Classification models for detection of lung cancer based on nine element distribution of urine samples

A critical review on the relevance, essentiality, and analytical techniques of trace elements in human cancer

Trace elements (TEs) are indispensable nutritional elements, playing a pivotal role in maintaining human health and serving as essential cofactors for numerous enzymes that facilitate crucial biological processes. The dysregulation (excess or deficiency) of TEs can affect the proper functioning of various organs and lead to diseases like cancer. However, the current research findings remain contentious, and the association between TE variations and cancer remains elusive. This article reviews the recent advances in the quantitative detection of TEs in tumor research to fully understand the important role of TEs in disease diagnosis and prognosis. The changes in the levels of various elements (such as Cu, Zn, Fe, Se, Ca, etc.) are analyzed and summarized from five systems of the human body, including the digestive system, urinary system, reproductive system, endocrine system, and respiratory system. By analyzing the relevant findings in diverse biological samples, we systematically investigate the disruption of TEs homeostasis in cancer patients, thereby underscoring the potential of TEs as cancer biomarkers. We also present novel analytical techniques such as isotope ratio determination and bioimaging, along with advanced auxiliary tools like machine learning, for the detection of TEs in disease research. This review aims to provide a comprehensive overview of TEs variations in the main cancer types of different systems, which addresses the knowledge gap in TEs on human health, and provides proposals for future research.

Recent advances in the application of metallomics in diagnosis and prognosis of human cancer

Metals play a critical role in human health and diseases. In recent years, metallomics has been introduced and extensively applied to investigate the distribution, regulation, function, and crosstalk of metal(loid) ions in various physiological and pathological processes. Based on high-throughput multielemental analytical techniques and bioinformatics methods, it is possible to elucidate the correlation between the metabolism and homeostasis of diverse metals and complex diseases, in particular for cancer. This review aims to provide an overview of recent progress made in the application of metallomics in cancer research. We mainly focuses on the studies about metallomic profiling of different human biological samples for several major types of cancer, which reveal distinct and dynamic patterns of metal ion contents and the potential benefits of using such information in the detection and prognosis of these malignancies. Elevated levels of copper appear to be a significant risk factor for various cancers, and each type of cancer has a unique distribution of metals in biofluids, hair/nails, and tumor-affected tissues. Furthermore, associations between genetic variations in representative metalloprotein genes and cancer susceptibility have also been demonstrated. Overall, metallomics not only offers a better understanding of the relationship between metal dyshomeostasis and the development of cancer but also facilitates the discovery of new diagnostic and prognostic markers for cancer translational medicine.

Disease Ionomics: Understanding the Role of Ions in Complex Disease

Ionomics is a novel multidisciplinary field that uses advanced techniques to investigate the composition and distribution of all minerals and trace elements in a living organism and their variations under diverse physiological and pathological conditions. It involves both high-throughput elemental profiling technologies and bioinformatic methods, providing opportunities to study the molecular mechanism underlying the metabolism, homeostasis, and cross-talk of these elements. While much effort has been made in exploring the ionomic traits relating to plant physiology and nutrition, the use of ionomics in the research of serious diseases is still in progress. In recent years, a number of ionomic studies have been carried out for a variety of complex diseases, which offer theoretical and practical insights into the etiology, early diagnosis, prognosis, and therapy of them. This review aims to give an overview of recent applications of ionomics in the study of complex diseases and discuss the latest advances and future trends in this area. Overall, disease ionomics may provide substantial information for systematic understanding of the properties of the elements and the dynamic network of elements involved in the onset and development of diseases.

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 Metallome of Lung Cancer and its Potential Use as Biomarker

Carcinogenesis is a very complex process in which metals have been found to be critically involved. In this sense, a disturbed redox status and metal dyshomeostasis take place during the onset and progression of cancer, and it is well-known that trace elements participate in the activation or inhibition of enzymatic reactions and metalloproteins, in which they usually participate as cofactors. Until now, the role of metals in cancer have been studied as an effect, establishing that cancer onset and progression affects the disturbance of the natural chemical form of the essential elements in the metabolism. However, it has also been studied as a cause, giving insights related to the high exposure of metals giving a place to the carcinogenic process. On the other hand, the chemical species of the metal or metallobiomolecule is very important, since it finally affects the biological activity or the toxicological potential of the element and their mobility across different biological compartments. Moreover, the importance of metal homeostasis and metals interactions in biology has also been demonstrated, and the ratios between some elements were found to be different in cancer patients; however, the interplay of elements is rarely reported. This review focuses on the critical role of metals in lung cancer, which is one of the most insidious forms of cancer, with special attention to the analytical approaches and pitfalls to extract metals and their species from tissues and biofluids, determining the ratios of metals, obtaining classification profiles, and finally defining the metallome of lung cancer.

Metal dyshomeostasis based biomarkers of lung cancer using human biofluids

Metals, ratios, interactions and species in serum, urine and bronchoalveolar lavage fluid as biomarkers of lung cancer.

MicroRNA-122-3p inhibits tumor cell proliferation and induces apoptosis by targeting Forkhead box O in A549 cells

The imbalance between cell proliferation and apoptosis was implicated to serve key roles in cancer pathogenesis. The characteristics of microRNAs (miRNAs/miRs) have attracted much attention in research focusing on cancer pathogenesis in recent years. miR-122-3p has been reported to be associated with a number of disease processes and pathogenesis, including lung cancer. The present study aimed to investigate the association of miR-122-3p expression level with cell proliferation and apoptosis in a lung cancer cell line. A549 cells were transfected with miR-122-3p to interrupt the expression of miR-122-3p. Subsequently, MTT and BrdU assay, and western blot were used to analyze the influence of miR-122-3p on lung cancer cell proliferation, cell viability and its underlying mechanism. The present study revealed that, by targeting p27, overexpression of miR-122-3p inhibited cell proliferation in lung cancer. Furthermore, the cell apoptosis analysis suggested that overexpression of miR-122-3p was able to inhibit cell apoptosis by targeting Forkhead box O. These findings suggest that miR-122-3p may be associated with the pathology and progression of lung cancer and be a new therapeutic target for this disease.

Essential and Toxic Metals in Oral Fluid-a Potential Role in the Diagnosis of Periodontal Diseases

Recently, many studies have investigated the relationship between the level of metals in the body and various diseases. The objective of this study was to examine any possible influence of periodontal disease upon the concentration of metals in oral fluid and blood and to explore the usability of applying cluster analysis coupled with the analysis of selected elements in oral fluid, calcium (Ca), copper (Cu), iron (Fe), magnesium (Mg), manganese (Mn), zinc (Zn), cadmium (Cd) and lead (Pb), for effectively distinguishing people affected by periodontitis from healthy individuals. The quantification of eight metals in oral fluid and blood samples was performed by two inductively coupled plasma techniques-inductively coupled plasma mass spectrometry (ICP-MS) and inductively coupled plasma optical emission spectrometry (ICP-OES). Most of the examined elements were detected at elevated concentration in the oral fluid of periodontal patients. However, the differences were statistically significant in the case of three metals: Cu, Mg and Mn (p < 0.05). Approximately, fivefold increase in the concentration of Cu, threefold-elevated levels of Mn and a twofold increase in the concentration of Mg were found in the oral fluid of the periodontal patients compared to the controls. Cluster analysis confirmed the statistical significance of the differences in the level of metals in the oral fluid between the two groups in most cases, plus enabled the correct classification of the subjects into patients and controls. The relationship between concentrations of metals and periodontal disease may in the future serve to prevent the development of such disease.

Accuracy of volatile urine biomarkers for the detection and characterization of lung cancer

Background

The mixture of volatile organic compounds in the headspace gas of urine may be able to distinguish lung cancer patients from relevant control populations.

Methods

Subjects with biopsy confirmed untreated lung cancer, and others at risk for developing lung cancer, provided a urine sample. A colorimetric sensor array was exposed to the headspace gas of neat and pre-treated urine samples. Random forest models were trained from the sensor output of 70 % of the study subjects and were tested against the remaining 30 %. Models were developed to separate cancer and cancer subgroups from control, and to characterize the cancer. An additional model was developed on the largest clinical subgroup.

Results

90 subjects with lung cancer and 55 control subjects participated. The accuracies, reported as C-statistics, for models of cancer or cancer subgroups vs. control ranged from 0.795 – 0.917. A model of lung cancer vs. control built using only subjects from the largest available clinical subgroup (30 subjects) had a C-statistic of 0.970. Models developed and tested to characterize cancer histology, and to compare early to late stage cancer, had C-statistics of 0.849 and 0.922 respectively.

Conclusions

The colorimetric sensor array signature of volatile organic compounds in the urine headspace may be capable of distinguishing lung cancer patients from clinically relevant controls. The incorporation of clinical phenotypes into the development of this biomarker may optimize its accuracy.

Classification models based on the level of metals in hair and nails of laryngeal cancer patients: diagnosis support or rather speculation?

Several larynx cancer prediction models were built and each was weighted according to their performance.