Accelerating Drug Development Using Spatial Multi-omics

SUMMARY

Spatial biology approaches enabled by innovations in imaging biomarker platforms and artificial intelligence-enabled data integration and analysis provide an assessment of patient and disease heterogeneity at ever-increasing resolution. The utility of spatial biology data in accelerating drug programs, however, requires balancing exploratory discovery investigations against scalable and clinically applicable spatial biomarker analysis.

Imaging tumor lactate is feasible for identifying intermediate-risk prostate cancer patients with postsurgical biochemical recurrence

While radical prostatectomy remains the mainstay of prostate cancer (PCa) treatment, 20 to 40% of patients develop postsurgical biochemical recurrence (BCR). A particularly challenging clinical cohort includes patients with intermediate-risk disease whose risk stratification would benefit from advanced approaches that complement standard-of-care diagnostic tools. Here, we show that imaging tumor lactate using hyperpolarized 13C MRI and spatial metabolomics identifies BCR-positive patients in two prospective intermediate-risk surgical cohorts. Supported by spatially resolved tissue analysis of established glycolytic biomarkers, this study provides the rationale for multicenter trials of tumor metabolic imaging as an auxiliary tool to support PCa treatment decision-making.

Vitamin B5 supports MYC oncogenic metabolism and tumor progression in breast cancer

Tumors are intrinsically heterogeneous and it is well established that this directs their evolution, hinders their classification and frustrates therapy1-3. Consequently, spatially resolved omics-level analyses are gaining traction4-9. Despite considerable therapeutic interest, tumor metabolism has been lagging behind this development and there is a paucity of data regarding its spatial organization. To address this shortcoming, we set out to study the local metabolic effects of the oncogene c-MYC, a pleiotropic transcription factor that accumulates with tumor progression and influences metabolism10,11. Through correlative mass spectrometry imaging, we show that pantothenic acid (vitamin B5) associates with MYC-high areas within both human and murine mammary tumors, where its conversion to coenzyme A fuels Krebs cycle activity. Mechanistically, we show that this is accomplished by MYC-mediated upregulation of its multivitamin transporter SLC5A6. Notably, we show that SLC5A6 over-expression alone can induce increased cell growth and a shift toward biosynthesis, whereas conversely, dietary restriction of pantothenic acid leads to a reversal of many MYC-mediated metabolic changes and results in hampered tumor growth. Our work thus establishes the availability of vitamins and cofactors as a potential bottleneck in tumor progression, which can be exploited therapeutically. Overall, we show that a spatial understanding of local metabolism facilitates the identification of clinically relevant, tractable metabolic targets.

Combining the AKT inhibitor capivasertib and SERD fulvestrant is effective in palbociclib-resistant ER+ breast cancer preclinical models

Combining the selective AKT inhibitor, capivasertib, and SERD, fulvestrant improved PFS in a Phase III clinical trial (CAPItello-291), treating HR+ breast cancer patients following aromatase inhibitors, with or without CDK4/6 inhibitors. However, clinical data suggests CDK4/6 treatment may reduce response to subsequent monotherapy endocrine treatment. To support understanding of trials such as CAPItello-291 and gain insight into this emerging population of patients, we explored how CDK4/6 inhibitor treatment influences ER+ breast tumour cell function and response to fulvestrant and capivasertib after CDK4/6 inhibitor treatment. In RB+, RB- T47D and MCF7 palbociclib-resistant cells ER pathway ER and Greb-1 expression were reduced versus naïve cells. PI3K-AKT pathway activation was also modified in RB+ cells, with capivasertib less effective at reducing pS6 in RB+ cells compared to parental cells. Expression profiling of parental versus palbociclib-resistant cells confirmed capivasertib, fulvestrant and the combination differentially impacted gene expression modulation in resistant cells, with different responses seen in T47D and MCF7 cells. Fulvestrant inhibition of ER-dependent genes was reduced. In resistant cells, the combination was less effective at reducing cell cycle genes, but a consistent reduction in cell fraction in S-phase was observed in naïve and resistant cells. Despite modified signalling responses, both RB+ and RB- resistant cells responded to combination treatment despite some reduction in relative efficacy and was effective in vivo in palbociclib-resistant PDX models. Collectively these findings demonstrate that simultaneous inhibition of AKT and ER signalling can be effective in models representing palbociclib resistance despite changes in pathway dependency.

Metabolic profiling stratifies colorectal cancer and reveals adenosylhomocysteinase as a therapeutic target

The genomic landscape of colorectal cancer (CRC) is shaped by inactivating mutations in tumour suppressors such as APC, and oncogenic mutations such as mutant KRAS. Here we used genetically engineered mouse models, and multimodal mass spectrometry-based metabolomics to study the impact of common genetic drivers of CRC on the metabolic landscape of the intestine. We show that untargeted metabolic profiling can be applied to stratify intestinal tissues according to underlying genetic alterations, and use mass spectrometry imaging to identify tumour, stromal and normal adjacent tissues. By identifying ions that drive variation between normal and transformed tissues, we found dysregulation of the methionine cycle to be a hallmark of APC-deficient CRC. Loss of Apc in the mouse intestine was found to be sufficient to drive expression of one of its enzymes, adenosylhomocysteinase (AHCY), which was also found to be transcriptionally upregulated in human CRC. Targeting of AHCY function impaired growth of APC-deficient organoids in vitro, and prevented the characteristic hyperproliferative/crypt progenitor phenotype driven by acute deletion of Apc in vivo, even in the context of mutant Kras. Finally, pharmacological inhibition of AHCY reduced intestinal tumour burden in ApcMin/+ mice indicating its potential as a metabolic drug target in CRC.

Targeted Desorption Electrospray Ionization Mass Spectrometry Imaging for Drug Distribution, Toxicity, and Tissue Classification Studies

With increased use of mass spectrometry imaging (MSI) in support of pharmaceutical research and development, there are opportunities to develop analytical pipelines that incorporate exploratory high-performance analysis with higher capacity and faster targeted MSI. Therefore, to enable faster MSI data acquisition we present analyte-targeted desorption electrospray ionization–mass spectrometry imaging (DESI-MSI) utilizing a triple-quadrupole (TQ) mass analyzer. The evaluated platform configuration provided superior sensitivity compared to a conventional time-of-flight (TOF) mass analyzer and thus holds the potential to generate data applicable to pharmaceutical research and development. The platform was successfully operated with sampling rates up to 10 scans/s, comparing positively to the 1 scan/s commonly used on comparable DESI-TOF setups. The higher scan rate enabled investigation of the desorption/ionization processes of endogenous lipid species such as phosphatidylcholines and a co-administered cassette of four orally dosed drugs—erlotininb, moxifloxacin, olanzapine, and terfenadine. This was used to enable understanding of the impact of the desorption/ionization processes in order to optimize the operational parameters, resulting in improved compound coverage for olanzapine and the main olanzapine metabolite, hydroxy-olanzapine, in brain tissue sections compared to DESI-TOF analysis or matrix-assisted laser desorption/ionization (MALDI) platforms. The approach allowed reducing the amount of recorded information, thus reducing the size of datasets from up to 150 GB per experiment down to several hundred MB. The improved performance was demonstrated in case studies investigating the suitability of this approach for mapping drug distribution, spatially resolved profiling of drug-induced nephrotoxicity, and molecular–histological tissue classification of ovarian tumors specimens.

Brain metastatic outgrowth and osimertinib resistance are potentiated by RhoA in EGFR-mutant lung cancer

The brain is a major sanctuary site for metastatic cancer cells that evade systemic therapies. Through pre-clinical pharmacological, biological, and molecular studies, we characterize the functional link between drug resistance and central nervous system (CNS) relapse in Epidermal Growth Factor Receptor- (EGFR-) mutant non-small cell lung cancer, which can progress in the brain when treated with the CNS-penetrant EGFR inhibitor osimertinib. Despite widespread osimertinib distribution in vivo, the brain microvascular tumor microenvironment (TME) is associated with the persistence of malignant cell sub-populations, which are poised to proliferate in the brain as osimertinib-resistant lesions over time. Cellular and molecular features of this poised state are regulated through a Ras homolog family member A (RhoA) and Serum Responsive Factor (SRF) gene expression program. RhoA potentiates the outgrowth of disseminated tumor cells on osimertinib treatment, preferentially in response to extracellular laminin and in the brain. Thus, we identify pre-existing and adaptive features of metastatic and drug-resistant cancer cells, which are enhanced by RhoA/SRF signaling and the brain TME during the evolution of osimertinib-resistant disease.

Exploring New Methods to Study and Moderate Proton Beam Damage for Multimodal Imaging on a Single Tissue Section

Characterizing proton beam damage in biological materials is of interest to enable the integration of proton microprobe elemental mapping techniques with other imaging modalities. It is also of relevance to obtain a deeper understanding of mechanical damage to lipids in tissues during proton beam cancer therapy. We have developed a novel strategy to characterize proton beam damage to lipids in biological tissues based on mass spectrometry imaging. This methodology is applied to characterize changes to lipids in tissues ex vivo, irradiated under different conditions designed to mitigate beam damage. This work shows that performing proton beam irradiation at ambient pressure, as well as including the application of an organic matrix prior to irradiation, can reduce damage to lipids in tissues. We also discovered that, irrespective of proton beam irradiation, placing a sample in a vacuum prior to desorption electrospray ionization imaging can enhance lipid signals, a conclusion that may be of future benefit to the mass spectrometry imaging community.

Evaluation of Formalin-Fixed and FFPE Tissues for Spatially Resolved Metabolomics and Drug Distribution Studies

Fixation of samples is broadly used prior to the histological evaluation of tissue samples. Though recent reports demonstrated the ability to use fixed tissues for mass spectrometry imaging (MSI) based proteomics, glycomics and tumor classification studies, to date comprehensive evaluation of fixation-related effects for spatially resolved metabolomics and drug disposition studies is still missing. In this study we used matrix assisted laser desorption/ionization (MALDI) and desorption electrospray ionization (DESI) MSI to investigate the effect of formalin-fixation and formalin-fixation combined with paraffin embedding on the detectable metabolome including xenobiotics. Formalin fixation was found to cause significant washout of polar molecular species, including inorganic salts, amino acids, organic acids and carnitine species, oxidation of endogenous lipids and formation of reaction products between lipids and fixative ingredients. The slow fixation kinetics under ambient conditions resulted in increased lipid hydrolysis in the tissue core, correlating with the time-dependent progression of the fixation. Paraffin embedding resulted in subsequent partial removal of structural lipids resulting in the distortion of the elucidated biodistributions.

Mass Spectrometry Detection and Imaging of a Non‐Covalent Protein–Drug Complex in Tissue from Orally Dosed Rats

Here, we demonstrate detection by mass spectrometry of an intact protein–drug complex directly from liver tissue from rats that had been orally dosed with the drug. The protein–drug complex comprised fatty acid binding protein 1, FABP1, non‐covalently bound to the small molecule therapeutic bezafibrate. Moreover, we demonstrate spatial mapping of the [FABP1+bezafibrate] complex across a thin section of liver by targeted mass spectrometry imaging. This work is the first demonstration of in situ mass spectrometry analysis of a non‐covalent protein–drug complex formed in vivo and has implications for early stage drug discovery by providing a route to target‐drug characterization directly from the physiological environment.

Mass Spectrometry Detection and Imaging of a Non-Covalent Protein-Drug Complex in Tissue from Orally Dosed Rats

Here, we demonstrate detection by mass spectrometry of an intact protein-drug complex directly from liver tissue from rats that had been orally dosed with the drug. The protein-drug complex comprised fatty acid binding protein 1, FABP1, non-covalently bound to the small molecule therapeutic bezafibrate. Moreover, we demonstrate spatial mapping of the [FABP1+bezafibrate] complex across a thin section of liver by targeted mass spectrometry imaging. This work is the first demonstration of in situ mass spectrometry analysis of a non-covalent protein-drug complex formed in vivo and has implications for early stage drug discovery by providing a route to target-drug characterization directly from the physiological environment.

Ischemia-Selective Cardioprotection by Malonate for Ischemia/Reperfusion Injury

BACKGROUND

Inhibiting SDH (succinate dehydrogenase), with the competitive inhibitor malonate, has shown promise in ameliorating ischemia/reperfusion injury. However, key for translation to the clinic is understanding the mechanism of malonate entry into cells to enable inhibition of SDH, its mitochondrial target, as malonate itself poorly permeates cellular membranes. The possibility of malonate selectively entering the at-risk heart tissue on reperfusion, however, remains unexplored.

METHODS

C57BL/6J mice, C2C12 and H9c2 myoblasts, and HeLa cells were used to elucidate the mechanism of selective malonate uptake into the ischemic heart upon reperfusion. Cells were treated with malonate while varying pH or together with transport inhibitors. Mouse hearts were either perfused ex vivo (Langendorff) or subjected to in vivo left anterior descending coronary artery ligation as models of ischemia/reperfusion injury. Succinate and malonate levels were assessed by liquid chromatography-tandem mass spectrometry LC-MS/MS, in vivo by mass spectrometry imaging, and infarct size by TTC (2,3,5-triphenyl-2H-tetrazolium chloride) staining.

RESULTS

Malonate was robustly protective against cardiac ischemia/reperfusion injury, but only if administered at reperfusion and not when infused before ischemia. The extent of malonate uptake into the heart was proportional to the duration of ischemia. Malonate entry into cardiomyocytes in vivo and in vitro was dramatically increased at the low pH (≈6.5) associated with ischemia. This increased uptake of malonate was blocked by selective inhibition of MCT1 (monocarboxylate transporter 1). Reperfusion of the ischemic heart region with malonate led to selective SDH inhibition in the at-risk region. Acid-formulation greatly enhances the cardioprotective potency of malonate.

CONCLUSIONS

Cardioprotection by malonate is dependent on its entry into cardiomyocytes. This is facilitated by the local decrease in pH that occurs during ischemia, leading to its selective uptake upon reperfusion into the at-risk tissue, via MCT1. Thus, malonate's preferential uptake in reperfused tissue means it is an at-risk tissue-selective drug that protects against cardiac ischemia/reperfusion injury.

Atmospheric-Pressure Infrared Laser-Ablation Plasma-Postionization Mass Spectrometry Imaging of Formalin-Fixed Paraffin-Embedded (FFPE) and Fresh-Frozen Tissue Sections with No Sample Preparation

Mass spectrometry imaging (MSI) encompasses a powerful suit of techniques which provide spatially resolved atomic and molecular information from almost any sample type. MSI is now widely used in preclinical research to provide insight into metabolic phenotypes of disease. Typically, fresh-frozen tissue preparations are considered optimal for biological MSI and other traditional preservation methods such as formalin fixation, alone or with paraffin embedding (FFPE), are considered less optimal or even incompatible. Due to the prevalence of FFPE tissue storage, particularly for rare and therefore high-value tissue samples, there is substantial motivation for optimizing MSI methods for analysis of FFPE tissue. Here, we present a novel modality, atmospheric-pressure infrared laser-ablation plasma postionization (AP-IR-LA-PPI), with the first proof-of-concept examples of MSI for FFPE and fresh-frozen tissues, with no post-sectioning sample preparation. We present ion images from FFPE and fresh tissues in positive and negative ion modes. Molecular annotations (via the Metaspace annotation engine) and on-tissue MS/MS provide additional confidence that the detected ions arise from a broad range of metabolite and lipid classes from both FFPE and fresh-frozen tissues.

Quantitative Characterization of Three Carbonic Anhydrase Inhibitors by LESA Mass Spectrometry

Liquid extraction surface analysis (LESA) coupled to native mass spectrometry (MS) presents unique analytical opportunities due to its sensitivity, speed, and automation. Here, we examine whether this tool can be used to quantitatively probe protein-ligand interactions through calculation of equilibrium dissociation constants (K_d values). We performed native LESA MS analyses for a well-characterized system comprising bovine carbonic anhydrase II and the ligands chlorothiazide, dansylamide, and sulfanilamide, and compared the results with those obtained from direct infusion mass spectrometry and surface plasmon resonance measurements. Two LESA approaches were considered: In one approach, the protein and ligand were premixed in solution before being deposited and dried onto a solid substrate for LESA sampling, and in the second, the protein alone was dried onto the substrate and the ligand was included in the LESA sampling solvent. Good agreement was found between the K_d values derived from direct infusion MS and LESA MS when the protein and ligand were premixed; however, K_d values determined from LESA MS measurements where the ligand was in the sampling solvent were inconsistent. Our results suggest that LESA MS is a suitable tool for quantitative analysis of protein-ligand interactions when the dried sample comprises both protein and ligand.

Correlating Mass Spectrometry Imaging and Liquid Chromatography-Tandem Mass Spectrometry for Tissue-Based Pharmacokinetic Studies

Liquid chromatography-tandem mass spectrometry (LC-MS/MS) is a standard tool used for absolute quantification of drugs in pharmacokinetic (PK) studies. However, all spatial information is lost during the extraction and elucidation of a drugs biodistribution within the tissue is impossible. In the study presented here we used a sample embedding protocol optimized for mass spectrometry imaging (MSI) to prepare up to 15 rat intestine specimens at once. Desorption electrospray ionization (DESI) and matrix assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) were employed to determine the distributions and relative abundances of four benchmarking compounds in the intestinal segments. High resolution MALDI-MSI experiments performed at 10 µm spatial resolution allowed to determine the drug distribution in the different intestinal histological compartments to determine the absorbed and tissue bound fractions of the drugs. The low tissue bound drug fractions, which were determined to account for 56–66% of the total drug, highlight the importance to understand the spatial distribution of drugs within the histological compartments of a given tissue to rationalize concentration differences found in PK studies. The mean drug abundances of four benchmark compounds determined by MSI were correlated with the absolute drug concentrations. Linear regression resulted in coefficients of determination (R2) ranging from 0.532 to 0.926 for MALDI-MSI and R2 values ranging from 0.585 to 0.945 for DESI-MSI, validating a quantitative relation of the imaging data. The good correlation of the absolute tissue concentrations of the benchmark compounds and the MSI data provides a bases for relative quantification of compounds within and between tissues, without normalization to an isotopically labelled standard, provided that the compared tissues have inherently similar ion suppression effects.

Method To Visualize the Intratumor Distribution and Impact of Gemcitabine in Pancreatic Ductal Adenocarcinoma by Multimodal Imaging

Gemcitabine (dFdC) is a common treatment for pancreatic cancer; however, it is thought that treatment may fail because tumor stroma prevents drug distribution to tumor cells. Gemcitabine is a pro-drug with active metabolites generated intracellularly; therefore, visualizing the distribution of parent drug as well as its metabolites is important. A multimodal imaging approach was developed using spatially coregistered mass spectrometry imaging (MSI), imaging mass cytometry (IMC), multiplex immunofluorescence microscopy (mIF), and hematoxylin and eosin (H&E) staining to assess the local distribution and metabolism of gemcitabine in tumors from a genetically engineered mouse model of pancreatic cancer (KPC) allowing for comparisons between effects in the tumor tissue and its microenvironment. Mass spectrometry imaging (MSI) enabled the visualization of the distribution of gemcitabine (100 mg/kg), its phosphorylated metabolites dFdCMP, dFdCDP and dFdCTP, and the inactive metabolite dFdU. Distribution was compared to small-molecule ATR inhibitor AZD6738 (25 mg/kg), which was codosed. Gemcitabine metabolites showed heterogeneous distribution within the tumor, which was different from the parent compound. The highest abundance of dFdCMP, dFdCDP, and dFdCTP correlated with distribution of endogenous AMP, ADP, and ATP in viable tumor cell regions, showing that gemcitabine active metabolites are reaching the tumor cell compartment, while AZD6738 was located to nonviable tumor regions. The method revealed that the generation of active, phosphorylated dFdC metabolites as well as treatment-induced DNA damage primarily correlated with sites of high proliferation in KPC PDAC tumor tissue, rather than sites of high parent drug abundance.

Holistic Characterization of a Salmonella Typhimurium Infection Model Using Integrated Molecular Imaging

A more complete and holistic view on host-microbe interactions is needed to understand the physiological and cellular barriers that affect the efficacy of drug treatments and allow the discovery and development of new therapeutics. Here, we developed a multimodal imaging approach combining histopathology with mass spectrometry imaging (MSI) and same section imaging mass cytometry (IMC) to study the effects of Salmonella Typhimurium infection in the liver of a mouse model using the S. Typhimurium strains SL3261 and SL1344. This approach enables correlation of tissue morphology and specific cell phenotypes with molecular images of tissue metabolism. IMC revealed a marked increase in immune cell markers and localization in immune aggregates in infected tissues. A correlative computational method (network analysis) was deployed to find metabolic features associated with infection and revealed metabolic clusters of acetyl carnitines, as well as phosphatidylcholine and phosphatidylethanolamine plasmalogen species, which could be associated with pro-inflammatory immune cell types. By developing an IMC marker for the detection of Salmonella LPS, we were further able to identify and characterize those cell types which contained S. Typhimurium.

GSK-3 Inhibition Is Cytotoxic in Glioma Stem Cells through Centrosome Destabilization and Enhances the Effect of Radiotherapy in Orthotopic Models

BACKGROUND

Previous data on glycogen synthase kinase 3 (GSK-3) inhibition in cancer models support a cytotoxic effect with selectivity for tumor cells compared to normal tissue but the effect of these inhibitors in glioma has not been widely studied. Here, we investigate their potential as cytotoxics in glioma.

METHODS

We assessed the effect of pharmacologic GSK-3 inhibition on established (U87, U251) and patient-derived (GBM1, GBM4) glioblastoma (GBM) cell lines using cytotoxicity assays as well as undertaking a detailed investigation of the effect on cell cycle, mitosis, and centrosome biology. We also assessed drug uptake and efficacy of GSK-3 inhibition alone and in combination with radiation in xenograft models.

RESULTS

Using the selective GSK-3 inhibitor AZD2858, we demonstrated single agent cytotoxicity in two patient-derived glioma cell lines (GBM1, GBM4) and two established cell lines (U251 and U87) with IC50 in the low micromolar range promoting centrosome disruption, failed mitosis, and S-phase arrest. Glioma xenografts exposed to AZD2858 also showed growth delay compared to untreated controls. Combined treatment with radiation increased the cytotoxic effect of clinical radiation doses in vitro and in orthotopic glioma xenografts.

CONCLUSIONS

These data suggest that GSK-3 inhibition promotes cell death in glioma through disrupting centrosome function and promoting mitotic failure and that AZD2858 is an effective adjuvant to radiation at clinical doses.

Correlative Imaging of Trace Elements and Intact Molecular Species in a Single-Tissue Sample at the 50 μm Scale

Elemental and molecular imaging play a crucial role in understanding disease pathogenesis. To accurately correlate elemental and molecular markers, it is desirable to perform sequential elemental and molecular imaging on a single-tissue section. However, very little is known about the impact of performing these measurements in sequence. In this work, we highlight some of the challenges and successes associated with performing elemental mapping in sequence with mass spectrometry imaging. Specifically, the feasibility of molecular mapping using the mass spectrometry imaging (MSI) techniques matrix-assisted laser desorption ionization (MALDI) and desorption electrospray ionization (DESI) in sequence with the elemental mapping technique particle-induced X-ray emission (PIXE) is explored. Challenges for integration include substrate compatibility, as well as delocalization and spectral changes. We demonstrate that while sequential imaging comes with some compromises, sequential DESI-PIXE imaging is sufficient to correlate sulfur, iron, and lipid markers in a single tissue section at the 50 μm scale.

Spatial visualization of comprehensive brain neurotransmitter systems and neuroactive substances by selective in situ chemical derivatization mass spectrometry imaging

Molecule-specific techniques such as MALDI and desorption electrospray ionization mass spectrometry imaging enable direct and simultaneous mapping of biomolecules in tissue sections in a single experiment. However, neurotransmitter imaging in the complex environment of biological samples remains challenging. Our covalent charge-tagging approach using on-tissue chemical derivatization of primary and secondary amines and phenolic hydroxyls enables comprehensive mapping of neurotransmitter networks. Here, we present robust and easy-to-use chemical derivatization protocols that facilitate quantitative and simultaneous molecular imaging of complete neurotransmitter systems and drugs in diverse biological tissue sections with high lateral resolution. This is currently not possible with any other imaging technique. The protocol, using fluoromethylpyridinium and pyrylium reagents, describes all steps from tissue preparation (~1 h), chemical derivatization (1-2 h), data collection (timing depends on the number of samples and lateral resolution) and data analysis and interpretation. The specificity of the chemical reaction can also help users identify unknown chemical identities. Our protocol can reveal the cellular locations in which signaling molecules act and thus shed light on the complex responses that occur after the administration of drugs or during the course of a disease.

Comparison of 13 C MRI of hyperpolarized [1-13 C]pyruvate and lactate with the corresponding mass spectrometry images in a murine lymphoma model

PURPOSE

To compare carbon-13 (13 C) MRSI of hyperpolarized [1-13 C]pyruvate metabolism in a murine tumor model with mass spectrometric (MS) imaging of the corresponding tumor sections in order to cross validate these metabolic imaging techniques and to investigate the effects of pyruvate delivery and tumor lactate concentration on lactate labeling.

METHODS

[1-13 C]lactate images were obtained from tumor-bearing mice, following injection of hyperpolarized [1-13 C]pyruvate, using a single-shot 3D 13 C spectroscopic imaging sequence in vivo and using desorption electrospray ionization MS imaging of the corresponding rapidly frozen tumor sections ex vivo. The images were coregistered, and levels of association were determined by means of Spearman rank correlation and Cohen kappa coefficients as well as linear mixed models. The correlation between [1-13 C]pyruvate and [1-13 C]lactate in the MRS images and between [12 C] and [1-13 C]lactate in the MS images were determined by means of Pearson correlation coefficients.

RESULTS

[1-13 C]lactate images generated by MS imaging were significantly correlated with the corresponding MRS images. The correlation coefficient between [1-13 C]lactate and [1-13 C]pyruvate in the MRS images was higher than between [1-13 C]lactate and [12 C]lactate in the MS images.

CONCLUSION

The inhomogeneous distribution of labeled lactate observed in the MRS images was confirmed by MS imaging of the corresponding tumor sections. The images acquired using both techniques show that the rate of 13 C label exchange between the injected pyruvate and endogenous tumor lactate pool is more correlated with the rate of pyruvate delivery to the tumor cells and is less affected by the endogenous lactate concentration.

Method to Investigate the Distribution of Water-Soluble Drug-Delivery Systems in Fresh Frozen Tissues Using Imaging Mass Cytometry

Imaging mass cytometry (IMC) offers the opportunity to image metal- and heavy halogen-containing xenobiotics in a highly multiplexed experiment with other immunochemistry-based reagents to distinguish uptake into different tissue structures or cell types. However, in practice, many xenobiotics are not amenable to this analysis, as any compound which is not bound to the tissue matrix will delocalize during aqueous sample-processing steps required for IMC analysis. Here, we present a strategy to perform IMC experiments on a water-soluble polysarcosine-modified dendrimer drug-delivery system (S-Dends). This strategy involves two consecutive imaging acquisitions on the same tissue section using the same instrumental platform, an initial laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MSI) experiment followed by tissue staining and a standard IMC experiment. We demonstrated that settings can be found for the initial ablation step that leave sufficient residual tissue for subsequent antibody staining and visualization. This workflow results in lateral resolution for the S-Dends of 2 μm followed by imaging of metal-tagged antibodies at 1 μm.

Deep Learning-Based Annotation Transfer between Molecular Imaging Modalities: An Automated Workflow for Multimodal Data Integration

An ever-increasing array of imaging technologies are being used in the study of complex biological samples, each of which provides complementary, occasionally overlapping information at different length scales and spatial resolutions. It is important to understand the information provided by one technique in the context of the other to achieve a more holistic overview of such complex samples. One way to achieve this is to use annotations from one modality to investigate additional modalities. For microscopy-based techniques, these annotations could be manually generated using digital pathology software or automatically generated by machine learning (including deep learning) methods. Here, we present a generic method for using annotations from one microscopy modality to extract information from complementary modalities. We also present a fast, general, multimodal registration workflow [evaluated on multiple mass spectrometry imaging (MSI) modalities, matrix-assisted laser desorption/ionization, desorption electrospray ionization, and rapid evaporative ionization mass spectrometry] for automatic alignment of complex data sets, demonstrating an order of magnitude speed-up compared to previously published work. To demonstrate the power of the annotation transfer and multimodal registration workflows, we combine MSI, histological staining (such as hematoxylin and eosin), and deep learning (automatic annotation of histology images) to investigate a pancreatic cancer mouse model. Neoplastic pancreatic tissue regions, which were histologically indistinguishable from one another, were observed to be metabolically different. We demonstrate the use of the proposed methods to better understand tumor heterogeneity and the tumor microenvironment by transferring machine learning results freely between the two modalities.

Implications of Peak Selection in the Interpretation of Unsupervised Mass Spectrometry Imaging Data Analyses

Mass spectrometry imaging can produce large amounts of complex spectral and spatial data. Such data sets are often analyzed with unsupervised machine learning approaches, which aim at reducing their complexity and facilitating their interpretation. However, choices made during data processing can impact the overall interpretation of these analyses. This work investigates the impact of the choices made at the peak selection step, which often occurs early in the data processing pipeline. The discussion is done in terms of visualization and interpretation of the results of two commonly used unsupervised approaches: t-distributed stochastic neighbor embedding and k-means clustering, which differ in nature and complexity. Criteria considered for peak selection include those based on hypotheses (exemplified herein in the analysis of metabolic alterations in genetically engineered mouse models of human colorectal cancer), particular molecular classes, and ion intensity. The results suggest that the choices made at the peak selection step have a significant impact in the visual interpretation of the results of either dimensionality reduction or clustering techniques and consequently in any downstream analysis that relies on these. Of particular significance, the results of this work show that while using the most abundant ions can result in interesting structure-related segmentation patterns that correlate well with histological features, using a smaller number of ions specifically selected based on prior knowledge about the biochemistry of the tissues under investigation can result in an easier-to-interpret, potentially more valuable, hypothesis-confirming result. Findings presented will help researchers understand and better utilize unsupervised machine learning approaches to mine high-dimensionality data.

Evaluation of UV-C Decontamination of Clinical Tissue Sections for Spatially Resolved Analysis by Mass Spectrometry Imaging (MSI)

Clinical tissue specimens are often unscreened, and preparation of tissue sections for analysis by mass spectrometry imaging (MSI) can cause aerosolization of particles potentially carrying an infectious load. We here present a decontamination approach based on ultraviolet-C (UV-C) light to inactivate clinically relevant pathogens such as herpesviridae, papovaviridae human immunodeficiency virus, or SARS-CoV-2, which may be present in human tissue samples while preserving the biodistributions of analytes within the tissue. High doses of UV-C required for high-level disinfection were found to cause oxidation and photodegradation of endogenous species. Lower UV-C doses maintaining inactivation of clinically relevant pathogens to a level of increased operator safety were found to be less destructive to the tissue metabolome and xenobiotics. These doses caused less alterations of the tissue metabolome and allowed elucidation of the biodistribution of the endogenous metabolites. Additionally, we were able to determine the spatially integrated abundances of the ATR inhibitor ceralasertib from decontaminated human biopsies using desorption electrospray ionization-MSI (DESI-MSI).

The amino acid transporter SLC7A5 is required for efficient growth of KRAS-mutant colorectal cancer

Oncogenic KRAS mutations and inactivation of the APC tumor suppressor co-occur in colorectal cancer (CRC). Despite efforts to target mutant KRAS directly, most therapeutic approaches focus on downstream pathways, albeit with limited efficacy. Moreover, mutant KRAS alters the basal metabolism of cancer cells, increasing glutamine utilization to support proliferation. We show that concomitant mutation of Apc and Kras in the mouse intestinal epithelium profoundly rewires metabolism, increasing glutamine consumption. Furthermore, SLC7A5, a glutamine antiporter, is critical for colorectal tumorigenesis in models of both early- and late-stage metastatic disease. Mechanistically, SLC7A5 maintains intracellular amino acid levels following KRAS activation through transcriptional and metabolic reprogramming. This supports the increased demand for bulk protein synthesis that underpins the enhanced proliferation of KRAS-mutant cells. Moreover, targeting protein synthesis, via inhibition of the mTORC1 regulator, together with Slc7a5 deletion abrogates the growth of established Kras-mutant tumors. Together, these data suggest SLC7A5 as an attractive target for therapy-resistant KRAS-mutant CRC.

Bromopyrylium Derivatization Facilitates Identification by Mass Spectrometry Imaging of Monoamine Neurotransmitters and Small Molecule Neuroactive Compounds

Mass spectrometry imaging using matrix-assisted laser desorption/ionization and desorption electrospray ionization has recently been employed to investigate the distribution of neurotransmitters, including biogenic amines and amino acids, directly in brain tissue sections. Ionization is facilitated by charge-tagging through pyrylium derivatization of primary amine containing neurotransmitters directly in tissue sections, significantly improving the limit of detection. Since the derivatization adds carbon and hydrogen to the target compounds, the resulting isotopic patterns of the products are not distinctive from those of the nonderivatized species. Here, we describe an approach for chemically modifying the reactive pyrylium ion to introduce the distinct isotopic signature of bromine in mass spectra of chemically derivatized substances in tissue sections. The method enables monoamine compounds to be distinguished directly in tissue sections, facilitating their identification.

ILC2-driven innate immune checkpoint mechanism antagonizes NK cell antimetastatic function in the lung

Metastasis constitutes the primary cause of cancer-related deaths, with the lung being a commonly affected organ. We found that activation of lung-resident group 2 innate lymphoid cells (ILC2s) orchestrated suppression of natural killer (NK) cell-mediated innate antitumor immunity, leading to increased lung metastases and mortality. Using multiple models of lung metastasis, we show that interleukin (IL)-33-dependent ILC2 activation in the lung is involved centrally in promoting tumor burden. ILC2-driven innate type 2 inflammation is accompanied by profound local suppression of interferon-γ production and cytotoxic function of lung NK cells. ILC2-dependent suppression of NK cells is elaborated via an innate regulatory mechanism, which is reliant on IL-5-induced lung eosinophilia, ultimately limiting the metabolic fitness of NK cells. Therapeutic targeting of IL-33 or IL-5 reversed NK cell suppression and alleviated cancer burden. Thus, we reveal an important function of IL-33 and ILC2s in promoting tumor metastasis via their capacity to suppress innate type 1 immunity.

Characterization of an Aggregated Three-Dimensional Cell Culture Model by Multimodal Mass Spectrometry Imaging

Mass spectrometry imaging (MSI) is an established analytical tool capable of defining and understanding complex tissues by determining the spatial distribution of biological molecules. Three-dimensional (3D) cell culture models mimic the pathophysiological environment of in vivo tumors and are rapidly emerging as a valuable research tool. Here, multimodal MSI techniques were employed to characterize a novel aggregated 3D lung adenocarcinoma model, developed by the group to mimic the in vivo tissue. Regions of tumor heterogeneity and the hypoxic microenvironment were observed based on the spatial distribution of a variety of endogenous molecules. Desorption electrospray ionization (DESI)-MSI defined regions of a hypoxic core and a proliferative outer layer from metabolite distribution. Targeted metabolites (e.g., lactate, glutamine, and citrate) were mapped to pathways of glycolysis and the TCA cycle demonstrating tumor metabolic behavior. The first application of imaging mass cytometry (IMC) with 3D cell culture enabled single-cell phenotyping at 1 μm spatial resolution. Protein markers of proliferation (K_i-67) and hypoxia (glucose transporter 1) defined metabolic signaling in the aggregoid model, which complemented the metabolite data. Laser ablation inductively coupled plasma (LA-ICP)-MSI analysis localized endogenous elements including magnesium and copper, further differentiating the hypoxia gradient and validating the protein expression. Obtaining a large amount of molecular information on a complementary nature enabled an in-depth understanding of the biological processes within the novel tumor model. Combining powerful imaging techniques to characterize the aggregated 3D culture highlighted a future methodology with potential applications in cancer research and drug development.

A Critical and Concise Review of Mass Spectrometry Applied to Imaging in Drug Discovery

During the past decade, mass spectrometry imaging (MSI) has become a robust and versatile methodology to support modern pharmaceutical research and development. The technologies provide data on the biodistribution, metabolism, and delivery of drugs in tissues, while also providing molecular maps of endogenous metabolites, lipids, and proteins. This allows researchers to make both pharmacokinetic and pharmacodynamic measurements at cellular resolution in tissue sections or clinical biopsies. Despite drug imaging within samples now playing a vital role within research and development (R&D) in leading pharmaceutical companies, however, the challenges in turning compounds into medicines continue to evolve as rapidly as the technologies used to discover them. The increasing cost of development of new and emerging therapeutic modalities, along with the associated risks of late-stage program attrition, means there is still an unmet need in our ability to address an increasing array of challenging bioanalytical questions within drug discovery. We require new capabilities and strategies of integrated imaging to provide context for fundamental disease-related biological questions that can also offer insights into specific project challenges. Integrated molecular imaging and advanced image analysis have the opportunity to provide a world-class capability that can be deployed on projects in which we cannot answer the question with our battery of established assays. Therefore, here we will provide an updated concise review of the use of MSI for drug discovery; we will also critically consider what is required to embed MSI into a wider evolving R&D landscape and allow long-lasting impact in the industry.

Microbiome-derived carnitine mimics as previously unknown mediators of gut-brain axis communication

Alterations to the gut microbiome are associated with various neurological diseases, yet evidence of causality and identity of microbiome-derived compounds that mediate gut-brain axis interaction remain elusive. Here, we identify two previously unknown bacterial metabolites 3-methyl-4-(trimethylammonio)butanoate and 4-(trimethylammonio)pentanoate, structural analogs of carnitine that are present in both gut and brain of specific pathogen-free mice but absent in germ-free mice. We demonstrate that these compounds are produced by anaerobic commensal bacteria from the family Lachnospiraceae (Clostridiales) family, colocalize with carnitine in brain white matter, and inhibit carnitine-mediated fatty acid oxidation in a murine cell culture model of central nervous system white matter. This is the first description of direct molecular inter-kingdom exchange between gut prokaryotes and mammalian brain cells, leading to inhibition of brain cell function.

High-resolution 3D visualization of nanomedicine distribution in tumors

To improve the clinical translation of anti-cancer nanomedicines, it is necessary to begin building specific insights into the broad concept of the Enhanced Permeability and Retention (EPR) effect, using detailed investigations of the accumulation, distribution and retention of nanomedicines in solid tumors. Nanomedicine accumulation in preclinical tumors has been extensively studied; however, treatment efficacy will be heavily influenced by both the quantity of drug-loaded nanomedicines reaching the tumor as well as their spatial distribution throughout the tumor. It remains a challenge to image the heterogeneity of nanomedicine distribution in 3 dimensions within solid tumors with a high degree of spatial resolution using standard imaging approaches.

Methods: To achieve this, an ex vivo micro computed tomography (µCT) imaging approach was developed to visualize the intratumoral distribution of contrast agent-loaded PEGylated liposomes. Using this semi-quantitative method, whole 3-dimensional (3D) tumor liposome distribution was determined with 17 µm resolution in a phenotypically diverse panel of four preclinical xenograft and patient-derived explant (PDX) tumor models.

Results: High-resolution ex vivo μCT imaging revealed striking differences in liposome distribution within tumors in four models with different vascular patterns and densities, stromal contents, and microenvironment morphologies. Following intravenous dosing, the model with the highest density of pericyte-supported vessels showed the greatest liposome accumulation, while the model with vessels present in regions of high α-smooth muscle actin (αSMA) content presented with a large proportion of the liposomes at depths beyond the tumor periphery. The two models with an unsupported vascular network demonstrated a more restricted pattern of liposome distribution.

Conclusion: Taken together, vessel distribution and support (the latter indicative of functionality) appear to be key factors determining the accumulation and distribution pattern of liposomes in tumors. Our findings demonstrate that high-resolution 3D visualization of nanomedicine distribution is a useful tool for preclinical nanomedicine research, providing valuable insights into the influence of the tumor vasculature and microenvironment on nanomedicine localization.

Nanoextraction Coupled to Liquid Chromatography Mass Spectrometry Delivers Improved Spatially Resolved Analysis

Direct analyte-probed nanoextraction (DAPNe) is a technique that allows extraction of drug and endogenous compounds from a discrete location on a tissue sample using a nano capillary filled with solvent. Samples can be extracted from spot diameters as low as 6 μm. Studies previously undertaken by our group have shown that the technique can provide good precision (5%) for analyzing drug molecules in 150 μm diameter areas of homogenized tissue, provided an internal standard is sprayed on to the tissue prior to analysis. However, without an isotopically labeled standard, the repeatability is poor, even after normalization to the spot area or matrix compounds. By application to tissue homogenates spiked with drug compounds, we can demonstrate that it is possible to significantly improve the repeatability of the technique by incorporating a liquid chromatography separation step. Liquid chromatography is a technique for separating compounds prior to mass spectrometry (LC-MS) which enables separation of isomeric compounds that cannot be discriminated using mass spectrometry alone, as well as reducing matrix interferences. Conventionally, LC-MS is carried out on bulk or homogenized samples, which means analysis is essentially an average of the sample and does not take into account discrete areas. This work opens a new opportunity for spatially resolved liquid chromatography mass spectrometry with precision better than 20%.

Quantitative Imaging of Proteins in Tissue by Stable Isotope Labeled Mimetic Liquid Extraction Surface Analysis Mass Spectrometry

Absolute quantification of proteins in tissue is important for numerous fields of study. Liquid chromatography–mass spectrometry (LC–MS) methods are the norm but typically involve lengthy sample preparation including tissue homogenization, which results in the loss of information relating to spatial distribution. Here, we propose liquid extraction surface analysis (LESA) mass spectrometry (MS) of stable isotope labeled mimetic tissue models for the spatially resolved quantification of intact ubiquitin in rat and mouse brain tissue. Measured ubiquitin concentrations are in agreement with values found in the literature. Images of rat and mouse brain tissue demonstrate spatial variation in the concentration of ubiquitin and demonstrate the utility of spatially resolved quantitative measurement of proteins in tissue. Although we have focused on ubiquitin, the method has the potential for broader application to the absolute quantitation of any endogenous protein or protein-based drug in tissue.

Revealing the Regional Localization and Differential Lung Retention of Inhaled Compounds by Mass Spectrometry Imaging

Background: For the treatment of respiratory disease, inhaled drug delivery aims to provide direct access to pharmacological target sites while minimizing systemic exposure. Despite this long-held tenet of inhaled therapeutic advantage, there are limited data of regional drug localization in the lungs after inhalation. The aim of this study was to investigate the distribution and retention of different chemotypes typifying available inhaled drugs [slowly dissolving neutral fluticasone propionate (FP) and soluble bases salmeterol and salbutamol] using mass spectrometry imaging (MSI). Methods: Salmeterol, salbutamol, and FP were simultaneously delivered by inhaled nebulization to rats. In the same animals, salmeterol-d₃, salbutamol-d₃, and FP-d₃ were delivered by intravenous (IV) injection. Samples of lung tissue were obtained at 2- and 30-minute postdosing, and high-resolution MSI was used to study drug distribution and retention. Results: IV delivery resulted in homogeneous lung distribution for all molecules. In comparison, while inhalation also gave rise to drug presence in the entire lung, there were regional chemotype-dependent areas of higher abundance. At the 30-minute time point, inhaled salmeterol and salbutamol were preferentially retained in bronchiolar tissue, whereas FP was retained in all regions of the lungs. Conclusion: This study clearly demonstrates that inhaled small molecule chemotypes are differentially distributed in lung tissue after inhalation, and that high-resolution MSI can be applied to study these retention patterns.

Correction to: Assessing the effect of nitisinone induced hypertyrosinaemia on monoamine neurotransmitters in brain tissue from a murine model of alkaptonuria using mass spectrometry imaging

The original publication of this article contained an incorrect version that did not include some final reviewers' suggestions, was inadvertently received for production and published. The original article has been corrected.

Assessing the effect of nitisinone induced hypertyrosinaemia on monoamine neurotransmitters in brain tissue from a murine model of alkaptonuria using mass spectrometry imaging

OBJECTIVE

Nitisinone induced hypertyrosinaemia is a concern in patients with Alkaptonuria (AKU). It has been suggested that this may alter neurotransmitter metabolism, specifically dopamine and serotonin. Herein mass spectrometry imaging (MSI) is used for the direct measurement of 2,4-diphenyl-pyranylium tetrafluoroborate (DPP-TFB) derivatives of monoamine neurotransmitters in brain tissue from a murine model of AKU following treatment with nitisinone.

METHODS

Metabolite changes were assessed using MSI on DPP-TFB derivatised fresh frozen tissue sections directing analysis towards primary amine neurotransmitters. Matched tail bleed plasma samples were analysed using LC-MS/MS. Eighteen BALB/c mice were included in this study: HGD^-/- (n = 6, treated with nitisinone-4 mg/L, in drinking water); HGD^-/- (n = 6, no treatment) and HGD^+/- (n = 6, no treatment).

RESULTS

Ion intensity and distribution of DPP-TFB derivatives in brain tissue for dopamine, 3-methoxytyramine, noradrenaline, tryptophan, serotonin, and glutamate were not significantly different following treatment with nitisinone in HGD ^-/- mice, and no significant differences were observed between HGD^-/- and HGD^+/- mice that received no treatment. Tyrosine (10-fold in both comparisons, p = 0.003; [BALB/c HGD^-/- (n = 6) and BALB/c HGD^+/- (n = 6) (no treatment) vs. BALB/c HGD^-/- (n = 6, treated)] and tyramine (25-fold, p = 0.02; 32-fold, p = 0.02) increased significantly following treatment with nitisinone. Plasma tyrosine and homogentisic acid increased (ninefold, p = < 0.0001) and decreased (ninefold, p = 0.004), respectively in HGD^-/- mice treated with nitisinone.

CONCLUSIONS

Monoamine neurotransmitters in brain tissue from a murine model of AKU did not change following treatment with nitisinone. These findings have significant implications for patients with AKU as they suggest monoamine neurotransmitters are not altered following treatment with nitisinone.

Liquid Extraction Surface Analysis (LESA) Electron-Induced Dissociation and Collision-Induced Dissociation Mass Spectrometry of Small Molecule Drug Compounds

Here, we present liquid extraction surface analysis (LESA) coupled with electron-induced dissociation (EID) mass spectrometry in a Fourier-transform ion cyclotron resonance mass spectrometer for the analysis of small organic pharmaceutical compounds directly from dosed tissue. First, the direct infusion electrospray ionisation EID and collision-induced dissociation (CID) behaviour of erlotinib, moxifloxacin, clozapine and olanzapine standards were compared. EID mass spectra were also compared with experimental or reference electron impact ionisation mass spectra. The results show that (with the exception of erlotinib) EID and CID result in complementary fragment ions. Subsequently, we performed LESA EID MS/MS and LESA CID MS/MS on singly charged ions of moxifloxacin and erlotinib extracted from a thin tissue section of rat kidney from a cassette-dosed animal. Both techniques provided structural information, with the majority of peaks observed for the drug standards also observed for the tissue-extracted species. Overall, these results demonstrate the feasibility of LESA EID MS/MS of drug compounds from dosed tissue and extend the number of molecular structures for which EID behaviour has been determined. Graphical Abstract ᅟ.

Uncovering the regional localization of inhaled salmeterol retention in the lung

Treatment of respiratory disease with a drug delivered via inhalation is generally held as being beneficial as it provides direct access to the lung target site with a minimum systemic exposure. There is however only limited information of the regional localization of drug retention following inhalation. The aim of this study was to investigate the regional and histological localization of salmeterol retention in the lungs after inhalation and to compare it to systemic administration. Lung distribution of salmeterol delivered to rats via nebulization or intravenous (IV) injection was analyzed with high-resolution mass spectrometry imaging (MSI). Salmeterol was widely distributed in the entire section at 5 min after inhalation, by 15 min it was preferentially retained in bronchial tissue. Via a novel dual-isotope study, where salmeterol was delivered via inhalation and d₃-salmeterol via IV to the same rat, could the effective gain in drug concentration associated with inhaled delivery relative to IV, expressed as a site-specific lung targeting factor, was 5-, 31-, and 45-fold for the alveolar region, bronchial sub-epithelium and epithelium, respectively. We anticipate that this MSI-based framework for quantifying regional and histological lung targeting by inhalation will accelerate discovery and development of local and more precise treatments of respiratory disease.

Application of Various Normalization Methods for Microscale Analysis of Tissues Using Direct Analyte Probed Nanoextraction

Direct analyte probed nanoextraction (DAPNe) is a method of extracting material from a microscale region of a sample and provides the opportunity for detailed mass spectrometry analysis of extracted analytes from a small area. The technique has been shown to provide enhanced sensitivity compared with bulk analysis by selectively removing analytes from their matrix and has been applied for selective analysis of single cells and even single organelles. However, the quantitative capabilities of the technique are yet to be fully evaluated. In this study, various normalization techniques were investigated in order to improve the quantitative capabilities of the technique. Two methods of internal standard incorporation were applied to test substrates, which were designed to replicate biological sample matrices. Additionally, normalization to the extraction spot area and matrix compounds were investigated for suitability in situations when an internal standard is not available. The variability observed can be significantly reduced by using a sprayed internal standard and, in some cases, by normalizing to the extracted area.

Quantitation of Endogenous Metabolites in Mouse Tumors Using Mass-Spectrometry Imaging

Described is a quantitative-mass-spectrometry-imaging (qMSI) methodology for the analysis of lactate and glutamate distributions in order to delineate heterogeneity among mouse tumor models used to support drug-discovery efficacy testing. We evaluate and report on preanalysis-stabilization methods aimed at improving the reproducibility and efficiency of quantitative assessments of endogenous molecules in tissues. Stability experiments demonstrate that optimum stabilization protocols consist of frozen-tissue embedding, post-tissue-sectioning desiccation, and storage at -80 °C of tissue sections sealed in vacuum-tight containers. Optimized stabilization protocols are used in combination with qMSI methodology for the absolute quantitation of lactate and glutamate in tumors, incorporating the use of two different stable-isotope-labeled versions of each analyte and spectral-clustering performed on each tissue section using k-means clustering to allow region-specific, pixel-by-pixel quantitation. Region-specific qMSI was used to screen different tumor models and identify a phenotype that has low lactate heterogeneity, which will enable accurate measurements of lactate modulation in future drug-discovery studies. We conclude that using optimized qMSI protocols, it is possible to quantify endogenous metabolites within tumors, and region-specific quantitation can provide valuable insight into tissue heterogeneity and the tumor microenvironment.