Automatic 3D Nonlinear Registration of Mass Spectrometry Imaging and Magnetic Resonance Imaging Data.

Multimodal integration between mass spectrometry imaging (MSI) and radiology-established modalities such as magnetic resonance imaging (MRI) would allow the investigations of key questions in complex biological systems such as the central nervous system. Such integration would provide complementary multiscale data to bridge the gap between molecular and anatomical phenotypes, potentially revealing new insights into molecular mechanisms underlying anatomical pathologies presented on MRI. Automatic coregistration between 3D MSI/MRI is a computationally challenging process due to dimensional complexity, MSI data sparsity, lack of direct spatial-correspondences, and nonlinear tissue deformation. Here, we present a new computational approach based on stochastic neighbor embedding to nonlinearly align 3D MSI to MRI data, identify and reconstruct biologically relevant molecular patterns in 3D, and fuse the MSI datacube to the MRI space. We demonstrate our method using multimodal high-spectral resolution matrix-assisted laser desorption ionization (MALDI) 9.4 T MSI and 7 T in vivo MRI data, acquired from a patient-derived, xenograft mouse brain model of glioblastoma following administration of the EGFR inhibitor drug of Erlotinib. Results show the distribution of some identified molecular ions of the EGFR inhibitor erlotinib, a phosphatidylcholine lipid, and cholesterol, which were reconstructed in 3D and mapped to the MRI space. The registration quality was evaluated on two normal mouse brains using the Dice coefficient for the regions of brainstem, hippocampus, and cortex. The method is generic and can therefore be applied to hyperspectral images from different mass spectrometers and integrated with other established in vivo imaging modalities such as computed tomography (CT) and positron emission tomography (PET).

In Vitro Liquid Extraction Surface Analysis Mass Spectrometry (ivLESA-MS) for Direct Metabolic Analysis of Adherent Cells in Culture.

Conventional metabolomic methods include extensive sample preparation steps and long analytical run times, increasing the likelihood of processing artifacts and limiting high throughput applications. We present here in vitro liquid extraction surface analysis mass spectrometry (ivLESA-MS), a variation on LESA-MS, performed directly on adherent cells grown in 96-well cell culture plates. To accomplish this, culture medium was aspirated immediately prior to analysis, and metabolites were extracted using LESA from the cell monolayer surface, followed by nano-electrospray ionization and MS analysis in negative ion mode. We applied this platform to characterize and compare lipidomic profiles of multiple breast cancer cell lines growing in culture (MCF-7, ZR-75-1, MDA-MB-453, and MDA-MB-231) and revealed distinct and reproducible lipidomic signatures between the cell lines. Additionally, we demonstrated time-dependent processing artifacts, underscoring the importance of immediate analysis. ivLESA-MS represents a rapid in vitro metabolomic method, which precludes the need for quenching, cell harvesting, sample preparation, and chromatography, significantly shortening preparation and analysis time while minimizing processing artifacts. This method could be further adapted to test drugs in vitro in a high throughput manner.

Detoxification of Atrazine by Endophytic Streptomyces sp. Isolated from Sugarcane and Detection of Nontoxic Metabolite.

Atrazine is still one of the most used agricultural pesticides worldwide and it has been recognized as a major contaminant of surface and ground water. The aims of this research were to isolate an endophytic microorganism from leaves of sugarcane, evaluate its ability to degrade atrazine, and investigate the formation of metabolites. By sequencing of the 16S rRNA gene, the endophytic isolate atz2 was identified as Streptomyces sp. The reduction in atrazine concentration by Streptomyces sp. atz2 was 98 % and UHPLC-MS/MS analyses showed the appearance of an unknown metabolite observed as m/z 311. Ecotoxicity tests with an aquatic organism, Daphnia similis, confirmed that this metabolite was nontoxic. This mechanism of detoxification of atrazine is different from the ones of other free-living microorganisms that inhabit the soil or rhizosphere. The results show new aspects of atrazine detoxification, highlighting a new role of endophytic bacteria in plants.

Multimodal platform for assessing drug distribution and response in clinical trials.

BACKGROUND: Response to targeted therapy varies between patients for largely unknown reasons. Here, we developed and applied an integrative platform using mass spectrometry imaging (MSI), phosphoproteomics, and multiplexed tissue imaging for mapping drug distribution, target engagement, and adaptive response to gain insights into heterogeneous response to therapy. METHODS: Patient-derived xenograft (PDX) lines of glioblastoma were treated with adavosertib, a Wee1 inhibitor, and tissue drug distribution was measured with MALDI-MSI. Phosphoproteomics was measured in the same tumors to identify biomarkers of drug target engagement and cellular adaptive response. Multiplexed tissue imaging was performed on sister sections to evaluate spatial co-localization of drug and cellular response. The integrated platform was then applied on clinical specimens from glioblastoma patients enrolled in the phase 1 clinical trial. RESULTS: PDX tumors exposed to different doses of adavosertib revealed intra- and inter-tumoral heterogeneity of drug distribution and integration of the heterogeneous drug distribution with phosphoproteomics and multiplexed tissue imaging revealed new markers of molecular response to adavosertib. Analysis of paired clinical specimens from patients enrolled in the phase 1 clinical trial informed the translational potential of the identified biomarkers in studying patient's response to adavosertib. CONCLUSIONS: The multimodal platform identified a signature of drug efficacy and patient-specific adaptive responses applicable to preclinical and clinical drug development. The information generated by the approach may inform mechanisms of success and failure in future early phase clinical trials, providing information for optimizing clinical trial design and guiding future application into clinical practice.

Spatial Distribution of Transcytosis Relevant Phospholipids in Response to Omega-3 Dietary Deprivation.

The cell membrane of brain endothelial cells is enriched in omega-3 phospholipid species. Numerous omega-3 phospholipid species were recently proposed to be important for maintaining the low rate of transcytosis and, thus, could be important for regulating one of the mechanisms of the blood brain barrier (BBB). However, the spatial distribution of these phospholipid species within the brain was previously unknown. Here, we combined advanced mass spectrometry imaging techniques to generate a map of these phospholipids in the brain at near single cell resolution. Furthermore, we explored the effects of omega-3 dietary deprivation on both docosahexaenoic acid (DHA)-containing phospholipids and the global brain phospholipid profile. We demonstrate the unique spatial distribution of individual DHA-containing phospholipids, which may be important for the regiospecific properties of the BBB. Finally, 24 diet discriminative phospholipids were identified and showed an increase in saturated phospholipid species and ceramide containing phospholipid species under omega-3 dietary deficiency.

A unique subset of glycolytic tumour-propagating cells drives squamous cell carcinoma.

Head and neck squamous cell carcinoma (SCC) remains among the most aggressive human cancers. Tumour progression and aggressiveness in SCC are largely driven by tumour-propagating cells (TPCs). Aerobic glycolysis, also known as the Warburg effect, is a characteristic of many cancers; however, whether this adaptation is functionally important in SCC, and at which stage, remains poorly understood. Here, we show that the NAD+-dependent histone deacetylase sirtuin 6 is a robust tumour suppressor in SCC, acting as a modulator of glycolysis in these tumours. Remarkably, rather than a late adaptation, we find enhanced glycolysis specifically in TPCs. More importantly, using single-cell RNA sequencing of TPCs, we identify a subset of TPCs with higher glycolysis and enhanced pentose phosphate pathway and glutathione metabolism, characteristics that are strongly associated with a better antioxidant response. Together, our studies uncover enhanced glycolysis as a main driver in SCC, and, more importantly, identify a subset of TPCs as the cell of origin for the Warburg effect, defining metabolism as a key feature of intra-tumour heterogeneity.

Localized Metabolomic Gradients in Patient-Derived Xenograft Models of Glioblastoma.

Glioblastoma (GBM) is increasingly recognized as a disease involving dysfunctional cellular metabolism. GBMs are known to be complex heterogeneous systems containing multiple distinct cell populations and are supported by an aberrant network of blood vessels. A better understanding of GBM metabolism, its variation with respect to the tumor microenvironment, and resulting regional changes in chemical composition is required. This may shed light on the observed heterogeneous drug distribution, which cannot be fully described by limited or uneven disruption of the blood-brain barrier. In this work, we used mass spectrometry imaging (MSI) to map metabolites and lipids in patient-derived xenograft models of GBM. A data analysis workflow revealed that distinctive spectral signatures were detected from different regions of the intracranial tumor model. A series of long-chain acylcarnitines were identified and detected with increased intensity at the tumor edge. A 3D MSI dataset demonstrated that these molecules were observed throughout the entire tumor/normal interface and were not confined to a single plane. mRNA sequencing demonstrated that hallmark genes related to fatty acid metabolism were highly expressed in samples with higher acylcarnitine content. These data suggest that cells in the core and the edge of the tumor undergo different fatty acid metabolism, resulting in different chemical environments within the tumor. This may influence drug distribution through changes in tissue drug affinity or transport and constitute an important consideration for therapeutic strategies in the treatment of GBM. SIGNIFICANCE: GBM tumors exhibit a metabolic gradient that should be taken into consideration when designing therapeutic strategies for treatment.See related commentary by Tan and Weljie, p. 1231.

Molecular Characterization of Prostate Cancer with Associated Gleason Score Using Mass Spectrometry Imaging.

Diagnosis of prostate cancer is based on histologic evaluation of tumor architecture using a system known as the "Gleason score." This diagnostic paradigm, while the standard of care, is time-consuming, shows intraobserver variability, and provides no information about the altered metabolic pathways, which result in altered tissue architecture. Characterization of the molecular composition of prostate cancer and how it changes with respect to the Gleason score (GS) could enable a more objective and faster diagnosis. It may also aid in our understanding of disease onset and progression. In this work, we present mass spectrometry imaging for identification and mapping of lipids and metabolites in prostate tissue from patients with known prostate cancer with GS from 6 to 9. A gradient of changes in the intensity of various lipids was observed, which correlated with increasing GS. Interestingly, these changes were identified in both regions of high tumor cell density, and in regions of tissue that appeared histologically benign, possibly suggestive of precancerous metabolomic changes. A total of 31 lipids, including several phosphatidylcholines, phosphatidic acids, phosphatidylserines, phosphatidylinositols, and cardiolipins were detected with higher intensity in GS (4+3) compared with GS (3+4), suggesting they may be markers of prostate cancer aggression. Results obtained through mass spectrometry imaging studies were subsequently correlated with a fast, ambient mass spectrometry method for potential use as a clinical tool to support image-guided prostate biopsy. IMPLICATIONS: In this study, we suggest that metabolomic differences between prostate cancers with different Gleason scores can be detected by mass spectrometry imaging.

A large-scale drug screen identifies selective inhibitors of class I HDACs as a potential therapeutic option for SHH medulloblastoma.

BACKGROUND: Medulloblastoma (MB) is one of the most frequent malignant brain tumors of children, and a large set of these tumors is characterized by aberrant activation of the sonic hedgehog (SHH) pathway. While some tumors initially respond to inhibition of the SHH pathway component Smoothened (SMO), tumors ultimately recur due to downstream resistance mechanisms, indicating a need for novel therapeutic options. METHODS: Here we performed a targeted small-molecule screen on a stable, SHH-dependent murine MB cell line (SMB21). Comprehensive isotype profiling of histone deacetylase (HDAC) inhibitors was performed, and effects of HDAC inhibition were evaluated in cell lines both sensitive and resistant to SMO inhibition. Lastly, distinct mouse models of SHH MB were used to demonstrate pharmacologic efficacy in vivo. RESULTS: A subset of the HDAC inhibitors tested significantly inhibit tumor growth of SMB21 cells by preventing SHH pathway activation. Isotype profiling of HDAC inhibitors, together with genetic approaches suggested that concerted inhibition of multiple class I HDACs is necessary to achieve pathway inhibition. Of note, class I HDAC inhibitors were also efficacious in suppressing growth of diverse SMO inhibitor‒resistant clones of SMB21 cells. Finally, we show that the novel HDAC inhibitor quisinostat targets multiple class I HDACs, is well tolerated in mouse models, and robustly inhibits growth of SHH MB cells in vivo as well as in vitro. CONCLUSIONS: Our data provide strong evidence that quisinostat or other class I HDAC inhibitors might be therapeutically useful for patients with SHH MB, including those resistant to SMO inhibition.