Proteomics as a method for early detection of cancer: a review of proteomics, exhaled breath condensate, and lung cancer screening

Innovative laboratory techniques shaping cancer diagnosis and treatment in developing countries

Cancer is a major global health challenge, with approximately 19.3 million new cases and 10 million deaths estimated by 2020. Laboratory advancements in cancer detection have transformed diagnostic capabilities, particularly through the use of biomarkers that play crucial roles in risk assessment, therapy selection, and disease monitoring. Tumor histology, single-cell technology, flow cytometry, molecular imaging, liquid biopsy, immunoassays, and molecular diagnostics have emerged as pivotal tools for cancer detection. The integration of artificial intelligence, particularly deep learning and convolutional neural networks, has enhanced the diagnostic accuracy and data analysis capabilities. However, developing countries face significant challenges including financial constraints, inadequate healthcare infrastructure, and limited access to advanced diagnostic technologies. The impact of COVID-19 has further complicated cancer management in resource-limited settings. Future research should focus on precision medicine and early cancer diagnosis through sophisticated laboratory techniques to improve prognosis and health outcomes. This review examines the evolving landscape of cancer detection, focusing on laboratory research breakthroughs and limitations in developing countries, while providing recommendations for advancing tumor diagnostics in resource-constrained environments.

Proteomics: An In-Depth Review on Recent Technical Advances and Their Applications in Biomedicine

Proteins hold pivotal importance since many diseases manifest changes in protein activity. Proteomics techniques provide a comprehensive exploration of protein structure, abundance, and function in biological samples, enabling the holistic characterization of overall changes in organisms. Nowadays, the breadth of emerging methodologies in proteomics is unprecedentedly vast, with constant optimization of technologies in sample processing, data collection, data analysis, and its scope of application is steadily transitioning from the bench to the clinic. Here, we offer an insightful review of the technical developments in proteomics and its applications in biomedicine over the past 5 years. We focus on its profound contributions in profiling disease spectra, discovering new biomarkers, identifying promising drug targets, deciphering alterations in protein conformation, and unearthing protein-protein interactions. Moreover, we summarize the cutting-edge technologies and potential breakthroughs in the proteomics pipeline and provide the principal challenges in proteomics. Based on these, we aspire to broaden the applicability of proteomics and inspire researchers to enhance our understanding of complex biological systems by utilizing such techniques.

Unveiling Tumorigenesis Mechanisms and Drug Therapy in Neuroblastoma by Mass Spectrometry Based Proteomics

Neuroblastoma (NB) is the most common type of extracranial solid tumors in children. Despite the advancements in treatment strategies over the past years, the overall survival rate in patients within the high-risk NB group remains less than 50%. Therefore, new treatment options are urgently needed for this group of patients. Compared with genomic aberrations, proteomic alterations are more dynamic and complex, as well as more directly related to pathological phenotypes and external perturbations such as environmental changes and drug treatments. This review focuses on specific examples of proteomics application in various fundamental aspects of NB research, including tumorigenesis, drug treatment, drug resistance, and highlights potential protein signatures and related signaling pathways with translational values for clinical practice. Moreover, emerging cutting-edge proteomic techniques, such as single cell and spatial proteomics, as well as mass spectrometry imaging, are discussed for their potentials to probe intratumor heterogeneity of NB.

Current Evidence for a Lung Cancer Screening Program

Background

Lung cancer screening is still in an early phase compared to other cancer screening programs, despite its high lethality particularly when diagnosed late. Achieving early diagnosis is crucial to obtain optimal outcomes.

Summary

In this review, we will address the current evidence on lung cancer screening through low-dose computed tomography (LDCT) and its impact on mortality reduction, existing screening recommendations, patient eligibility criteria, screening frequency and duration, benefits and harms, cost-effectiveness and some insights on lung cancer screening implementation and adoption. Additionally, new non-imaging, noninvasive biomarkers with high diagnostic potential are also briefly highlighted.

Key Messages

LDCT screening in a prespecified population based on age and smoking history proved to reduce lung cancer mortality. Optimization of the target population and management of LDCT pitfalls can further improve lung cancer screening efficiency and cost-effectiveness. Novel screening technologies and biomarkers being studied can potentially be game-changers in lung cancer screening and diagnosis.

Exosomal Proteomics: Unveiling Novel Insights into Lung Cancer

Although significant progress has been made in early lung cancer screening over the past decade, it remains one of the most prevalent and deadliest forms of cancer worldwide. Exosomal proteomics has emerged as a transformative field in lung cancer research, with the potential to redefine diagnostics, prognostic assessments, and therapeutic strategies through the lens of precision medicine. This review discusses recent advances in exosome-related proteomic and glycoproteomic technologies, highlighting their potential to revolutionise lung cancer treatment by addressing issues of heterogeneity, integrating multiomics data, and utilising advanced analytical methods. While these technologies show promise, there are obstacles to overcome before they can be widely implemented, such as the need for standardization, gaps in clinical application, and the importance of dynamic monitoring. Future directions should aim to overcome the challenges to fully utilize the potential of exosomal proteomics in lung cancer. This promises a new era of personalized medicine that leverages the molecular complexity of exosomes for groundbreaking advancements in detection, prognosis, and treatment.

The role of volatile organic compounds for assessing characteristics and severity of non-cystic fibrosis bronchiectasis: an observational study

Background

Hypoxic conditions and Pseudomonas aeruginosa (P. aeruginosa) infection are significant factors influencing the prognosis and treatment of patients with bronchiectasis. This study aimed to explore the potential for breath analysis to detect hypoxic conditions and P. aeruginosa infection in bronchiectasis patients by analyzing of volatile organic compounds (VOCs) in exhaled breath condensate (EBC).

Methods

EBC samples were collected from stable bronchiectasis patients and analyzed using solid phase microextraction-gas chromatography-mass spectrometry (SPME-GCMS). The association of VOCs with bronchiectasis patients' phenotypes including hypoxic conditions and P. aeruginosa isolation was analyzed, which may relate to the severity of bronchiectasis disease.

Results

Levels of 10-heptadecenoic acid, heptadecanoic acid, longifolene, and decanol in the hypoxia group were higher compared to the normoxia group. Additionally, the levels of 13-octadecenoic acid, octadecenoic acid, phenol, pentadecanoic acid, and myristic acid were increased in P. aeruginosa (+) group compared to the P. aeruginosa (-) group. Subgroup analysis based on the bronchiectasis severity index (BSI)reveled that the levels of 10-heptadecenoic acid, heptadecanoic acid, decanol, 13-octadecenoic acid, myristic acid, and pentadecanoic acid were higher in the severe group compared to the moderate group. Multivariate linear regression showed that 10-heptadecenoic acid and age were independent prognostic factors for bronchiectasis patients with hypoxia. Furthermore, octadecenoic acid, phenol and gender were identified as independent prognostic factors for bronchiectasis patients with P. aeruginosa isolation.

Conclusion

The study provides evidence that specific VOCs in EBC are correlated with the severity of bronchiectasis, and 10-heptadecenoic acid is shown to be a predictive marker for hypoxia condition in bronchiectasis patients.

A Review on CNTs-Based Electrochemical Sensors and Biosensors: Unique Properties and Potential Applications

Carbon nanotubes (CNTs), are safe, biocompatible, bioactive, and biodegradable materials, and have sparked a lot of attention due to their unique characteristics in a variety of applications, including medical and dye industries, paper manufacturing and water purification. CNTs also have a strong film-forming potential, permitting them to be widely employed in constructing sensors and biosensors. This review concentrates on the application of CNT-based nanocomposites in the production of electrochemical sensors and biosensors. It emphasizes the synthesis and optimization of CNT-based sensors for a range of applications and outlines the benefits of using CNTs for biomolecule immobilization. In addition, the use of molecularly imprinted polymer (MIP)-CNTs in the production of electrochemical sensors is also discussed. The challenges faced by the current CNTs-based sensors, along with some the future perspectives and their future opportunities, are also briefly explained in this paper.

Advances in the application of proteomics in lung cancer

Although the incidence and mortality of lung cancer have decreased significantly in the past decade, it is still one of the leading causes of death, which greatly impairs people's life and health. Proteomics is an emerging technology that involves the application of techniques for identifying and quantifying the overall proteins in cells, tissues and organisms, and can be combined with genomics, transcriptomics to form a multi-omics research model. By comparing the content of proteins between normal and tumor tissues, proteomics can be applied to different clinical aspects like diagnosis, treatment, and prognosis, especially the exploration of disease biomarkers and therapeutic targets. The applications of proteomics have promoted the research on lung cancer. To figure out potential applications of proteomics associated with lung cancer, we summarized the role of proteomics in studies about tumorigenesis, diagnosis, prognosis, treatment and resistance of lung cancer in this review, which will provide guidance for more rational application of proteomics and potential therapeutic strategies of lung cancer.

Supplementation of Rumen-Protected Glucose Increased the Risk of Disturbance of Hepatic Metabolism in Early Postpartum Holstein Cows

The dual stress of reduced feed intake and increased milk yield in dairy cows early postpartum results in a negative energy balance. Rumen-protected glucose (RPG) has been reported to replenish energy, increase milk yield, and improve gut health. However, early postpartum cows often develop an insulin resistance, implying that RPG may not be well utilized and increased milk production may increase the liver's fat oxidization burden. This study aimed to investigate the effects of RPG on the hepatic oxidative/antioxidative status and protein profile. Starting 7 d before expected calving, six pairs of cows were supplemented with rumen-protected glucose (RPG, n = 6) or with an equal amount of rumen-protecting coating fat (CON, n = 6). Liver samples were obtained from 10 cows 14 d after calving (d 14). Concentration of malondialdehyde and activity of glutathione peroxidase were increased and the activities of catalase and superoxide dismutase tended to increase in the livers of the RPG cows compared to the CON cows. The revised quantitative insulin sensitivity check index (RQUICKI) was decreased by RPG, but triacylglycerol concentration in liver was increased by RPG supplementation. The overall profiles of hepatic proteins were similar between CON and RPG. A partial least square regression was conducted to identify the proteins associated with liver lipidosis, oxidative stress, and antioxidative capacity. The top twenty proteins, according to their variable importance value, were selected for metabolic pathway enrichment analysis. Eighteen enriched KEGG pathways were identified, including metabolism, the citrate cycle, propanoate metabolism, the peroxisome, and type II diabetes mellitus. Our study showed that RPG supplementation reduced insulin sensitivity but increased the liver triglyceride concentration and the oxidative stress in early postpartum cows. Liver proteins related to lipidosis, oxidative stress, and antioxidative capacity, were positively associated with the glutamine metabolism, citric acid cycle, peroxisome, and type II diabetes pathways, which may indicate an increased risk of liver metabolic disorders caused by RPG supplementation in early postpartum cows.

Multiplexing surface anchored functionalized iron carbide nanoparticle: A low molecular weight proteome responsive nano-tracer

Harvesting the low molecular weight (LMW) proteins from the cellular exudates is a big challenge for early disease detection. Here, we introduce a unique probe composed of surface-functionalized Fe₂C NPs with different functional groups to harvest, identify and profile differentially expressed biomarker proteins. Three different functionalization of Fe₂C NPs with Fe₂C@NH_2, Fe₂C@COOH and Fe₂C@PEG enabled to harvest 119 differentially expressed proteins from HeLa cell exudates. Among these proteins, 57 were LMW which 82.46 % were up-regulated and 17.54 % were down-regulated. The Fe₂C@NH₂ were able to separate 60S ribosomal proteins L7a, and L11, and leucine-rich repeat-containing protein 59. These proteins play a vital role in the maturation of large subunit ribosomal ribonucleic acid, mRNA splicing via spliceosome and cancer cell inhibitor, respectively. While, Fe₂C@COOH identifies the 60S ribosomal protein types L7, 40S ribosomal protein S11, and 60S ribosomal protein L24. These proteins were important for large ribosomal subunit biogenesis, translational initiation, and assembly of large subunit precursor of pre-ribosome. Finally, the Fe₂C@PEG extracted 40S ribosomal protein S2, splicing factor, arginine/serine-rich and 40S ribosomal protein S4, X isoform which were responsible for nonsense-mediated decay, oligodendrocyte differentiation and multicellular organism development. Thus, these results help us in defining oncogenic biomarkers for early disease detection.

Exhaled breath analysis in disease detection

Investigating the use of exhaled breath analysis to diagnose and monitor different diseases has attracted much interest in recent years. This review introduces conventionally used methods and some emerging technologies aimed at breath analysis and their relevance to lung disease, airway inflammation, gastrointestinal disorders, metabolic disorders and kidney diseases. One section correlates breath components and specific diseases, whereas the other discusses some unique ideas, strategies, and devices to analyze exhaled breath for the diagnosis of some common diseases. This review aims to briefly introduce the potential application of exhaled breath analysis for the diagnosis and screening of various diseases, thereby providing a new avenue for the detection of non-invasive diseases.

Metabolomics of Exhaled Breath Condensate by Nuclear Magnetic Resonance Spectroscopy and Mass Spectrometry: A Methodological Approach

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Respiratory diseases present a very high prevalence in the general population, with an increase in morbidity, mortality and health-care expenses worldwide. They are complex and heterogeneous pathologies that may present different pathological facets in different subjects, often with personal evolution. Therefore, there is a need to identify patients with similar characteristics, prognosis or treatment, defining the so-called phenotype, but also to mark specific differences within each phenotype, defining the endotypes.

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Biomarkers are very useful to study respiratory phenotypes and endotypes. Metabolomics, one of the recently introduced “omics”, is becoming a leading technique for biomarker discovery. For the airways, metabolomics appears to be well suited as the respiratory tract offers a natural matrix, the Exhaled Breath Condensate (EBC), in which several biomarkers can be measured. In this review, we will discuss the main methodological issues related to the application of Nuclear Magnetic Resonance (NMR) spectroscopy and Mass Spectrometry (MS) to EBC metabolomics for investigating respiratory diseases.

Histopathology-guided mass spectrometry differentiates benign nevi from malignant melanoma

PURPOSE

Distinguishing benign nevi from malignant melanoma using current histopathological criteria may be very challenging and is one the most difficult areas in dermatopathology. The goal of this study was to identify proteomic differences, which would more reliably differentiate between benign and malignant melanocytic lesions.

METHODS

We performed histolpathology - guided mass spectrometry (HGMS) profiling analysis on formalin-fixed, paraffin embedded tissue samples to identify differences at the proteomic level between different types of benign nevi and melanomas. A total of 756 cases, of which 357 cases of melanoma and 399 benign nevi, were included in the study. The specimens originated from both biopsies (376 samples) and tissue microarray (TMA) cores (380 samples). After obtaining mass spectra from each sample, classification models were built using a training set of biopsy specimens from 111 nevi and 100 melanomas. The classification algorithm developed on the training data set was validated on an independent set of 288 nevi and 257 melanomas from both biopsies and TMA cores.

RESULTS

In the melanoma cohort, 239/257 (93%) cases classified correctly in the validation set, 3/257 (1.2%) classified incorrectly, and 15/257 (5.8%) classified as indeterminate. In the cohort of nevi, 282/288 (98%) cases classified correctly, 1/288 (0.3%) classified incorrectly, and 5/288 (1.7%) were indeterminate. HGMS showed a sensitivity of 98.76% and specificity of 99.65% in determining benign vs malignant.

CONCLUSION

HGMS proteomic analysis is an objective and reliable test with minimal tissue requirements, which can be a helpful ancillary test in the diagnosis of challenging melanocytic lesions.

Mass Spectrometry Analysis of the Exhaled Breath Condensate and Proposal of Dermcidin and S100A9 as Possible Markers for Lung Cancer Prognosis

INTRODUCTION

New sampling techniques to analyse lung diseases, such as exhaled breath condensate (EBC), are a breakthrough in research field since they are less invasive and less traumatic for the patients compared to lung biopsies. Nevertheless, there is an increasing need to optimize not only the sampling protocols but the storage and processing of specimens to get accurate results.

METHODS

Exhaled breath condensate was sampled employing the ECoScreen device. Concentrated protein was obtained after ultracentrifugation, lyophilization and reversed-phase chromatography. MALDI-time of flight (TOF)/TOF mass spectrometry (MS) was applied to determine the protein profile in EBC. Commercially available ELISA kits were used to detect the selected biomarker in the EBC after MALDI-MS proteins identification.

RESULTS

The obtained EBC volume after two periods of 10 min doubled the amount obtained after 20 min. One hundred peptides were detected by MALDI-MS, and 18 proteins were identified after reversed-phase chromatography concentration. Dermcidin (P81605), S100A9 (P06702) and Cathepsin G (P08311) were selected to be analysed by ELISA. Dermcidin and S100A9 expression were statistically higher in lung cancer versus healthy volunteers. VEGF concentrations decreased, respectively, by 5.94 and 11.42-fold after 1 and 2 years of frozen EBC preservation in parallel with the declined number of proteins identified by MALDI-MS.

CONCLUSION

Exhaled breath condensate analysis combined with MS technique may become a valuable method for lung cancer screening and Dermcidin and S100A9 may serve as biomarkers for lung cancer diagnosis or prognosis.

Production and Characterization of Monoclonal and Polyclonal Antibodies Against Truncated Recombinant Dickkopf-1 as a Candidate Biomarker

Several studies have reported an increased serum level of Dickkopf (DKK-1) protein in a variety of cancers, including multiple myeloma, lung, colorectal, bone loss, and Alzheimer's disease. This protein has potential to be used as a biomarker for the diagnosis of some cancers, especially bone loss in multiple myeloma. In the present study, to measure the concentration level of DKK-1 protein, rabbit polyclonal antibody (pAb) and mouse monoclonal antibodies (mAbs) were produced against this protein. New Zealand white rabbits and BALB/c mice were immunized with the chimeric recombinant DKK-1 antigen. Immunized mouse spleen cells were fused with SP2/0 cells to generate anti-rDKK-1 antibody-producing hybridoma cells. Antibodies were purified by protein A affinity chromatography and assessed using sodium dodecyl sulfate polyacrylamide gel, western blotting and enzyme-linked immunosorbent assay. These results implied that the pAb and mAb were produced against the DKK-1 protein. The Kd value of 5 × 10^-9 M was recorded for the mAb MR6F3 toward native DKK-1, and the Ig isotype was identified as IgG2b. No cross-reactivity was shown with DKK-2 by MR6F3. Collectively, our results revealed that the produced pAb and mAb could be used in the measurement of DKK-1 protein.

Analysis of Cytokine Pattern in Exhaled Breath Condensate of Patients with Squamous Cell Lung Carcinoma

Exhaled breath condensate (EBC) analysis is a promising method for investigating airway pathology. In this study we compared the cytokine pattern of EBC of patients suffering from squamous cell lung carcinoma with that of healthy smokers. Breath condensates collected from 8 smoking lung cancer patients before receiving any anticancer treatment and 8 smokers without any clinical or radiological evidence of pulmonary tumors were used for antibody microarray analysis testing 120 cytokines simultaneously. Ninety-eight cytokines on the array gave a detectable signal in both groups. Cytokine levels were similar across the samples, and none of the cytokines exhibited a significant increase or decrease in cancer patients as compared to healthy subjects with similar smoking status, lung function, and airway inflammation. The results of this pilot study suggest that patients with squamous cell lung carcinoma cannot be distinguished from smokers with no pulmonary tumors based on EBC cytokine signals only.

Electret filter collects more exhaled albumin than glass condenser: A method comparison based on human study

In recent years, noninvasive diagnosis based on biomarkers in exhaled breath has been extensively studied. The procedure of biomarker collection is a key step. However, the traditional condenser method has low efficacy in collecting nonvolatile compounds especially the protein biomarkers in breath. To solve this deficiency, here we propose an electret filter method.Exhaled breath of 6 volunteers was collected with a glass condenser and an electret filter. The amount of albumin was analyzed. Furthermore, the difference of exhaled albumin between smokers and nonsmokers was evaluated.The electret filter method collected more albumin than the glass condenser method at the same breath volume level (P < .01). Smokers exhaling more albumin than nonsmokers were also observed (P < .01).The electret filter is capable of collecting proteins more effectively than the condenser method. In addition, smokers tend to exhale more albumin than nonsmokers.

Exhaled breath condensate biomarkers for the early diagnosis of lung cancer using proteomics

We explored whether the proteomic analysis of exhaled breath condensate (EBC) may provide biomarkers for noninvasive screening for the early detection of lung cancer (LC). EBC was collected from 192 individuals [49 control (C), 49 risk factor-smoking (S), 46 chronic obstructive pulmonary disease (COPD) and 48 LC]. With the use of liquid chromatography and tandem mass spectrometry, 348 different proteins with a different pattern among the four groups were identified in EBC samples. Significantly more proteins were identified in the EBC from LC compared with other groups (C: 12.4 ± 1.3; S: 15.3 ± 1; COPD: 14 ± 1.6; LC: 24.2 ± 3.6; P = 0.0001). Furthermore, the average number of proteins identified per sample was significantly higher in LC patients, and receiver operating characteristic curve (ROC) analysis showed an area under the curve of 0.8, indicating diagnostic value. Proteins frequently detected in EBC, such as dermcidin and hornerin, along with others much less frequently detected, such as hemoglobin and histones, were identified. Cytokeratins (KRTs) were the most abundant proteins in EBC samples, and levels of KRT6A, KRT6B, and KRT6C isoforms were significantly higher in samples from LC patients ( P = 0.0031, 0.0011, and 0.0009, respectively). Moreover, the amount of most KRTs in EBC samples from LC patients showed a significant positive correlation with tumor size. Finally, we used a random forest algorithm to generate a robust model using EBC protein data for the diagnosis of patients with LC where the area under the ROC curve obtained indicated a good classification (82%). Thus this study demonstrates that the proteomic analysis of EBC samples is an appropriated approach to develop biomarkers for the diagnosis of lung cancer.

Imaging mass spectrometry assists in the classification of diagnostically challenging atypical Spitzoid neoplasms

BACKGROUND

Previously, using imaging mass spectrometry (IMS), we discovered proteomic differences between Spitz nevi and Spitzoid melanomas.

OBJECTIVE

We sought to determine whether IMS can assist in the classification of diagnostically challenging atypical Spitzoid neoplasms (ASN), to compare and correlate the IMS and histopathological diagnoses with clinical behavior.

METHODS

We conducted a retrospective collaborative study involving centers from 11 countries and 11 US institutions analyzing 102 ASNs by IMS. Patients were divided into clinical groups 1 to 4 representing best to worst clinical behavior. The association among IMS findings, histopathological diagnoses, and clinical groups was assessed.

RESULTS

There was a strong association between a diagnosis of Spitzoid melanoma by IMS and lesions categorized as clinical groups 2, 3, and 4 (recurrence of disease, metastases, or death) compared with clinical group 1 (no recurrence or metastasis beyond a sentinel node) (P < .0001). Older age and greater tumor thickness were strongly associated with poorer outcome (P = .01).

CONCLUSIONS

IMS diagnosis of ASN better predicted clinical outcome than histopathology. Diagnosis of Spitzoid melanoma by IMS was strongly associated with aggressive clinical behavior. IMS analysis using a proteomic signature may improve the diagnosis and prediction of outcome/risk stratification for patients with ASN.

Exhaled breath condensate for lung cancer protein analysis: a review of methods and biomarkers

Lung cancer is a leading cause of cancer-related deaths worldwide, and is considered one of the most aggressive human cancers, with a 5 year overall survival of 10-15%. Early diagnosis of lung cancer is ideal; however, it is still uncertain as to what technique will prove successful in the systematic screening of high-risk populations, with the strongest evidence currently supporting low dose computed tomography (LDCT). Analysis of exhaled breath condensate (EBC) has recently been proposed as an alternative low risk and non-invasive screening method to investigate early-stage neoplastic processes in the airways. However, there still remains a relative paucity of lung cancer research involving EBC, particularly in the measurement of lung proteins that are centrally linked to pathogenesis. Considering the ease and safety associated with EBC collection, and advances in the area of mass spectrometry based profiling, this technology has potential for use in screening for the early diagnosis of lung cancer. This review will examine proteomics as a method of detecting markers of neoplasia in patient EBC with a particular emphasis on LC, as well as discussing methodological challenges involving in proteomic analysis of EBC specimens.

Blood, sweat, and tears: developing clinically relevant protein biosensors for integrated body fluid analysis

Biosensors are being developed to provide rapid, quantitative, diagnostic information to clinicians in order to help guide patient treatment, without the need for centralised laboratory assays. The success of glucose monitoring is a key example of where technology innovation has met a clinical need at multiple levels – from the pathology laboratory all the way to the patient's home. However, few other biosensor devices are currently in routine use. Here we review the challenges and opportunities regarding the integration of biosensor techniques into body fluid sampling approaches, with emphasis on the point-of-care setting.

Proteomics in gastric cancer research: Benefits and challenges

Among various cancers, gastric cancer (GC) exhibits relatively high morbidity and mortality rate worldwide. The lack of effective methods in early detection and diagnosis, and immediate therapies makes treating such disease a challenge for both clinicians and oncologists. Proteomics has emerged as a promising technology platform for rationally identifying biomarkers and novel therapeutic targets for GC, as well as discovering underlying mechanisms of carcinogenesis. Its application has greatly benefited mechanistic studies of this disease. This review will demonstrate the applications of proteomic technology in GC research. The advantages and shortcomings of this technology, as reflected by current studies, will also be discussed to improve and expand its application in the field of cancer research.

Canine olfaction and electronic nose detection of volatile organic compounds in the detection of cancer: a review

Olfactory cancer detection shows promise as an affordable, precise, and noninvasive way to screen for cancer. This review focuses on two methods of olfactory cancer detection: first, the ability of canines to differentiate between cancerous and healthy individuals through the use of biological samples and second, electronic nose technology that uses chemical sensors to detect known biomarkers in exhaled breath. This review summarizes and critiques past research and outlines future directions to improve understanding of both canine olfaction and electronic nose technology.

Construction of a High-Quality Yeast Two-Hybrid Library and Its Application in Identification of Interacting Proteins with Brn1 in Curvularia lunata

Curvularia lunata is an important maize foliar fungal pathogen that distributes widely in maize growing area in China, and several key pathogenic factors have been isolated. An yeast two-hybrid (Y2H) library is a very useful platform to further unravel novel pathogenic factors in C. lunata. To construct a high-quality full length-expression cDNA library from the C. lunata for application to pathogenesis-related protein-protein interaction screening, total RNA was extracted. The SMART (Switching Mechanism At 5' end of the RNA Transcript) technique was used for cDNA synthesis. Double-stranded cDNA was ligated into the pGADT7-Rec vector with Herring Testes Carrier DNA using homologous recombination method. The ligation mixture was transformed into competent yeast AH109 cells to construct the primary cDNA library. Eventually, a high qualitative library was successfully established according to an evaluation on quality. The transformation efficiency was about 6.39 ×10(5) transformants/3 μg pGADT7-Rec. The titer of the primary cDNA library was 2.5×10(8) cfu/mL. The numbers for the cDNA library was 2.46×10(5). Randomly picked clones show that the recombination rate was 88.24%. Gel electrophoresis results indicated that the fragments ranged from 0.4 kb to 3.0 kb. Melanin synthesis protein Brn1 (1,3,8-hydroxynaphthalene reductase) was used as a "bait" to test the sufficiency of the Y2H library. As a result, a cDNA clone encoding VelB protein that was known to be involved in the regulation of diverse cellular processes, including control of secondary metabolism containing melanin and toxin production in many filamentous fungi was identified. Further study on the exact role of the VelB gene is underway.

Mass spectrometry-based methods for identifying oxidized proteins in disease: advances and challenges

Many inflammatory diseases have an oxidative aetiology, which leads to oxidative damage to biomolecules, including proteins. It is now increasingly recognized that oxidative post-translational modifications (oxPTMs) of proteins affect cell signalling and behaviour, and can contribute to pathology. Moreover, oxidized proteins have potential as biomarkers for inflammatory diseases. Although many assays for generic protein oxidation and breakdown products of protein oxidation are available, only advanced tandem mass spectrometry approaches have the power to localize specific oxPTMs in identified proteins. While much work has been carried out using untargeted or discovery mass spectrometry approaches, identification of oxPTMs in disease has benefitted from the development of sophisticated targeted or semi-targeted scanning routines, combined with chemical labeling and enrichment approaches. Nevertheless, many potential pitfalls exist which can result in incorrect identifications. This review explains the limitations, advantages and challenges of all of these approaches to detecting oxidatively modified proteins, and provides an update on recent literature in which they have been used to detect and quantify protein oxidation in disease.

Mass spectrometry-based proteomics in Chest Medicine, Gerontology, and Nephrology: subgroups omics for personalized medicine

Mass spectrometry (MS) is currently the most promising tool for studying proteomics to investigate largescale proteins in a specific proteome. Emerging MS-based proteomics is widely applied to decipher complex proteome for discovering potential biomarkers. Given its growing usage in clinical medicine for biomarker discovery to predict, diagnose and confer prognosis, MS-based proteomics can benefit study of personalized medicine. In this review we introduce some fundamental MS theory and MS-based quantitative proteomic approaches as well as several representative clinical MS-based proteomics issues in Chest Medicine, Gerontology, and Nephrology.

Breath sensors for lung cancer diagnosis

The scope of the applications of breath sensors is abundant in disease diagnosis. Lung cancer diagnosis is a well-fitting health-related application of this technology, which is of utmost importance in the health sector, because lung cancer has the highest death rate among all cancer types, and it brings a high yearly global burden. The aim of this review is first to provide a rational basis for the development of breath sensors for lung cancer diagnostics from a historical perspective, which will facilitate the transfer of the idea into the rapidly evolving sensors field. Following examples with diagnostic applications include colorimetric, composite, carbon nanotube, gold nanoparticle-based, and surface acoustic wave sensor arrays. These select sensor applications are widened by the state-of-the-art developments in the sensors field. Coping with sampling sourced artifacts and cancer staging are among the debated topics, along with the other concerns like proteomics approaches and biomimetic media utilization, feature selection for data classification, and commercialization.

Analysis of volatile compounds in exhaled breath condensate in patients with severe pulmonary arterial hypertension

BACKGROUND

An important challenge to pulmonary arterial hypertension (PAH) diagnosis and treatment is early detection of occult pulmonary vascular pathology. Symptoms are frequently confused with other disease entities that lead to inappropriate interventions and allow for progression to advanced states of disease. There is a significant need to develop new markers for early disease detection and management of PAH.

METHODOLGY AND FINDINGS

Exhaled breath condensate (EBC) samples were compared from 30 age-matched normal healthy individuals and 27 New York Heart Association functional class III and IV idiopathic pulmonary arterial hypertenion (IPAH) patients, a subgroup of PAH. Volatile organic compounds (VOC) in EBC samples were analyzed using gas chromatography/mass spectrometry (GC/MS). Individual peaks in GC profiles were identified in both groups and correlated with pulmonary hemodynamic and clinical endpoints in the IPAH group. Additionally, GC/MS data were analyzed using autoregression followed by partial least squares regression (AR/PLSR) analysis to discriminate between the IPAH and control groups. After correcting for medicaitons, there were 62 unique compounds in the control group, 32 unique compounds in the IPAH group, and 14 in-common compounds between groups. Peak-by-peak analysis of GC profiles of IPAH group EBC samples identified 6 compounds significantly correlated with pulmonary hemodynamic variables important in IPAH diagnosis. AR/PLSR analysis of GC/MS data resulted in a distinct and identifiable metabolic signature for IPAH patients.

CONCLUSIONS

These findings indicate the utility of EBC VOC analysis to discriminate between severe IPAH and a healthy population; additionally, we identified potential novel biomarkers that correlated with IPAH pulmonary hemodynamic variables that may be important in screening for less severe forms IPAH.

Endobiogeny: a global approach to systems biology (part 1 of 2)

Endobiogeny is a global systems approach to human biology that may offer an advancement in clinical medicine based in scientific principles of rigor and experimentation and the humanistic principles of individualization of care and alleviation of suffering with minimization of harm. Endobiogeny is neither a movement away from modern science nor an uncritical embracing of pre-rational methods of inquiry but a synthesis of quantitative and qualitative relationships reflected in a systems-approach to life and based on new mathematical paradigms of pattern recognition.

PROTEINS, PEPTIDES AND AMINO ACIDS AS MARKERS OF BRONCHOPULMONARY DISEASES

The article is a review of current literature on a content of proteins, peptides and amino acids in human exhaled breath. The results of proteomics and metabolomics applying for selective detection of individual proteins, peptides and amino acids are described. The study of exhaled breath condensate and exhaled endogenous particles contained lung proteins are considered. The peculiarities of protein, peptide and amino acid content in exhaled breath at various respiratory diseases are described. It is shown that the detectable substances may be specific markers of individual diseases.

Early lung cancer diagnosis by biosensors

Lung cancer causes an extreme threat to human health, and the mortality rate due to lung cancer has not decreased during the last decade. Prognosis or early diagnosis could help reduce the mortality rate. If microRNA and tumor-associated antigens (TAAs), as well as the corresponding autoantibodies, can be detected prior to clinical diagnosis, such high sensitivity of biosensors makes the early diagnosis and prognosis of cancer realizable. This review provides an overview of tumor-associated biomarker identifying methods and the biosensor technology available today. Laboratorial researches utilizing biosensors for early lung cancer diagnosis will be highlighted.

Integrating genomics and proteomics-oriented biomarkers to comprehend lung cancer

BACKGROUND

Lung cancer is the leading cause of cancer deaths worldwide. Recent years have brought tremendous progress in the development of genomic and proteomic platforms to study lung cancer progression and biomarker identification.

OBJECTIVE

To evaluate and integrate potential innovations of 'omics' (e.g., genomics and proteomics) technologies in dissecting biomarkers for lung cancer.

METHODS

Omics technologies permit simultaneous monitoring of many hundreds or thousands of macro and small molecules, as well as functional monitoring of multiple pivotal cellular pathways. Discussion follows to explore the principal challenges in the development of cancer biomarkers integrating genomics with proteomics data sets with their functional counterparts in conjunction with clinical data.

RESULTS/CONCLUSION

Sets of genes and gene interactions affecting different subsets of cancers can be determined using genomics in lung cancer. Proteomic studies have generated numerous functional data sets of potential diagnostic, prognostic and therapeutic significance in lung cancer. It is likely that omics will take a central place in the understanding, diagnosis, monitoring and treatment of lung cancer. Here the potential benefits and pitfalls of these methodologies are reviewed for the faster discovery of therapeutically valuable biomarkers for lung cancer.

Biomarkers of exposure to metal dust in exhaled breath condensate: methodology optimization

In occupational assessments where workers are exposed to metal dust, the liquid condensate of exhaled breath (EBC) may provide unique indication of pulmonary exposure. The main goal of this study was to demonstrate the quality of EBC to biological monitoring of human exposure. A pilot study was performed in a group of metal dust-exposed workers and a group of nonexposed individuals working in offices. Only metal dust-exposed workers were followed along the working week to determine the best time of collection. Metal analyses were performed with inductively coupled plasma mass spectrometry (ICP-MS). Analytical methodology was tested using an EBC sample pool for several occupationally exposed metals: potassium, chromium, manganese, copper, zinc, strontium, cadmium, antimony, and lead. Metal contents in EBC of exposed workers were higher than controls at the beginning of the shift and remained augmented throughout the working week. The results obtained support the establishment of EBC as an indicator of pulmonary exposure to metals.

The application of quantification techniques in proteomics for biomedical research

The systematic analysis of biological processes requires an understanding of the quantitative expression patterns of proteins, their interacting partners and their subcellular localization. This information was formerly difficult to accrue as the relative quantification of proteins relied on antibody-based methods and other approaches with low throughput. The advent of soft ionization techniques in mass spectrometry plus advances in separation technologies has aligned protein systems biology with messenger RNA, DNA, and microarray technologies to provide data on systems as opposed to singular protein entities. Another aspect of quantitative proteomics that increases its importance for the coming few years is the significant technical developments underway both for high pressure liquid chromatography and mass spectrum devices. Hence, robustness, reproducibility and mass accuracy are still improving with every new generation of instruments. Nonetheless, the methods employed require validation and comparison to design fit for purpose experiments in advanced protein analyses. This review considers the newly developed systematic protein investigation methods and their value from the standpoint that relative or absolute protein quantification is required de rigueur in biomedical research.

Exhaled breath condensate: a promising source for biomarkers of lung disease

Exhaled breath condensate (EBC) has been increasingly studied as a noninvasive research method for sampling the alveolar and airway space and is recognized as a promising source of biomarkers of lung diseases. Substances measured in EBC include oxidative stress and inflammatory mediators, such as arachidonic acid derivatives, reactive oxygen/nitrogen species, reduced and oxidized glutathione, and inflammatory cytokines. Although EBC has great potential as a source of biomarkers in many lung diseases, the low concentrations of compounds within the EBC present challenges in sample collection and analysis. Although EBC is viewed as a noninvasive method for sampling airway lining fluid (ALF), validation is necessary to confirm that EBC truly represents the ALF. Likewise, a dilution factor for the EBC is needed in order to compare across subjects and determine changes in the ALF. The aims of this paper are to address the characteristics of EBC; strategies to standardize EBC sample collection and review available analytical techniques for EBC analysis.

Discovery of biomarkers for osteosarcoma by proteomics approaches

Osteosarcomas are the most common malignant bone tumors, and the identification of useful tumor biomarkers and target proteins is required to predict the clinical outcome of patients and therapeutic response as well as to develop novel therapeutic strategies. Global protein expression studies, namely, proteomic studies, can offer important clues to understanding the tumor biology that cannot be obtained by other approaches. These studies, such as two-dimensional gel electrophoresis and mass spectrometry, have provided protein expression profiles of osteosarcoma that can be used to develop novel diagnostic and therapeutic biomarkers, as well as to understand biology of tumor progression and malignancy. In this paper, a brief description of the methodology will be provided followed by a few examples of the recent proteomic studies that have generated new information regarding osteosarcomas.

Detection of bladder cancer using proteomic profiling of urine sediments

We used protein expression profiles to develop a classification rule for the detection and prognostic assessment of bladder cancer in voided urine samples. Using the Ciphergen PBS II ProteinChip Reader, we analyzed the protein profiles of 18 pairs of samples of bladder tumor and adjacent urothelium tissue, a training set of 85 voided urine samples (32 controls and 53 bladder cancer), and a blinded testing set of 68 voided urine samples (33 controls and 35 bladder cancer). Using t-tests, we identified 473 peaks showing significant differential expression across different categories of paired bladder tumor and adjacent urothelial samples compared to normal urothelium. Then the intensities of those 473 peaks were examined in a training set of voided urine samples. Using this approach, we identified 41 protein peaks that were differentially expressed in both sets of samples. The expression pattern of the 41 protein peaks was used to classify the voided urine samples as malignant or benign. This approach yielded a sensitivity and specificity of 59% and 90%, respectively, on the training set and 80% and 100%, respectively, on the testing set. The proteomic classification rule performed with similar accuracy in low- and high-grade bladder carcinomas. In addition, we used hierarchical clustering with all 473 protein peaks on 65 benign voided urine samples, 88 samples from patients with clinically evident bladder cancer, and 127 samples from patients with a history of bladder cancer to classify the samples into Cluster A or B. The tumors in Cluster B were characterized by clinically aggressive behavior with significantly shorter metastasis-free and disease-specific survival.

Molecular and microscopic analysis of bacteria and viruses in exhaled breath collected using a simple impaction and condensing method

Exhaled breath condensate (EBC) is increasingly being used as a non-invasive method for disease diagnosis and environmental exposure assessment. By using hydrophobic surface, ice, and droplet scavenging, a simple impaction and condensing based collection method is reported here. Human subjects were recruited to exhale toward the device for 1, 2, 3, and 4 min. The exhaled breath quickly formed into tiny droplets on the hydrophobic surface, which were subsequently scavenged into a 10 µL rolling deionized water droplet. The collected EBC was further analyzed using culturing, DNA stain, Scanning Electron Microscope (SEM), polymerase chain reaction (PCR) and colorimetry (VITEK 2) for bacteria and viruses.Experimental data revealed that bacteria and viruses in EBC can be rapidly collected using the method developed here, with an observed efficiency of 100 µL EBC within 1 min. Culturing, DNA stain, SEM, and qPCR methods all detected high bacterial concentrations up to 7000 CFU/m(3) in exhaled breath, including both viable and dead cells of various types. Sphingomonas paucimobilis and Kocuria variants were found dominant in EBC samples using VITEK 2 system. SEM images revealed that most bacteria in exhaled breath are detected in the size range of 0.5-1.0 µm, which is able to enable them to remain airborne for a longer time, thus presenting a risk for airborne transmission of potential diseases. Using qPCR, influenza A H3N2 viruses were also detected in one EBC sample. Different from other devices restricted solely to condensation, the developed method can be easily achieved both by impaction and condensation in a laboratory and could impact current practice of EBC collection. Nonetheless, the reported work is a proof-of-concept demonstration, and its performance in non-invasive disease diagnosis such as bacterimia and virus infections needs to be further validated including effects of its influencing matrix.

Imaging mass spectrometry--a new and promising method to differentiate Spitz nevi from Spitzoid malignant melanomas

BACKGROUND

Differentiating Spitz nevus (SN) from Spitzoid malignant melanoma (SMM) is one the most difficult problems in dermatopathology.

SPECIFIC AIM

To identify differences on proteomic level between SN and SMM.

METHODS

We performed Imaging Mass Spectrometry analysis on formalin-fixed, paraffin-embedded tissue samples to identify differences on proteomic level between SN and SMM. The diagnosis of SN and SMM was based on histopathologic criteria, clinical features, and follow-up data, which confirmed that none of the lesions diagnosed as SN recurred or metastasized. The melanocytic component (tumor) and tumor microenvironment (dermis) from 114 cases of SN and SMM from the Yale Spitzoid Neoplasm Repository were analyzed. After obtaining mass spectra from each sample, classification models were built using a training set of biopsies from 26 SN and 25 SMM separately for tumor and for dermis. The classification algorithms developed on the training data set were validated on another set of 30 samples from SN and 33 from SMM.

RESULTS

We found proteomic differences between the melanocytic components of SN and SMM and identified 5 peptides that were differentially expressed in the 2 groups. From these data, 29 of 30 SN and 26 of 29 SMM were recognized correctly based on tumor analysis in the validation set. This method correctly classified SN with 97% sensitivity and 90% specificity in the validation cohort.

CONCLUSIONS

Imaging Mass Spectrometry analysis can reliably differentiate SN from SMM in formalin-fixed, paraffin-embedded tissue based on proteomic differences.

A classification method based on principal components of SELDI spectra to diagnose of lung adenocarcinoma

Purpose

Lung cancer is the leading cause of cancer death worldwide, but techniques for effective early diagnosis are still lacking. Proteomics technology has been applied extensively to the study of the proteins involved in carcinogenesis. In this paper, a classification method was developed based on principal components of surface-enhanced laser desorption/ionization (SELDI) spectral data. This method was applied to SELDI spectral data from 71 lung adenocarcinoma patients and 24 healthy individuals. Unlike other peak-selection-based methods, this method takes each spectrum as a unity. The aim of this paper was to demonstrate that this unity-based classification method is more robust and powerful as a method of diagnosis than peak-selection-based methods.

Results

The results showed that this classification method, which is based on principal components, has outstanding performance with respect to distinguishing lung adenocarcinoma patients from normal individuals. Through leaving-one-out, 19-fold, 5-fold and 2-fold cross-validation studies, we found that this classification method based on principal components completely outperforms peak-selection-based methods, such as decision tree, classification and regression tree, support vector machine, and linear discriminant analysis.

Conclusions and Clinical Relevance

The classification method based on principal components of SELDI spectral data is a robust and powerful means of diagnosing lung adenocarcinoma. We assert that the high efficiency of this classification method renders it feasible for large-scale clinical use.

PTRF/cavin-1 and MIF proteins are identified as non-small cell lung cancer biomarkers by label-free proteomics

With the completion of the human genome sequence, biomedical sciences have entered in the “omics” era, mainly due to high-throughput genomics techniques and the recent application of mass spectrometry to proteomics analyses. However, there is still a time lag between these technological advances and their application in the clinical setting. Our work is designed to build bridges between high-performance proteomics and clinical routine. Protein extracts were obtained from fresh frozen normal lung and non-small cell lung cancer samples. We applied a phosphopeptide enrichment followed by LC-MS/MS. Subsequent label-free quantification and bioinformatics analyses were performed. We assessed protein patterns on these samples, showing dozens of differential markers between normal and tumor tissue. Gene ontology and interactome analyses identified signaling pathways altered on tumor tissue. We have identified two proteins, PTRF/cavin-1 and MIF, which are differentially expressed between normal lung and non-small cell lung cancer. These potential biomarkers were validated using western blot and immunohistochemistry. The application of discovery-based proteomics analyses in clinical samples allowed us to identify new potential biomarkers and therapeutic targets in non-small cell lung cancer.

Changes in fibrinopeptide A peptides in the sera of rats chronically exposed to low doses of 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD)

2,3,7,8-Tetrachlorodibenzo-p-dioxin (TCDD) is a ubiquitously distributed endocrine disruptors. To investigate peptide changes in the sera of rats chronically exposed to TCDD and to explore the association of these changes with liver morphology, TCDD was administrated to male rats at doses of 140, 350, and 875 ng/kg/week for 29 weeks. Serum was collected and proteomic analysis was performed using automated Bruker Daltonics ClinProt with matrix-assisted laser desorption/ionization time-of-flight mass spectrometer. One peptide at 1740.89 was found to be significantly decreased and further identified with nano LC-MS/MS system. The MS BLAST homology search engine reported the peptide to be a partial sequence of fibrinopeptide A. Liver fatty degeneration and necrosis were assessed by hematoxylin and eosin staining. Liver fatty degeneration and necrosis were both found to be significantly increased after TCDD exposure. Levels of fibrinopeptide A were significantly correlated with liver fatty degeneration and necrosis.

Exhaled endogenous particles contain lung proteins

BACKGROUND

We recently developed a novel, noninvasive method for sampling nonvolatile material from the distal airways. The method is based on the collection of endogenous particles in exhaled air (PEx). The aim of this study was to characterize the protein composition of PEx and to verify that the origin of PEx is respiratory tract lining fluid (RTLF).

METHOD

Healthy individuals exhaled into the sampling device, which collected PEx onto a silicon plate inside a 3-stage impactor. After their extraction from the plates, PEx proteins were separated by SDS-PAGE and then analyzed by LC-MS. Proteins were identified by searching the International Protein Index human database with the Mascot search engine.

RESULTS

Analysis of the pooled samples identified 124 proteins. A comparison of the identified PEx proteins with published bronchoalveolar lavage (BAL) proteomic data showed a high degree of overlap, with 103 (83%) of the PEx proteins having previously been detected in BAL. The relative abundances of the proteins were estimated according to the Mascot exponentially modified protein abundance index protocol and were in agreement with the expected protein composition of RTLF. No amylase was detected, indicating the absence of saliva protein contamination with our sampling technique.

CONCLUSIONS

Our data strongly support that PEx originate from RTLF and reflect the composition of undiluted RTLF.