Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry Imaging: Diagnostic Pathways and Metabolites for Renal Tumor Entities.

BACKGROUND: Correct tumor subtyping of primary renal tumors is essential for treatment decision in daily routine. Most of the tumors can be classified based on morphology alone. Nevertheless, some diagnoses are difficult, and further investigations are needed for correct tumor subtyping. Besides histochemical investigations, high-mass-resolution matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) can detect new diagnostic biomarkers and hence improve the diagnostic. PATIENTS AND METHODS: Formalin-fixed paraffin embedded tissue specimens from clear cell renal cell carcinoma (ccRCC, n = 552), papillary renal cell carcinoma (pRCC, n = 122), chromophobe renal cell carcinoma (chRCC, n = 108), and renal oncocytoma (rO, n = 71) were analyzed by high-mass-resolution MALDI fourier-transform ion cyclotron resonance (FT-ICR) MSI. The SPACiAL pipeline was executed for automated co-registration of histological and molecular features. Pathway enrichment and pathway topology analysis were performed to determine significant differences between RCC subtypes. RESULTS: We discriminated the four histological subtypes (ccRCC, pRCC, chRCC, and rO) and established the subtype-specific pathways and metabolic profiles. rO showed an enrichment of pentose phosphate, taurine and hypotaurine, glycerophospholipid, amino sugar and nucleotide sugar, fructose and mannose, glycine, serine, and threonine pathways. ChRCC is defined by enriched pathways including the amino sugar and nucleotide sugar, fructose and mannose, glycerophospholipid, taurine and hypotaurine, glycine, serine, and threonine pathways. Pyrimidine, amino sugar and nucleotide sugar, glycerophospholipids, and glutathione pathways are enriched in ccRCC. Furthermore, we detected enriched phosphatidylinositol and glycerophospholipid pathways in pRCC. CONCLUSION: In summary, we performed a classification system with a mean accuracy in tumor discrimination of 85.13%. Furthermore, we detected tumor-specific biomarkers for the four most common primary renal tumors by MALDI-MSI. This method is a useful tool in differential diagnosis and biomarker detection.

Metabolic tumor constitution is superior to tumor regression grading for evaluating response to neoadjuvant therapy of esophageal adenocarcinoma patients.

The response to neoadjuvant therapy can vary widely between individual patients. Histopathological tumor regression grading (TRG) is a strong factor for treatment response and survival prognosis of esophageal adenocarcinoma (EAC) patients following neoadjuvant treatment and surgery. However, TRG systems are usually based on the estimation of residual tumor but do not consider stromal or metabolic changes after treatment. Spatial metabolomics analysis is a powerful tool for molecular tissue phenotyping but has not been used so far in the context of neoadjuvant treatment of esophageal cancer. We used imaging mass spectrometry to assess the potential of spatial metabolomics on tumor and stroma tissue for evaluating therapy response of neoadjuvant-treated EAC patients. With an accuracy of 89.7%, the binary classifier trained on spatial tumor metabolite data proved to be superior for stratifying patients when compared with histopathological response assessment, which had an accuracy of 70.5%. Sensitivities and specificities for the poor and favorable survival patient groups ranged from 84.9% to 93.3% using the metabolic classifier and from 62.2% to 78.1% using TRG. The tumor classifier was the only significant prognostic factor (HR 3.38, 95% CI 1.40-8.12, p = 0.007) when adjusted for clinicopathological parameters such as TRG (HR 1.01, 95% CI 0.67-1.53, p = 0.968) or stromal classifier (HR 1.86, 95% CI 0.81-4.25, p = 0.143). The classifier even allowed us to further stratify patients within the TRG1-3 categories. The underlying mechanisms of response to treatment have been figured out through network analysis. In summary, metabolic response evaluation outperformed histopathological response evaluation in our study with regard to prognostic stratification. This finding indicates that the metabolic constitution of the tumor may have a greater impact on patient survival than the quantity of residual tumor cells or the stroma. © 2021 The Authors. The Journal of Pathology published by John Wiley & Sons, Ltd. on behalf of The Pathological Society of Great Britain and Ireland.

A simple preparation step to remove excess liquid lipids in white adipose tissue enabling improved detection of metabolites via MALDI-FTICR imaging MS.

Matrix-assisted laser desorption ionization (MALDI) Fourier transform ion cyclotron resonance (FTICR) imaging mass spectrometry (MS) is a powerful technology used to analyze metabolites in various tissues. However, it faces significant challenges in studying adipose tissues. Poor matrix distribution and crystallization caused by excess liquid lipids on the surface of tissue sections hamper m/z species detection, an adverse effect that particularly presents in lipid-rich white adipose tissue (WAT). In this study, we integrated a simple and low-cost preparation step into the existing MALDI-FTICR imaging MS pipeline. The new method-referred to as filter paper application-is characterized by an easy sample handling and high reproducibility. The aforementioned filter paper is placed onto the tissue prior to matrix application in order to remove the layer of excess liquid lipids. Consequently, MALDI-FTICR imaging MS detection was significantly improved, resulting in a higher number of detected m/z species and higher ion intensities. After analyzing various durations of filter paper application, 30 s was found to be optimal, resulting in the detection of more than 3700 m/z species. Apart from the most common lipids found in WAT, other molecules involved in various metabolic pathways were detected, including nucleotides, carbohydrates, and amino acids. Our study is the first to propose a solution to a specific limitation of MALDI-FTICR imaging MS in investigating lipid-rich WAT. The filter paper approach can be performed quickly and is particularly effective for achieving uniform matrix distribution on fresh frozen WAT while maintaining tissue integrity. It thus helps to gain insight into the metabolism in WAT.

Multimodal analysis of formalin-fixed and paraffin-embedded tissue by MALDI imaging and fluorescence in situ hybridization for combined genetic and metabolic analysis.

Multimodal tissue analyses that combine two or more detection technologies provide synergistic value compared to single methods and are employed increasingly in the field of tissue-based diagnostics and research. Here, we report a technical pipeline that describes a combined approach of HER2/CEP17 fluorescence in situ hybridization (FISH) analysis with MALDI imaging on the very same section of formalin-fixed and paraffin-embedded (FFPE) tissue. FFPE biopsies and a tissue microarray of human gastroesophageal adenocarcinoma were analyzed by MALDI imaging. Subsequently, the very same section was hybridized by HER2/CEP17 FISH. We found that tissue morphology of both, the biopsies and the tissue microarray, was unaffected by MALDI imaging and the HER2 and CEP17 FISH signals were analyzable. In comparison with FISH analysis of samples without MALDI imaging, we observed no difference in terms of fluorescence signal intensity and gene copy number. Our combined approach revealed adenosine monophosphate, measured by MALDI imaging, as a prognostic marker. HER2 amplification, which was detected by FISH, is a stratifier between good and poor patient prognosis. By integrating both stratification parameters on the basis of our combined approach, we were able to strikingly improve the prognostic effect. Combining molecules detected by MALDI imaging with the gene copy number detected by HER2/CEP17 FISH, we found a synergistic effect, which enhances patient prognosis. This study shows that our combined approach allows the detection of genetic and metabolic properties from one very same FFPE tissue section, which are specific for HER2 and hence suitable for prognosis. Furthermore, this synergism might be useful for response prediction in tumors.

Molecular similarities and differences from human pulmonary fibrosis and corresponding mouse model: MALDI imaging mass spectrometry in comparative medicine.

Animal models can reproduce some model-specific aspects of human diseases, but some animal models translate poorly or fail to translate to the corresponding human disease. Here, we develop a strategy to systematically compare human and mouse tissues, and conduct a proof-of-concept experiment to identify molecular similarities and differences using patients with idiopathic pulmonary fibrosis and a bleomycin-induced fibrosis mouse model. Our novel approach employs high-throughput tissue microarrays (TMAs) of humans and mice, high-resolution matrix-assisted laser desorption/ionization-Fourier transform-ion cyclotron resonance-mass spectrometry imaging (MALDI-FT-ICR-MSI) to spatially resolve mass spectra at the level of specific metabolites, and hierarchical clustering and pathway enrichment analysis to identify functionally similar/different molecular patterns and pathways in pathological lesions of humans and mice. We identified a large number of common molecules (n=1366) and fewer exclusive molecules in humans (n=83) and mice (n=54). Among the common molecules, the 'ascorbate and aldarate metabolism' pathway had the highest similarity in human and mouse lesions. This proof-of-concept study demonstrates that our novel strategy employing a reliable and easy-to-perform experimental design accurately identifies pathways and factors that can be directly compared between animal models and human diseases.

PAXgene fixation enables comprehensive metabolomic and proteomic analyses of tissue specimens by MALDI MSI.

An alcohol-based non-crosslinking tissue fixative, PAXgene Tissue System, has been proposed as alternative fixation method to formalin, providing superior and morphological preservation. To date, metabolites have not been assessed in PAXgene-fixed tissues. The study focuses on a comparison between PAXgene and standard formalin fixation for metabolomic analysis by MALDI mass spectrometry imaging. Therefore, fifty-six samples from seven mice organs were fixed with PAXgene (PFPE) or formalin (FFPE), embedded in paraffin, and processed to a tissue microarray. PAXgene was able to spatially preserve metabolites in organs achieving an overlap of common metabolites ranging from 34 to 78% with FFPE. Highly similar signal intensities and visualization of molecules demonstrated negligible differences for metabolite imaging on PFPE compared to FFPE tissues. In addition, we performed proteomic analysis of intact proteins and peptides derived from enzymatic digestion. An overlap of 33 to 58% was found between FFPE and PFPE tissue samples in peptide analysis with a higher number of PFPE-specific peaks. Analysis of intact proteins achieved an overlap in the range of 0 to 28% owing to the poor detectability of cross-linked proteins in formalin-fixed tissues. Furthermore, metabolite and peptide profiles obtained from PFPE tissues were able to correctly classify organs independent of the fixation method, whereas a distinction of organs by protein profiles was only achieved by PAXgene fixation. Finally, we applied MALDI MSI to human biopsies by sequentially analyzing metabolites and peptides within the same tissue section. Concerning prospective studies, PAXgene can be used as an alternative fixative for multi-omic tissue analysis.

A new model system identifies epidermal growth factor receptor-human epidermal growth factor receptor 2 (HER2) and HER2-human epidermal growth factor receptor 3 heterodimers as potent inducers of oesophageal epithelial cell invasion.

Oesophageal squamous cell carcinomas and oesophageal adenocarcinomas show distinct patterns of ErbB expression and dimers. The functional effects of specific ErbB homodimers or heterodimers on oesophageal (cancer) cell behaviour, particularly invasion during early carcinogenesis, remain unknown. Here, a new cellular model system for controlled activation of epidermal growth factor receptor (EGFR) or human epidermal growth factor receptor 2 (HER2) and EGFR-HER2 or HER2-human epidermal growth factor receptor 3 (HER3) homodimers and heterodimers was studied in non-neoplastic squamous oesophageal epithelial Het-1A cells. EGFR, HER2 and HER3 intracellular domains (ICDs) were fused to dimerization domains (DmrA/DmrA and DmrC), and transduced into Het-1A cells lacking ErbB expression. Dimerization of EGFR, HER2 or EGFR-HER2 and HER2-HER3 ICDs was induced by synthetic ligands (A/A or A/C dimerizers). This was accompanied by phosphorylation of the respective EGFR, HER2 and HER3 ICDs and activation of distinct downstream signalling pathways, such as phospholipase Cγ1, Akt, STAT and Src family kinases. Phenotypically, ErbB dimers caused cell rounding and non-apoptotic blebbing, specifically in EGFR-HER2 and HER2-HER3 heterodimer cells. In a Transwell assay, cell migration velocity was elevated in HER2 dimer cells as compared with empty vector cells. In addition, HER2 dimer cells showed in increased cell invasion, reaching significance for induced HER2-HER3 heterodimers (P = 0.015). Importantly, in three-dimensional organotypic cultures, empty vector cells grew as a superficial cell layer, resembling oesophageal squamous epithelium. In contrast, induced HER2 homodimer cells were highly invasive into the matrix and formed cell clusters. This was associated with partial loss of cytokeratin 7 (when HER2 homodimers were modelled) and p63 (when EGFR-HER2 heterodimers were modelled), which suggests a change or loss of squamous cell differentiation. Controlled activation of specific EGFR, HER2 and HER3 homodimers and heterodimers caused oesophageal squamous epithelial cell migration and/or invasion, especially in a three-dimensional microenvironment, thereby functionally identifying ErbB homodimers and heterodimers as important drivers of oesophageal carcinogenesis. Copyright © 2017 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Round robin study of formalin-fixed paraffin-embedded tissues in mass spectrometry imaging.

Mass spectrometry imaging (MSI) has provided many results with translational character, which still have to be proven robust in large patient cohorts and across different centers. Although formalin-fixed paraffin-embedded (FFPE) specimens are most common in clinical practice, no MSI multicenter study has been reported for FFPE samples. Here, we report the results of the first round robin MSI study on FFPE tissues with the goal to investigate the consequences of inter- and intracenter technical variation on masking biological effects. A total of four centers were involved with similar MSI instrumentation and sample preparation equipment. A FFPE multi-organ tissue microarray containing eight different types of tissue was analyzed on a peptide and metabolite level, which enabled investigating different molecular and biological differences. Statistical analyses revealed that peptide intercenter variation was significantly lower and metabolite intercenter variation was significantly higher than the respective intracenter variations. When looking at relative univariate effects of mass signals with statistical discriminatory power, the metabolite data was more reproducible across centers compared to the peptide data. With respect to absolute effects (cross-center common intensity scale), multivariate classifiers were able to reach on average > 90% accuracy for peptides and > 80% for metabolites if trained with sufficient amount of cross-center data. Overall, our study showed that MSI data from FFPE samples could be reproduced to a high degree across centers. While metabolite data exhibited more reproducibility with respect to relative effects, peptide data-based classifiers were more directly transferable between centers and therefore more robust than expected. Graphical abstract ᅟ.

How Suitable is Matrix-Assisted Laser Desorption/Ionization-Time-of-Flight for Metabolite Imaging from Clinical Formalin-Fixed and Paraffin-Embedded Tissue Samples in Comparison to Matrix-Assisted Laser Desorption/Ionization-Fourier Transform Ion Cyclotron Resonance Mass Spectrometry?

In research and clinical settings, formalin-fixed and paraffin-embedded (FFPE) tissue specimens are collected routinely and therefore this material constitutes a highly valuable source to gather insight in metabolic changes of diseases. Among mass spectrometry techniques to examine the molecular content of FFPE tissue, mass spectrometry imaging (MSI) is the most appropriate when morphological and histological features are to be related to metabolic information. Currently, high-resolution mass spectrometers are widely used for metabolomics studies. However, with regards to matrix-assisted laser desorption/ionization (MALDI) MSI, no study has so far addressed the necessity of instrumental mass resolving power in terms of clinical diagnosis and prognosis using archived FFPE tissue. For this matter we performed for the first time a comprehensive comparison between a high mass resolution Fourier-transform ion cyclotron resonance (FTICR) mass spectrometer and a time-of-flight (TOF) instrument with lower mass resolving power. Spectra analysis revealed that about one-third of the detected peaks remained unresolved by MALDI-TOF, which led to a 3-5 times lower number of m/z features compared to FTICR measurements. Overlaid peak information and background noise in TOF images made a precise assignment of molecular attributes to morphological features more difficult and limited classification approaches. This clearly demonstrates the need for high-mass resolution capabilities for metabolite imaging. Nevertheless, MALDI-TOF allowed reproducing and verifying individual markers identified previously by MALDI-FTICR MSI. The systematic comparison gives rise to a synergistic combination of the different MSI platforms for high-throughput discovery and validation of biomarkers.

MALDI imaging mass spectrometry as a novel tool for detecting histone modifications in clinical tissue samples.

Histone post-translational modifications (PTMs), histone variants and enzymes responsible for the incorporation or the removal of the PTMs are being increasingly associated with human disease. Combinations of histone PTMs and the specific incorporation of variants contribute to the establishment of cellular identity and hence are potential markers that could be exploited in disease diagnostics and prognostics and therapy response prediction. Due to the scarcity of suitable antibodies and the pre-requirement of tissue homogenization for more advanced analytical techniques, comprehensive information regarding the spatial distribution of these factors at the tissue level has been lacking. MALDI imaging mass spectrometry provides an ideal platform to measure histone PTMs and variants from tissues while maintaining the information about their spatial distribution. Discussed in this review are the relevance of histones in the context of human disease and the contribution of MALDI imaging mass spectrometry in measuring histones in situ.

High-resolution MALDI-FT-ICR MS imaging for the analysis of metabolites from formalin-fixed, paraffin-embedded clinical tissue samples.

We present the first analytical approach to demonstrate the in situ imaging of metabolites from formalin-fixed, paraffin-embedded (FFPE) human tissue samples. Using high-resolution matrix-assisted laser desorption/ionization Fourier-transform ion cyclotron resonance mass spectrometry imaging (MALDI-FT-ICR MSI), we conducted a proof-of-principle experiment comparing metabolite measurements from FFPE and fresh frozen tissue sections, and found an overlap of 72% amongst 1700 m/z species. In particular, we observed conservation of biomedically relevant information at the metabolite level in FFPE tissues. In biomedical applications, we analysed tissues from 350 different cancer patients and were able to discriminate between normal and tumour tissues, and different tumours from the same organ, and found an independent prognostic factor for patient survival. This study demonstrates the ability to measure metabolites in FFPE tissues using MALDI-FT-ICR MSI, which can then be assigned to histology and clinical parameters. Our approach is a major technical, histochemical, and clinicopathological advance that highlights the potential for investigating diseases in archived FFPE tissues.

Distribution and quantification of irinotecan and its active metabolite SN-38 in colon cancer murine model systems using MALDI MSI.

Tissue distribution and quantitative analysis of small molecules is a key to assess the mechanism of drug action and evaluate treatment efficacy. The prodrug irinotecan (CPT-11) is widely used for chemotherapeutic treatment of colorectal cancer. CPT-11 requires conversion into its active metabolite SN-38 to exert the desired pharmacological effect. MALDI-Fourier transform ion cyclotron resonance (FT-ICR) and MALDI-time-of-flight (TOF) mass spectrometry imaging (MSI) were performed for detection of CPT-11 and SN-38 in tissue sections from mice post CPT-11 injection. In-depth information was gained about the distribution and quantity of drug compounds in normal and tumor tissue. The prodrug was metabolized, as proven by the detection of SN-38 in liver, kidney and digestive tract. In tumors from genetic mouse models for colorectal cancer (Apc (1638N/wt) x pvillin-Kras (V12G) ), CPT-11 was detected but not the active metabolite. In order to correlate drug distribution relative to vascularization, MALDI data were superimposed with CD31 (PECAM-1) immunohistochemistry. This analysis indicated that intratumoral access of CPT-11 mainly occurred by extravasation from microvessels. The present study exploits the power of MALDI MSI in drug analysis, and presents a novel approach to monitor drug distribution in relation to vessel functionality in preclinical and clinical research.

Patterns of Carbon-Bound Exogenous Compounds Impact Disease Pathophysiology in Lung Cancer Subtypes in Different Ways.

Carbon-bound exogenous compounds, such as polycyclic aromatic hydrocarbons (PAHs), tobacco-specific nitrosamines, aromatic amines, and organohalogens, are known to affect both tumor characteristics and patient outcomes in lung squamous cell carcinoma (LUSC); however, the roles of these compounds in lung adenocarcinoma (LUAD) remain unclear. We analyzed 11 carbon-bound exogenous compounds in LUAD and LUSC samples using in situ high mass-resolution matrix-assisted laser desorption/ionization Fourier-transform ion cyclotron resonance mass spectrometry imaging and performed a cluster analysis to compare the patterns of carbon-bound exogenous compounds between these two lung cancer subtypes. Correlation analyses were conducted to investigate associations among exogenous compounds, endogenous metabolites, and clinical data, including patient survival outcomes and smoking behaviors. Additionally, we examined differences in exogenous compound patterns between normal and tumor tissues. Our analyses revealed that PAHs, aromatic amines, and organohalogens were more abundant in LUAD than in LUSC, whereas the tobacco-specific nitrosamine nicotine-derived nitrosamine ketone was more abundant in LUSC. Patients with LUAD and LUSC could be separated according to carbon-bound exogenous compound patterns detected in the tumor compartment. The same compounds had differential impacts on patient outcomes, depending on the cancer subtype. Correlation and network analyses indicated substantial differences between LUAD and LUSC metabolomes, associated with substantial differences in the patterns of the carbon-bound exogenous compounds. These data suggest that the contributions of these carcinogenic compounds to cancer biology may differ according to the cancer subtypes.

Ascorbate deficiency increases progression of shigellosis in guinea pigs and mice infection models.

Shigella spp. are the causative agents of bacterial dysentery and shigellosis, mainly in children living in developing countries. The study of Shigella entire life cycle in vivo and the evaluation of vaccine candidates' protective efficacy have been hampered by the lack of a suitable animal model of infection. None of the studies evaluated so far (rabbit, guinea pig, mouse) allowed the recapitulation of full shigellosis symptoms upon Shigella oral challenge. Historical reports have suggested that dysentery and scurvy are both metabolic diseases associated with ascorbate deficiency. Mammals, which are susceptible to Shigella infection (humans, non-human primates and guinea pigs) are among the few species unable to synthesize ascorbate. We optimized a low-ascorbate diet to induce moderate ascorbate deficiency, but not scurvy, in guinea pigs to investigate whether poor vitamin C status increases the progression of shigellosis. Moderate ascorbate deficiency increased shigellosis symptom severity during an extended period of time (up to 48 h) in all strains tested (Shigella sonnei, Shigella flexneri 5a, and 2a). At late time points, an important influx of neutrophils was observed both within the disrupted colonic mucosa and in the luminal compartment, although Shigella was able to disseminate deep into the organ to reach the sub-mucosal layer and the bloodstream. Moreover, we found that ascorbate deficiency also increased Shigella penetration into the colon epithelium layer in a Gulo-/- mouse infection model. The use of these new rodent models of shigellosis opens new doors for the study of both Shigella infection strategies and immune responses to Shigella infection.

Spatial metabolomics reveals upregulation of several pyrophosphate-producing pathways in cortical bone of Hyp mice.

Patients with the renal phosphate-wasting disease X-linked hypophosphatemia (XLH) and Hyp mice, the murine homolog of XLH, are characterized by loss-of-function mutations in phosphate-regulating endopeptidase homolog X-linked (PHEX), leading to excessive secretion of the bone-derived phosphotropic hormone FGF23. The mineralization defect in patients with XLH and Hyp mice is caused by a combination of hypophosphatemia and local accumulation of mineralization-inhibiting molecules in bone. However, the mechanism by which PHEX deficiency regulates bone cell metabolism remains elusive. Here, we used spatial metabolomics by employing matrix-assisted laser desorption/ionization (MALDI) Fourier-transform ion cyclotron resonance mass spectrometry imaging (MSI) of undecalcified bone cryosections to characterize in situ metabolic changes in bones of Hyp mice in a holistic, unbiased manner. We found complex changes in Hyp bone metabolism, including perturbations in pentose phosphate, purine, pyrimidine, and phospholipid metabolism. Importantly, our study identified an upregulation of several biochemical pathways involved in intra- and extracellular production of the mineralization inhibitor pyrophosphate in the bone matrix of Hyp mice. Our data emphasize the utility of MSI-based spatial metabolomics in bone research and provide holistic in situ insights as to how Phex deficiency-induced changes in biochemical pathways in bone cells are linked to impaired bone mineralization.

Spatial metabolomics for evaluating response to neoadjuvant therapy in non-small cell lung cancer patients.

BACKGROUND: The response to neoadjuvant chemotherapy (NAC) differs substantially among individual patients with non-small cell lung cancer (NSCLC). Major pathological response (MPR) is a histomorphological read-out used to assess treatment response and prognosis in patients NSCLC after NAC. Although spatial metabolomics is a promising tool for evaluating metabolic phenotypes, it has not yet been utilized to assess therapy responses in patients with NSCLC. We evaluated the potential application of spatial metabolomics in cancer tissues to assess the response to NAC, using a metabolic classifier that utilizes mass spectrometry imaging combined with machine learning. METHODS: Resected NSCLC tissue specimens obtained after NAC (n = 88) were subjected to high-resolution mass spectrometry, and these data were used to develop an approach for assessing the response to NAC in patients with NSCLC. The specificities of the generated tumor cell and stroma classifiers were validated by applying this approach to a cohort of biologically matched chemotherapy-naïve patients with NSCLC (n = 85). RESULTS: The developed tumor cell metabolic classifier stratified patients into different prognostic groups with 81.6% accuracy, whereas the stroma metabolic classifier displayed 78.4% accuracy. By contrast, the accuracies of MPR and TNM staging for stratification were 62.5% and 54.1%, respectively. The combination of metabolic and MPR classifiers showed slightly lower accuracy than either individual metabolic classifier. In multivariate analysis, metabolic classifiers were the only independent prognostic factors identified (tumor: P = 0.001, hazards ratio [HR] = 3.823, 95% confidence interval [CI] = 1.716-8.514; stroma: P = 0.049, HR = 2.180, 95% CI = 1.004-4.737), whereas MPR (P = 0.804; HR = 0.913; 95% CI = 0.445-1.874) and TNM staging (P = 0.078; HR = 1.223; 95% CI = 0.977-1.550) were not independent prognostic factors. Using Kaplan-Meier survival analyses, both tumor and stroma metabolic classifiers were able to further stratify patients as NAC responders (P < 0.001) and non-responders (P < 0.001). CONCLUSIONS: Our findings indicate that the metabolic constitutions of both tumor cells and the stroma are valuable additions to the classical histomorphology-based assessment of tumor response.

Spatial Metabolomics Identifies Distinct Tumor-Specific Subtypes in Gastric Cancer Patients.

PURPOSE: Current systems of gastric cancer molecular classification include genomic, molecular, and morphological features. Gastric cancer classification based on tissue metabolomics remains lacking. This study aimed to define metabolically distinct gastric cancer subtypes and identify their clinicopathological and molecular characteristics. EXPERIMENTAL DESIGN: Spatial metabolomics by high mass resolution imaging mass spectrometry was performed in 362 patients with gastric cancer. K-means clustering was used to define tumor and stroma-related subtypes based on tissue metabolites. The identified subtypes were linked with clinicopathological characteristics, molecular features, and metabolic signatures. Responses to trastuzumab treatment were investigated across the subtypes by introducing an independent patient cohort with HER2-positive gastric cancer from a multicenter observational study. RESULTS: Three tumor- and three stroma-specific subtypes with distinct tissue metabolite patterns were identified. Tumor-specific subtype T1(HER2+MIB+CD3+) positively correlated with HER2, MIB1, DEFA-1, CD3, CD8, FOXP3, but negatively correlated with MMR. Tumor-specific subtype T2(HER2-MIB-CD3-) negatively correlated with HER2, MIB1, CD3, FOXP3, but positively correlated with MMR. Tumor-specific subtype T3(pEGFR+) positively correlated with pEGFR. Patients with tumor subtype T1(HER2+MIB+CD3+) had elevated nucleotide levels, enhanced DNA metabolism, and a better prognosis than T2(HER2-MIB-CD3-) and T3(pEGFR+). An independent validation cohort confirmed that the T1 subtype benefited from trastuzumab therapy. Stroma-specific subtypes had no association with clinicopathological characteristics, however, linked to distinct metabolic pathways and molecular features. CONCLUSIONS: Patient subtypes derived by tissue-based spatial metabolomics are a valuable addition to existing gastric cancer molecular classification systems. Metabolic differences between the subtypes and their associations with molecular features could provide a valuable tool to aid in selecting specific treatment approaches.

MALDI Mass Spectrometry Imaging-Prognostic Pathways and Metabolites for Renal Cell Carcinomas.

High mass resolution matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) is a suitable method for biomarker detection for several tumor entities. Renal cell carcinoma (RCC) is the seventh most common cancer type and accounts for more than 80% of all renal tumors. Prognostic biomarkers for RCC are still missing. Therefore, we analyzed a large, multicenter cohort including the three most common RCC subtypes (clear cell RCC (ccRCC), papillary RCC (pRCC) and chromophobe RCC (chRCC)) by MALDI for prognostic biomarker detection. MALDI-Fourier-transform ion cyclotron resonance (FT-ICR)-MSI analysis was performed for renal carcinoma tissue sections from 782 patients. SPACiAL pipeline was integrated for automated co-registration of histological and molecular features. Kaplan-Meier analyses with overall survival as endpoint were executed to determine the metabolic features associated with clinical outcome. We detected several pathways and metabolites with prognostic power for RCC in general and also for different RCC subtypes.

Patterns of Carbon-Bound Exogenous Compounds in Patients with Lung Cancer and Association with Disease Pathophysiology.

Asymptomatic anthracosis is the accumulation of black carbon particles in adult human lungs. It is a common occurrence, but the pathophysiologic significance of anthracosis is debatable. Using in situ high mass resolution matrix-assisted laser desorption/ionization (MALDI) fourier-transform ion cyclotron resonance (FT-ICR) mass spectrometry imaging analysis, we discovered noxious carbon-bound exogenous compounds, such as polycyclic aromatic hydrocarbons (PAH), tobacco-specific nitrosamines, or aromatic amines, in a series of 330 patients with lung cancer in highly variable and unique patterns. The characteristic nature of carbon-bound exogenous compounds had a strong association with patient outcome, tumor progression, the tumor immune microenvironment, programmed death-ligand 1 (PD-L1) expression, and DNA damage. Spatial correlation network analyses revealed substantial differences in the metabolome of tumor cells compared with tumor stroma depending on carbon-bound exogenous compounds. Overall, the bioactive pool of exogenous compounds is associated with several changes in lung cancer pathophysiology and correlates with patient outcome. Given the high prevalence of anthracosis in the lungs of adult humans, future work should investigate the role of carbon-bound exogenous compounds in lung carcinogenesis and lung cancer therapy. SIGNIFICANCE: This study identifies a bioactive pool of carbon-bound exogenous compounds in patient tissues associated with several tumor biological features, contributing to an improved understanding of drivers of lung cancer pathophysiology.

De novo discovery of metabolic heterogeneity with immunophenotype-guided imaging mass spectrometry.

BACKGROUND: Imaging mass spectrometry enables in situ label-free detection of thousands of metabolites from intact tissue samples. However, automated steps for multi-omics analyses and interpretation of histological images have not yet been implemented in mass spectrometry data analysis workflows. The characterization of molecular properties within cellular and histological features is done via time-consuming, non-objective, and irreproducible definitions of regions of interest, which are often accompanied by a loss of spatial resolution due to mass spectra averaging. METHODS: We developed a new imaging pipeline called Spatial Correlation Image Analysis (SPACiAL), which is a computational multimodal workflow designed to combine molecular imaging data with multiplex immunohistochemistry (IHC). SPACiAL allows comprehensive and spatially resolved in situ correlation analyses on a cellular resolution. To demonstrate the method, matrix-assisted laser desorption-ionization (MALDI) Fourier-transform ion cyclotron resonance (FTICR) imaging mass spectrometry of metabolites and multiplex IHC staining were performed on the very same tissue section of mouse pancreatic islets and on human gastric cancer tissue specimens. The SPACiAL pipeline was used to perform an automatic, semantic-based, functional tissue annotation of histological and cellular features to identify metabolic profiles. Spatial correlation networks were generated to analyze metabolic heterogeneity associated with cellular features. RESULTS: To demonstrate the new method, the SPACiAL pipeline was used to identify metabolic signatures of alpha and beta cells within islets of Langerhans, which are cell types that are not distinguishable via morphology alone. The semantic-based, functional tissue annotation allows an unprecedented analysis of metabolic heterogeneity via the generation of spatial correlation networks. Additionally, we demonstrated intra- and intertumoral metabolic heterogeneity within HER2/neu-positive and -negative gastric tumor cells. CONCLUSIONS: We developed the SPACiAL workflow to provide IHC-guided in situ metabolomics on intact tissue sections. Diminishing the workload by automated recognition of histological and functional features, the pipeline allows comprehensive analyses of metabolic heterogeneity. The multimodality of immunohistochemical staining and extensive molecular information from imaging mass spectrometry has the advantage of increasing both the efficiency and precision for spatially resolved analyses of specific cell types. The SPACiAL method is a stepping stone for the objective analysis of high-throughput, multi-omics data from clinical research and practice that is required for diagnostics, biomarker discovery, or therapy response prediction.