Urinary metabolomic study of non-small cell lung carcinoma based on ultra high performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry

Data-driven identification of plasma metabolite clusters and metabolites of interest for potential detection of early-stage non-small cell lung cancer cases versus cancer-free controls

BACKGROUND

Metabolomics is a potential means for biofluid-based lung cancer detection. We conducted a non-targeted, data-driven assessment of plasma from early-stage non-small cell lung cancer (ES-NSCLC) cases versus cancer-free controls (CFC) to explore and identify the classes of metabolites for further targeted metabolomics biomarker development.

METHODS

Plasma from 250 ES-NSCLC cases and 250 CFCs underwent ultra-high-performance liquid chromatography/quadrupole time-of-flight mass spectrometry (UHPLC-QTOF-MS) in positive and negative electrospray ionization (ESI) modes. Molecular feature extraction, formula generation, and find-by-ion tools annotated metabolic entities. Analysis was restricted to endogenous metabolites present in ≥ 80% of samples. Unsupervised hierarchical cluster analysis identified clusters of metabolites. The metabolites with the strongest correlation with the principal component of each cluster were included in logistic regression modeling to assess discriminatory performance with and without adjustment for clinical covariates.

RESULTS

A total of 1900 UHPLC-QTOF-MS assessments identified 1667 and 2032 endogenous metabolites in the ESI-positive and ESI-negative modes, respectively. After data filtration, 676 metabolites remained, and 12 clusters of metabolites were identified from each ESI mode. Multivariable logistic regression using the representative metabolite from each cluster revealed effective classification of cases from controls with overall diagnostic accuracy of 91% (ESI positive) and 94% (ESI negative). Metabolites of interest identified for further targeted analysis include the following: 1b, 3a, 12a-trihydroxy-5b-cholanoic acid, pyridoxamine 5'-phosphate, sphinganine 1-phosphate, gamma-CEHC, 20-carboxy-leukotriene B4, isodesmosine, and 18-hydroxycortisol.

CONCLUSIONS

Plasma-based metabolomic detection of early-stage NSCLC appears feasible. Further metabolomics studies targeting phospholipid, steroid, and fatty acid metabolism are warranted to further develop noninvasive metabolomics-based detection of early-stage NSCLC.

High-resolution metabolomic biomarkers for lung cancer diagnosis and prognosis

Lung cancer is the leading cause of human cancer mortality due to the lack of early diagnosis technology. The low-dose computed tomography scan (LDCT) is one of the main techniques to screen cancers. However, LDCT still has a risk of radiation exposure and it is not suitable for the general public. In this study, plasma metabolic profiles of lung cancer were performed using a comprehensive metabolomic method with different liquid chromatography methods coupled with a Q-Exactive high-resolution mass spectrometer. Metabolites with different polarities (amino acids, fatty acids, and acylcarnitines) can be detected and identified as differential metabolites of lung cancer in small volumes of plasma. Logistic regression models were further developed to identify cancer stages and types using those significant biomarkers. Using the Variable Importance in Projection (VIP) and the area under the curve (AUC) scores, we have successfully identified the top 5, 10, and 20 metabolites that can be used to differentiate lung cancer stages and types. The discrimination accuracy and AUC score can be as high as 0.829 and 0.869 using the five most significant metabolites. This study demonstrated that using 5 + metabolites (Palmitic acid, Heptadecanoic acid, 4-Oxoproline, Tridecanoic acid, Ornithine, and etc.) has the potential for early lung cancer screening. This finding is useful for transferring the diagnostic technology onto a point-of-care device for lung cancer diagnosis and prognosis.

Differences in Fatty Acid Oxidation between Nab-Paclitaxel- and Solvent-Based Paclitaxel-Treated A549 Cells Based on Metabolomics

The pharmacokinetics, safety, and anticancer efficacy profiles of nanoparticle albumin-bound (nab)-paclitaxel formulations are superior to those of solvent-based paclitaxel formulations. The aims of the present study were to study the effects of nab-paclitaxel and solvent-based paclitaxel formulations on the metabolic profiles of the model cell line (A549) and attempt to elucidate the associated metabolic pathways. A mass spectrometry-based cell metabolomics approach and viability evaluation were used to explore the potential difference. Western blotting was utilized to measure the levels of relevant proteins, and carnitine palmitoyltransferase 1 (CPT1) activities were quantified. Fold changes normalized to controls in levels of carnitine and several acylcarnitines were significantly different (p < 0.05) between A549 cells treated with nab-paclitaxel and those treated with solvent-based paclitaxel. Relative to the controls, there were also significant fold change differences in palmitic and linoleic acid levels in the cell lysates, mitochondrial CPT1 activities, and mitochondrial medium-chain acyl-CoA dehydrogenase (MCAD) protein levels in the A549 cells subjected to the nab-paclitaxel and solvent-based paclitaxel formulations. Results suggested that the two formulations differentially modulated fatty acid oxidation in the A549 cells. While cell viability results did not reveal significant differences, the findings implied that a mass spectrometry-based cell metabolomics approach could be a sensitive tool to explore the differences caused by formulation changes without using animals. Since uncertainties of products containing nanomaterials warrant holistic screening to address safety concerns, the aforementioned approach may be of regulatory importance and is worth further investigation.

Advances in lung cancer biomarkers: The role of (metal-) metabolites and selenoproteins

Lung cancer (LC) is the second most common cause of death in men after prostate cancer, and the third most recurrent type of tumor in women after breast and colon cancers. Unfortunately, when LC symptoms begin to appear, the disease is already in an advanced stage and the survival rate only reaches 2%. Thus, there is an urgent need for early diagnosis of LC using specific biomarkers, as well as effective therapies and strategies against LC. On the other hand, the influence of metals on more than 50% of proteins is responsible for their catalytic properties or structure, and their presence in molecules is determined in many cases by the genome. Research has shown that redox metal dysregulation could be the basis for the onset and progression of LC disease. Moreover, metals can interact between them through antagonistic, synergistic and competitive mechanisms, and for this reason metals ratios and correlations in LC should be explored. One of the most studied antagonists against the toxic action of metals is selenium, which plays key roles in medicine, especially related to selenoproteins. The study of potential biomarkers able to diagnose the disease in early stage is conditioned by the development of new analytical methodologies. In this sense, omic methodologies like metallomics, proteomics and metabolomics can greatly assist in the discovery of biomarkers for LC early diagnosis.

The integration of metabolome and proteome reveals bioactive polyphenols and hispidin in ARTP mutagenized Phellinus baumii

Phellinus baumii, also called “Sang Huang” in China, is broadly used as a kind of health food or folk medicine in Asia for its high biological activities, e.g. anti-tumor, anti-oxidation and anti-inflammatory activities. Although some previous studies have indicated that polysaccharides and flavonoids showed the activity of inhibiting tumor cells, the active metabolites of P. baumii needs further research. In our study, a stable P. baumii mutant (A67), generated by ARTP mutagenesis strategy, showed more significantly inhibiting tumor cells and enhancing antioxidant activity. Our further studies found that the increase of polyphenols content, especially hispidin, was an important reason of the biological activity enhancement of A67. According to the results of the integrated metabolome and proteome study, the increase of polyphenol content was caused by upregulation of the phenylpropanoid biosynthesis. This study expanded the understanding of active compounds and metabolic pathway of P. baumii.

Current Trends in Cancer Biomarker Discovery Using Urinary Metabolomics: Achievements and New Challenges

BACKGROUND

The development of effective screening methods for early cancer detection is one of the foremost challenges facing modern cancer research. Urinary metabolomics has recently emerged as a potentially transformative approach to cancer biomarker discovery owing to its noninvasive sampling characteristics and robust analytical feasibility.

OBJECTIVE

To provide an overview of new developments in urinary metabolomics, cover the most promising aspects of hyphenated techniques in untargeted and targeted metabolomics, and to discuss technical and clinical limitations in addition to the emerging challenges in the field of urinary metabolomics and its application to cancer biomarker discovery.

METHODS

A systematic review of research conducted in the past five years on the application of urinary metabolomics to cancer biomarker discovery was performed. Given the breadth of this topic, our review focused on the five most widely studied cancers employing urinary metabolomics approaches, including lung, breast, bladder, prostate, and ovarian cancers.

RESULTS

As an extension of conventional metabolomics, urinary metabolomics has benefitted from recent technological developments in nuclear magnetic resonance, mass spectrometry, gas and liquid chromatography, and capillary electrophoresis that have improved urine metabolome coverage and analytical reproducibility. Extensive metabolic profiling in urine has revealed a significant number of altered metabolic pathways and putative biomarkers, including pteridines, modified nucleosides, and acylcarnitines, that have been associated with cancer development and progression.

CONCLUSION

Urinary metabolomics presents a transformative new approach toward cancer biomarker discovery with high translational capacity to early cancer screening.

Next-generation metabolomics in lung cancer diagnosis, treatment and precision medicine: mini review

Lung cancer is the leading cause of cancer-related death. Next-generation metabolomics is becoming a powerful emerging technology for studying the systems biology and chemistry of health and disease. This mini review summarized the main platforms of next-generation metabolomics and its main applications in lung cancer including early diagnosis, pathogenesis, classifications and precision medicine. The period covers between 2009 and August, 2017. The major issues and future directions of metabolomics in lung cancer research and clinical applications were also discussed.

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.

Accumulation of Palmitoylcarnitine and Its Effect on Pro-Inflammatory Pathways and Calcium Influx in Prostate Cancer

BACKGROUND

Acylcarnitines are intermediates of fatty acid oxidation and accumulate as a consequence of the metabolic dysfunction resulting from the insufficient integration between β-oxidation and the tricarboxylic acid (TCA) cycle. The aim of this study was to investigate whether acylcarnitines accumulate in prostate cancer tissue, and whether their biological actions could be similar to those of dihydrotestosterone (DHT), a structurally related compound associated with cancer development.

METHODS

Levels of palmitoylcarnitine (palcar), a C16:00 acylcarnitine, were measured in prostate tissue using LC-MS/MS. The effect of palcar on inflammatory cytokines and calcium (Ca(2+) ) influx was investigated in in vitro models of prostate cancer.

RESULTS

We observed a significantly higher level of palcar in prostate cancerous tissue compared to benign tissue. High levels of palcar have been associated with increased gene expression and secretion of the pro-inflammatory cytokine IL-6 in cancerous PC3 cells, compared to normal PNT1A cells. Furthermore, we found that high levels of palcar induced a rapid Ca(2+) influx in PC3 cells, but not in DU145, BPH-1, or PNT1A cells. This pattern of Ca(2+) influx was also observed in response to DHT. Through the use of whole genome arrays we demonstrated that PNT1A cells exposed to palcar or DHT have a similar biological response.

CONCLUSIONS

This study suggests that palcar might act as a potential mediator for prostate cancer progression through its effect on (i) pro-inflammatory pathways, (ii) Ca(2+) influx, and (iii) DHT-like effects. Further studies need to be undertaken to explore whether this class of compounds has different biological functions at physiological and pathological levels. Prostate 76:1326-1337, 2016. © 2016 The Authors. The Prostate published by Wiley Periodicals, Inc.

Tandem mass spectrometry-based newborn screening strategy could be used to facilitate rapid and sensitive lung cancer diagnosis

Objective

Newborn screening (NBS) helps in the early detection of inborn errors of metabolism (IEM). The most effective NBS strategy prevailing in clinics is tandem mass spectrometry (MS/MS) analysis using dried blood spot (DBS) samples. Taking lung cancer (LC) as an example, this study tried to explore if this technique could be of any assistance for the discovery of tumor metabolite markers.

Materials and methods

Twenty-six acylcarnitines and 23 amino acids, which are commonly used in IEM screening, were quantified using DBS samples from 222 LC patients, 118 benign lung disease (LD) patients, and 96 healthy volunteers (CONT). Forty-four calculated ratios based on the abovementioned metabolites were also included using MS/MS quantification results.

Results

This pilot study led to the findings of 65 significantly changed amino acids, acylcarnitines, and some of their ratios for the LC, LD, and CONT groups. Among the differential parameters, 12 items showed reverse changing trends between the LC and LD groups compared to the CONT group. Regression analysis demonstrated that six of them – Arg, Pro, C10:1, Arg/Orn, Cit/Arg, and C5-OH/C0 – could be used to diagnose LC with a sensitivity of 91.3% and a specificity of 92.7%.

Conclusion

This study demonstrated the DBS-based MS/MS strategy was a promising tool for the discovery of tumor metabolite markers. Remarkably, this MS/MS analysis could be finished in several minutes, implying that it was a proper measure complementary to the traditional serum protein biomarker quantitation strategy for cancerous disease diagnosis and screening purposes.

A short review of applications of liquid chromatography mass spectrometry based metabolomics techniques to the analysis of human urine

Mass spectrometry based metabolomics profiling.