The human colonic microbiota has been estimated to contain 38 trillion bacteria whereas the total human somatic cells constitute 30 trillion. The mutualistic relationship between host and microbiome is ancient and believed to have evolved over 600 million years ago. Other than a digestive function and provision to the host of certain vitamins, the gut microbiome has a single important and overarching purpose, which is maintenance of homeostasis by regulation of host metabolism and immune function. Consuming a diet that maintains gut microbial eubiosis and avoids dysbiosis is essential for a long healthy life. Dysbiosis contributes to noncommunicable illnesses, including hypertension, cardiovascular disease, obesity, diabetes, inflammatory bowel disease, and cancer, any of which can reduce lifespan. The combined impact of diabetes and heart disease alone potentially shortens lifespan by up to 15-23 years. Although there has been considerable research on the bacterial abundance and diversity of the human gut microbiota, relatively little detailed attention has been given to the metabolites it produces, especially in relation to morbidity and mortality. By a thorough analysis of the gut bacterial species associated with longevity, we have identified a number of their metabolites that are beneficial to the host in this regard. The action of these metabolites underlines an important principle - that what is generated by the intestinal microbiota from a wholesome diet determines healthy aging and ultimately longevity. Future research on gut microbiota function should focus on the detailed mechanisms of action of beneficial bacterial metabolites that prolong both healthspan and lifespan.

Both the gut and the lungs possess a microbiome, a community of commensal bacteria, archaea, fungi, and viruses that perform important housekeeping functions in those organs. The colonic microbiome primarily ferments indigestible dietary fibers into essential short-chain fatty acids, synthesizes essential vitamins, regulates the mucosal immune system, and forms a protective barrier against pathogenic colonization. The lung microbiome maintains respiratory health primarily by regulating mucosal immunity, providing a physical barrier against invading pathogens, and producing beneficial metabolites. Several colonic microbiota metabolites, including the short-chain fatty acids acetate, propionate, and butyrate, together with the tryptophan metabolites indole-3-acetate and indole-3-propionate, secondary bile acids, and the polyamines spermidine and putrescine, are transported to the lungs via the gut-lung axis. These colonic microbiota biomolecules suppress lung inflammation, strengthen immune homeostasis, and reduce the severity of respiratory diseases. In contrast, lung microorganisms and their metabolites can travel to the gut via the gut-lung axis, influencing intestinal immune responses and potentially leading to an imbalance of gut microorganisms or dysbiosis. This means that respiratory diseases may lead to digestive issues, intestinal inflammation and chronic diseases. Here, we have reviewed this crosstalk and its impact on the principal pulmonary diseases: asthma, chronic obstructive pulmonary disease, cystic fibrosis, bronchogenic carcinoma, COVID-19, interstitial lung diseases, pneumonia, and tuberculosis. It is concluded that the gut microbiome plays a significant part in lung health and disease. Diet, tobacco smoking and electronic cigarette vaping all impact both the gut and lung microbiomes.

Metabolic dysfunction-associated steatotic liver disease (MASLD) is a condition wherein excessive fat accumulates in the liver, leading to inflammation and potential liver damage. In this narrative review, we evaluate the tissue microbiota, how they arise and their constituent microbes, and the role of the intestinal and hepatic microbiota in MASLD. The history of bacteriophages (phages) and their occurrence in the microbiota, their part in the potential causation of MASLD, and conversely, “phage therapy” for antibiotic resistance, obesity, and MASLD, are all described. The microbiota metabolism of bile acids and dietary tryptophan and histidine is defined, together with the impacts of their individual metabolites on MASLD pathogenesis. Both periodontitis and intestinal microbiota dysbiosis may cause MASLD, and how individual microorganisms and their metabolites are involved in these processes is discussed. Novel treatment opportunities for MASLD involving the microbiota exist and include fecal microbiota transplantation, probiotics, prebiotics, synbiotics, tryptophan dietary supplements, intermittent fasting, and phages or their holins and endolysins. Although FDA is yet to approve phage therapy in clinical use, there are multiple FDA-approved clinical trials, and this may represent a new horizon for the future treatment of MASLD.

From a detailed review of 90 experimental and clinical metabolomic investigations of obesity and metabolic dysfunction-associated steatotic liver disease (MASLD), we have developed metabolomic hallmarks for both obesity and MASLD. Obesity studies were conducted in mice, rats, and humans, with consensus biomarker groups in plasma/serum being essential and nonessential amino acids, energy metabolites, gut microbiota metabolites, acylcarnitines and lysophosphatidylcholines (LPC), which formed the basis of the six metabolomic hallmarks of obesity. Additionally, mice and rats shared elevated cholesterol, humans and rats shared elevated fatty acids, and humans and mice shared elevated VLDL/LDL, bile acids and phosphatidylcholines (PC). MASLD metabolomic studies had been performed in mice, rats, hamsters, cows, geese, blunt snout breams, zebrafish, and humans, with the biomarker groups in agreement between experimental and clinical investigations being energy metabolites, essential and nonessential amino acids, fatty acids, and bile acids, which lay the foundation of the five metabolomic hallmarks of MASLD. Furthermore, the experimental group had higher LPC/PC and cholesteryl esters, and the clinical group had elevated acylcarnitines, lysophosphatidylethanolamines/phosphatidylethanolamines (LPE/PE), triglycerides/diglycerides, and gut microbiota metabolites. These metabolomic hallmarks aid in the understanding of the metabolic role played by obesity in MASLD development, inform mechanistic studies into underlying disease pathogenesis, and are critical for new metabolite-inspired therapies.

Both experimental and clinical liver fibrosis leave a metabolic footprint that can be uncovered and defined using metabolomic approaches. Metabolomics combines pattern recognition algorithms with analytical chemistry, in particular, 1H and 13C nuclear magnetic resonance spectroscopy (NMR), gas chromatography–mass spectrometry (GC–MS) and various liquid chromatography–mass spectrometry (LC–MS) platforms. The analysis of liver fibrosis by each of these methodologies is reviewed separately. Surprisingly, there was little general agreement between studies within each of these three groups and also between groups. The metabolomic footprint determined by NMR (two or more hits between studies) comprised elevated lactate, acetate, choline, 3-hydroxybutyrate, glucose, histidine, methionine, glutamine, phenylalanine, tyrosine and citrate. For GC–MS, succinate, fumarate, malate, ascorbate, glutamate, glycine, serine and, in agreement with NMR, glutamine, phenylalanine, tyrosine and citrate were delineated. For LC–MS, only β-muricholic acid, tryptophan, acylcarnitine, p-cresol, valine and, in agreement with NMR, phosphocholine were identified. The metabolomic footprint of liver fibrosis was upregulated as regards glutamine, phenylalanine, tyrosine, citrate and phosphocholine. Several investigators employed traditional Chinese medicine (TCM) treatments to reverse experimental liver fibrosis, and a commentary is given on the chemical constituents that may possess fibrolytic activity. It is proposed that molecular docking procedures using these TCM constituents may lead to novel therapies for liver fibrosis affecting at least one-in-twenty persons globally, for which there is currently no pharmaceutical cure. This in-depth review summarizes the relevant literature on metabolomics and its implications in addressing the clinical problem of liver fibrosis, cirrhosis and its sequelae.

A mass spectrometry-based lipidomic investigation of 30 patients with chronic hepatitis C virus (HCV) infection and 30 age- and sex-matched healthy blood donor controls was undertaken. The clustering and complete separation of these two groups was found by both unsupervised and supervised multivariate data analyses. Three patients who had spontaneously cleared the virus and three who were successfully treated with direct-acting antiviral drugs remained within the HCV-positive metabotype, suggesting that the metabolic effects of HCV may be longer-lived. We identified 21 metabolites that were upregulated in plasma and 34 that were downregulated (p < 1 × 10−16 to 0.0002). Eleven members of the endocannabinoidome were elevated, including anandamide and eight fatty acid amides (FAAs). These likely activated the cannabinoid receptor GPR55, which is a pivotal host factor for HCV replication. FAAH1, which catabolizes FAAs, reduced mRNA expression. Four phosphosphingolipids, d16:1, d18:1, d19:1 sphingosine 1-phosphate, and d18:0 sphinganine 1-phosphate, were increased, together with the mRNA expression for their synthetic enzyme SPHK1. Among the most profoundly downregulated plasma lipids were several lysophosphatidylinositols (LPIs) from 3- to 3000-fold. LPIs are required for the synthesis of phosphatidylinositol 4-phosphate (PI4P) pools that are required for HCV replication, and LPIs can also activate the GPR55 receptor. Our plasma lipidomic findings shed new light on the pathobiology of HCV infection and show that a subset of bioactive lipids that may contribute to liver pathology is altered by HCV infection.

In this review we trace the passage of fundamental ideas through 20th century cancer research that began with observations on mustard gas toxicity in World War I. The transmutation of these ideas across scientific and national boundaries, was channeled from chemical carcinogenesis labs in London via Yale and Chicago, then ultimately to the pharmaceutical industry in Bielefeld, Germany. These first efforts to checkmate cancer with chemicals led eventually to the creation of one of the most successful groups of cancer chemotherapeutic drugs, the oxazaphosphorines, first cyclophosphamide (CP) in 1958 and soon thereafter its isomer ifosfamide (IFO). The giant contributions of Professor Sir Alexander Haddow, Dr. Alfred Z. Gilman & Dr. Louis S. Goodman, Dr. George Gomori and Dr. Norbert Brock step by step led to this breakthrough in cancer chemotherapy. A developing understanding of the metabolic disposition of ifosfamide directed efforts to ameliorate its side-effects, in particular, ifosfamide-induced encephalopathy (IIE). This has resulted in several candidates for the encephalopathic metabolite, including 2-chloroacetaldehyde, 2-chloroacetic acid, acrolein, 3-hydroxypropionic acid and S-carboxymethyl-L-cysteine. The pros and cons for each of these, together with other IFO metabolites, are discussed in detail. It is concluded that IFO produces encephalopathy in susceptible patients, but CP does not, by a “perfect storm,” involving all of these five metabolites. Methylene blue (MB) administration appears to be generally effective in the prevention and treatment of IIE, in all probability by the inhibition of monoamine oxidase in brain potentiating serotonin levels that modulate the effects of IFO on GABAergic and glutamatergic systems. This review represents the authors’ analysis of a large body of published research.

We wished to understand the metabolic reprogramming underlying liver fibrosis progression in mice. Administration to male C57BL/6J mice of the hepatotoxins carbon tetrachloride (CCl4), thioacetamide (TAA), or a 60% high-fat diet, choline-deficient, amino-acid-defined diet (HF-CDAA) was conducted using standard protocols. Livers collected at different times were analyzed by gas chromatography–mass spectrometry-based metabolomics. RNA was extracted from liver and assayed by qRT-PCR for mRNA expression of 11 genes potentially involved in the synthesis of ascorbic acid from hexoses, Gck, Adpgk, Hk1, Hk2, Ugp2, Ugdh, Ugt1a1, Akr1a4, Akr1b3, Rgn and Gulo. All hepatotoxins resulted in similar metabolic changes during active fibrogenesis, despite different etiology and resultant scarring pattern. Diminished hepatic glucose, galactose, fructose, pentose phosphate pathway intermediates, glucuronic acid and long-chain fatty acids were compensated by elevated ascorbate and the product of collagen prolyl 4-hydroxylase, succinate and its downstream metabolites fumarate and malate. Recovery from the HF-CDAA diet challenge (F2 stage fibrosis) after switching to normal chow was accompanied by increased glucose, galactose, fructose, ribulose 5-phosphate, glucuronic acid, the ascorbate metabolite threonate and diminished ascorbate. During the administration of CCl4, TAA and HF-CDAA, aldose reductase Akr1b3 transcription was induced six- to eightfold, indicating increased conversion of glucuronic acid to gulonic acid, a precursor of ascorbate synthesis. Triggering hepatic fibrosis by three independent mechanisms led to the hijacking of glucose and galactose metabolism towards ascorbate synthesis, to satisfy the increased demand for ascorbate as a cofactor for prolyl 4-hydroxylase for mature collagen production. This metabolic reprogramming and causal gene expression changes were reversible. The increased flux in this pathway was mediated predominantly by increased transcription of aldose reductase Akr1b3.

PDF file - 1526KB, Supplementary Table 1 shows random forest analysis results for predictions of lung cancer status in the training set. Supplementary Table 2 shows associations with survival in the training set when the top four predictive metabolites are combined in all cases. Supplementary Table 3 shows associations with survival in the training set, stratified by self-reported race. Supplementary Table 4 shows intraclass correlation coefficients in the quantitated subset. Supplementary Figure 1 depicts workflow of the classification analysis. Supplementary Figure 2 depicts quality control assessment in the training set. Supplementary Figure 3 shows predictions of smoking status in the training set determined by random forest analysis and abundances of tobacco-related metabolites. Supplementary Figure 4 shows overlap of metabolites predictive of lung cancer status in the training set based on random forest analysis, stratified by gender, race and smoking status. Supplementary Figure 5 shows fragmentation patterns of top four predictive metabolites determined by tandem mass spectrometry. Supplementary Figure 6 depicts identification of creatine riboside by NMR. Supplementary Figure 7 shows diurnal effects on top four predictive metabolites. Supplementary Figure 8 shows top four predictive metabolite abundances stratified by smoking status. Supplementary Figure 9 shows Kaplan-Meier survival estimates in the training set depicted for the top four predictive metabolites in stages I-II and their combination. Supplementary Figure 10 shows metabolite abundances stratified by chemotherapy/radiation status and surgery status.

Over the years, a substantial body of information has accumulated suggesting dietary consumption of grapes may have a positive influence on human health. Here, we investigate the potential of grapes to modulate the human microbiome. Microbiome composition as well as urinary and plasma metabolites were sequentially assessed in 29 healthy free-living male (age 24–55 years) and female subjects (age 29–53 years) following two-weeks of a restricted diet (Day 15), two-weeks of a restricted diet with grape consumption (equivalent to three servings per day) (Day 30), and four-weeks of restricted diet without grape consumption (Day 60). Based on alpha-diversity indices, grape consumption did not alter the overall composition of the microbial community, other than with the female subset based on the Chao index. Similarly, based on beta-diversity analyses, the diversity of species was not significantly altered at the three time points of the study. However, following 2 weeks of grape consumption, taxonomic abundance was altered (e.g., decreased Holdemania spp. and increased Streptococcus thermophiles ), as were various enzyme levels and KEGG pathways. Further, taxonomic, enzyme and pathway shifts were observed 30 days following the termination of grape consumption, some of which returned to baseline and some of which suggest a delayed effect of grape consumption. Metabolomic analyses supported the functional significance of these alterations wherein, for example, 2′-deoxyribonic acid, glutaconic acid, and 3-hydroxyphenylacetic acid were elevated following grape consumption and returned to baseline following the washout period. Inter-individual variation was observed and exemplified by analysis of a subgroup of the study population showing unique patterns of taxonomic distribution over the study period. The biological ramifications of these dynamics remain to be defined. However, while it seems clear that grape consumption does not perturb the eubiotic state of the microbiome with normal, healthy human subjects, it is likely that shifts in the intricate interactive networks that result from grape consumption have physiological significance of relevance to grape action.

Over three million Americans are affected by skin cancer each year, largely as a result of exposure to sunlight. The purpose of this study was to determine the potential of grape consumption to modulate UV-induced skin erythema. With 29 human volunteers, we report that nine demonstrated greater resistance to UV irradiation of the skin after consuming the equivalent of three servings of grapes per day for two weeks. We further explored any potential relationship to the gut–skin axis. Alpha- and beta-diversity of the gut microbiome were not altered, but grape consumption modulated microbiota abundance, enzyme levels, and KEGG pathways. Striking differences in the microbiome and metabolome were discerned when comparing the nine individuals showing greater UV resistance with the 20 non-responders. Notably, three urinary metabolites, 2′-deoxyribonic acid, 3-hydroxyphenyl acetic and scyllo-inositol, were depressed in the UV-resistant group. A ROC curve revealed a 71.8% probability that measurement of urinary 2′-deoxyribonic acid identifies a UV skin non-responder. 2′-Deoxyribonic acid is cleaved from the DNA backbone by reactive oxygen species. Three of the nine subjects acquiring UV resistance following grape consumption showed a durable response, and these three demonstrated unique microbiomic and metabolomic profiles. Variable UV skin sensitivity was likely due to glutathione S-transferase polymorphisms. We conclude that a segment of the population is capable of demonstrating greater resistance to a dermal response elicited by UV irradiation as a result of grape consumption. It is uncertain if modulation of the gut-skin axis leads to enhanced UV resistance, but there is correlation. More broadly, it is reasonable to expect that these mechanisms relate to other health outcomes anticipated to result from grape consumption.

Hepatocellular carcinoma (HCC) arises principally against a background of cirrhosis and these two diseases are responsible globally for over 2 million deaths a year. There are few treatment options for liver cirrhosis and HCC, so it is vital to arrest these pathologies early in their development. To do so, we propose dietary and therapeutic solutions that involve the gut microbiota and its consequences. Integrated dietary, environmental and intrinsic signals result in a bidirectional connection between the liver and the gut with its microbiota, known as the gut-liver axis. Numerous lifestyle factors can result in dysbiosis with a change in the functional composition and metabolic activity of the microbiota. A panoply of metabolites can be produced by the microbiota, including ethanol, secondary bile acids, trimethylamine, indole, quinolone, phenazine and their derivatives and the quorum sensor acyl homoserine lactones that may contribute to HCC but have yet to be fully investigated. Gram-negative bacteria can activate the pattern recognition receptor toll-like receptor 4 (TLR4) in the liver leading to nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) signaling, which can contribute to HCC initiation and progression. The goal in preventing HCC should be to ensure a healthy gut microbiota using probiotic supplements containing beneficial bacteria and prebiotic plant fibers such as oligosaccharides that stimulate their growth. The clinical development of TLR4 antagonists is urgently needed to counteract the pathological effects of dysbiosis on the liver and other organs. Further nutrigenomic studies are required to understand better how the diet influences the gut microbiota and its adverse effects on the liver.

The benefits of fruit and vegetable dietary consumption are largely defined in epidemiological terms. Relatively little is known about the discrete effects on metabolic pathways elicited by individual dietary fruits and vegetables. To address this, grape powder was added to both a standard and a high-fat Western pattern diet given to 10-week-old female C57BL/6J mice for a period of 91 days, whereupon 24 h urines were collected and the mice euthanized after a 12 h fast for the collection of liver tissue. Alterations in hepatic and urinary metabolite patterns were determined by gas chromatography-mass spectrometry-based metabolomics. Urinary excretion of the gut microbiota metabolites 4-hydroxyphenylacetic acid, 5-hydroxyindole, glyceric acid, gluconic acid and myo-inositol was attenuated when grape was added to the standard diet but the gut microbiota metabolites gluconic acid, scyllo-inositol, mannitol, xylitol, 5-hydroxyindole and 2-deoxyribonic acid were increased in urine when grape was added to the high-fat diet. Increased hepatic ascorbic acid and 5-oxoproline levels indicated the anti-oxidant effect of grape powder on the liver. Pathway enrichment analysis demonstrated that for both standard and high-fat diets, grape addition significantly upregulated the malate-aspartate shuttle indicating enhanced hepatic utilization of glucose via cytosolic glycolysis for mitochondrial ATP production. It is concluded that a grape diet reprogrammes gut microbiota metabolism, attenuates the hepatic oxidative stress of a high-fat diet and increases the efficiency of glucose utilization by the liver for energy production.

The study of low-molecular-weight metabolites that exist in cells and organisms is known as metabolomics and is often conducted using mass spectrometry laboratory platforms. Definition of oncometabolites in the context of the metabolic phenotype of cancer cells has been accomplished through metabolomics. Oncometabolites result from mutations in cancer cell genes or from hypoxia-driven enzyme promiscuity. As a result, normal metabolites accumulate in cancer cells to unusually high concentrations or, alternatively, unusual metabolites are produced. The typical oncometabolites fumarate, succinate, (2R)-hydroxyglutarate and (2S)-hydroxyglutarate inhibit 2-oxoglutarate-dependent dioxygenases, such as histone demethylases and HIF prolyl-4-hydroxylases, together with DNA cytosine demethylases. As a result of the cancer cell acquiring this new metabolic phenotype, major changes in gene transcription occur and the modification of the epigenetic landscape of the cell promotes proliferation and progression of cancers. Stabilization of HIF1α through inhibition of HIF prolyl-4-hydroxylases by oncometabolites such as fumarate and succinate leads to a pseudohypoxic state that promotes inflammation, angiogenesis and metastasis. Metabolomics has additionally been employed to define the metabolic phenotype of cancer cells and patient biofluids in the search for cancer biomarkers. These efforts have led to the uncovering of the putative oncometabolites sarcosine, glycine, lactate, kynurenine, methylglyoxal, hypotaurine and (2R,3S)-dihydroxybutanoate, for which further research is required.

The human population is burdened by morbidity and mortality from liver diseases that largely arise due to hepatitis virus infection, alcohol abuse, obesity, and diabetes. Despite 2 million global deaths per annum from liver disease, the number of drugs approved by the U.S. Food and Drug Administration (FDA) for the treatment of these disorders is sparse. Eastern medicine embodies a millennia long tradition in the use of natural product remedies for liver disease, which has attracted the interest of western medical practitioners and patients alike. Questions remain regarding the safety, efficacy, and quality of such natural products in a western medical context. Of particular concern is whether or not the mechanism of action of the product is known and, if the remedy has multiple natural constituents, how these interact at a biochemical, physiological, and clinical level. In this Commentary, we have examined the potential of metabolomics to help answer these queries, illustrated by investigations of yin chen hao tang, silymarin, and xiaozhang tie. In all cases, unique understandings of the mechanism of action of these natural products was obtained through metabolomic investigations in animal models, cell culture systems, and in clinical studies. Such mechanistic insights help assure the safety and efficacy of these natural product therapies.

A lipidomic and metabolomic investigation of serum and liver from mice was performed to gain insight into the tumor suppressor gene Hint1. A major reprogramming of lipid homeostasis was found in both serum and liver of Hint1-null (Hint−/−) mice, with significant changes in the levels of many lipid molecules, as compared with gender-, age-, and strain-matched WT mice. In the Hint1−/− mice, serum total and esterified cholesterol were reduced 2.5-fold, and lysophosphatidylcholines (LPCs) and lysophosphatidic acids were 10-fold elevated in serum, with a corresponding fall in phosphatidylcholines (PCs). In the liver, MUFAs and PUFAs, including arachidonic acid (AA) and its metabolic precursors, were also raised, as was mRNA encoding enzymes involved in AA de novo synthesis. There was also a significant 50% increase in hepatic macrophages in the Hint1−/− mice. Several hepatic ceramides and acylcarnitines were decreased in the livers of Hint1−/− mice. The changes in serum LPCs and PCs were neither related to hepatic phospholipase A2 activity nor to mRNAs encoding lysophosphatidylcholine acetyltransferases 1-4. The lipidomic phenotype of the Hint1−/− mouse revealed decreased inflammatory eicosanoids with elevated proliferative mediators that, combined with decreased ceramide apoptosis signaling molecules, may contribute to the tumor suppressor activity of Hint1.

When Santiago Ramón y Cajal was awarded the Nobel Prize for Physiology or Medicine in 1906 for his work on the anatomy of the nervous system, he shared the prize with Camillo Golgi. Working in a simple laboratory set up in his kitchen, Golgi developed in 1873 the “black reaction,” the hardening of tissue in potassium dichromate followed by permeation of the nervous components by silver nitrate.1 This Golgi stain greatly facilitated his own studies on nerve cells in the brain and the work of others such as Ramón y Cajal, who developed the concept of the neuron, a single cell body with multiple branching dendrites and an axon that can stretch for up to 1 meter in humans, all visible with the Golgi stain. This specific black staining of single neurons was the cradle of neuroanatomy and a very early example of a chemical-biological interaction. The chemical staining of tissues for microscopic examination, either directly or first by targeting with an antibody, remains the central pillar of histopathology and owes much to the pioneering works of Golgi and Ramón y Cajal. Technological advances in the field of mass spectrometry in the past 15 years now offer a completely new way of examining tissues, as did Golgi's great advance 140 years ago. Unlike histochemistry and immunohistochemistry (IHC), this new technology does not target molecules in tissues. It is a discovery tool that can be adapted to screening once novel tissue targets have been defined and is known by the forbidding name of matrix-assisted laser desorption/ionization (MALDI) imaging mass spectrometry (MALDI-IMS). Modern mass spectrometers can measure low numbers of ions with accurate mass, meaning that attomole levels of proteins and peptides can be detected as charged species whose mass can be determined with high resolution, facilitating their identification from databases. The secret is not the mass spectrometer, but rather how to persuade molecules such as proteins, peptides, and lipids within tissues to ionize without decomposition into hundreds of smaller fragments. First, a laser is used and rastered across the surface of a mounted tissue section. The principle employed is “soft ionization,” the addition of a matrix to the sample, which absorbs the energy of the laser, and “gently” transfers it to biological molecules causing them to form singly charged ions that can be attracted into the mass spectrometer. The term “matrix-assisted laser desorption” was coined after the discovery that in a mixture of tryptophan and alanine, tryptophan could assist alanine to ionize at a laser energy only 10% of that needed for alanine alone.2 Now there are several aromatic molecules like tryptophan that are used to assist soft ionization of molecules in biological samples. After spraying with a matrix solution, the thin matrix coating extracts biological molecules from the underlying tissue which co-crystallize with the matrix. When the tissue is then painted with a narrow laser beam, the matrix absorbs the laser energy and facilitates the desorption and ionization of the biological molecules. The ions formed are acquired by the mass spectrometer at defined geometric coordinates across the whole tissue section and result in a large dataset of ions acquired at hundreds to thousands of discrete and defined pixels across the 2D surface of the tissue. Software then displays the pixels in terms of the ions detected at each of those points and distributions of the ion intensities can then be produced. Using their accurate masses or their mass spectra produced when the ion is permitted to fragment prior to entry to the mass spectrometer, ions can be solved in terms of the molecules from which they were derived3, 4 and then density maps of these molecules are produced across the tissue section under examination.5, 6 This, in essence, is MALDI-IMS (Fig. 1). How does MALDI-IMS analysis of tissue samples differ from classical histology or immunohistochemistry? First and importantly, as stated above, IHC, for example, is a targeted analysis using specific antibodies as detection tools. In contrast, MALDI-IMS can be used as a discovery tool and the finding of novel molecules confirmed by IHC. This was recently accomplished with the finding that monomeric ubiquitin distinguished hepatocellular carcinoma (HCC) from adjacent cirrhotic tissue.7 Second, traditional histology and IHC view light transmitted through the stained tissue section and the trained observer can record the architecture of the tissue, its organelles, and the distribution within the section of the target molecule, in the case of IHC. With MALDI-IMS, the distribution across the tissue section of a large number of different molecules can be visualized simultaneously. This permitted, for example, the understanding that specific phosphocholine species were distributed in zones within hepatocytes from healthy obese patients and those with simple steatosis, but that this zonation was lost in nonalcoholic steatohepatitis (NASH). These observations led to further investigations and to conclusions regarding the etiopathogenesis of NASH.8 The hepatic metabolism of drugs and the occurrence of drug-induced hepatocellular damage both have a long research history. The tyrosine kinase inhibitor lapatinib, used for the treatment of breast cancer, was repeat-administered to dogs and their livers examined by MALDI-IMS. Parent drug and 22 metabolites were visible in liver sections at a special resolution of 50 μm. Two of these metabolites generated ions of 473.1045 and 473.1175, that is, different by <0.002%, but were completely resolved by MALDI-IMS displaying differential tissue distributions. The ability to distinguish the parent drug from its metabolites in tissue sections without the use of radioisotopes makes MALDI-IMS a unique methodology. As the authors state, “The ability to map pharmacological receptors to drug or metabolite distribution is transformational in drug development. New insights into the mechanisms of pharmacology and toxicology will be possible.”6 MALDI-IMS gives powerful new insights into tissues such as the liver, not only for the spatial distribution of proteins and peptides, but also for lipid species, drugs, and their metabolites. However, it should be recognized that MALDI-IMS is not without its limitations. Specifically, it is not itself a proteomic or metabolomic tool, meaning that global analysis of proteins, lipids, and small molecules is not possible with MALDI-IMS alone. MALDI-IMS images can be generated only for the most prevalent ions, representing perhaps 1,000 proteins, which is a relatively small fraction of the complete proteome for most tissues. Nevertheless, compared with histology or IHC, it represents a major advance in tissue imaging. In addition, the signals obtained by MALDI-IMS are only semiquantitative, but more quantitative than IHC. To obtain further quantitative data on the amounts of a protein, lipid, or small molecule in a tissue, triple quadrupole mass spectrometry (TQMS) with multiple reactions monitoring (MRM) would be required. TQMS with MRM is the basic workhorse of proteomics and lipidomics. In the current issue, Turtoi et al.9 seize on the issue of tumor heterogeneity and the major obstacle that this presents to cancer treatment.10 They employed MALDI-IMS to examine the heterogeneity of the proteome of colorectal carcinoma liver metastases. They accumulated data on over 1,000 proteins and their spatial distribution in the membrane and peritumoral region for eight such metastases. To their surprise, they found that these regions harbored a pattern of protein biomarkers that was reproducible and occurred in defined tissue zones. Their MALDI-IMS findings can be summarized as enhanced protein and lipid synthesis in the peritumoral zone, increased carbohydrate metabolism and DNA repair at the heart of the metastases, and finally, elevated markers for proliferation, motility, and drug metabolism on the metastatic boundary. In addition, two novel biomarkers, latent transforming growth factor beta-binding protein (LTBP2) and transforming growth factor, beta-induced (TGFBI), were consistently expressed in these eight metastases. LTBP2 was found mostly on the rim of the metastasis while TGFBI accumulated mostly at the core of the metastasis. The authors eliminated the possibility that the expression of these two antigens was caused by inflammation, by IHC in 10 cases of cirrhosis due to either alcohol or viral hepatitis. Inflammatory cells were clearly present but the tissues were negative for LTBP2 and TGFBI. The authors were keen to establish that this new information might be useful for in vivo targeting liver metastases using antibodies against LTBP2 and TGFBI. To this end, human colorectal carcinoma cells were xenografted onto the chorioallantoic membrane of fertilized chicken eggs, taking care to select tumor cells (SW1222) that expressed LTBP2 and TGFBI. After 7 days, fluorescence tagged anti-LTBP2 and anti-TGFBI polyclonal antibodies were injected and, after a further day, the xenografts were examined and found to be positively labeled. This work holds out early hopes that antibody-drug conjugates targeted against these two novel therapeutic targets may display sufficient specificity and efficacy to be added to the cancer chemotherapeutic armamentarium. The work of Turtoi et al.9 demonstrates amply how the emergent technology of MALDI-IMS can furnish new and important insights into tumors11 and into liver pathology and also lead rapidly to further investigations that directly seek to define novel therapeutic targets. But to what extent will MALDI-IMS revolutionize the practice of liver histology and replace or enhance current protocols that employ mostly IHC? The best lessons perhaps can be drawn from bacteriology. Back in 1975, it was first demonstrated that inserting lyophilized bacteria on a probe directly into a mass spectrometer and heating the probe to pyrolyze the bacteria under vacuum would produce mass spectra that were characteristic of each bacterial species under investigation. In the case of gram-negative bacteria, these spectra were shown to result from the pyrolysis of phospholipids and ubiquinones in the bacterial samples.12 Today, it is anticipated that MALDI-TOFMS analysis of bacterial spots may replace Gram staining and biochemical identification of bacterial species in the near future.13 Why is this? In a study of 1,660 bacterial isolates, 95.4% were correctly identified by MALDI-TOFMS. In most cases, test failure or erroneous identification was due to incorrect database entries. The authors calculated that identification of a single isolate took 6 minutes at a cost of 22%-32% of the cost of traditional bacteriological methods.13 The high degree of accuracy, high-throughput, low-cost procedures should be welcomed and we predict that they must also come in histopathology in the guise of MALDI-IMS. The scientific case has been made and is obvious, but there is at least one other important practical consideration. Mass spectrometer manufacturers need to recognize that huge floor-standing instruments costing upwards of $1 million are not going to proliferate in routine pathology labs. A much greater effort is required to reduce the size and unit cost, together with development of software that would be regarded as “friendly” by a pathologist, offset by the promise of proliferation of such instruments. History teaches us some lessons in this regard. Those who invented, developed, and named the polymerase chain reaction14 in 1986 probably could not have predicted the wildfire spread of PCR instruments across the globe. Rendering the PCR instrument easy to use has been one of the great endowments of the manufacturing community. Doubtless, commercial competition has played a role. Although MALDI-IMS appears considerably more complex than PCR, this should not deter the quest for the proteomic and metabolomic equivalent of PCR. Diren BeyoĂlu and Jeffrey R. Idle Hepatology Research Group, Department of Clinical Research, University of Bern, Bern, Switzerland

CYP2D6: Genetics, Pharmacology and Clinical Relevance A history and overview of phenotypic variability in CYP2D6 activityDiren Beyoğlu & Jeffrey R IdleDiren BeyoğluDiren Beyoğlu is a PhD pharmacist, toxicologist and research fellow working in J Idle’s group and in collaboration with the US National Cancer Institute on mass spectrometry-based discovery metabolomics and the definition of metabolomic biomarkers of clinical relevance. Currently, her research focuses on metabolomic insights into hepatobiliary diseases.Search for more papers by this author & Jeffrey R IdleJeffrey R Idle is Visiting Professor in the Hepatology Research Group at the University of Bern (Switzerland). In 1977 he was the codiscoverer of the CYP2D6 genetic polymorphism in debrisoquine 4-hydroxylation. His research is centered on metabolomics using various mass spectrometry platforms and the broad application of the findings to medicine. Search for more papers by this authorPublished Online:20 Feb 2014https://doi.org/10.2217/fmeb2013.13.97AboutSectionsView ArticleView Full TextPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack Citations ShareShare onFacebookTwitterLinkedInReddit View chapterAbstract: CYP2D6 is a human cytochrome P450 that is responsible for the metabolism of a large number of drugs and chemicals. Interest in CYP2D6 has largely centered on the wide interindividual variability in its catalytic activity that stems from a common genetic polymorphism in the CYP2D6 gene. Two major phenotypes exist, extensive metabolizer (EM) and poor metabolizer (PM), together with the two less studied phenotypes of ultrarapid metabolizer (UM) and intermediate metabolizer. These phenotypes are the expression of an underlying allelomorphism in CYP2D6 and are also context dependent. Several drugs that are CYP2D6 substrates display polymorphic metabolism, that is, the existence in the population of multiple phenotypes, in particular EM and PM. The most notable drugs in this regard are debrisoquine and sparteine, although there are also data for a few others, in particular, dextromethorphan and metoprolol. Many nongenetic factors can alter the expression of CYP2D6 phenotypes, the most significant of which is the presence of other drugs. In this context, the EM phenotype may not be immutable, with potential conversion into a PM phenocopy, due to significantly impaired CYP2D6 metabolism in the presence of other CYP2D6 substrates and inhibitors. This phenotype interconversion generated great concern and helped drive the movement away from phenotyping based upon drug administration to genotyping of acquired DNA samples. 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Hepatocellular carcinoma (HCC) is one of the commonest causes of death from cancer. A plethora of metabolomic investigations of HCC have yielded molecules in biofluids that are both up‐ and down‐regulated but no real consensus has emerged regarding exploitable biomarkers for early detection of HCC. We report here a different approach, a combined transcriptomics and metabolomics study of energy metabolism in HCC. A panel of 31 pairs of HCC tumors and corresponding nontumor liver tissues from the same patients was investigated by gas chromatography‐mass spectrometry (GCMS)‐based metabolomics. HCC was characterized by ∼2‐fold depletion of glucose, glycerol 3‐ and 2‐phosphate, malate, alanine, myo‐inositol, and linoleic acid. Data are consistent with a metabolic remodeling involving a 4‐fold increase in glycolysis over mitochondrial oxidative phosphorylation. A second panel of 59 HCC that had been typed by transcriptomics and classified in G1 to G6 subgroups was also subjected to GCMS tissue metabolomics. No differences in glucose, lactate, alanine, glycerol 3‐phosphate, malate, myo‐inositol, or stearic acid tissue concentrations were found, suggesting that the Wnt/β‐catenin pathway activated by CTNNB1 mutation in subgroups G5 and G6 did not exhibit specific metabolic remodeling. However, subgroup G1 had markedly reduced tissue concentrations of 1‐stearoylglycerol, 1‐palmitoylglycerol, and palmitic acid, suggesting that the high serum α‐fetoprotein phenotype of G1, associated with the known overexpression of lipid catabolic enzymes, could be detected through metabolomics as increased lipid catabolism. Conclusion: Tissue metabolomics yielded precise biochemical information regarding HCC tumor metabolic remodeling from mitochondrial oxidation to aerobic glycolysis and the impact of molecular subtypes on this process. (HEPATOLOGY 2013)

Abstract Lung cancer remains the most common cause of cancer deaths world-wide. Despite the intensive research over many years, the prognosis of this deadly disease is still very poor, with fewer than 15% of the patients surviving 5 years after primary diagnosis. While there are several methodologies described and proposed for early detection of lung cancer (spiral CT, circulating pro-inflammatory cytokines IL6, IL8 and CRP), the specificity and robustness remains to be achieved. What we readily know is that cancer cells have a distinguishable metabolic fingerprint compared to normal cells. Metabolomics holds promise to be able to detect and capture subtle shifts in multiple metabolic paths and cellular modifiers that will enable identification of critical components of cancer risk and tumor behavior. We conducted a first of its kind effort using mass spectrometry-based untargeted metabolic profiling of urine samples obtained from 469 lung cancer patients and 536 healthy population controls. We identified four robust biomarkers, high levels of which are associated with lung cancer diagnosis and poorer survival. After the adjustment for potential confounding factors, all four biomarkers were significantly associated with lung cancer diagnosis (FDR-adjusted p-values <0.05, ORs ranging from 1.9 to 5.1), whereas one of four was associated with diagnosis in early I and II stages (OR =3.3, p-value =0.002). Furthermore, all four biomarkers are associated with prognosis (HRs ranging from 1.49 to 1.97, after adjustment for potential confounders, p-values <0.02), whereas two were associated with survival in stages I and II (HRs of 1.83 and 9.33, p-values 0.03 and 0.0006 respectively). A combination of the four biomarkers resulted in stronger associations, suggesting that they may be independent of one another. Significantly higher levels of these biomarkers were confirmed in an independent sample set from the same cohort, confirming our findings and eliminating storage time as a potential confounder. A targeted quantitation was carried out in a representative subset of 198 samples, further validating previous findings from the untargeted screen. Furthermore, intraclass correlation analysis revealed high repeatability of two independent measurements over a year apart (ICCs between 0.82 and 0.99). Lastly, the metabolome of 62 tumor and 62 adjacent normal tissues was profiled (stage I adeno- and squamous cell- carcinomas), linking two urinary biomarkers directly to the tumor metabolism (FCs of 1.7 and 19.0; p-values 0.03 and <0.00001, respectively). In addition to their potential to further identify those high risk groups who would most benefit from an invasive screen, thereby minimizing the false positive rate, these markers may also illuminate novel lung carcinogenesis pathways, as well as potential therapeutic targets. Mechanistic studies elucidating effected pathways are ongoing. Citation Format: Majda Haznadar, Ewy Mathe, Andrew D. Patterson, Soumen K. Manna, Kristopher W. Krausz, Elise D. Bowman, Jeffrey R. Idle, Dickran G. Kazandjian, Frank J. Gonzalez, Curtis C. Harris. Untargeted metabolomic profiling identifies diagnostic and prognostic biomarkers of lung cancer. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 1901. doi:10.1158/1538-7445.AM2013-1901