Plasma Metabolite Profiling in the Search for Early-Stage Biomarkers for Lung Cancer: Some Important Breakthroughs.

Lung cancer is the leading cause of cancer-related mortality worldwide. In order to improve its overall survival, early diagnosis is required. Since current screening methods still face some pitfalls, such as high false positive rates for low-dose computed tomography, researchers are still looking for early biomarkers to complement existing screening techniques in order to provide a safe, faster, and more accurate diagnosis. Biomarkers are biological molecules found in body fluids, such as plasma, that can be used to diagnose a condition or disease. Metabolomics has already been shown to be a powerful tool in the search for cancer biomarkers since cancer cells are characterized by impaired metabolism, resulting in an adapted plasma metabolite profile. The metabolite profile can be determined using nuclear magnetic resonance, or NMR. Although metabolomics and NMR metabolite profiling of blood plasma are still under investigation, there is already evidence for its potential for early-stage lung cancer diagnosis, therapy response, and follow-up monitoring. This review highlights some key breakthroughs in this research field, where the most significant biomarkers will be discussed in relation to their metabolic pathways and in light of the altered cancer metabolism.

Electron-Beam-Initiated Crosslinking of Methacrylated Alginate and Diacrylated Poly(ethylene glycol) Hydrogels.

An ideal wound dressing not only needs to absorb excess exudate but should also allow for a moist wound-healing environment as well as being mechanically strong. Such a dressing can be achieved by combining both a natural (alginate) and synthetic (poly(ethylene glycol) polymer. Interestingly, using an electron beam on (meth)acrylated polymers allows their covalent crosslinking without the use of toxic photo-initiators. The goal of this work was to crosslink alginate at different methacrylation degrees (26.1 and 53.5% of the repeating units) with diacrylated poly(ethylene glycol) (PEGDA) using electron-beam irradiation at different doses to create strong, transparent hydrogels. Infrared spectroscopy showed that both polymers were homogeneously distributed within the irradiated hydrogel. Rheology showed that the addition of PEGDA into alginate with a high degree of methacrylation and a polymer concentration of 6 wt/v% improved the storage modulus up to 15,867 ± 1102 Pa. Gel fractions > 90% and swelling ratios ranging from 10 to 250 times its own weight were obtained. It was observed that the higher the storage modulus, the more limited the swelling ratio due to a more crosslinked network. Finally, all species were highly transparent, with transmittance values > 80%. This may be beneficial for the visual inspection of healing progression. Furthermore, these polymers may eventually be used as carriers of photosensitizers, which is favorable in applications such as photodynamic therapy.

Gamma radiation effects on AG MP-50 cation exchange resin and sulfonated activated carbon for bismuth-213 separation.

Medical 225Ac/213Bi radionuclide generators are designed to provide a local supply of the short-lived 213Bi for cancer treatment. However, radiation-induced damage to the sorbents commonly used in such radionuclide generators remains a major concern. In this study, the effects of gamma radiation on AG MP-50 cation exchange resin and sulfonated activated carbon (SAC) were studied by analyzing the changes in the morphological characteristics, functional groups, and the La3+/Bi3+ sorption performance, with La3+ being a suitable non-radioactive substitute for Ac3+. The surface sulfonic acid groups of AG MP-50 resin suffered from severe radiation-induced degradation, while the particle morphology was changed markedly after being exposed to absorbed doses of approximately 11 MGy. As a result, the sorption performance of irradiated AG MP-50 for La3+ and Bi3+ was significantly decreased with increasing absorbed doses. In contrast, no apparent changes in acquired morphological characteristics were observed for pristine and irradiated SAC based on SEM and XRD characterization. The surface oxygen content (e.g., O-C[double bond, length as m-dash]O) of irradiated SAC increased for an absorbed dose of 11 MGy due to free radical-induced oxidation. The sorption performance of pristine and irradiated SAC materials for La3+ and Bi3+ remained generally the same at pH values of 1 and 2. Furthermore, the applicability of AG MP-50 and SAC in the 225Ac/213Bi generators was illustrated in terms of their radiolytic stability. This study provides further evidence for the practical implementation of both AG MP-50 and SAC in 225Ac/213Bi radionuclide generators.

Altering Mechanical Properties to Improve Electrode Contacts by Organic Modification of Silica-Based Ionogel Electrolytes for Sodium-Ion Batteries.

Sodium-ion batteries (SIBs) are a possible candidate to create safe, sustainable, and cost-effective batteries. Solid sodium-ion conducting organically modified ionogel electrolytes are investigated. Silica-based ionogels typically consist of an ionic liquid electrolyte (ILE) confined within a silica matrix and possess high thermal stability, good ionic conductivity, safety, and good electrochemical stability. However, they readily deteriorate when stress is applied, decreasing the electrolyte's and battery's overall performance. The mechanical characteristics of silica can be improved using organic moieties, creating Ormosils®. Silica-based ionogels with phenyl-modified silanes improve the mechanical characteristics by a reduction of their Young's modulus (from 29 to 6 MPa). This is beneficial to the charge-transfer resistance, which decreases after implementing the electrolyte in half cells, demonstrating the improved interfacial contact. Most importantly, the phenyl groups change the interacting species at the silica interface. Cationic imidazolium species pi-stacked to the phenyl groups of the silica matrix, pushing the anions to the bulk of the ILE, which affects the ionic conductivity and electrochemical stability, and might affect the quality of the SEI in half cells. In essence, the work at hand can be used as a directory to improve mechanical characteristics and modify and control functional properties of ionogel electrolytes.

NMR-Metabolomics Reveals a Metabolic Shift after Surgical Resection of Non-Small Cell Lung Cancer.

BACKGROUND: Lung cancer can be detected by measuring the patient's plasma metabolomic profile using nuclear magnetic resonance (NMR) spectroscopy. This NMR-based plasma metabolomic profile is patient-specific and represents a snapshot of the patient's metabolite concentrations. The onset of non-small cell lung cancer (NSCLC) causes a change in the metabolite profile. However, the level of metabolic changes after complete NSCLC removal is currently unknown. PATIENTS AND METHODS: Fasted pre- and postoperative plasma samples of 74 patients diagnosed with resectable stage I-IIIA NSCLC were analyzed using 1H-NMR spectroscopy. NMR spectra (s = 222) representing two preoperative and one postoperative plasma metabolite profile at three months after surgical resection were obtained for all patients. In total, 228 predictors, i.e., 228 variables representing plasma metabolite concentrations, were extracted from each NMR spectrum. Two types of supervised multivariate discriminant analyses were used to train classifiers presenting a strong differentiation between the pre- and postoperative plasma metabolite profiles. The validation of these trained classification models was obtained by using an independent dataset. RESULTS: A trained multivariate discriminant classification model shows a strong differentiation between the pre- and postoperative NSCLC profiles with a specificity of 96% (95% CI [86-100]) and a sensitivity of 92% (95% CI [81-98]). Validation of this model results in an excellent predictive accuracy of 90% (95% CI [77-97]) and an AUC value of 0.97 (95% CI [0.93-1]). The validation of a second trained model using an additional preoperative control sample dataset confirms the separation of the pre- and postoperative profiles with a predictive accuracy of 93% (95% CI [82-99]) and an AUC value of 0.97 (95% CI [0.93-1]). Metabolite analysis reveals significantly increased lactate, cysteine, asparagine and decreased acetate levels in the postoperative plasma metabolite profile. CONCLUSIONS: The results of this paper demonstrate that surgical removal of NSCLC generates a detectable metabolic shift in blood plasma. The observed metabolic shift indicates that the NSCLC metabolite profile is determined by the tumor's presence rather than donor-specific features. Furthermore, the ability to detect the metabolic difference before and after surgical tumor resection strongly supports the prospect that NMR-generated metabolite profiles via blood samples advance towards early detection of NSCLC recurrence.

Changes in Metabolism as a Diagnostic Tool for Lung Cancer: Systematic Review.

Lung cancer is the leading cause of cancer-related mortality worldwide, with five-year survival rates varying from 3-62%. Screening aims at early detection, but half of the patients are diagnosed in advanced stages, limiting therapeutic possibilities. Positron emission tomography-computed tomography (PET-CT) is an essential technique in lung cancer detection and staging, with a sensitivity reaching 96%. However, since elevated 18F-fluorodeoxyglucose (18F-FDG) uptake is not cancer-specific, PET-CT often fails to discriminate between malignant and non-malignant PET-positive hypermetabolic lesions, with a specificity of only 23%. Furthermore, discrimination between lung cancer types is still impossible without invasive procedures. High mortality and morbidity, low survival rates, and difficulties in early detection, staging, and typing of lung cancer motivate the search for biomarkers to improve the diagnostic process and life expectancy. Metabolomics has emerged as a valuable technique for these pitfalls. Over 150 metabolites have been associated with lung cancer, and several are consistent in their findings of alterations in specific metabolite concentrations. However, there is still more variability than consistency due to the lack of standardized patient cohorts and measurement protocols. This review summarizes the identified metabolic biomarkers for early diagnosis, staging, and typing and reinforces the need for biomarkers to predict disease progression and survival and to support treatment follow-up.

Unraveling the Rewired Metabolism in Lung Cancer Using Quantitative NMR Metabolomics.

Lung cancer cells are well documented to rewire their metabolism and energy production networks to enable proliferation and survival in a nutrient-poor and hypoxic environment. Although metabolite profiling of blood plasma and tissue is still emerging in omics approaches, several techniques have shown potential in cancer diagnosis. In this paper, the authors describe the alterations in the metabolic phenotype of lung cancer patients. In addition, we focus on the metabolic cooperation between tumor cells and healthy tissue. Furthermore, the authors discuss how metabolomics could improve the management of lung cancer patients.

Detection of Lung Cancer via Blood Plasma and 1H-NMR Metabolomics: Validation by a Semi-Targeted and Quantitative Approach Using a Protein-Binding Competitor.

Metabolite profiling of blood plasma, by proton nuclear magnetic resonance (1H-NMR) spectroscopy, offers great potential for early cancer diagnosis and unraveling disruptions in cancer metabolism. Despite the essential attempts to standardize pre-analytical and external conditions, such as pH or temperature, the donor-intrinsic plasma protein concentration is highly overlooked. However, this is of utmost importance, since several metabolites bind to these proteins, resulting in an underestimation of signal intensities. This paper describes a novel 1H-NMR approach to avoid metabolite binding by adding 4 mM trimethylsilyl-2,2,3,3-tetradeuteropropionic acid (TSP) as a strong binding competitor. In addition, it is demonstrated, for the first time, that maleic acid is a reliable internal standard to quantify the human plasma metabolites without the need for protein precipitation. Metabolite spiking is further used to identify the peaks of 62 plasma metabolites and to divide the 1H-NMR spectrum into 237 well-defined integration regions, representing these 62 metabolites. A supervised multivariate classification model, trained using the intensities of these integration regions (areas under the peaks), was able to differentiate between lung cancer patients and healthy controls in a large patient cohort (n = 160), with a specificity, sensitivity, and area under the curve of 93%, 85%, and 0.95, respectively. The robustness of the classification model is shown by validation in an independent patient cohort (n = 72).

The Metabolic Landscape of Lung Cancer: New Insights in a Disturbed Glucose Metabolism.

Metabolism encompasses the biochemical processes that allow healthy cells to keep energy, redox balance and building blocks required for cell development, survival, and proliferation steady. Malignant cells are well-documented to reprogram their metabolism and energy production networks to support rapid proliferation and survival in harsh conditions via mutations in oncogenes and inactivation of tumor suppressor genes. Despite the histologic and genetic heterogeneity of tumors, a common set of metabolic pathways sustain the high proliferation rates observed in cancer cells. This review with a focus on lung cancer covers several fundamental principles of the disturbed glucose metabolism, such as the "Warburg" effect, the importance of the glycolysis and its branching pathways, the unanticipated gluconeogenesis and mitochondrial metabolism. Furthermore, we highlight our current understanding of the disturbed glucose metabolism and how this might result in the development of new treatments.

Correlations between the metabolic profile and 18F-FDG-Positron Emission Tomography-Computed Tomography parameters reveal the complexity of the metabolic reprogramming within lung cancer patients.

Several studies have demonstrated that the metabolite composition of plasma may indicate the presence of lung cancer. The metabolism of cancer is characterized by an enhanced glucose uptake and glycolysis which is exploited by 18F-FDG positron emission tomography (PET) in the work-up and management of cancer. This study aims to explore relationships between 1H-NMR spectroscopy derived plasma metabolite concentrations and the uptake of labeled glucose (18F-FDG) in lung cancer tissue. PET parameters of interest are standard maximal uptake values (SUVmax), total body metabolic active tumor volumes (MATVWTB) and total body total lesion glycolysis (TLGWTB) values. Patients with high values of these parameters have higher plasma concentrations of N-acetylated glycoproteins which suggest an upregulation of the hexosamines biosynthesis. High MATVWTB and TLGWTB values are associated with higher concentrations of glucose, glycerol, N-acetylated glycoproteins, threonine, aspartate and valine and lower levels of sphingomyelins and phosphatidylcholines appearing at the surface of lipoproteins. These higher concentrations of glucose and non-carbohydrate glucose precursors such as amino acids and glycerol suggests involvement of the gluconeogenesis pathway. The lower plasma concentration of those phospholipids points to a higher need for membrane synthesis. Our results indicate that the metabolic reprogramming in cancer is more complex than the initially described Warburg effect.

Glutamine Addiction and Therapeutic Strategies in Lung Cancer.

Lung cancer cells are well-documented to rewire their metabolism and energy production networks to support rapid survival and proliferation. This metabolic reorganization has been recognized as a hallmark of cancer. The increased uptake of glucose and the increased activity of the glycolytic pathway have been extensively described. However, over the past years, increasing evidence has shown that lung cancer cells also require glutamine to fulfill their metabolic needs. As a nitrogen source, glutamine contributes directly (or indirectly upon conversion to glutamate) to many anabolic processes in cancer, such as the biosynthesis of amino acids, nucleobases, and hexosamines. It plays also an important role in the redox homeostasis, and last but not least, upon conversion to α-ketoglutarate, glutamine is an energy and anaplerotic carbon source that replenishes tricarboxylic acid cycle intermediates. The latter is generally indicated as glutaminolysis. In this review, we explore the role of glutamine metabolism in lung cancer. Because lung cancer is the leading cause of cancer death with limited curative treatment options, we focus on the potential therapeutic approaches targeting the glutamine metabolism in cancer.