The performance of a novel amino acid multivariate index for detecting lung cancer: A case control study in Korea

Metabolomics and lipidomics in non-small cell lung cancer

Due to its insidious nature, lung cancer remains a leading cause of cancer-related deaths worldwide. Therefore, there is an urgent need to identify sensitive/specific biomarkers for early diagnosis and monitoring. The current study was designed to provide a current metabolic profile of non-small cell lung cancer (NSCLC) by systematically reviewing and summarizing various metabolomic/ lipidomic studies based on NSCLC blood samples, attempting to find biomarkers in human blood that can predict or diagnose NSCLC, and investigating the involvement of key metabolites in the pathogenesis of NSCLC. We searched all articles on lung cancer published in Elsevier, PubMed, Web of Science and the Cochrane Library between January 2012 and December 2022. After critical selection, a total of 31 studies (including 2768 NSCLC patients and 9873 healthy individuals) met the inclusion criteria, and 22 were classified as "high quality". Forty-six metabolites related to NSCLC were repeatedly identified, involving glucose metabolism, amino acid metabolism, lipid metabolism and nucleotide metabolism. Pyruvic acid, carnitine, phenylalanine, isoleucine, kynurenine and 3-hydroxybutyrate showed upward trends in all studies, citric acid, glycine, threonine, cystine, alanine, histidine, inosine, betaine and arachidic acid showed downward trends in all studies. This review summarizes the existing metabolomic/lipidomic studies related to the identification of blood biomarkers in NSCLC, examines the role of key metabolites in the pathogenesis of NSCLC, and provides an important reference for the clinical diagnosis and treatment of NSCLC. Due to the limited size and design heterogeneity of the existing studies, there is an urgent need for standardization of future studies, while validating existing findings with more studies.

Effects of methionine deficiency on B7H3-DAP12-CAR-T cells in the treatment of lung squamous cell carcinoma

Lung squamous cell carcinoma (LUSC) is a subtype of lung cancer for which precision therapy is lacking. Chimeric antigen receptor T-cells (CAR-T) have the potential to eliminate cancer cells by targeting specific antigens. However, the tumor microenvironment (TME), characterized by abnormal metabolism could inhibit CAR-T function. Therefore, the aim of this study was to improve CAR-T efficacy in solid TME by investigating the effects of amino acid metabolism. We found that B7H3 was highly expressed in LUSC and developed DAP12-CAR-T targeting B7H3 based on our previous findings. When co-cultured with B7H3-overexpressing LUSC cells, B7H3-DAP12-CAR-T showed significant cell killing effects and released cytokines including IFN-γ and IL-2. However, LUSC cells consumed methionine (Met) in a competitive manner to induce a Met deficiency. CAR-T showed suppressed cell killing capacity, reduced cytokine release and less central memory T phenotype in medium with lower Met, while the exhaustion markers were up-regulated. Furthermore, the gene NKG7, responsible for T cell cytotoxicity, was downregulated in CAR-T cells at low Met concentration due to a decrease in m5C modification. NKG7 overexpression could partially restore the cytotoxicity of CAR-T in low Met. In addition, the anti-tumor efficacy of CAR-T was significantly enhanced when co-cultured with SLC7A5 knockdown LUSC cells at low Met concentration. In conclusion, B7H3 is a prospective target for LUSC, and B7H3-DAP12-CAR-T cells are promising for LUSC treatment. Maintaining Met levels in CAR-T may help overcome TME suppression and improve its clinical application potential.

Amino Acid Profiles in the Biological Fluids and Tumor Tissue of CRC Patients

Amino acids are the building blocks of proteins and essential players in pathways such as the citric acid and urea cycle, purine and pyrimidine biosynthesis, and redox cell signaling. Therefore, it is unsurprising that these molecules have a significant role in cancer metabolism and its metabolic plasticity. As one of the most prevalent malign diseases, colorectal cancer needs biomarkers for its early detection, prognostic, and prediction of response to therapy. However, the available biomarkers for this disease must be more powerful and present several drawbacks, such as high costs and complex laboratory procedures. Metabolomics has gathered substantial attention in the past two decades as a screening platform to study new metabolites, partly due to the development of techniques, such as mass spectrometry or liquid chromatography, which have become standard practice in diagnostic procedures for other diseases. Extensive metabolomic studies have been performed in colorectal cancer (CRC) patients in the past years, and several exciting results concerning amino acid metabolism have been found. This review aims to gather and present findings concerning alterations in the amino acid plasma pool of colorectal cancer patients.

Normative Data on Serum and Plasma Tryptophan and Kynurenine Concentrations from 8089 Individuals Across 120 Studies: A Systematic Review and Meta-Analysis

In this systematic review and meta-analysis, a normative dataset is generated from the published literature on the kynurenine pathway in control participants extracted from case-control and methodological validation studies. Study characteristics were mapped, and studies were evaluated in terms of analytical rigour and methodological validation. Meta-analyses of variance between types of instruments, sample matrices and metabolites were conducted. Regression analyses were applied to determine the relationship between metabolite, sample matrix, biological sex, participant age and study age. The grand mean concentrations of tryptophan in the serum and plasma were 60.52 ± 15.38 μM and 51.45 ± 10.47 μM, respectively. The grand mean concentrations of kynurenine in the serum and plasma were 1.96 ± 0.51 μM and 1.82 ± 0.54 μM, respectively. Regional differences in metabolite concentrations were observed across America, Asia, Australia, Europe and the Middle East. Of the total variance within the data, mode of detection (MOD) accounted for up to 2.96%, sample matrix up to 3.23%, and their interaction explained up to 1.53%; the latter of which was determined to be negligible. This review was intended to inform future empirical research and method development studies and successfully synthesised pilot data. The pilot data reported in this study will inform future precision medicine initiatives aimed at targeting the kynurenine pathway by improving the availability and quality of normative data.

Serum Metabolomic Profiles for Distinguishing Lung Cancer From Pulmonary Tuberculosis: Identification of Rapid and Noninvasive Biomarker

BACKGROUND

Pulmonary tuberculosis (PTB) and lung cancer (LC) have similar clinical symptoms and atypical imaging findings, which are easily misdiagnosed. There is an urgent need for a noninvasive and accurate biomarker to distinguish LC from PTB.

METHODS

A total of 694 subjects were enrolled and divided into discovery set (n = 122), identification set (n = 214), and validation set (n = 358). Metabolites were identified by multivariate and univariate analyses. Receiver operating characteristic curve were used to evaluate the diagnostic efficacy of biomarkers.

RESULTS

Seven metabolites were identified and validated. Phenylalanylphenylalanine for distinguishing LC from PTB yielded an area under the curve of 0.89, sensitivity of 71%, and specificity of 92%. It also showed good diagnostic abilities in discovery set and identification set. Compared with that in healthy volunteers (median [interquartile range], 1.57 [1.01, 2.34] μg/mL), it was elevated in LC (4.76 [2.74, 7.08] μg/mL; ratio of median, [ROM] = 3.03, P < .01) and reduced in PTB (1.06 [0.51, 2.09] μg/mL; ROM = 0.68, P < .05).

CONCLUSIONS

The metabolomic profile of LC and PTB was described and a key biomarker identified. We produced a rapid and noninvasive method to supplement existing clinical diagnostic examinations for distinguishing LC from PTB.

Causal associations of histidine and 12 site-specific cancers: a bidirectional Mendelian randomization study

An increasing number of studies indicate that cancer patients' histidine (HIS) circulating levels have changed. However, the causality between HIS and cancer is still not well established. Thus, to ascertain the causal link between HIS and cancers, we performed a bidirectional Mendelian randomization (MR) analysis. Summary-level data are derived from publicly available genome-wide association studies (GWAS). The causal effects were mainly estimated using the inverse-variance weighted method (IVW). The weighted-median (WM) method and MR-Egger regression were conducted as sensitivity analyses. In the forward-MR, we found malignant neoplasm of respiratory system and intrathoracic organs (OR: 1.020; 95% CI: 1.006-1.035; pIVW = 0.007) genetically associated with circulating HIS. And there was no significant genetic correlation between HIS and another 11 site-specific cancers using IVW method. In the reversed-MR, we did not observe the causal relationship between HIS and 12 site-specific cancers. Our findings help clarify that HIS, as a biomarker for malignant neoplasms of respiratory system and intrathoracic organs, is causal rather than a secondary biomarker of the cancerous progression. The mechanism between histidine and cancer progression deserves further investigation.

Recent Analytical Advances for Decoding Metabolic Reprogramming in Lung Cancer

Lung cancer is the leading cause of cancer-related death worldwide. Metabolic reprogramming is a fundamental trait associated with lung cancer development that fuels tumor proliferation and survival. Monitoring such metabolic pathways and their intermediate metabolites can provide new avenues concerning treatment strategies, and the identification of prognostic biomarkers that could be utilized to monitor drug responses in clinical practice. In this review, recent trends in the analytical techniques used for metabolome mapping of lung cancer are capitalized. These techniques include nuclear magnetic resonance (NMR), gas chromatography-mass spectrometry (GC-MS), liquid chromatography-mass spectrometry (LC-MS), and imaging mass spectrometry (MSI). The advantages and limitations of the application of each technique for monitoring the metabolite class or type are also highlighted. Moreover, their potential applications in the analysis of many biological samples will be evaluated.

Diagnostic Value of Salivary Amino Acid Levels in Cancer

This review analyzed 21 scientific papers on the determination of amino acids in various types of cancer in saliva. Most of the studies are on oral cancer (8/21), breast cancer (4/21), gastric cancer (3/21), lung cancer (2/21), glioblastoma (2/21) and one study on colorectal, pancreatic, thyroid and liver cancer. The amino acids alanine, valine, phenylalanine, leucine and isoleucine play a leading role in the diagnosis of cancer via the saliva. In an independent version, amino acids are rarely used; the authors combine either amino acids with each other or with other metabolites, which makes it possible to obtain high values of sensitivity and specificity. Nevertheless, a logical and complete substantiation of the changes in saliva occurring in cancer, including changes in salivary amino acid levels, has not yet been formed, which makes it important to continue research in this direction.

Organic-Inorganic Porphyrinoid Frameworks for Biomolecule Sensing

Porphyrinoids and their analogous compounds play an important role in biosensing applications on account of their unique and versatile catalytic, coordination, photophysical, and electrochemical properties. Their remarkable arrays of properties can be finely tuned by synthetically modifying the porphyrinoid ring and varying the various structural parameters such as peripheral functionalization, metal coordination, and covalent or physical conjugation with other organic or inorganic scaffolds such as nanoparticles, metal-organic frameworks, and polymers. Porphyrinoids and their organic-inorganic conjugates are not only used as responsive materials but also utilized for the immobilization and embedding of biomolecules for applications in wearable devices, fast sensing devices, and other functional materials. The present review delineates the impact of different porphyrinoid conjugates on their physicochemical properties and their specificity as biosensors in a range of applications. The newest porphyrinoid types and their synthesis, modification, and functionalization are presented along with their advantages and performance improvements.

Metabolomic profiling identifies hair as a robust biological sample for identifying women with cervical cancer

Metabolomics serves as a useful tool for identifying biomarkers of disease and uncovering pathogenic mechanisms. However, most metabolomic studies use biological fluids such as blood and urine as biospecimens, which could be dramatically influenced by daily activities and dietary variation, resulting in measurement fluctuations. In contrast, hair may serve as a robust source of stable longitudinal metabolite information. Here, we conducted a pilot study to investigate the possibility of using hair as a biospecimen for the metabolomic analysis of cervical cancer. Hair, plasma, urine, and cervical tissue samples from cervical cancer and benign tumor patients were collected. Biospecimens were then tested using a gas chromatography-mass spectrometry-based metabolomic platform. The expressions of enzymatic genes related to metabolic changes were validated using qPCR. Statistical analyses were calculated via the R-console platform. Metabolite profiles in both hair and cervical tissue samples were significantly different between cancer and control groups, while no difference was observed in plasma and urine samples. Further analysis showed that most of the altered metabolites in hair were upregulated, and they had a negative correlation with those in the cervical tissue. Eight common metabolites showed an area under the Receiver Operating Characteristic curve greater than 0.95. These metabolites primarily participated in amino acid metabolism, cofactor synthesis, ferroptosis, and glycolysis. The gene expressions (IDH1, OGDH, GLUD1, ENO1, GSS, and GPX4) associated with the shortlisted metabolic pathways were also upregulated. Our study is the first to reveal metabolomic changes of hair in cervical cancer patients and demonstrates the potential for the hair metabolome to be used for biomarker identification in cervical cancer.

Serum untargeted metabolomics reveal metabolic alteration of non-small cell lung cancer and refine disease detection

This study was performed to characterize the metabolic alteration of non-small-cell lung cancer (NSCLC) and discover blood-based metabolic biomarkers relevant to lung cancer detection. An untargeted metabolomics-based approach was applied in a case-control study with 193 NSCLC patients and 243 healthy controls. Serum metabolomics were determined by using an ultra high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) method. We screened differential metabolites based on univariate and multivariate analysis, followed by identification of the metabolites and related pathways. For NSCLC detection, machine learning was employed to develop and validate the model based on the altered serum metabolite features. The serum metabolic pattern of NSCLC was definitely different from the healthy condition. In total, 278 altered features were found in the serum of NSCLC patients comparing with healthy people. About one-fifth of the abundant differential features were identified successfully. The altered metabolites were enriched in metabolic pathways such as phenylalanine metabolism, linoleic acid metabolism, and biosynthesis of bile acids. We demonstrated a panel of 10 metabolic biomarkers which representing excellent discriminating capability for NSCLC discrimination, with a combined area under the curve (AUC) in the validation set of 0.95 (95% CI: 0.91-0.98). Moreover, this model showed a desirable performance for the detection of NSCLC at an early stage (AUC = 0.95, 95% CI: 0.92-0.97). Our study offers a perspective on NSCLC metabolic alteration. The finding of the biomarkers might shed light on the clinical detection of lung cancer, especially for those cancers in an early stage in Chinese population.

Changes in serum amino acid levels in non-small cell lung cancer: a case-control study in Chinese population

Background

Previous studies have shown the alteration of amino acid (AA) profile in patients with non-small cell lung cancer (NSCLC). However, there is little data regarding AA profile in NSCLC in Chinese population. The aim of this study was to evaluate AA profile in Chinese NSCLC patients, explore its utility in sample classification and further discuss its related metabolic pathways.

Methods

The concentrations of 22 AAs in serum samples from 200 patients with NSCLC and 202 healthy controls were determined by liquid chromatography-tandem mass spectrometer (LC-MS/MS). AA levels in different tumor stages and histological types were also discussed. The performance of AA panel in classifying the cases and controls was evaluated in the training data set and validation data set based on the receiver operating characteristic (ROC) curve, and the important metabolic pathways were identified.

Results

The concentrations of tryptophan (Trp), phenylalanine (Phe), isoleucine (Ile), glycine (Gly), serine (Ser), aspartic acid (Asp), asparagine (Asn), cystein (Cys), glutamic acid (Glu), ornithine (Orn) and citrulline (Cit) were significantly altered in NSCLC patients compared with controls (all P-FDR < 0.05). Among these, four AAs including Asp, Cys, Glu and Orn were substantially up-regulated in NSCLC patients (FC ≥ 1.2). AA levels were significantly altered in patients with late-stage NSCLC, but not in those with early-stage when comparing with healthy controls. In terms of histological type, these AAs were altered in both adenocarcinoma and squamous cell carcinoma. For discrimination of NSCLC from controls, the area under the ROC curve (AUC) was 0.80 (95% CI [0.74-0.85]) in the training data set and 0.79 (95%CI [0.71-0.87]) in the validation data set. The AUCs for early-stage and late-stage NSCLC were 0.75 (95% CI [0.68-0.81]) and 0.86 (95% CI [0.82-0.91]), respectively. Moreover, the model showed a better performance in the classification of squamous cell carcinoma (AUC = 0.90, 95% CI [0.85-0.95]) than adenocarcinoma (AUC = 0.77, 95% CI [0.71-0.82]) from controls. Three important metabolic pathways were involved in the alteration of AA profile, including Gly, Ser and Thr metabolism; Ala, Asp and Glu metabolism; and Arg biosynthesis.

Conclusions

The levels of several AAs in serum were altered in Chinese NSCLC patients. These altered AAs may be utilized to classify the cases from the controls. Gly, Ser and Thr metabolism; Ala, Asp and Glu metabolism and Arg biosynthesis pathways may play roles in metabolism of the NSCLC patient.

Tryptophan and Its Metabolites in Lung Cancer: Basic Functions and Clinical Significance

Lung cancer is the most lethal malignancy worldwide. Recently, it has been recognized that metabolic reprogramming is a complex and multifaceted factor, contributing to the process of lung cancer. Tryptophan (Try) is an essential amino acid, and Try and its metabolites can regulate the progression of lung cancer. Here, we review the pleiotropic functions of the Try metabolic pathway, its metabolites, and key enzymes in the pathogenic process of lung cancer, including modulating the tumor environment, promoting immune suppression, and drug resistance. We summarize the recent advance in therapeutic drugs targeting the Try metabolism and kynurenine pathway and their clinical trials.

High-Throughput Salivary Metabolite Profiling on an Ultralow Noise Tip-Enhanced Laser Desorption Ionization Mass Spectrometry Platform for Noninvasive Diagnosis of Early Lung Cancer

Lung cancer (LC) is a widespread cancer that is the cause of the highest mortality rate accounting for 25% of all cancer deaths. To date, most LC patients are diagnosed at the advanced stage owing to the lack of obvious symptoms in the early stage and the limitations of current clinical diagnostic techniques. Therefore, developing a high throughput technique for early screening is of great importance. In this work, we established an effective and rapid salivary metabolic analysis platform for early LC diagnosis and combined metabolomics and transcriptomics to reveal the metabolic fluctuations correlated to LC. Saliva samples were collected from a total of 150 volunteers including 89 patients with early LC, 11 patients with advanced LC, and 50 healthy controls. The metabolic profiling of noninvasive samples was investigated on an ultralow noise TELDI-MS platform. In addition, data normalization methods were screened and assessed to overcome the MS signal variation caused by individual difference for biomarker mining. For untargeted metabolic profiling of saliva samples, around 264 peaks could be reliably detected in each sample. After multivariate analysis, 23 metabolites were sorted out and verified to be related to the dysfunction of the amino acid and nucleotide metabolism in early LC. Notably, transcriptomic data from online TCGA repository were utilized to support findings from the salivary metabolomics experiment, including the disorder of amino acid biosynthesis and amino acid metabolism. Based on the verified differential metabolites, early LC patients could be clearly distinguished from healthy controls with a sensitivity of 97.2% and a specificity of 92%. The ultralow noise TELDI-MS platform displayed satisfactory ability to explore salivary metabolite information and discover potential biomarkers that may help develop a noninvasive screening tool for early LC.

Assessment of Blood Plasma Free-amino Acid Levels in Infertile Men

BACKGROUND/AIM

The objective of this study was to investigate the significance of the blood levels of free amino acids (AAs) in infertile men.

PATIENTS AND METHODS

Ninety-three men who underwent examinations for infertility were included. The concentrations of 20 AAs were measured and compared in four groups (normospermia, obstructive azoospermia, oligozoospermia, non-obstructive azoospermia) based on semen analysis and clinical parameters.

RESULTS

When the 93 men were divided into normospermia, obstructive azoospermia, oligozoospermia, and non-obstructive azoospermia groups, no significant differences were found in the concentrations of the 20 AAs between them. We then compared 49 men diagnosed with normozoospermia or oligozoospermia according to the median sperm motility and morphology abnormalities rates (30% and 20%, respectively). Men with low motility rates had significantly lower levels of tryptophan and alanine, and men with high abnormal morphology rates had significantly lower levels of aspartate and glutamate.

CONCLUSION

AAs are probably involved in the pathogenesis of male infertility, particularly oligozoospermia.

A Pilot Study for Investigation of Plasma Amino Acid Profile in Neurofibromatosis Type 1 Patients

BACKGROUND

Neurofibromatosis, also known as Von Recklinghausen disease, is a systemic and progressive genetic disease that primarily affects the skin, eyes, nervous system and bones. The disease can occur in a variety of ways and can vary from individuals. Metabolomic-based research using blood samples has enabled new diagnostic methods to be used in the diagnosis of various diseases, especially cancer. Among metabolites, profiling of plasma free amino acids (PFAA) is a promising approach because PFAAs bind all organ systems and play an important role in metabolism.

OBJECTIVE

This study aimed to determine the characteristics of PFAA profiles in neurofibromatosis patients and the possibility of using them for early detection and treatment of the disease.

METHOD

Patients with a diagnosis of Neurofibromatosis Type I confirmed by genetic analysis and healthy individuals of the same age group without any disease were included in the study. We analysed the nineteen plasma free amino acids (phenylalanine, proline, threonine, arginine, asparagine, cystine, valine, glutamate, tyrosine, serine, glutamine, glycine, tryptophane, leucine, lysine, methionine, isoleucine, aspartate and alanine) from neurofibromatosis Type I patients and control group by liquid chromatography tandem mass spectrometry (LC-MS/MS) in Metabolism Laboratory of Harran University Research and Application Hospital. The results of the plasma free amino acid levels were divided into 3 groups as essential, semi-essential and non-essential. The differences of amino acid levels between groups were determined.

RESULTS

Eight amino acid levels (methionine, arginine, cystine, glutamine, proline, asparagine, serine, aspartate) were significantly altered in patients with neurofibromatosis type 1. In essential amino acids, methionine levels were significantly higher in the patient group than the control group. While the levels of arginine and glutamine in semi-essential amino acids were statistically significantly higher in the patient group, a significant decrease was observed in cystine and proline levels compared to the control group's amino acid levels. In non-essential amino acids group, asparagine, serine and aspartate amino acid levels were significantly higher in the patient group compared to the control group.

CONCLUSION

The current research predicates that eight amino acids, nsmely methionine, arginine, cystine, glutamine, proline, asparagine, serine, aspartate can be considered to be valuable biomarkers for neurofibromatosis type I. This present study is the first to build models for neurofibromatosis Type I screening using plasma free amino acids and the amino acid profile will guide the predicting of the complications that may occur during the course of the disease.

Preoperative AminoIndex Cancer Screening (AICS) abnormalities predict postoperative recurrence in patients undergoing curative resection for non-small cell lung cancer

BACKGROUND

AminoIndex™ Cancer Screening (AICS (lung)) was developed as a screening test for lung cancer using a multivariate analysis of plasma-free amino acid (PFAA) profiles. According to the developed index composed of PFAA, the probability of lung cancer was categorized into AICS (lung) ranks A, B, and C in order of increasing risk. The aim of the present study was to investigate the relationship between the preoperative AICS (lung) rank and surgical outcomes in patients who underwent curative resection for non-small cell lung cancer (NSCLC).

METHODS

Preoperative blood samples were collected from 297 patients who underwent curative resection for NSCLC between 2006 and 2015. PFAA concentrations were measured. The relationship between the preoperative AICS (lung) rank and clinicopathological factors was examined. The effects of the preoperative AICS (lung) rank on postoperative outcomes were also analyzed.

RESULTS

The AICS (lung) rank was A in 93 patients (31.3%), B in 82 (27.6%), and C in 122 (41.1%). The AICS (lung) rank did not correlate with any clinicopathological factors, except for age. Based on follow-up data (median follow-up period of 6 years), postoperative recurrence was observed in 22 rank A patients (23.7%), 15 rank B (18.3%) and 49 rank C (40.2%). In the univariate analysis, preoperative AICS (lung) rank C was a worse factor of recurrence-free survival (p = 0.0002). The multivariate analysis identified preoperative AICS (lung) rank C (HR: 2.17, p = 0.0005) as a significant predictor of postoperative recurrence, particularly in patients with early-stage disease or adenocarcinoma.

CONCLUSION

Preoperative AICS (lung) rank C is a high-risk predictor of postoperative recurrence in patients undergoing curative resection for NSCLC.

Amino acid recognition by a fluorescent chemosensor based on cucurbit[8]uril and acridine hydrochloride

A new fluorescent chemosensor comprised of cucurbit[8]uril (Q[8]) and acridine hydrochloride (AC) has been designed and utilized for the recognition of amino acids. The AC was encapsulated by the Q[8] cavity and formed a 1:2 host-guest inclusion complex both in solution (aqueous) and in the solid-state. Whilst free AC is known to be strongly fluorescent, this strong fluorescence was quenched in the inclusion complex Q [8]-AC. This non-fluorescent complex Q[8]-AC was capable of serving as a fluorescence "off-on" probe, and was able to recognize either L-Phe or L-Trp via the competitive interaction between L-Phe or L-Trp. Moreover, the pH responsive nature of the probe allowed for the detection of basic amino acids, namely L-Arg, L-His, or L-Lys). As a result, a fluorescence method for the detection of five amino acids using a single system has been developed.

Association between Metabolites and the Risk of Lung Cancer: A Systematic Literature Review and Meta-Analysis of Observational Studies

Globally, lung cancer is the most prevalent cancer type. However, screening and early detection is challenging. Previous studies have identified metabolites as promising lung cancer biomarkers. This systematic literature review and meta-analysis aimed to identify metabolites associated with lung cancer risk in observational studies. The literature search was performed in PubMed and EMBASE databases, up to 31 December 2019, for observational studies on the association between metabolites and lung cancer risk. Heterogeneity was assessed using the I² statistic and Cochran’s Q test. Meta-analyses were performed using either a fixed-effects or random-effects model, depending on study heterogeneity. Fifty-three studies with 297 metabolites were included. Most identified metabolites (252 metabolites) were reported in individual studies. Meta-analyses were conducted on 45 metabolites. Five metabolites (cotinine, creatinine riboside, N-acetylneuraminic acid, proline and r-1,t-2,3,c-4-tetrahydroxy-1,2,3,4-tetrahydrophenanthrene) and five metabolite groups (total 3-hydroxycotinine, total cotinine, total nicotine, total 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (sum of concentrations of the metabolite and its glucuronides), and total nicotine equivalent (sum of total 3-hydroxycotinine, total cotinine and total nicotine)) were associated with higher lung cancer risk, while three others (folate, methionine and tryptophan) were associated with lower lung cancer risk. Significant heterogeneity was detected across most studies. These significant metabolites should be further evaluated as potential biomarkers for lung cancer.

Clinical significance of circulating tumor cells and metabolic signatures in lung cancer after surgical removal

Background

Lung cancer (LC) remains the deadliest form of cancer globally. While surgery remains the optimal treatment strategy for individuals with early-stage LC, what the metabolic consequences are of such surgical intervention remains uncertain.

Methods

Negative enrichment-fluorescence in situ hybridization (NE-FISH) was used in an effort to detect circulating tumor cells (CTCs) in pre- and post-surgery peripheral blood samples from 51 LC patients. In addition, targeted metabolomics analyses, multivariate statistical analyses, and pathway analyses were used to explore surgery-associated metabolic changes.

Results

LC patients had significantly higher CTC counts relative to healthy controls with 66.67% of LC patients having at least 1 detected CTC before surgery. CTC counts were associated with clinical outcomes following surgery. In a targeted metabolomics analysis, we detected 34 amino acids, 147 lipids, and 24 fatty acids. When comparing LC patients before and after surgery to control patients, metabolic shifts were detected via PLS-DA and pathway analysis. Further surgery-associated metabolic changes were identified when comparing LA (LC patients after surgery) and LB (LC patients before surgery) groups. We identified SM 42:4, Ser, Sar, Gln, and LPC 18:0 for inclusion in a biomarker panel for early-stage LC detection based upon an AUC of 0.965 (95% CI 0.900–1.000). This analysis revealed that SM 42:2, SM 35:1, PC (16:0/14:0), PC (14:0/16:1), Cer (d18:1/24:1), and SM 38:3 may offer diagnostic and prognostic benefits in LC.

Conclusions

These findings suggest that CTC detection and plasma metabolite profiling may be an effective means of diagnosing early-stage LC and identifying patients at risk for disease recurrence.

Resolution and Assignment of Differential Ion Mobility Spectra of Sarcosine and Isomers

Due to their central role in biochemical processes, fast separation and identification of amino acids (AA) is of importance in many areas of the biomedical field including the diagnosis and monitoring of inborn errors of metabolism and biomarker discovery. Due to the large number of AA together with their isomers and isobars, common methods of AA analysis are tedious and time-consuming because they include a chromatographic separation step requiring pre- or post-column derivatization. Here, we propose a rapid method of separation and identification of sarcosine, a biomarker candidate of prostate cancer, from isomers using differential ion mobility spectrometry (DIMS) interfaced with a tandem mass spectrometer (MS/MS) instrument. Baseline separation of protonated sarcosine from α- and β-alanine isomers can be easily achieved. Identification of DIMS peak is performed using an isomer-specific activation mode where DIMS- and mass-selected ions are irradiated at selected wavenumbers allowing for the specific fragmentation via an infrared multiple photon dissociation (IRMPD) process. Two orthogonal methods to MS/MS are thus added, where the MS/MS(IRMPD) is nothing but an isomer-specific multiple reaction monitoring (MRM) method. The identification relies on the comparison of DIMS-MS/MS(IRMPD) chromatograms recorded at different wavenumbers. Based on the comparison of IR spectra of the three isomers, it is shown that specific depletion of the two protonated α- and β-alanine can be achieved, thus allowing for clear identification of the sarcosine peak. It is also demonstrated that DIMS-MS/MS(IRMPD) spectra in the carboxylic C=O stretching region allow for the resolution of overlapping DIMS peaks. Graphical Abstract ᅟ.

Models including plasma levels of sphingomyelins and phosphatidylcholines as diagnostic and prognostic biomarkers of endometrial cancer

In endometrial cancer, biomarkers for preoperative identification of patients with low risk for disease progression would enable stratification according to the extent of surgery needed, and would avoid the complications that can be associated with radical surgery. A panel of proteins, amino acids, enzymes, and miRNA has been investigated as potential biomarkers for endometrial cancer. At the time of the manuscript submission targeted metabolomics/lipidomics approaches have not been applied to biomarker research in endometrial cancer. Using electrospray ionization-tandem mass spectrometry we quantified 163 metabolites in 126 plasma samples (61 patients with endometrial cancer, 65 control patients). Three single phosphatidylcholines were identified with significantly decreased levels in patients with endometrial cancer. A diagnostic model was defined as the ratio between acylcarnitine C16 and phosphatidylcholine PCae C40:1, the ratio between proline and tyrosine, and the ratio between the two phosphatidylcholines PCaa C42:0 and PCae C44:5; which provided sensitivity of 85.25%, specificity of 69.23%, and AUC of 0.837. Addition of smoking status further improved the constructed diagnostic model (AUC = 0.855). The presence of the major prognostic factors of deep myometrial invasion and lymphovascular invasion were also associated with altered metabolite concentrations. A prognostic model for deep myometrial invasion included the ratio between two hydroxysphingomyelins SMOH C14:1 and SMOH C24:1, and the ratio between two phosphatidylcholines PCaa C40:2 and PCaa C42:6, which provided sensitivity of 81.25%, specificity of 86.36%, and AUC of 0.857. The model for lymphovascular invasion included the ratio between two phosphatidylcholines PCaa C34:4 and PCae C38:3, and the ratio between acylcarnitine C16:2 and phosphatidylcholine PCaa C38:1, which provided sensitivity of 88.89%, specificity of 84.31%, and AUC of 0.935.

Protein restriction and cancer

Protein restriction without malnutrition is currently an effective nutritional intervention known to prevent diseases and promote health span from yeast to human. Recently, low protein diets are reported to be associated with lowered cancer incidence and mortality risk of cancers in human. In murine models, protein restriction inhibits tumor growth via mTOR signaling pathway. IGF-1, amino acid metabolic programing, FGF21, and autophagy may also serve as potential mechanisms of protein restriction mediated cancer prevention. Together, dietary intervention aimed at reducing protein intake can be beneficial and has the potential to be widely adopted and effective in preventing and treating cancers.

Amino acid profiles as potential biomarkers for pediatric cancers: a preliminary communication

AIM

Childhood cancer remains one of the main cause of death in the pediatric population. Amino acids (AAs) level alterations in plasma are considered to play a role in carcinogenesis and further course of the disease.

METHODS

Seventy-seven children with cancer, including 47 with hematological and 30 with solid tumors were enrolled in this study and compared with healthy children. Twenty-two plasma-free AAs were determined by HPLC with fluorometric detection.

RESULTS

The results revealed significant decrease in glutamine levels for oncological patients and significant increase in aspartic acid, glutamic acid, asparagine, serine, citrulline, alanine, GABA, tryptophan, methionine, valine, phenylalanine and isoleucine levels in cancer children versus control.

CONCLUSION

Plasma-free AA profile as a biomarker, which combines metabolic and clinical data, as an innovative and interdisciplinary approach, may allow for faster detection of tumor occurrence, and in the future for monitoring patient during treatment, and possible prediction of cancer recurrence.

Plasma-free amino acid profiles are predictors of cancer and diabetes development

Type 2 diabetes (T2D) and cancers are two major causes of morbidity and mortality worldwide. Nowadays, there is convincing evidence of positive associations between T2D and the incidence or prognosis of a wide spectrum of cancers, for example, breast, colon, liver and pancreas. Many observational studies suggest that certain medications used to treat hyperglycemia (or T2D) may affect cancer cells directly or indirectly. The potential mechanisms of the direct T2D cancer links have been hypothesized to be hyperinsulinemia, hyperglycemia and chronic inflammation; however, the metabolic pathways that lead to T2D and cancers still remain elusive. Plasma-free amino acid (PFAA) profiles have been highlighted in their associations with the risks of developing T2D and cancers in individuals with different ethnic groups and degree of obesity. The alterations of PFAAs might be predominately caused by the metabolic shift resulted from insulin resistance. The underlying mechanisms have not been fully elucidated, in particular whether the amino acids are contributing to these diseases development in a causal manner. This review addresses the molecular and clinical associations between PFAA alterations and both T2D and cancers, and interprets possible mechanisms involved. Revealing these interactions and mechanisms may improve our understanding of the complex pathogenesis of diabetes and cancers and improve their treatment strategies.

Study of early stage non-small-cell lung cancer using Orbitrap-based global serum metabolomics

Purpose

The aim of the project was to apply ultra-high-performance liquid chromatography–quadrupole-Orbitrap-high-resolution mass spectrometry for serum metabolite profiling of non-small-cell lung cancer (NSCLC). This Orbitrap-based methodology has been applied for a study of NSCLC potential markers for the first time.

Methods

After extraction using protein precipitation, sera were separated on the ACE Excel 2 C18-PFP (100 × 2.1 mm, 2.0 µm) column using gradient elution and analyzed within the range of 70–1000 m/z. Only patients with early stage disease (stages IA–IIB) were included in the study, providing opportunity to find biomarkers for early lung cancer detection. The resulting metabolite profiles were subjected to univariate and multivariate statistical tests.

Results

36 features were found significantly changed between NSCLC group and controls after FDR adjustment and 19 were identified using various metabolite databases (in-house library, HMDB, mzCloud). The study revealed a number of NSCLC biomarker candidates which belong to such compound classes as acylcarnitines, organic acids, and amino acids. Multivariate ROC curve built using 12 identified metabolites was characterized by AUC = 0.836 (0.722–0.946). There were no significant differences in the serum metabolite profiles between two most common histological types of lung cancer—adenocarcinoma and squamous cell carcinoma.

Conclusions

Through identification of novel potential tumor markers, Orbitrap-based global metabolic profiling is a useful strategy in cancer research. Our study can accelerate development of new diagnostic and therapeutic strategies in NSCLC. The metabolites involved in discrimination between NSCLC patients and the control subjects should be further explored using a targeted approach.

Electronic supplementary material

The online version of this article (doi:10.1007/s00432-017-2347-0) contains supplementary material, which is available to authorized users.

Evaluation of serum amino acid profiles' utility in non-small cell lung cancer detection in Polish population

OBJECTIVES

Data from studies performed in Japanese and Korean populations suggest that free amino acid profiles have the potential to aid in non-small cell lung cancer (NSCLC) detection. However, there is still no data regarding abnormalities of free amino acids and their usefulness in NSCLC detection in European populations. The aim of the study was an evaluation of utility of amino acid profiles in NSCLC detection in Polish patients.

MATERIALS AND METHODS

Levels of 31 free amino acids were determined in 153 serum samples applying a liquid chromatography-tandem mass spectrometry-based methodology. Patients with I stage lung cancer represented a significant part of the studied group (46.7%). The obtained metabolite profiles along with clinical data were subjected to multivariate statistical tests.

RESULTS

The presented study indicated that the increased serum level of phenylalanine and decreased level of citrulline are among the most robust cancer signatures in blood of NSCLC group. In addition, increased levels of aspartic acid and β-alanine were also recognized as important features of NSCLC. Amino acid selected based on studies of Asian patients were found to have insufficient specificity in NSCLC detection in the studied population. Therefore, we proposed a new set of 6 amino acids (aspartic acid, β-alanine, histidine, asparagine, phenylalanine and serine), which ensured higher accuracy in sample classification (from 90.3% to 77.1% depending of histological type).

CONCLUSION

We indicated that some of the free amino acid alterations occur in serum of NSCLC patients in early stage of disease and thus they can be valuable components of a blood multi-marker panel for NSCLC detection.