The Haptoglobin β chain as a supportive biomarker for human lung cancers

Liquid biopsy in cancer current: status, challenges and future prospects

Cancer has a high mortality rate across the globe, and tissue biopsy remains the gold standard for tumor diagnosis due to its high level of laboratory standardization, good consistency of results, relatively stable samples, and high accuracy of results. However, there are still many limitations and drawbacks in the application of tissue biopsy in tumor. The emergence of liquid biopsy provides new ideas for early diagnosis and prognosis of tumor. Compared with tissue biopsy, liquid biopsy has many advantages in the diagnosis and treatment of various types of cancer, including non-invasive, quickly and so on. Currently, the application of liquid biopsy in tumor detection has received widely attention. It is now undergoing rapid progress, and it holds significant potential for future applications. Around now, liquid biopsies encompass several components such as circulating tumor cells, circulating tumor DNA, exosomes, microRNA, circulating RNA, tumor platelets, and tumor endothelial cells. In addition, advances in the identification of liquid biopsy indicators have significantly enhanced the possibility of utilizing liquid biopsies in clinical settings. In this review, we will discuss the application, advantages and challenges of liquid biopsy in some common tumors from the perspective of diverse systems of tumors, and look forward to its future development prospects in the field of cancer diagnosis and treatment.

Assessment of hypoxia and oxidative-related changes in a lung-derived brain metastasis model by [64Cu][Cu(ATSM)] PET and proteomic studies

BACKGROUND

Brain metastases (BM) are the most frequent malignant brain tumors. The aim of this study was to characterize the tumor microenvironment (TME) of BM and particularly hypoxia and redox state, known to play a role in tumor growth and treatment resistance with multimodal PET and MRI imaging, immunohistochemical and proteomic approaches in a human lung cancer (H2030-BrM3)-derived BM model in rats.

RESULTS

First, in vitro studies confirmed that H2030-BrM3 cells respond to hypoxia with increasing expression of HIF-1, HIF-2 and their target genes. Proteomic analyses revealed, among expression changes, proteins associated with metabolism, oxidative stress, metal response and hypoxia signaling in particular in cortical BM. [64Cu][Cu(ATSM)] PET revealed a significant uptake by cortical BM (p < 0.01), while no uptake is observed in striatal BM 23 days after tumor implantation. Pimonidazole, HIF-1α, HIF-2α, CA-IX as well as GFAP, CTR1 and DMT1 immunostainings are positive in both BM.

CONCLUSION

Overall, [64Cu][Cu(ATSM)] imaging and proteomic results showed the presence of hypoxia and protein expression changes linked to hypoxia and oxidative stress in BM, which are more pronounced in cortical BM compared to striatal BM. Moreover, it emphasized the interest of [64Cu][Cu(ATSM)] PET to characterize TME of BM and depict inter-metastasis heterogeneity that could be useful to guide treatments.

Proteomic Profiling of Small-Cell Lung Cancer: A Systematic Review

The accurate diagnosis of small-cell lung cancer (SCLC) is crucial, as treatment strategies differ from those of other lung cancers. This systematic review aims to identify proteins differentially expressed in SCLC compared to normal lung tissue, evaluating their potential utility in diagnosing and prognosing the disease. Additionally, the study identifies proteins differentially expressed between SCLC and large cell neuroendocrine carcinoma (LCNEC), aiming to discover biomarkers distinguishing between these two subtypes of neuroendocrine lung cancers. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, a comprehensive search was conducted across PubMed/MEDLINE, Scopus, Embase, and Web of Science databases. Studies reporting proteomics information and confirming SCLC and/or LCNEC through histopathological and/or cytopathological examination were included, while review articles, non-original articles, and studies based on animal samples or cell lines were excluded. The initial search yielded 1705 articles, and after deduplication and screening, 16 articles were deemed eligible. These studies revealed 117 unique proteins significantly differentially expressed in SCLC compared to normal lung tissue, along with 37 unique proteins differentially expressed between SCLC and LCNEC. In conclusion, this review highlights the potential of proteomics technology in identifying novel biomarkers for diagnosing SCLC, predicting its prognosis, and distinguishing it from LCNEC.

Liquid Biopsy for Lung Cancer: Up-to-Date and Perspectives for Screening Programs

Lung cancer is the deadliest cancer worldwide. Tissue biopsy is currently employed for the diagnosis and molecular stratification of lung cancer. Liquid biopsy is a minimally invasive approach to determine biomarkers from body fluids, such as blood, urine, sputum, and saliva. Tumor cells release cfDNA, ctDNA, exosomes, miRNAs, circRNAs, CTCs, and DNA methylated fragments, among others, which can be successfully used as biomarkers for diagnosis, prognosis, and prediction of treatment response. Predictive biomarkers are well-established for managing lung cancer, and liquid biopsy options have emerged in the last few years. Currently, detecting EGFR p.(Tyr790Met) mutation in plasma samples from lung cancer patients has been used for predicting response and monitoring tyrosine kinase inhibitors (TKi)-treated patients with lung cancer. In addition, many efforts continue to bring more sensitive technologies to improve the detection of clinically relevant biomarkers for lung cancer. Moreover, liquid biopsy can dramatically decrease the turnaround time for laboratory reports, accelerating the beginning of treatment and improving the overall survival of lung cancer patients. Herein, we summarized all available and emerging approaches of liquid biopsy-techniques, molecules, and sample type-for lung cancer.

Circulating microvesicles and exosomes in small cell lung cancer by quantitative proteomics

BACKGROUND

Early detection of small cell lung cancer (SCLC) crucially demands highly reliable markers. Growing evidence suggests that extracellular vesicles carry tumor cell-specific cargo suitable as protein markers in cancer. Quantitative proteomic profiling of circulating microvesicles and exosomes can be a high-throughput platform for discovery of novel molecular insights and putative markers. Hence, this study aimed to investigate proteome dynamics of plasma-derived microvesicles and exosomes in newly diagnosed SCLC patients to improve early detection.

METHODS

Plasma-derived microvesicles and exosomes from 24 healthy controls and 24 SCLC patients were isolated from plasma by either high-speed- or ultracentrifugation. Proteins derived from these extracellular vesicles were quantified using label-free mass spectrometry and statistical analysis was carried out aiming at identifying significantly altered protein expressions between SCLC patients and healthy controls. Furthermore, significantly expressed proteins were subjected to functional enrichment analysis to identify biological pathways implicated in SCLC pathogenesis.

RESULTS

Based on fold change (FC) ≥ 2 or ≤ 0.5 and AUC ≥ 0.70 (p < 0.05), we identified 10 common and 16 and 17 unique proteins for microvesicles and exosomes, respectively. Among these proteins, we found dysregulation of coagulation factor XIII A (Log₂ FC =  - 1.1, p = 0.0003, AUC = 0.82, 95% CI: 0.69-0.96) and complement factor H-related protein 4 (Log₂ FC = 1.2, p = 0.0005, AUC = 0.82, 95% CI; 0.67-0.97) in SCLC patients compared to healthy individuals. Our data may indicate a novel tumor-suppressing role of blood coagulation and involvement of complement activation in SCLC pathogenesis.

CONCLUSIONS

In comparing SCLC patients and healthy individuals, several differentially expressed proteins were identified. This is the first study showing that circulating extracellular vesicles may encompass specific proteins with potential diagnostic attributes for SCLC, thereby opening new opportunities as novel non-invasive markers.

Challenges and Opportunities in Clinical Applications of Blood-Based Proteomics in Cancer

Simple Summary

The traditional approach in identifying cancer related protein biomarkers has focused on evaluation of a single peptide/protein in tissue or circulation. At best, this approach has had limited success for clinical applications, since multiple pathological tumor pathways may be involved during initiation or progression of cancer which diminishes the significance of a single candidate protein/peptide. Emerging sensitive proteomic based technologies like liquid chromatography mass spectrometry (LC-MS)-based quantitative proteomics can provide a platform for evaluating serial serum or plasma samples to interrogate secreted products of tumor–host interactions, thereby revealing a more “complete” repertoire of biological variables encompassing heterogeneous tumor biology. However, several challenges need to be met for successful application of serum/plasma based proteomics. These include uniform pre-analyte processing of specimens, sensitive and specific proteomic analytical platforms and adequate attention to study design during discovery phase followed by validation of discovery-level signatures for prognostic, predictive, and diagnostic cancer biomarker applications.

Abstract

Blood is a readily accessible biofluid containing a plethora of important proteins, nucleic acids, and metabolites that can be used as clinical diagnostic tools in diseases, including cancer. Like the on-going efforts for cancer biomarker discovery using the liquid biopsy detection of circulating cell-free and cell-based tumor nucleic acids, the circulatory proteome has been underexplored for clinical cancer biomarker applications. A comprehensive proteome analysis of human serum/plasma with high-quality data and compelling interpretation can potentially provide opportunities for understanding disease mechanisms, although several challenges will have to be met. Serum/plasma proteome biomarkers are present in very low abundance, and there is high complexity involved due to the heterogeneity of cancers, for which there is a compelling need to develop sensitive and specific proteomic technologies and analytical platforms. To date, liquid chromatography mass spectrometry (LC-MS)-based quantitative proteomics has been a dominant analytical workflow to discover new potential cancer biomarkers in serum/plasma. This review will summarize the opportunities of serum proteomics for clinical applications; the challenges in the discovery of novel biomarkers in serum/plasma; and current proteomic strategies in cancer research for the application of serum/plasma proteomics for clinical prognostic, predictive, and diagnostic applications, as well as for monitoring minimal residual disease after treatments. We will highlight some of the recent advances in MS-based proteomics technologies with appropriate sample collection, processing uniformity, study design, and data analysis, focusing on how these integrated workflows can identify novel potential cancer biomarkers for clinical applications.

The Expression Pattern of ZIC5 and its Prognostic Value in Lung Cancer

Background: Lung cancer (LC) represents a leading cause of cancer-related deaths. The aim of this study was to analyze the application value of ZIC5 in the prognosis evaluation of LC. Materials and Methods: The mRNA and protein levels of ZIC5 in LC tissues and adjacent normal controls were detected by quantitative real-time polymerase chain reaction and Western blot analysis, respectively. Chi-square test was performed to estimate the association between ZIC5 expression and clinical features. Furthermore, overall survival (OS) curves were plotted using Kaplan-Meier method with log rank test. The prognosis analysis was analyzed using Cox proportional hazards model. Results: Compared with that of noncancerous tissues, the expression of ZIC5 in LC tissues was significantly increased at both protein and mRNA levels (p < 0.001). Moreover, ZIC5 expression showed a positive correlation with differentiation (p = 0.001) and tumor size (p = 0.016). Survival analysis suggested that high expression of ZIC5 predicted shorter OS (log rank test, p = 0.007). ZIC5 might be an independent prognostic biomarker for LC (hazard ratio = 2.892; 95% confidence interval, 1.297-6.449; p = 0.009). Conclusions: ZIC5 expression is upregulated in LC, and it may be employed as a prognostic biomarker for patients with LC.

Applications and strategies in nanodiagnosis and nanotherapy in lung cancer

Lung cancer is the second most common cancer and the leading cause of death in both men and women in the world. Lung cancer is heterogeneous in nature and diagnosis is often at an advanced stage as it develops silently in the lung and is frequently associated with high mortality rates. Despite the advances made in understanding the biology of lung cancer, progress in early diagnosis, cancer therapy modalities and considering the mechanisms of drug resistance, the prognosis and outcome still remains low for many patients. Nanotechnology is one of the fastest growing areas of research that can solve many biological problems such as cancer. A growing number of therapies based on using nanoparticles (NPs) have successfully entered the clinic to treat pain, cancer, and infectious diseases. Recent progress in nanotechnology has been encouraging and directed to developing novel nanoparticles that can be one step ahead of the cancer reducing the possibility of multi-drug resistance. Nanomedicine using NPs is continuingly impacting cancer diagnosis and treatment. Chemotherapy is often associated with limited targeting to the tumor, side effects and low solubility that leads to insufficient drug reaching the tumor. Overcoming these drawbacks of chemotherapy by equipping NPs with theranostic capability which is leading to the development of novel strategies. This review provides a synopsis of current progress in theranostic applications for lung cancer diagnosis and therapy using NPs including liposome, polymeric NPs, quantum dots, gold NPs, dendrimers, carbon nanotubes and magnetic NPs.

Identification of lung cancer gene markers through kernel maximum mean discrepancy and information entropy

BACKGROUND

The early diagnosis of lung cancer has been a critical problem in clinical practice for a long time and identifying differentially expressed gene as disease marker is a promising solution. However, the most existing gene differential expression analysis (DEA) methods have two main drawbacks: First, these methods are based on fixed statistical hypotheses and not always effective; Second, these methods can not identify a certain expression level boundary when there is no obvious expression level gap between control and experiment groups.

METHODS

This paper proposed a novel approach to identify marker genes and gene expression level boundary for lung cancer. By calculating a kernel maximum mean discrepancy, our method can evaluate the expression differences between normal, normal adjacent to tumor (NAT) and tumor samples. For the potential marker genes, the expression level boundaries among different groups are defined with the information entropy method.

RESULTS

Compared with two conventional methods t-test and fold change, the top average ranked genes selected by our method can achieve better performance under all metrics in the 10-fold cross-validation. Then GO and KEGG enrichment analysis are conducted to explore the biological function of the top 100 ranked genes. At last, we choose the top 10 average ranked genes as lung cancer markers and their expression boundaries are calculated and reported.

CONCLUSION

The proposed approach is effective to identify gene markers for lung cancer diagnosis. It is not only more accurate than conventional DEA methods but also provides a reliable method to identify the gene expression level boundaries.

Impact of Heat Shock Protein 90 Inhibition on the Proteomic Profile of Lung Adenocarcinoma as Measured by Two-Dimensional Electrophoresis Coupled with Mass Spectrometry

Heat shock protein 90 (HSP90) is an important chaperone in lung adenocarcinoma, with relevant protein drivers such as EGFR (epidermal growth factor receptor) and EML4-ALK (echinoderm microtubule-associated protein-like protein4 fused to anaplastic lymphoma kinase) depending on it for their correct function, therefore HSP90 inhibitors show promise as potential treatments for lung adenocarcinoma. To study responses to its inhibition, HSP90 was pharmacologically interrupted by geldanamycin and resorcinol derivatives or with combined inhibition of HSP90 plus HSP70 in lung adenocarcinoma cell lines. Two-dimensional electrophoresis was performed to identify proteomic profiles associated with inhibition which will help to understand the biological basis for the responses. HSP90 inhibition resulted in altered protein profiles that differed according the treatment condition studied. Results revealed 254 differentially expressed proteins after treatments, among which, eukaryotic translation initiation factor3 subunit I (eIF3i) and citrate synthase demonstrated their potential role as response biomarkers. The differentially expressed proteins also enabled signalling pathways involved in responses to be identified; these included apoptosis, serine-glycine biosynthesis and tricarboxylic acid cycle. The proteomic profiles identified here contribute to an improved understanding of HSP90 inhibition and open possibilities for the detection of potential response biomarkers which will be essential to maximize treatment efficacy in lung adenocarcinoma.

Quantum Dot Based Nano-Biosensors for Detection of Circulating Cell Free miRNAs in Lung Carcinogenesis: From Biology to Clinical Translation

Lung cancer is the most frequently occurring malignancy and the leading cause of cancer-related death for men in our country. The only recommended screening method is clinic based low-dose computed tomography (also called a low-dose CT scan, or LDCT). However, the effect of LDCT on overall mortality observed in lung cancer patients is not statistically significant. Over-diagnosis, excessive cost, risks associated with radiation exposure, false positive results and delay in the commencement of the treatment procedure questions the use of LDCT as a reliable technique for population-based screening. Therefore, identification of minimal-invasive biomarkers able to detect malignancies at an early stage might be useful to reduce the disease burden. Circulating nucleic acids are emerging as important source of information for several chronic pathologies including lung cancer. Of these, circulating cell free miRNAs are reported to be closely associated with the clinical outcome of lung cancer patients. Smaller size, sequence homology between species, low concentration and stability are some of the major challenges involved in characterization and specific detection of miRNAs. To circumvent these problems, synthesis of a quantum dot based nano-biosensor might assist in sensitive, specific and cost-effective detection of differentially regulated miRNAs. The wide excitation and narrow emission spectra of these nanoparticles result in excellent fluorescent quantum yields with a broader color spectrum which make them ideal bio-entities for fluorescence resonance energy transfer (FRET) based detection for sequential or simultaneous study of multiple targets. In addition, photo-resistance and higher stability of these nanoparticles allows extensive exposure and offer state-of-the art sensitivity for miRNA targeting. A major obstacle for integrating QDs into clinical application is the QD-associated toxicity. However, the use of non-toxic shells along with surface modification not only overcomes the toxicity issues, but also increases the ability of QDs to quickly detect circulating cell free miRNAs in a non-invasive mode. The present review illustrates the importance of circulating miRNAs in lung cancer diagnosis and highlights the translational prospects of developing QD-based nano-biosensor for rapid early disease detection.

Quiescin Sulfhydryl Oxidase 1 (QSOX1) Secreted by Lung Cancer Cells Promotes Cancer Metastasis

As lung cancer shows the highest mortality in cancer-related death, serum biomarkers are demanded for lung cancer diagnosis and its treatment. To discover lung cancer protein biomarkers, secreted proteins from primary cultured lung cancer and adjacent normal tissues from patients were subjected to LC/MS⁻MS proteomic analysis. Quiescin sulfhydryl oxidase (QSOX1) was selected as a biomarker candidate from the enriched proteins in the secretion of lung cancer cells. QSOX1 levels were higher in 82% (51 of 62 tissues) of lung cancer tissues compared to adjacent normal tissues. Importantly, QSOX1 serum levels were significantly higher in cancer patients (p < 0.05, Area Under curve (AUC) = 0.89) when measured by multiple reaction monitoring (MRM). Higher levels of QSOX1 were also uniquely detected in lung cancer tissues, among several other solid cancers, by immunohistochemistry. QSOX1-knock-downed Lewis lung cancer (LLC) cells were less viable from oxidative stress and reduced migration and invasion. In addition, LLC mouse models with QSOX1 knock-down also proved that QSOX1 functions in promoting cancer metastasis. In conclusion, QSOX1 might be a lung cancer tissue-derived biomarker and be involved in the promotion of lung cancers, and thus can be a therapeutic target for lung cancers.

High circulating activin A level is associated with tumor progression and predicts poor prognosis in lung adenocarcinoma

Activin A (ActA)/follistatin (FST) signaling has been shown to be deregulated in different tumor types including lung adenocarcinoma (LADC). Here, we report that serum ActA protein levels are significantly elevated in LADC patients (n=64) as compared to controls (n=46, p=0.015). ActA levels also correlated with more advanced disease stage (p<0.0001) and T (p=0.0035) and N (p=0.0002) factors. M1 patients had significantly higher ActA levels than M0 patients (p<0.001). High serum ActA level was associated with poor overall survival (p<0.0001) and was confirmed as an independent prognostic factor (p=0.004). Serum FST levels were increased only in female LADC patients (vs. female controls, p=0.031). Two out of five LADC cell lines secreted biologically active ActA, while FST was produced in all of them. Transcripts of both type I and II ActA receptors were detected in all five LADC cell lines. In conclusion, our study does not only suggest that measuring blood ActA levels in LADC patients might improve the prediction of prognosis, but also indicates that this parameter might be a novel non-invasive biomarker for identifying LADC patients with organ metastases.

Current and Prospective Protein Biomarkers of Lung Cancer

Lung cancer is a malignant lung tumor with various histological variants that arise from different cell types, such as bronchial epithelium, bronchioles, alveoli, or bronchial mucous glands. The clinical course and treatment efficacy of lung cancer depends on the histological variant of the tumor. Therefore, accurate identification of the histological type of cancer and respective protein biomarkers is crucial for adequate therapy. Due to the great diversity in the molecular-biological features of lung cancer histological types, detection is impossible without knowledge of the nature and origin of malignant cells, which release certain protein biomarkers into the bloodstream. To date, different panels of biomarkers are used for screening. Unfortunately, a uniform serum biomarker composition capable of distinguishing lung cancer types is yet to be discovered. As such, histological analyses of tumor biopsies and immunohistochemistry are the most frequently used methods for establishing correct diagnoses. Here, we discuss the recent advances in conventional and prospective aptamer based strategies for biomarker discovery. Aptamers like artificial antibodies can serve as molecular recognition elements for isolation detection and search of novel tumor-associated markers. Here we will describe how these small synthetic single stranded oligonucleotides can be used for lung cancer biomarker discovery and utilized for accurate diagnosis and targeted therapy. Furthermore, we describe the most frequently used in-clinic and novel lung cancer biomarkers, which suggest to have the ability of differentiating between histological types of lung cancer and defining metastasis rate.

Clinical proteomics-driven precision medicine for targeted cancer therapy: current overview and future perspectives

Cancer is a common disease that is a leading cause of death worldwide. Currently, early detection and novel therapeutic strategies are urgently needed for more effective management of cancer. Importantly, protein profiling using clinical proteomic strategies, with spectacular sensitivity and precision, offer excellent promise for the identification of potential biomarkers that would direct the development of targeted therapeutic anticancer drugs for precision medicine. In particular, clinical sample sources, including tumor tissues and body fluids (blood, feces, urine and saliva), have been widely investigated using modern high-throughput mass spectrometry-based proteomic approaches combined with bioinformatic analysis, to pursue the possibilities of precision medicine for targeted cancer therapy. Discussed in this review are the current advantages and limitations of clinical proteomics, the available strategies of clinical proteomics for the management of precision medicine, as well as the challenges and future perspectives of clinical proteomics-driven precision medicine for targeted cancer therapy.

Personalized Medicine in Respiratory Disease: Role of Proteomics

Respiratory diseases affect humanity globally, with chronic lung diseases (e.g., asthma, chronic obstructive pulmonary disease, idiopathic pulmonary fibrosis, among others) and lung cancer causing extensive morbidity and mortality. These conditions are highly heterogeneous and require an early diagnosis. However, initial symptoms are nonspecific, and the clinical diagnosis is made late frequently. Over the last few years, personalized medicine has emerged as a medical care approach that uses novel technology aiming to personalize treatments according to the particular patient's medical needs. This review highlights the contributions of proteomics toward the understanding of personalized medicine in respiratory disease and its potential applications in the clinic.

Expression of two basic mRNA biomarkers in peripheral blood of patients with non-small cell lung cancer detected by real-time rt-PCR, individually and simultaneously

INTRODUCTION

Although extensive research has been conducted on lung cancer markers, a singular clinically applicable marker has not been found yet. The objective of this study was to evaluate the sensitivity and the specificity of carcinoembryonic antigen (CEA) mRNA and lung-specific X protein (LUNX) mRNA biomarkers in peripheral blood to detect lung cancer individually and simultaneously.

METHODS

Thirty patients affected by lung cancer and 30 healthy individuals were studied in this research. Three vials of cDNA were made from each sample after taking peripheral blood samples and extracting total RNA. Each sample was examined by the real-time RT-PCR technique. The result from each vial was then compared with the sensitivity of overall marker.

RESULTS

The CEA mRNA was positive in 24 out of 30 lung cancer patients. Hence, its sensitivity was determined at 80%, differing significantly from that observed in healthy individuals, where 11 positive cases were seen. The overall sensitivity of this marker was significantly associated with positivity in vials 2 and 3 but not in vial 1. The LUNX mRNA was positive in 21 out of 30 patients, indicating 70% sensitivity. This finding significantly differed from that in healthy individuals. The overall sensitivity of this marker was significantly associated with positivity in vials 1 and 3, but not in vial 2. In 93.3% of the patients, at least one positive marker was observed.

CONCLUSION

The mentioned mRNA could be suggested as sensitive and specific markers in peripheral blood for primary diagnosis of lung cancer.

Lung Cancer Biomarkers

Lung cancer is the most frequently occurring cancer in the world and continually leads in mortality among cancers. The overall 5-year survival rate for lung cancer has risen only 4% (from 12% to 16%) over the past 4 decades, and late diagnosis is a major obstacle in improving lung cancer prognosis. Survival of patients undergoing lung resection is greater than 80%, suggesting that early detection and diagnosis of cancers before they become inoperable and lethal will greatly improve mortality. Lung cancer biomarkers can be used for screening, detection, diagnosis, prognosis, prediction, stratification, therapy response monitoring, and so on. This review focuses on noninvasive diagnostic and prognostic biomarkers. For that purpose, our discussion in this review will focus on biological fluid-based biomarkers. The body fluids include blood (serum or plasma), sputum, saliva, BAL, pleural effusion, and VOC. Since it is rich in different cellular and molecular elements and is one of the most convenient and routine clinical procedures, serum or plasma is the main source for the development and validation of many noninvasive biomarkers. In terms of molecular aspects, the most widely validated ones are proteins, some of which are used in the clinical sector, though in limited accessory purposes. We will also discuss the lung cancer (protein) biomarkers in clinical trials and currently in the validation phase with hundreds of samples. After proteins, we will discuss microRNAs, methylated DNA, and circulating tumor cells, which are being vigorously developed and validated as potential lung cancer biomarkers. The main aim of this review is to provide researchers and clinicians with an understanding of the potential noninvasive lung cancer biomarkers in biological fluids that have recently been discovered.

Respiratory proteomics: from descriptive studies to personalized medicine

Respiratory diseases are highly prevalent and affect humankind worldwide, causing extensive morbidity and mortality with the environment playing an important role. Given the complex structure of the airways, sophisticated tools are required for early diagnosis; initial symptoms are nonspecific, and the clinical diagnosis is made frequently late. Over the past few years, proteomics has made high technological progress in mass-spectrometry-based protein identification and has allowed us to gain new insights into disease mechanisms and identify potential novel therapeutic targets. This review will highlight the contributions of proteomics toward the understanding of the respiratory proteome listing potential biomarkers and its potential application to the clinic. We also outline the contributions of proteomics to creating a personalized approach in respiratory medicine.

Serum-based protein biomarkers for detection of lung cancer

Lung cancer is one of the most common cancers in terms of both incidence and mortality.The major reasons for the increasing number of deaths from lung cancer are late detection and lack of effective therapies. To improve our understanding of lung cancer biology, there is urgent need for blood-based, non-invasive molecular tests to assist in its detection in a cost-effective manner at an early stage when curative interventions are still possible. Recent advances in proteomic technology have provided extensive, high throughput analytical tools for identification, characterization and functional studies of proteomes. Changes in protein expression patterns in response to stimuli can serve as indicators or biomarkers of biological and pathological processes as well as physiological and pharmacological responses to drug treatment, thus aiding in early diagnosis and prognosis of disease. However, only a few biomarkers have been approved by the FDA to date for screening and diagnostic purposes. This review provides a brief overview of currently available proteomic techniques, their applications and limitations and the current state of knowledge about important serum biomarkers in lung cancer and their potential value as prognostic and diagnostic tools.

Subunit-specific mass spectrometry method identifies haptoglobin subunit alpha as a diagnostic marker in non-small cell lung cancer

Haptoglobin (Hp) subunits have been suggested as a potential serum marker for lung cancer. Research is intense on the application of Hp subunits to predict the cancer earlier. Nevertheless, it remains difficult to accurately measure the content of Hp subunits. We developed stable isotope dilution-multiple reaction monitoring mass spectrometry (SID-MRM-MS) capable of measuring Hp subunits (alpha and beta chains). Three isotopic analogs (NPANPVQ, TEGDGVYTLNDK and ILGGHLDAK for alpha, alpha2 and beta chain, respectively) were used as internal standard (IS) for SID-MRM-MS. Serum levels of each Hp subunit were measured in 210 clinical samples using SID-MRM-MS. A concentration ratio of each Hp subunit to total Hp was investigated. Secretion levels of alpha and beta chains were significantly increased in non-small cell lung cancer (NSCLC) compared to controls (P<0.0001). Alterations of the alpha chain ratio were more apparent than beta chain between controls and NSCLC (P=0.0001 and 0.338 for alpha and beta chains, respectively). In conclusion, this study provides not only an efficient quantitative method to determine each Hp subunit in crude sera, but also evidence that Hp alpha chain is a more prospective biomarker to diagnose NSCLC than beta chain.

BIOLOGICAL SIGNIFICANCE

Recent several studies have reported Hp as a potential biomarker for diagnosis of lung cancer. However a successful evaluation of the value of Hp subunits was not achieved on clinical samples. To evaluate the diagnostic performance of each Hp subunit, the development of an accurate quantitative assay of Hp subunits is necessary. In this regard, we employed a new analytical method using stable isotope dilution-multiple reaction monitoring mass spectrometry (SID-MRM-MS), capable of measuring Hp subunits in 210 clinical specimens. In this article, we measured the Hp subunit concentrations and Hp subunits/total Hp ratios in patients with NSCLC using SID-MRM-MS. This is the first report on the evaluation of each Hp subunit as a lung cancer marker using SID-MRM-MS. Consequently, we evaluated specific three tryptic peptides (e.g. NPANPVQ, TEGDGVYTLNDK and ILGGHLDAK for alpha, alpha2 and beta chain, respectively) with high specificity and sensitivity for determination of Hp subunits. Through future large prospective cohort studies, the clinical application of Hp subunits as complementary markers, especially Hp alpha, would be useful for the diagnosis of NSCLC.

Identification of proteomic signatures associated with lung cancer and COPD

Lung cancer (LC) and chronic obstructive pulmonary disease (COPD) commonly coexist in smokers, and the presence of COPD increases the risk of developing LC. The aim of this study was to identify distinct proteomic profiles able to discriminate these two pathological entities. Protein content was assessed in the bronchoalveolar lavage (BAL) of 60 patients classified in four groups: COPD, COPD and LC, LC without COPD, and control with neither COPD nor LC. Proteins were separated into spots by bidimensional polyacrylamide gel electrophoresis (2D-PAGE) and examined by matrix-assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF/TOF). A total of 40 proteins were differentially expressed in the LC and/or COPD groups as compared with the control group. Distinct protein profiles were identified and validated for each pathological entity (LC and COPD). The main networks involved were related to inflammatory signalling, free radical scavenging and oxidative stress response, and glycolysis and gluconeogenesis pathways. The most relevant signalling link between LC and COPD was through the NF-κB pathway. In conclusion, the protein profiles identified contribute to elucidate the underlying pathogenic pathways of both diseases, and provide new tools of potential use as biomarkers for the early diagnosis of LC.

BIOLOGICAL SIGNIFICANCE

Sequence coverage. The protein sequence coverage (95%) was estimated for specific proteins by the percentage of matching amino acids from the identified peptides having confidence greater than or equal to 95% divided by the total number of amino acids in the sequence. Ingenuity Pathways Analysis. Mapping of our proteins onto biological pathways and disease networks demonstrated that 22 proteins were linked to inflammatory signalling (p-value: 1.35 10(-08)-1.42 10(-02)), 15 proteins were associated with free radical scavenging and oxidative stress response (p-value: 4.93 10(-11)-1.27 10(-02)), and 9 proteins were related with glycolysis and gluconeogenesis pathways (p-value: 7.39 10(-09)-1.58 10(-02)).

MicroRNA-365 regulates NKX2-1, a key mediator of lung cancer

MicroRNAs constitute a class of small noncoding RNAs that play roles in tumorigenesis. We found that NKX2-1 protein levels were generally high in the lung cancer tissues whereas miRNA-365 expression levels were downregulated. Ectopic miR-365 expression decreased NKX2-1 expression in lung cancer cell lines. Transfection of a miR-365 mimic led to reduced proliferation of lung cancer cells; conversely, a miR-365 inhibitor slightly increased cell proliferation. The NKX2-1 overexpression significantly increased the cell proliferation by overcoming the suppressive effect of miR-365. Our data suggest that miR-365 is an important regulator of NKX2-1 and can be a target for lung cancer therapies.

Mass spectrometry-based proteomics: the road to lung cancer biomarker discovery

Lung cancer is the leading cause of cancer death in men and women in Western nations, and is among the deadliest cancers with a 5-year survival rate of 15%. The high mortality caused by lung cancer is attributable to a late-stage diagnosis and the lack of effective treatments. So, it is crucial to identify new biomarkers that could function not only to detect lung cancer at an early stage but also to shed light on the molecular mechanisms that underlie cancer development and serve as the basis for the development of novel therapeutic strategies. Considering that DNA-based biomarkers for lung cancer showed inadequate sensitivity, specificity, and reproducibility, proteomics could represent a better tool for the identification of useful biomarkers and therapeutic targets for this cancer type. Among the proteomics technologies, the most powerful tool is mass spectrometry. In this review, we describe studies that use mass spectrometry-based proteomics technologies to analyze tumor proteins and peptides, which might represent new diagnostic, prognostic, and predictive markers for lung cancer. We focus in particular on those findings that hold promise to impact significantly on the clinical management of this disease.

Identification of oxidative stress related proteins as biomarkers for lung cancer and chronic obstructive pulmonary disease in bronchoalveolar lavage

Lung cancer (LC) and chronic obstructive pulmonary disease (COPD) commonly coexist in smokers, and the presence of COPD increases the risk of developing LC. Cigarette smoke causes oxidative stress and an inflammatory response in lung cells, which in turn may be involved in COPD and lung cancer development. The aim of this study was to identify differential proteomic profiles related to oxidative stress response that were potentially involved in these two pathological entities. Protein content was assessed in the bronchoalveolar lavage (BAL) of 60 patients classified in four groups: COPD, COPD and LC, LC, and control (neither COPD nor LC). Proteins were separated into spots by two dimensional polyacrylamide gel electrophoresis (2D-PAGE) and examined by matrix-assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF/TOF). A total of 16 oxidative stress regulatory proteins were differentially expressed in BAL samples from LC and/or COPD patients as compared with the control group. A distinct proteomic reactive oxygen species (ROS) protein signature emerged that characterized lung cancer and COPD. In conclusion, our findings highlight the role of the oxidative stress response proteins in the pathogenic pathways of both diseases, and provide new candidate biomarkers and predictive tools for LC and COPD diagnosis.

Fucosylated glycoproteomic approach to identify a complement component 9 associated with squamous cell lung cancer (SQLC)

Human lung cancer is a major cause of cancer mortality worldwide. Understanding the pathophysiological features and the development of novel biomarkers for diagnosis as well as treatment are major tasks. In the present study, sera from ten SQLC patients and healthy control (HEC) were collected and pooled, respectively. The pooled sera were depleted via an immunoaffinity method and further subjected to fucosylation enrichment. Enriched fucosylated glycoproteins were resolved by SDS-PAGE and subsequently analyzed by LC-ESI-MS/MS. From comparative proteomic analysis, we selected the C9 protein. C9 protein levels were validated by Western blot, protein arrays and the fucosylation levels of C9 by hybrid lectin ELISA (HLE) in the sera of 120 HEC and 118 SQLC patients. The C9 protein level was 6.4-fold higher in SQLC patients compared to HEC, as determined by Western blot analysis. The results were concurrently confirmed by a protein array that showed a C9 level significantly higher in SQLC patients, as compared to HEC, with a sensitivity of 53% and a specificity of 89%. C9 fucosylation levels were significantly higher in SQLC patients compared to HEC (p<0.05) when tested by HLE. These findings suggest that C9 and fucosylated form could serve as a useful marker for SQLC.

Lung cancer proteomics: recent advances in biomarker discovery

Lung cancer is the most common cause of cancer death in both men and women in Western countries, with a 5-year survival rate of 15%, which is among the lowest of all cancers. The high mortality from lung cancer is due not only to the late stage diagnosis but also to the lack of effective treatments even for patients diagnosed with stage I lung cancer. Therefore, there is an urgent need to identify new markers for early diagnosis and prognosis that could serve to open novel therapeutic avenues. Proteomics can represent an important tool for the identification of biomarkers and therapeutic targets for lung cancer since DNA-based biomarkers did not prove to have adequate sensitivity, specificity, and reproducibility. In this paper we will describe studies focused on the identification of new diagnostic, prognostic, and predictive markers for lung cancer, using proteomics technologies.