fundamentals, the sample preparation process, the evolution of the mass spectrometry techniques used, and data analysis strategies. We also review MSI advances associated with cancer research in the last 5 years, including spatial lipidomics and glycomics, the adoption of three-dimensional and multimodal imaging MSI approaches, and the implementation of artificial intelligence/machine learning in MSI-based cancer studies. The adoption of MSI in clinical research and for single-cell metabolomics is also discussed. Spatially resolved studies on other small molecule metabolites such as amino acids, polyamines, and nucleotides/nucleosides will not be discussed in the context.

Molecular characterization of human peripheral nerves using desorption electrospray ionization mass spectrometry imaging.

Desorption electrospray ionization mass spectrometry imaging (DESI-MSI) is a molecular imaging method that can be used to elucidate the small-molecule composition of tissues and map their spatial information using two-dimensional ion images. This technique has been used to investigate the molecular profiles of variety of tissues, including within the central nervous system, specifically the brain and spinal cord. To our knowledge, this technique has yet to be applied to tissues of the peripheral nervous system (PNS). Data generated from such analyses are expected to advance the characterization of these structures. The study aimed to: (i) establish whether DESI-MSI can discriminate the molecular characteristics of peripheral nerves and distinguish them from surrounding tissues and (ii) assess whether different peripheral nerve subtypes are characterized by unique molecular profiles. Four different nerves for which are known to carry various nerve fiber types were harvested from a fresh cadaveric donor: mixed, motor and sensory (sciatic and femoral); cutaneous, sensory (sural); and autonomic (vagus). Tissue samples were harvested to include the nerve bundles in addition to surrounding connective tissue. Samples were flash-frozen, embedded in optimal cutting temperature compound in cross-section, and sectioned at 14 µm. Following DESI-MSI analysis, identical tissue sections were stained with hematoxylin and eosin. In this proof-of-concept study, a combination of multivariate and univariate statistical methods was used to evaluate molecular differences between the nerve and adjacent tissue and between nerve subtypes. The acquired mass spectral profiles of the peripheral nerve samples presented trends in ion abundances that seemed to be characteristic of nerve tissue and spatially corresponded to the associated histology of the tissue sections. Principal component analysis (PCA) supported the separation of the samples into distinct nerve and adjacent tissue classes. This classification was further supported by the K-means clustering analysis, which showed separation of the nerve and background ions. Differences in ion expression were confirmed using ANOVA which identified statistically significant differences in ion expression between the nerve subtypes. The PCA plot suggested some separation of the nerve subtypes into four classes which corresponded with the nerve types. This was supported by the K-means clustering. Some overlap in classes was noted in these two clustering analyses. This study provides emerging evidence that DESI-MSI is an effective tool for metabolomic profiling of peripheral nerves. Our results suggest that peripheral nerves have molecular profiles that are distinct from the surrounding connective tissues and that DESI-MSI may be able to discriminate between nerve subtypes. DESI-MSI of peripheral nerves may be a valuable technique that could be used to improve our understanding of peripheral nerve anatomy and physiology. The ability to utilize ambient mass spectrometry techniques in real time could also provide an unprecedented advantage for surgical decision making, including in nerve-sparing procedures in the future.

Site-specific genotoxicity of rubiadin: localization and histopathological changes in the kidneys of rats.

Rubiadin (Rub) is a genotoxic component of madder color (MC) that is extracted from the root of Rubia tinctorum L. MC induces renal tumors and preneoplastic lesions that are found in the proximal tubule of the outer stripe of the outer medulla (OSOM), suggesting that the renal carcinogenicity of MC is site specific. To clarify the involvement of Rub in renal carcinogenesis of MC, we examined the distribution of Rub in the kidney of male gpt delta rats that were treated with Rub for 28 days. We used desorption electrospray ionization quadrupole time-of-flight mass spectrometry imaging (DESI-Q-TOF-MSI), along with the histopathological analysis, immunohistochemical staining, and reporter gene mutation assays of the kidney. DESI-Q-TOF-MSI revealed that Rub and its metabolites, lucidin and Rub-sulfation, were specifically distributed in the OSOM. Histopathologically, karyomegaly characterized by enlarged nuclear and microvesicular vacuolar degeneration occurred in proximal tubule epithelial cells in the OSOM. The ɤ-H2AX- and p21-positive cells were also found in the OSOM rather than the cortex. Although dose-dependent increases in gpt and Spi- mutant frequencies were observed in both the medulla and cortex, the mutant frequencies in the medulla were significantly higher. The mutation spectra of gpt mutants showed that A:T-T:A transversion was predominant in Rub-induced gene mutations, consistent with those of MC. Overall, the data showed that the distribution of Rub and its metabolites resulted in site-specific histopathological changes, DNA damage, and gene mutations, suggesting that the distribution of genotoxic components and metabolites is responsible for the site-specific renal carcinogenesis of MC.

Updating the Clinical Application of Blood Biomarkers and Their Algorithms in the Diagnosis and Surveillance of Hepatocellular Carcinoma: A Critical Review.

The most common primary liver cancer is hepatocellular carcinoma (HCC), and its mortality rate is increasing globally. The overall 5-year survival of patients with liver cancer is currently 10-20%. Moreover, because early diagnosis can significantly improve prognosis, which is highly correlated with tumor stage, early detection of HCC is critical. International guidelines advise using α-FP biomarker with/without ultrasonography for HCC surveillance in patients with advanced liver disease. However, traditional biomarkers are sub-optimal for risk stratification of HCC development in high-risk populations, early diagnosis, prognostication, and treatment response prediction. Since about 20% of HCCs do not produce α-FP due to its biological diversity, combining α-FP with novel biomarkers can enhance HCC detection sensitivity. There is a chance to offer promising cancer management methods in high-risk populations by utilizing HCC screening strategies derived from new tumor biomarkers and prognostic scores created by combining biomarkers with distinct clinical parameters. Despite numerous efforts to identify molecules as potential biomarkers, there is no single ideal marker in HCC. When combined with other clinical parameters, the detection of some biomarkers has higher sensitivity and specificity in comparison with a single biomarker. Therefore, newer biomarkers and models, such as the Lens culinaris agglutinin-reactive fraction of Alpha-fetoprotein (α-FP), α-FP-L3, Des-γ-carboxy-prothrombin (DCP or PIVKA-II), and the GALAD score, are being used more frequently in the diagnosis and prognosis of HCC. Notably, the GALAD algorithm was effective in HCC prevention, particularly for cirrhotic patients, regardless of the cause of their liver disease. Although the role of these biomarkers in surveillance is still being researched, they may provide a more practical alternative to traditional imaging-based surveillance. Finally, looking for new diagnostic/surveillance tools may help improve patients' survival. This review discusses the current roles of the most used biomarkers and prognostic scores that may aid in the clinical management of HCC patients.

Advances in ionisation techniques for mass spectrometry-based omics research.

Omics analysis by mass spectrometry (MS) is a vast field, with proteomics, metabolomics and lipidomics dominating recent research by exploiting biological MS ionisation techniques. Traditional MS ionisation techniques such as electrospray ionisation have limitations in analyte-specific sensitivity, modes of sampling and throughput, leading to many researchers investigating new ionisation methods for omics research. In this review, we examine the current landscape of these new ionisation techniques, divided into the three groups of (electro)spray-based, laser-based and other miscellaneous ionisation techniques. Due to the wide range of new developments, this review can only provide a starting point for further reading on each ionisation technique, as each have unique benefits, often for specialised applications, which promise beneficial results for different areas in the omics world.

Stress upregulates 2-arachidonoylglycerol levels in the hypothalamus, midbrain, and hindbrain, and it is sustained by green nut oil supplementation in SAMP8 mice revealed by DESI-MSI.

The endocannabinoid 2-arachidonoylglycerol (2AG) is an important modulator of stress responses. Its level in the brain increases in response to stress, but region-specific effects of stress on brain 2AG are not well known yet. Moreover, green nut oil (GNO), oil extracted from the seeds of Plukenetia volubilis has several health benefits, but its effects on brain 2AG levels are unknown. Therefore, we conducted this study to explore the effects of stress and GNO supplementation on 2AG levels in specific brain regions of senescence-accelerated mouse prone 8 (SAMP8). In this study, desorption electrospray ionization-mass spectrometry imaging (DESI-MSI) revealed that water-immersion stress for three days significantly increased 2AG levels in several brain regions of SAMP8 mice, including the hypothalamus, midbrain, and hindbrain. No significant change was observed in the relative abundance of brain 2AG in stress given SAMP8 mice after eighteen days of removing stress load compared to control SAMP8 mice. GNO supplementation also increased brain 2AG in SAMP8 mice without stress load. Additionally, GNO supplementation sustained the increased brain 2AG levels in stress given SAMP8 mice after eighteen days of removing stress load. Among all brain regions, a relatively higher accumulation of 2AG was noted in the hypothalamus, midbrain, and hindbrain of GNO-fed SAMP8. Our data explored the potentiality of GNO supplementation to improve brain 2AG levels which might be used to treat anxiety and depressive behaviors.

Early Changes in Alpha-Fetoprotein Are a Useful Predictor of Efficacy of Atezolizumab plus Bevacizumab Treatment in Patients with Advanced Hepatocellular Carcinoma.

INTRODUCTION: The aim of this study was to investigate the early changes in alpha-fetoprotein (AFP) and des-γ-carboxy prothrombin (DCP) levels in patients with advanced hepatocellular carcinoma (HCC) treated with atezolizumab plus bevacizumab and to evaluate the relationship between changes in these tumor markers and treatment efficacy. METHODS: Of 58 consecutive patients who started atezolizumab plus bevacizumab at our institution, 50 patients with information on antitumor response obtained at 6 weeks after therapy were enrolled in this study and their treatment outcomes were retrospectively evaluated. RESULTS: According to the Response Evaluation Criteria in Solid Tumors at 6 weeks, the objective response (OR) rate was 22.0% and the disease control (DC) rate was 78.0%. In patients who achieved OR at 6 weeks, median AFP and DCP ratios at weeks 1, 2, 3, and 6 were significantly lower than those in patients who did not achieve OR. AFP ratios in patients who did not achieve DC at 6 weeks (Non-6W-DC group) were significantly higher than in those who achieved DC at week 6 (6W-DC group). Median overall survival in the Non-6W-DC group was significantly shorter than in the 6W-DC group (156 days vs. not reached, p = 0.0008). An AFP ratio of 1.4 or higher at 3 weeks had a specificity of 88.0% and a sensitivity of 88.9% for predicting Non-6W-DC. Median progression-free survival was significantly shorter in patients with an AFP ratio of 1.4 or higher at 3 weeks than in those with an AFP ratio of <1.4 (42 days vs. 210 days, p = 0.0003). CONCLUSION: Early changes in AFP might be useful for predicting the antitumor efficacy of atezolizumab plus bevacizumab in patients with advanced HCC. An AFP ratio of 1.4 or higher at 3 weeks might be an early predictor of refractoriness to atezolizumab plus bevacizumab therapy.

Tissue distribution and metabolic profiling of cyclosporine (CsA) in mouse and rat investigated by DESI and MALDI mass spectrometry imaging (MSI) of whole-body and single organ cryo-sections.

Therapeutic peptides are a fast-growing class of pharmaceuticals. Like small molecules, the costs associated with their discovery and development are significant. In addition, since the preclinical data guides first-in-human studies, there is a need for analytical techniques that accelerate and improve our understanding of the absorption, distribution, metabolism, and excretion (ADME) characteristics of early drug candidates. Mass spectrometry imaging (MSI), which can be used to visualize drug distribution in intact tissue, has been extensively used to study small molecule drugs, but only applied to a limited extent to larger molecules, such as peptides, after dosing. Herein, we use MSI to obtain spatial information on the distribution and metabolism of a peptide drug. The immunosuppressant cyclosporine (CsA), a cyclic undecapeptide, was used as a-proof-of-concept peptide and investigated by desorption electrospray ionization (DESI) MSI. Calibration curves were made based on a spiked tissue homogenate model. Different washing protocols were tested to improve sensitivity, but CsA, being a quite lipophilic peptide, was found not to benefit from tissue washing. The distribution of CsA and its metabolites were mapped in whole-body mouse sections and within rat organs. Whole-body DESI-MSI studies in mice showed widespread distribution of CsA with highest abundance in organs like the pancreas and liver. After 24 h, hydroxy and dihydroxy metabolites of CsA were detected predominantly in the intestines, which were largely devoid of CsA. In addition to the DESI-MSI experiments, MALDI-MSI was also conducted on rat jejunum at higher spatial resolution, revealing the morphology of the jejenum at greater detail; however, DESI provided similar results for drug and metabolite distribution in rat jejunum at apparent slightly better sensitivity. Given its label-free nature, MSI could provide valuable ADME insight, especially for candidates in the early-stage pipeline before radiolabeling.