Epigenetic regulation in lung cancer

Lung cancer is indeed a major cause of cancer-related deaths worldwide. The development of tumors involves a complex interplay of genetic, epigenetic, and environmental factors. Epigenetic mechanisms, including DNA methylation (DNAm), histone modifications, and microRNA expression, play a crucial role in this process. Changes in DNAm patterns can lead to the silencing of important genes involved in cellular functions, contributing to the development and progression of lung cancer. MicroRNAs and exosomes have also emerged as reliable biomarkers for lung cancer. They can provide valuable information about early diagnosis and treatment assessment. In particular, abnormal hypermethylation of gene promoters and its effects on tumorigenesis, as well as its roles in the Wnt signaling pathway, have been extensively studied. Epigenetic drugs have shown promise in the treatment of lung cancer. These drugs target the aberrant epigenetic modifications that are involved in the development and progression of the disease. Several factors have been identified as drug targets in non-small cell lung cancer. Recently, combination therapy has been discussed as a successful strategy for overcoming drug resistance. Overall, understanding the role of epigenetic mechanisms and their targeting through drugs is an important area of research in lung cancer treatment.

Establishment and verification of a prediction model based on clinical characteristics and positron emission tomography/computed tomography (PET/CT) parameters for distinguishing malignant from benign ground-glass nodules

Background

To develop and verify a prediction model for distinguishing malignant from benign ground-glass nodules (GGNs) combined with clinical characteristics and ¹⁸F-fluorodeoxyglucose (FDG) positron emission tomography-computed tomography (PET/CT) parameters.

Methods

We retrospectively analyzed 170 patients (56 males and 114 females) with GGNs who underwent PET/CT and high-resolution CT examination in our hospital from November 2011 to December 2019. The clinical and imaging data of all patients were collected, and the nodules were randomly divided into a derivation set and a validation set. For the derivation set, we used multivariate logistic regression to develop a prediction model for distinguishing benign from malignant GGNs. A receiver operating characteristic (ROC) curve was used to evaluate the diagnostic efficacy of the model, and the data in the validation set were used to verify the prediction model.

Results

Among the 170 patients, 197 GGNs were confirmed via postoperative pathological examination or clinical follow-up. There were 21 patients with 27 GGNs in the benign group and 149 patients with 170 GGNs in the adenocarcinoma group. A total of five parameters, including the patient's sex, nodule location, margin, pleural indentation, and standardized uptake value (SUV) index (the ratio of nodule SUVmax to liver SUVmean), were selected to develop a prediction model for distinguishing benign from malignant GGNs. The area under the curve (AUC) of the model was 0.875 in the derivation set, with a sensitivity of 0.702 and a specificity of 0.923. The positive likelihood ratio was 9.131, and the negative likelihood ratio was 0.322. In the validation set, the AUC of the model was 0.874, which was not significantly different from the derivation set (P=0.989).

Conclusions

This study developed and validated a prediction model based on ¹⁸F-FDG PET/CT imaging and clinical characteristics for distinguishing malignant from benign GGNs. The model showed good diagnostic efficacy and high specificity, which can improve the preoperative diagnosis of high-risk GGNs.

Clinical Application of Mass Spectrometry-Based Proteomics in Lung Cancer Early Diagnosis

The current knowledge on proteomic biomarker analysis for the early diagnosis of lung cancer is summarized, underlining the diversity among the results and the current interest in translating research results into clinical practice. A MEDLINE/PubMed literature search to retrieve all the papers published in the last 10 years is performed. Proteomics studies on lung cancer have gathered evidence on the potential role of biomarkers in early diagnosis. Although promising, none of them have proved to be sufficiently reliable to achieve validation. Future research should evolve toward a multipanel analysis of proteins, considering the possibility that individual biomarkers might not be specific enough to diagnose lung cancer, but could be related to oncological conditions.

The diagnostic performance of lysine(K)-specific demethylase 6B (KDM6B) in non-small cell lung cancer

Objectives: Accumulating evidence show that histone demethylases play important roles in various types of cancers, including non-small cell lung cancer (NSCLC). In the current study, we evaluated the diagnostic value of lysine(K)-specific demethylase 6B (KDM6B) in NSCLC. Methods: Serum KDM6B expression levels of 115 NSCLC patients and 88 healthy volunteers were detected by reverse transcription quantitative real-time polymerase chain reaction (qRT-PCR). The relationship between KDM6B and clinical characteristics was assessed by chi-square test. Receiver operating characteristic (ROC) analysis was applied to evaluate diagnostic efficacy. Results: Serum KDM6B was significantly lower in NSCLC patients than that in healthy controls (p < .001). Moreover, low KDM6B expression was significantly associated with the high clinical stage (p = .028) and positive lymph node metastasis (p = .031). Besides, we found that the expression of KDM6B mRNA was also significantly different among healthy controls, NSCLC early stage and later stage patients (p < .05). ROC curve indicated that KDM6B could serve as a diagnostic marker for NSCLC with the cut-off value of 0.955. The AUC was 0.897 with a sensitivity of 79.5% and specificity of 84.3%. Conclusion: Down-regulation of KDM6B is significantly associated with aggressive progression of NSCLC and KDM6B may be a tool of early detection of NSCLC.

High Sensitive Immunoelectrochemical Measurement of Lung Cancer Tumor Marker ProGRP Based on TiO₂-Au Nanocomposite

Progastrin-releasing peptide (ProGRP), which is known to be highly specific and sensitive to small cell lung cancer (SCLC), has been proven to be a valuable substitute for neuron-specific enolase in SCLC diagnostics and monitoring, especially in its early stages. The detection of ProGRP levels also facilitates a selection of therapeutic treatments. For the fabrication of our proposed biosensor, titanium (IV) oxide microparticles were first used, followed by dispersing gold nanoparticles into chitosan and immobilizing them onto a carbon paste electrode (CPE) surface. The developed immunosensor exhibits a much higher biosensing performance in comparison with current methods, when it comes to the detection of ProGRP. Therefore, the proposed CPE/TiO₂/(CS+AuNPs)/anti-ProGRP/BSA/ProGRP is excellent for the development of a compact diagnostics apparatus.

Mass spectrometry imaging for clinical research - latest developments, applications, and current limitations

Mass spectrometry is being used in many clinical research areas ranging from toxicology to personalized medicine. Of all the mass spectrometry techniques, mass spectrometry imaging (MSI), in particular, has continuously grown towards clinical acceptance. Significant technological and methodological improvements have contributed to enhance the performance of MSI recently, pushing the limits of throughput, spatial resolution, and sensitivity. This has stimulated the spread of MSI usage across various biomedical research areas such as oncology, neurological disorders, cardiology, and rheumatology, just to name a few. After highlighting the latest major developments and applications touching all aspects of translational research (i.e. from early pre-clinical to clinical research), we will discuss the present challenges in translational research performed with MSI: data management and analysis, molecular coverage and identification capabilities, and finally, reproducibility across multiple research centers, which is the largest remaining obstacle in moving MSI towards clinical routine.

Differential Proteomic Analysis between Small Cell Lung Carcinoma (SCLC) and Pulmonary Carcinoid Tumors Reveals Molecular Signatures for Malignancy in Lung Cancer

PURPOSE

The molecular underpinnings that may prognosticate survival and increase our understanding of tumor development and progression are still poorly understood. This study aimed to define the molecular signatures for malignancy in small cell lung carcinoma (SCLC), which is known for its highly aggressive clinical features and poor prognosis.

EXPERIMENTAL DESIGN

Using clinical specimens, the authors perform a comparative proteomic analysis of high-grade SCLCs and low-grade pulmonary carcinoid tumors (PCTs), both of which are types of neuroendocrine tumors. A label-free LC-MS-based quantitative proteomic analysis is applied to tumor cells laser-microdissected from their formalin-fixed paraffin-embedded (FFPE) tissues obtained from six patients each.

RESULTS

Overall, 1991 proteins are identified from tumor cells in the FFPE tissues. Through the protein-protein interaction network analysis of 201 proteins significantly, the authors find that SCLC is functionally characterized by activation of molecular pathways for spliceosome, RNA transport, and DNA replication and cell cycle. Particularly, 11 proteins involved in tumor proliferation (MCM2, 4, 6, 7, and MSH2), metastasis (RCC2, CORO1C, CHD4, and IPO9), and cancer metabolism (PHGDH and TYMP) are identified as SCLC-specific proteins. Furthermore, their prognostic significances are demonstrated by online Kaplan-Meier survival analysis.

CONCLUSIONS AND CLINICAL RELEVANCE

These clinical tissue proteomic approach for SCLC reveals the proteins associated with aggressiveness and poor prognosis. The identified SCLC-specific proteins represent potential therapeutic targets. Moreover, MCMs and PHGDH can be poor prognostic factors for lung cancer.

The impact of growth hormone on proteomic profiles: a review of mouse and adult human studies

Growth hormone (GH) is a protein that is known to stimulate postnatal growth, counter regulate insulin's action and induce expression of insulin-like growth factor-1. GH exerts anabolic or catabolic effects depending upon on the targeted tissue. For instance, GH increases skeletal muscle and decreases adipose tissue mass. Our laboratory has spent the past two decades studying these effects, including the effects of GH excess and depletion, on the proteome of several mouse and human tissues. This review first discusses proteomic techniques that are commonly used for these types of studies. We then examine the proteomic differences found in mice with excess circulating GH (bGH mice) or mice with disruption of the GH receptor gene (GHR^-/-). We also describe the effects of increased and decreased GH action on the proteome of adult patients with either acromegaly, GH deficiency or patients after short-term GH treatment. Finally, we explain how these proteomic studies resulted in the discovery of potential biomarkers for GH action, particularly those related with the effects of GH on aging, glucose metabolism and body composition.

Lung cancer samples preserved in liquid medium: One step beyond cytology

Lung cancer is one of the most common cancer types in men and women worldwide with a high mortality rate. World Health Organization (WHO) classification has accepted biopsy as the primary sample for lung cancer diagnosis, pathological classification and molecular testing for management of patients, yet, the use of alternative sampling procedures is highly encouraged. Bronchial cytological samples require a less invasive collection technique and may be suitable for pathological and molecular analysis and storage in liquid medium. Furthermore, the molecular analysis of bronchial cytological samples allows the detection of molecular biomarkers, which may be useful for the selection of molecular targeted therapies. Thus, the purpose of this review is to describe the usefulness of bronchial cytological samples preserved in liquid medium from lung cancer patients for pathological diagnosis and molecular investigation.

Recent mass spectrometry-based proteomics for biomarker discovery in lung cancer, COPD, and asthma

INTRODUCTION

Lung cancer and related diseases have been one of the most common causes of deaths worldwide. Genomic-based biomarkers may hardly reflect the underlying dynamic molecular mechanism of functional protein interactions, which is the center of a disease. Recent developments in mass spectrometry (MS) have made it possible to analyze disease-relevant proteins expressed in clinical specimens by proteomic challenges. Areas covered: To understand the molecular mechanisms of lung cancer and its subtypes, chronic obstructive pulmonary disease (COPD), asthma and others, great efforts have been taken to identify numerous relevant proteins by MS-based clinical proteomic approaches. Since lung cancer is a multifactorial disease that is biologically associated with asthma and COPD among various lung diseases, this study focused on proteomic studies on biomarker discovery using various clinical specimens for lung cancer, COPD, and asthma. Expert commentary: MS-based exploratory proteomics utilizing clinical specimens, which can incorporate both experimental and bioinformatic analysis of protein-protein interaction and also can adopt proteogenomic approaches, makes it possible to reveal molecular networks that are relevant to a disease subgroup and that could differentiate between drug responders and non-responders, good and poor prognoses, drug resistance, and so on.

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.

Circulating MACC1 as a novel diagnostic and prognostic biomarker for nonsmall cell lung cancer

PURPOSE

Metastasis-associated in colon cancer-1 (MACC1) is a newly identified gene that plays an important role in cancer progression and metastasis. MACC1 has important functions in the differentiation, invasion, and metastasis of nonsmall cell lung cancer (NSCLC). However, the value of circulating MACC1 as a potential diagnostic and prognostic biomarker for NSCLC remains unknown.

METHODS

Plasma MACC1 mRNA levels were examined in 272 patients with NSCLC, 61 with benign lung disease, and 80 healthy volunteers using reverse transcription quantitative real-time polymerase chain reaction.

RESULTS

MACC1 was more highly expressed in NSCLC patients than in patients with benign disease (P < 0.001) or in healthy volunteers (P < 0.001). High MACC1 expression was significantly associated with NSCLC stage (P = 0.013) and lymph node metastasis (P = 0.016). The area under the receiver operating characteristic curve was 0.766, and the optimal cutoff value was 0.105, providing a sensitivity of 71.4 % and a specificity of 89.1 %. The diagnostic capability of circulating MACC1 mRNA was higher than that of carcinoembryonic antigen (P = 0.025) or cytokeratin-19 (P = 0.010). Furthermore, high MACC1 expression was associated with poor overall survival (OS) and disease-free survival (DFS) and predicted poor survival in NSCLC patients. Consequently, MACC1 mRNA was an independent prognostic factor of OS and DFS.

CONCLUSION

We concluded that circulating MACC1 mRNA represents a potential noninvasive, diagnostic and prognostic marker for NSCLC.

Associations between epidermal growth factor receptor gene mutation and serum tumor markers in advanced lung adenocarcinomas: a retrospective study

OBJECTIVE

To investigate the associations between epidermal growth factor receptor (EGFR) gene mutations and serum tumor markers in advanced lung adenocarcinomas.

METHODS

We investigated the association between EGFR gene mutations and clinical features, including serum tumor marker levels, in 97 advanced lung adenocarcinomas patients who did not undergo the treatment of EGFR tyrosine kinase inhibitors. EGFR gene mutation was detected by real-time PCR at exons 18, 19, 20, and 21. Serum tumor marker concentrations were analyzed by chemiluminescence assay kit at the same time.

RESULTS

EGFR gene mutations were detected in 42 (43%) advanced lung adenocarcinoma patients. Gender (P=0.003), smoking status (P=0.001), and abnormal serum status of carcinoembryonic antigen (CEA, P=0.028) were significantly associated with EGFR gene mutation incidence. Multivariate analysis showed the abnormal CEA level in serum was independently associated with the incidence of EGFR gene mutation (P=0.046) with an odds ratio of 2.613 (95% CI: 1.018-6.710). However, receiver operating characteristic (ROC) curve analysis revealed CEA was not an ideal predictive marker for EGFR gene mutation status in advanced lung adenocarcinoma (the area under the ROC curve was 0.608, P=0.069).

CONCLUSIONS

EGFR gene mutation status is significantly associated with serum CEA status in advanced lung adenocarcinmoas. However, serum CEA is not an ideal predictor for EGFR mutation.

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.

Clinical observations on the association between diagnosis of lung cancer and serum tumor markers in combination

OBJECTIVE

To evaluate the association of a diagnosis of lung cancer and combined detection of serum carcinoembryonic antigen (CEA), carbohydrate antigen 19-9 (CA19-9), neuron specific enolase (NSE) as well as the cytokeratin 19 fragment (CYFRA21-1).

METHODS

Serum CEA, CA19-9, NSE and CYFRA21-1 were assessed in 150 patients with lung cancer, 100 patients with benign lung disease and 100 normal control subjects, and differences of expression were compared in each group, and joint effects of these tumor markers in the diagnosis of lung cancer were analyzed.

RESULTS

Serum CEA, CA19-9, NSE and CYFRA21-1 in patients with lung cancer were significantly higher than those with benign lung disease and normal controls (p<0.01). It is suggested that these four tumor markers combined together could produce a positive detection rate of 90.2%, significantly higher than that of any single test.

CONCLUSION

Combination detection of CEA, CA19-9, NSE and CYFRA21-1 could significantly improve the sensitivity and specificity in diagnosis of lung cancer, and could be important in early detection.

Overexpression of adenylate cyclase-associated protein 1 is associated with metastasis of lung cancer

Lung cancer ranks first in both prevalence and mortality rates among all types of cancer. Metastasis is the main cause of treatment failure. Biomarkers are critical to early diagnosis and prediction and monitoring of progressive lesions. Several biomarkers have been identified for lung cancer but none have been routinely used clinically. The present study assessed the diagnostic and prognostic value of cyclase-associated protein 1 (CAP1) for lung cancer. CAP1 mRNA abundance and protein content were determined by real-time PCR and western blot analysis and/or immunostaining in biopsy specimens (24 neoplastic and 6 non-neoplastic) freshly collected at surgical lung resection, in 82 pathologically banked lung cancer specimens and in cultured non-invasive (95-C) and invasive (95-D) lung cancer cells. Multivariate regression analysis was performed to correlate immunoreactive CAP1 signal with cancer type and stage. In vitro cell migration was performed to determine the effect of RNA interference-mediated CAP1 gene silencing on invasiveness of 95-D cells. These analyses collectively demonstrated that: i) both CAP1 mRNA abundance and protein content were significantly higher in neoplastic compared to non-neoplastic specimens and in metastatic compared to non-metastatic specimens but not different between adenocarcinoma and squamous cell carcinoma; ii) immunoreactive CAP1 signal was significantly stronger in metastatic specimens and 95-D cells compared to non-metastatic specimens and 95-C cells; and iii) RNA interference-mediated CAP1 gene silencing adequately attenuated the invasive capacity of 95-D cells in vitro. These findings suggest that overexpression of CAP1 in lung cancer cells, particularly at the metastatic stage, may have significant clinical implications as a diagnostic/prognostic factor for lung cancer.

An omics strategy for discovering pulmonary biomarkers potentially relevant to the evaluation of tobacco products

Smoking is known to cause serious lung diseases including chronic bronchitis, chronic obstructive lung disease, obstruction of small airways, emphysema and cancer. Tobacco smoke is a complex chemical aerosol containing at least 8000 chemical constituents, either tobacco derived or added by tobacco product manufacturers. Identification of all of the toxic agents in tobacco smoke is challenging, and efforts to understand the mechanisms by which tobacco use causes disease will be informed by new biomarkers of exposure and harm. In 2009, President Obama signed into law the Family Smoking Prevention and Tobacco Control Act granting the US FDA the authority to regulate tobacco products to protect public health. This perspective article presents the background, rationale and strategy for using omics technologies to develop new biomarkers, which may be of interest to the FDA when implementing the Family Smoking Prevention and Tobacco Control Act.

Digging deeper into the field of the small cell lung cancer tumor marker ProGRP: a method for differentiation of its isoforms

In this paper, we have used a newly developed immunocapture and LC-MS method to demonstrate for the first time the presence of protein isoforms 1 and 3 of the small cell lung cancer (SCLC) marker progastrin-releasing peptide (ProGRP) in sera. In addition, the method allows for indirect determination of the relative presence of the other known isoform of ProGRP, also known as ProGRP isoform 2. This new method is able to determine total ProGRP as a marker in sera at clinically relevant levels and to differentiate between isoforms at the low-pM level through combining selective sample preparation by immunoextraction, tryptic digestion, and separation followed by detection with LC-SRM-MS of the signature peptides, NLLGLIEAK (total ProGRP), LSAPGSQR (ProGRP isoform 1), and DLVDSLLQVLNVK (ProGRP isoform 3), with accuracies ≤ 25% for lower limit of quantification (LLOQ) and precisions ≤ 33%. By analyzing serum samples from four patients diagnosed with SCLC using the here described new and fully validated method, the ability is shown to both determine total ProGRP concentration and to differentiate between ProGRP isoforms 1 and 3 in one single run. Quantification of various ProGRP isoforms in one single run may be helpful for further understanding of the underlying biochemical processes in SCLC and differentiation of small cell lung cancer.

Analysis of tumor markers in cytological fluid obtained from computed tomography-guided needle aspiration biopsies for the diagnosis of ground-glass opacity pulmonary lesions

BACKGROUND

The purpose of this study was to assess whether analyses of tumor markers in cytological fluid can improve the performance of computed tomography (CT)-guided needle aspiration biopsy (NAB) for the diagnosis of ground-glass opacity (GGO) pulmonary lesions.

METHODS

Forty-two patients were prospectively enrolled for CT-guided NAB. Levels of cytokeratin 19 fragments (CYFRA 21-1) and carcinoembryonic antigen (CEA) from serum and cytological fluid were measured. The cutoff values of 3.3 ng/mL for CYFRA 21-1 and 5.0 ng/mL for CEA (threshold A) or thresholds by adding 2 standard deviations to the mean levels of markers found in patients without malignancy (threshold B) were used to identify malignancy. The sensitivity and area under the curve (AUC) of NAB alone were compared with those of NAB combined with serum or cytological tumor markers.

RESULTS

Among the 42 patients, 30 (71.4%) had malignant and 12 (28.6%) had benign lesions. For NAB alone, the sensitivity, specificity, and AUC for diagnosing GGO were 70.0%, 100%, and 0.850, respectively. The sensitivity and AUC increased significantly for NAB with cytological CYFRA 21-1 compared with NAB alone, using both thresholds (threshold A: 86.7%, P=.026 and .933, P=.016; threshold B: 93.3%, P=.008 and .925, P=.046).

CONCLUSIONS

Cytological fluid measurements of CYFRA 21-1 can improve the diagnostic performance of CT-guided NAB for GGO pulmonary lesions.

Additional diagnostic value of tumor markers in cytological fluid for diagnosis of non-small-cell lung cancer

Background

Cytological fluid from a needle aspiration biopsy (NAB) is obtained directly from tumor tissue, therefore many biomarker candidates will be present in high concentrations. The aim of this study was to prospectively assess and validate the tumor markers CYFRA 21–1, CEA, and SCC in cytological fluid obtained from NAB samples to determine if they improved the performance of NAB for diagnosing non-small cell lung cancer (NSCLC).

Methods

A total of 194 patients (M:F = 128:66, mean age 63.7 years) with suspected malignant pulmonary lesions were prospectively enrolled and underwent percutaneous NAB. Levels of CYFRA 21–1, CEA, and SCC were measured by immunoassay in serum and cytological fluid obtained during aspiration biopsy. Cut-off values to determined malignancy were 3.3 ng/mL in serum and 15.7 ng/mL in cytological fluid for CYFRA 21–1, 5 ng/mL and 0.6 ng/mL for CEA, and 2 ng/mL and 0.86 ng/mL for SCC.

Results

Of 194 patients, 139 patients (71.6%) had NSCLC and 55 (28.4%) had benign lesions. Sensitivity increased significantly for NAB combined with cytological tumor markers compared with NAB alone (CYFRA 21–1: 95% versus 83.5%, p < 0.001, CEA: 92.1% versus 83.5%, p = 0.002, SCC: 91.4% versus 83.5%, p = 0.003). Accuracy improved significantly for NAB combined with cytological CYFRA 21–1 compared with NAB alone (95.9% versus 88.1%, p < 0.001). The area under curve (AUC) of NAB with cytological CYFRA 21–1 was significantly larger than for NAB alone (0.966 versus 0.917, p = 0.009).

Conclusion

Of the tested tumor markers, cytological fluid measurements of CYFRA 21–1 improved the diagnostic performance of NAB for NSCLC.

Analysis of tumor markers in the cytological fluid obtained from computed tomography-guided needle aspiration biopsy for the diagnosis of non-small cell lung cancer

PURPOSE

The aim of this study was to prospectively assess whether analysis of the tumor markers cytokeratin 19 fragments (CYFRA 21-1), carcinoembryonic antigen (CEA), and squamous cell carcinoma (SCC) antigen in cytological fluid can improve the performance of computed tomography (CT)-guided needle aspiration biopsy (NAB) in the diagnosis of non-small cell lung cancer (NSCLC).

METHODS

A total of 100 patients (men:women = 41:59, mean age: 63 years) with suspected malignant pulmonary lesions were prospectively enrolled for CT-guided NAB procedures. Levels of CYFRA 21-1, CEA, and SCC in the cytological fluid were measured by immunoradiometric assays. The cutoff value for tumor markers was selected on the basis of best accuracy through receiver operating characteristic curves. The sensitivity and areas under the curve (AUC) of NAB alone were compared with those of NAB combined with cytological tumor markers (CYFRA 21-1, CEA, and SCC).

RESULTS

Among 100 patients, 71 (71%) had NSCLC and 29 (29%) had benign lesions. The sensitivity, specificity, and accuracy for diagnosing NSCLC were 85.7%, 100%, and 89%, respectively, for NAB alone. The sensitivity increased significantly for NAB combined with a tumor marker compared with NAB alone (100% for CYFRA 21-1, 92.9% for CEA, and 94.2% for SCC; p = 0.001, p = 0.025, and p = 0.014, respectively). The AUC of NAB with CYFRA 21-1 was significantly larger than the AUC of NAB alone (p = 0.001).

CONCLUSION

Evaluation of tumor markers CYFRA 21-1, CEA, and SCC in the cytological fluid can improve the diagnostic performance of CT-guided NAB for NSCLC. Of these markers, CYFRA 21-1 is the most useful cytological tumor marker.

Impact of protein stability, cellular localization, and abundance on proteomic detection of tumor-derived proteins in plasma

Tumor-derived, circulating proteins are potentially useful as biomarkers for detection of cancer, for monitoring of disease progression, regression and recurrence, and for assessment of therapeutic response. Here we interrogated how a protein's stability, cellular localization, and abundance affect its observability in blood by mass-spectrometry-based proteomics techniques. We performed proteomic profiling on tumors and plasma from two different xenograft mouse models. A statistical analysis of this data revealed protein properties indicative of the detection level in plasma. Though 20% of the proteins identified in plasma were tumor-derived, only 5% of the proteins observed in the tumor tissue were found in plasma. Both intracellular and extracellular tumor proteins were observed in plasma; however, after normalizing for tumor abundance, extracellular proteins were seven times more likely to be detected. Although proteins that were more abundant in the tumor were also more likely to be observed in plasma, the relationship was nonlinear: Doubling the spectral count increased detection rate by only 50%. Many secreted proteins, even those with relatively low spectral count, were observed in plasma, but few low abundance intracellular proteins were observed. Proteins predicted to be stable by dipeptide composition were significantly more likely to be identified in plasma than less stable proteins. The number of tryptic peptides in a protein was not significantly related to the chance of a protein being observed in plasma. Quantitative comparison of large versus small tumors revealed that the abundance of proteins in plasma as measured by spectral count was associated with the tumor size, but the relationship was not one-to-one; a 3-fold decrease in tumor size resulted in a 16-fold decrease in protein abundance in plasma. This study provides quantitative support for a tumor-derived marker prioritization strategy that favors secreted and stable proteins over all but the most abundant intracellular proteins.

Urinary metabonomic study of lung cancer by a fully automatic hyphenated hydrophilic interaction/RPLC-MS system

Lung cancer is one of the most common and lethal cancers in the world. In this study, a home-devised hydrophilic interaction chromatography/RPLC-MS (HILIC/RPLC-MS) system was developed to study the urinary metabonomics of lung cancer patients. This system combined the orthogonal selectivity of HILIC and RPLC and could chromatographically reveal more comprehensive information of the urinary metabolites. Within a total analysis time of 50 min, we detected 577 polar metabolite ions on the first HILIC column and 261 apolar ones on the second RPLC column. In addition, an orthogonal signal correction partial least-squares discriminant analysis model was constructed to characterize differences between health and lung cancer cases. Eleven potential biomarkers, ten from HILIC column and one from the second RP column, were identified and all of these biomarkers were found upregulated in lung cancer patients. Overall, the results indicated that the developed HILIC/RPLC-MS system is a promising tool for metabonomic studies in revealing more information of highly complex samples.

Have advanced research technologies made real impact on respiratory medicine?

Tremendous sophistication in our ability to detect, measure and manipulate the genes and proteins involved in lung disease has provided unique insights to the pathobiology of a number of lung disorders affecting humans today. Gene array analysis and genetic manipulation of animals have helped to identify novel pathways and their potential role in disease initiation and progression. Proteomics is a relatively novel tool in molecular research in respiratory medicine. Silencing gene expression by using small interfering RNA may, sooner than later, become part of novel therapies. Despite the excitement, to date, there has been little direct impact on therapeutic interventions available to clinicians. However, the rapidity with which these early data have accumulated, and the expected advances in bioinformatics and systems biology, should bring forward tangible therapeutic benefits for many acute and chronic lung diseases within the next ten years.