Metabolome-based biomarkers: their potential role in the early detection of lung cancer

A Systematic Role of Metabolomics, Metabolic Pathways, and Chemical Metabolism in Lung Cancer

Lung cancer (LC) is considered as one of the leading causes of cancer-associated mortalities. Cancer cells' reprogrammed metabolism results in changes in metabolite concentrations, which can be utilized to identify a distinct metabolic pattern or fingerprint for cancer detection or diagnosis. By detecting different metabolic variations in the expression levels of LC patients, this will help and enhance early diagnosis methods as well as new treatment strategies. The majority of patients are identified at advanced stages after undergoing a number of surgical procedures or diagnostic testing, including the invasive procedures. This could be overcome by understanding the mechanism and function of differently regulated metabolites. Significant variations in the metabolites present in the different samples can be analyzed and used as early biomarkers. They could also be used to analyze the specific progression and type as well as stages of cancer type making it easier for the treatment process. The main aim of this review article is to focus on rewired metabolic pathways and the associated metabolite alterations that can be used as diagnostic and therapeutic targets in lung cancer diagnosis as well as treatment strategies.

Serum Metabolic Disturbances in Lung Cancer Investigated through an Elaborative NMR-Based Serum Metabolomics Approach

Detection of metabolic disturbances in lung cancer (LC) has the potential to aid early diagnosis/prognosis and hence improve disease management strategies through reliable grading, staging, and determination of neoadjuvant status in LC. However, a majority of previous metabolomics studies compare the normalized spectral features which not only provide ambiguous information but further limit the clinical translation of this information. Various such issues can be resolved by performing the concentration profiling of various metabolites with respect to formate as an internal reference using commercial software Chenomx. Continuing our efforts in this direction, the serum metabolic profiles were measured on 39 LC patients and 42 normal controls (NCs, comparable in age/sex) using high-field 800 MHz NMR spectroscopy and compared using multivariate statistical analysis tools to identify metabolic disturbances and metabolites of diagnostic potential. Partial least-squares discriminant analysis (PLS-DA) model revealed a distinct separation between LC and NC groups and resulted in excellent discriminatory ability with the area under the receiver-operating characteristic (AUROC) = 0.97 [95% CI = 0.89-1.00]. The metabolic features contributing to the differentiation of LC from NC samples were identified first using variable importance in projection (VIP) score analysis and then checked for their statistical significance (with p-value < 0.05) and diagnostic potential using the ROC curve analysis. The analysis revealed relevant metabolic disturbances associated with LC. Among various circulatory metabolites, six metabolites, including histidine, glutamine, glycine, threonine, alanine, and valine, were found to be of apposite diagnostic potential for clinical implications. These metabolic alterations indicated altered glucose metabolism, aberrant fatty acid synthesis, and augmented utilization of various amino acids including active glutaminolysis in LC.

Metabolomic Laboratory-Developed Tests: Current Status and Perspectives

Laboratory-developed tests (LDTs) are a subset of in vitro diagnostic devices, which the US Food and Drug Administration defines as "tests that are manufactured by and used within a single laboratory". The review describes the emergence and history of LDTs. The current state and development prospects of LDTs based on metabolomics are analyzed. By comparing LDTs with the scientific metabolomics study of human bio samples, the characteristic features of metabolomic LDT are shown, revealing its essence, strengths, and limitations. The possibilities for further developments and scaling of metabolomic LDTs and their potential significance for healthcare are discussed. The legal aspects of LDT regulation in the United States, European Union, and Singapore, demonstrating different approaches to this issue, are also provided. Based on the data presented in the review, recommendations were made on the feasibility and ways of further introducing metabolomic LDTs into practice.

Functional Metabolomics and Chemoproteomics Approaches Reveal Novel Metabolic Targets for Anticancer Therapy

Cancer cells exhibit different metabolic patterns compared to their normal counterparts. Although the reprogrammed metabolism has been indicated as strong biomarkers of cancer initiation and progression, increasing evidences suggest that metabolic alteration tuned by oncogenic drivers contributes to the occurrence and development of cancers rather than just being a hallmark of cancer. With this notion, targeting cancer metabolism holds promise as a novel anticancer strategy and is embracing its renaissance during the past two decades. Herein we have summarized the most recent developments in omics technology, including both metabolomics and proteomics, and how the combined use of these analytical tools significantly impacts this field by comprehensively and systematically recording the metabolic changes in cancer and hence reveals potential therapeutic targets that function by modulating the disrupted metabolic pathways.

Targeted Metabolomics Analyses Reveal Specific Metabolic Alterations in High-Grade Prostate Cancer Patients

Prostate cancer (PCa) is a hormone-dependent tumor characterized by an extremely heterogeneous prognosis. Despite recent advances in partially uncovering some of the biological processes involved in its progression, there is still an urgent need for identifying more accurate and specific prognostic procedures to differentiate between disease stages. In this context, targeted approaches, focused on mapping dysregulated metabolic pathways, could play a critical role in identifying the mechanisms driving tumorigenesis and metastasis. In this study, a targeted analysis of the nuclear magnetic resonance-based metabolomic profile of PCa patients with different tumor grades, guided by transcriptomics profiles associated with their stages, was performed. Serum and urine samples were collected from 73 PCa patients. Samples were classified according to their Gleason score (GS) into low-GS (GS < 7) and high-GS PCa (GS ≥ 7) groups. A total of 36 metabolic pathways were found to be dysregulated in the comparison between different PCa grades. Particularly, the levels of glucose, glycine and 1-methlynicotinamide, metabolites involved in energy metabolism and nucleotide synthesis were significantly altered between both groups of patients. These results underscore the potential of targeted metabolomic profiling to characterize relevant metabolic changes involved in the progression of this neoplastic process.

[Ten years of the Russian metabolomics: history of development and achievements]

Metabolomics is one of the omics sciences, the technologies of which are widely used today in many life sciences. Its application influenced the discovery of new biomarkers of diseases, the description of biochemical processes occurring in many organisms, laid the basis for a new generation of clinical laboratory diagnostics. The purpose of this review is to show how metabolomics is represented in the studies of Russian scientists, to demonstrate the main directions and achievements of the Russian science in this field. The review also highlights the history of metabolomics, existing problems and the place of Russian metabolomics in their solution.

[Blood metabolome analysis for creating a digital image of a healthy person]

In the frame of the work, data on the implementation of metabolomics tests in medicine have been systematized. Based on the obtained data, a set of protocols was proposed, the sequential realization of which makes it possible to conduct a blood metabolome analysis for medical purposes. Using this analysis and the number of blood samples from healthy volunteers, a prototype of a healthy person's metabolomic image has been developed; it allows visually and digitally to assess the compliance of the human blood metabolome with the norm. At the same time, 99% of the metabolic processes reflected in the blood plasma are estimated. If abnormalities are detected, the metabolomic image allows to get the value of these deviations of metabolic processes in digital terms.

A High-Performing Plasma Metabolite Panel for Early-Stage Lung Cancer Detection

The objective of this research is to use metabolomic techniques to discover and validate plasma metabolite biomarkers for the diagnosis of early-stage non-small cell lung cancer (NSCLC). The study included plasma samples from 156 patients with biopsy-confirmed NSCLC along with age and gender-matched plasma samples from 60 healthy controls. A fully quantitative targeted mass spectrometry (MS) analysis (targeting 138 metabolites) was performed on all samples. The sample set was split into a discovery set and validation set. Metabolite concentration data, clinical data, and smoking history were used to determine optimal sets of biomarkers and optimal regression models for identifying different stages of NSCLC using the discovery sets. The same biomarkers and regression models were used and assessed on the validation models. Univariate and multivariate statistical analysis identified β-hydroxybutyric acid, LysoPC 20:3, PC ae C40:6, citric acid, and fumaric acid as being significantly different between healthy controls and stage I/II NSCLC. Robust predictive models with areas under the curve (AUC) > 0.9 were developed and validated using these metabolites and other, easily measured clinical data for detecting different stages of NSCLC. This study successfully identified and validated a simple, high-performing, metabolite-based test for detecting early stage (I/II) NSCLC patients in plasma. While promising, further validation on larger and more diverse cohorts is still required.

The roles of M30 and M65 in the assessment of treatment response and prognosis in patients with non-small cell lung cancer, who receive neoadjuvant treatment

Aim of the study

To investigate the efficacy of evaluating prognosis and response to lung cancer treatment using M30 and M65 antigens, which are indicators of necrosis.

Material and methods

Forty-eightpatients with lung cancer, who were planned to receive neoadjuvant chemotherapy, and 38 healthy volunteers were enrolled in the study. Using M30 and M65 levels, cytokeratin 18 levels were measured twice: before and 48 hours after the first chemotherapy treatment. Apoptotic and total necrosis levels were determined by measuring the M65 and M30 levels.

Results

The M30 and M65 antigen levels in the patient group were significantly higher than in the control group (p< 0.001). The M30 and M65 antigen levels were significantly higher 48 hours after the chemotherapy compared with before the chemotherapy (p< 0.001). There were no significant differences in M65 levels between patients who responded to treatment and patients who progressed. The M30 levels increased significantly in patients with disease progression (p= 0.694 and p = 0.024, respectively). No significant differences in serum M30 and M65 antigen levels were found when compared between the surviving and deceased patients (p = 0.126 and p = 0.340, respectively).

Conclusions

A significant increase was detected in serum M30 and M65 levels in patients with lung cancer. There was a greater increase in serum M30 levels in patients who did not respond to the chemotherapy. This result gives rise to the thought that evaluating apoptosis and total necrosis through M30 and M65 measurements alone only in patients receiving neoadjuvant chemotherapy would be insufficient for specifying the effectiveness of the treatment.

Predictive value and clinical significance of increased SSAT-1 activity in healthy adults

AIM

Spermidine/spermine N1-acetyltransferase (SSAT-1) regulates cell growth, proliferation and death. Amantadine is converted by SSAT-1 to acetylamantadine (AA). In our earlier studies, although SSAT-1 was activated in patients with cancer, a number of ostensibly healthy adult volunteers had higher than expected AA concentration. This study was therefore undertaken to examine the outlier group.

MATERIALS & METHODS

A follow up of urine analysis for AA by liquid chromatography-tandem mass spectrometry as well as clinical assessments and additional blood analyses were conducted.

RESULTS

In some of the outlier controls, higher than expected AA concentration was linked to increased serum carcinoembryonic antigen. Clinical and radiographic assessments revealed underlying abnormalities in other cases that could represent premalignant conditions. Hematology tests revealed elevations in white blood cells and platelets, which are markers of inflammation.

CONCLUSION

High urine concentration of AA could be used as a simple and useful test for screening of cancer in high-risk populations.

Translational Metabolomics: Current Challenges and Future Opportunities

Metabolomics is one of the latest omics technologies that has been applied successfully in many areas of life sciences. Despite being relatively new, a plethora of publications over the years have exploited the opportunities provided through this data and question driven approach. Most importantly, metabolomics studies have produced great breakthroughs in biomarker discovery, identification of novel metabolites and more detailed characterisation of biological pathways in many organisms. However, translation of the research outcomes into clinical tests and user-friendly interfaces has been hindered due to many factors, some of which have been outlined hereafter. This position paper is the summary of discussion on translational metabolomics undertaken during a peer session of the Australian and New Zealand Metabolomics Conference (ANZMET 2018) held in Auckland, New Zealand. Here, we discuss some of the key areas in translational metabolomics including existing challenges and suggested solutions, as well as how to expand the clinical and industrial application of metabolomics. In addition, we share our perspective on how full translational capability of metabolomics research can be explored.