Diagnostic Tool For Lung Cancer Research Articles

Multiplex plasma protein assays as a diagnostic tool for lung cancer.

Lack of the established noninvasive diagnostic biomarkers causes delay in diagnosis of lung cancer (LC). The aim of this study was to explore the association between inflammatory and cancer-associated plasma proteins and LC and thereby discover potential biomarkers. Patients referred for suspected LC and later diagnosed with primary LC, other cancers, or no cancer (NC) were included in this study. Demographic information and plasma samples were collected, and diagnostic information was later retrieved from medical records. Relative quantification of 92 plasma proteins was carried out using the Olink Immuno-Onc-I panel. Association between expression levels of panel of proteins with different diagnoses was assessed using generalized linear model (GLM) with the binomial family and a logit-link function, considering confounder effects of age, gender, smoking, and pulmonary diseases. The analysis showed that the combination of five plasma proteins (CD83, GZMA, GZMB, CD8A, and MMP12) has higher diagnostic performance for primary LC in both early and advanced stages compared with NC. This panel demonstrated lower diagnostic performance for other cancer types. Moreover, inclusion of four proteins (GAL9, PDCD1, CD4, and HO1) to the aforementioned panel significantly increased the diagnostic performance for primary LC in advanced stage as well as for other cancers. Consequently, the collective expression profiles of select plasma proteins, especially when analyzed in conjunction, might have the potential to distinguish individuals with LC from NC. This suggests their utility as predictive biomarkers for identification of LC patients. The synergistic application of these proteins as biomarkers could pave the way for the development of diagnostic tools for early-stage LC detection.

Central Lung Cancer Location Along with Bronchoscopic Correlation- A Retrospective Cross-Sectional Study

Background: Lung cancer is currently the leading cause of death from neoplastic diseases worldwide. During the preceding decades, it was the most commonly occurring malignant disease, both in terms of impact and mortality. Fiberoptic bronchoscopy is the most important diagnostic tool for lung cancer. Early tissue diagnosis and proper staging remains the key to the management of the lung cancer patient. Endobronchial forceps biopsy has high diagnostic yield from the visible lesions. The aim of the study was to evaluate diagnostic yield of endobronchial biopsy. Methods: A Cross Sectional Retrospective study of all patients with provisional diagnosis of lung cancer based on computed tomography (CT) scan of chest undergoing fiberoptic bronchoscopy was done at Department of Respiratory Medicine, Ibn Sina Diagnostic & Consultation Center, Chattogram, Bangladesh from July 2022 to June 2023. All fiberoptic bronchoscopy was done in endoscopy suite under local anesthesia. Patients were explained about the procedure thoroughly. Endobronchial biopsy was the main procedure performed. Results: A total of 120 patients underwent bronchoscopy for suspected lung cancer. The mean age of the patients was 58 years with range of 18 to 75 years. Among them 93 (77.5%) were male and 27 (22.5%) were female. Majority of the patients, 108 (90%) were smoker with a mean pack year of 42. The lesion was present more in right side (N=65) than the left side (N=55). Majority of the lesion was present in lobar bronchus followed by main bronchus. Bronchoscopy was normal in 10 patients (8.3%). 12 patients had lesion in multiple locations. The diagnostic yield of endobronchial biopsy was 75%. The diagnostic yield for central tumor was 81.6% which was statistically significant (p<0.001) compared to peripheral tumor and extrinsic compression. Conclusion: Endobronchial biopsy provides good diagnostic yield especially in central tumors. Fiberoptic bronchoscopy is a safe procedure.

Thermophoretic Aggregation Imaging of Tumor-Derived Exosomes by CRISPR-Cas13a-Based Nanoprobes.

The inherent heterogeneity of tumor-derived exosomes holds great promise for enhancing the precision of cancer diagnostics. MicroRNAs (miRNAs) encapsulated in tumor-associated exosomes have emerged as valuable biomarkers for the early detection of cancers. Nevertheless, the flexible structure and inherent instability of RNA limit its application in biological diagnostics. The CRISPR-Cas13a system, distinguished by its target-responsive "collateral effect", represents a powerful tool for advancing cancer diagnostics. In this study, we harness the CRISPR-Cas13a system as an innovative signal amplification tool to image cancer-related exosomal miRNA in situ. Furthermore, we capitalize on the thermophoretic aggregation effect exhibited by gold nanoparticles (Au NPs) to consolidate the fluorescent signals generated by the CRISPR-Cas13a system. Subsequently, the developed nanoprobe is applied to detect lung cancer-related exosomal miRNA from human serum, enabling the aggregated visualization of low-abundance cancer exosomes in individuals with lung cancer compared with healthy individuals. This sensitive thermophoretic aggregation assay provides a diagnostic tool for lung cancer in the clinic.

Combination Analysis of PCDHGA12 and CDO1 DNA Methylation in Bronchial Washing Fluid for Lung Cancer Diagnosis.

When suspicious lesions are observed on computer-tomography (CT), invasive tests are needed to confirm lung cancer. Compared with other procedures, bronchoscopy has fewer complications. However, the sensitivity of peripheral lesion through bronchoscopy including washing cytology is low. A new test with higher sensitivity through bronchoscopy is needed. In our previous study, DNA methylation of PCDHGA12 in bronchial washing cytology has a diagnostic value for lung cancer. In this study, combination of PCDHGA12 and CDO1 methylation obtained through bronchial washing cytology was evaluated as a diagnostic tool for lung cancer. A total of 187 patients who had suspicious lesions in CT were enrolled. PCDHGA12 methylation test, CDO1 methylation test, and cytological examination were performed using 3-plex LTE-qMSP test. Sixty-two patients were diagnosed with benign diseases and 125 patients were diagnosed with lung cancer. The sensitivity of PCDHGA12 was 74.4% and the specificity of PCDHGA12 was 91.9% respectively. CDO1 methylation test had a sensitivity of 57.6% and a specificity of 96.8%. The combination of both PCDHGA12 methylation test and CDO1 methylation test showed a sensitivity of 77.6% and a specificity of 90.3%. The sensitivity of lung cancer diagnosis was increased by combining both PCDHGA12 and CDO1 methylation tests. Checking DNA methylation of both PCDHGA12 and CDO1 genes using bronchial washing fluid can reduce the invasive procedure to diagnose lung cancer.

Breath Analysis for Lung Cancer Early Detection-A Clinical Study.

This clinical study presents a comprehensive investigation into the utility of breath analysis as a non-invasive method for the early detection of lung cancer. The study enrolled 14 lung cancer patients, 14 non-lung cancer controls with diverse medical conditions, and 3 tuberculosis (TB) patients for biomarker discovery. Matching criteria including age, gender, smoking history, and comorbidities were strictly followed to ensure reliable comparisons. A systematic breath sampling protocol utilizing a BIO-VOC sampler was employed, followed by VOC analysis using Thermal Desorption-Gas Chromatography-Mass Spectrometry (TD-GC/MS). The resulting VOC profiles were subjected to stringent statistical analysis, including Orthogonal Projections to Latent Structures-Discriminant Analysis (OPLS-DA), Kruskal-Wallis test, and Receiver Operating Characteristic (ROC) analysis. Notably, 13 VOCs exhibited statistically significant differences between lung cancer patients and controls. The combination of eight VOCs (hexanal, heptanal, octanal, benzaldehyde, undecane, phenylacetaldehyde, decanal, and benzoic acid) demonstrated substantial discriminatory power with an area under the curve (AUC) of 0.85, a sensitivity of 82%, and a specificity of 76% in the discovery set. Validation in an independent cohort yielded an AUC of 0.78, a sensitivity of 78%, and a specificity of 64%. Further analysis revealed that elevated aldehyde levels in lung cancer patients' breath could be attributed to overactivated Alcohol Dehydrogenase (ADH) pathways in cancerous tissues. Addressing methodological challenges, this study employed a matching of physiological and pathological confounders, controlled room air samples, and standardized breath sampling techniques. Despite the limitations, this study's findings emphasize the potential of breath analysis as a diagnostic tool for lung cancer and suggest its utility in differentiating tuberculosis from lung cancer. However, further research and validation are warranted for the translation of these findings into clinical practice.

Determination of hexanal and heptanal in saliva samples by an adapted magnetic headspace adsorptive microextraction for diagnosis of lung cancer

In this work, an analytical method for the determination of two endogenous aldehydes (hexanal and heptanal) as lung cancer biomarkers in saliva samples is presented for the first time. The method is based on a modification of magnetic headspace adsorptive microextraction (M–HS–AME) followed by gas chromatography coupled to mass spectrometry (GC-MS). For this purpose, an external magnetic field generated by a neodymium magnet is used to hold the magnetic sorbent (i.e., CoFe2O4 magnetic nanoparticles embedded into a reversed-phase polymer) in the headspace of a microtube to extract the volatilized aldehydes. Subsequently, the analytes are desorbed in the appropriate solvent and the extract is injected into the GC-MS system for separation and determination. Under the optimized conditions, the method was validated and showed good analytical features in terms of linearity (at least up to 50 ng mL−1), limits of detection (0.22 and 0.26 ng mL−1 for hexanal and heptanal, respectively), and repeatability (RSD ≤12%). This new approach was successfully applied to saliva samples from healthy volunteers and those with lung cancer, obtaining notably differences between both groups. These results reveal the prospect of the method as potential diagnostic tool for lung cancer by saliva analysis. This work contributes to the Analytical Chemistry field presenting a double novelty: on the one hand, the use of M–HS–AME in bioanalysis is unprecedentedly proposed, thus expanding the analytical potential of this technique, and, on the other hand, the determination of hexanal and heptanal is carried out in saliva samples for the first time.

The lung cancers: staging and response, CT, 18F-FDG PET/CT, MRI, DWI: review and new perspectives.

Lung cancer is the most commonly diagnosed cancer and the leading cause of cancer deaths in both sexes combined. Recent years have seen major advances in the diagnostic and treatment options for patients with non-small-cell lung cancer (NSCLC), including the routine use of 2-deoxy-2[18F]-fluoro-D-glucose positron emission tomography/computed tomography (18F-FDG PET/CT) in staging and response evaluation, minimally invasive endoscopic biopsy, targeted radiotherapy, minimally invasive surgery, and molecular and immunotherapies. In this review, the central roles of CT and 18F-FDG PET/CT in staging and response in both NSCLC and malignant pleural mesothelioma (MPM) are critically assessed. The Tumour Node Metastases (TNM-8) staging systems for NSCLC and MPM are presented with critical appraisal of the strengths and pitfalls of imaging. Overviews of the Response Evaluation Criteria in Solid Tumours (RECIST 1.1) for NSCLC and the modified RECIST criteria for MPM are provided, together with discussion of the benefits and limitations of these anatomical-based tools. Metabolic response assessment (not evaluated by RECIST 1.1) will be explored. We introduce the Positron Emission Tomography Response Criteria in Solid Tumours (PERCIST 1.0) to include its advantages and challenges. The limitations of both anatomical and metabolic assessment criteria when applied to NSCLC treated with immunotherapy and the important concept of pseudoprogression are addressed with reference to immune RECIST (iRECIST). Separate consideration is given to the diagnosis and follow up of solitary pulmonary nodules with reference to the British Thoracic Society guidelines and Fleischner guidelines and use of the Brock (CT-based) and Herder (addition of 18F-FDG PET/CT) models for assessing malignant potential. We discuss how these models inform decisions by the multidisciplinary team, including referral of suspicious nodules for non-surgical management in patients unsuitable for surgery. We briefly outline current lung screening systems being used in the UK, Europe and North America. Emerging roles for MRI in lung cancer imaging are reviewed. The use of whole-body MRI in diagnosing and staging NSCLC is discussed with reference to the recent multicentre Streamline L trial. The potential use of diffusion-weighted MRI to distinguish tumour from radiotherapy-induced lung toxicity is discussed. We briefly summarise the new PET-CT radiotracers being developed to evaluate specific aspects of cancer biology, other than glucose uptake. Finally, we describe how CT, MRI and 18F-FDG PET/CT are moving from primarily diagnostic tools for lung cancer towards having utility in prognostication and personalised medicine with the agency of artificial intelligence.

Serum proteomics profiling identifies a preliminary signature for the diagnosis of early-stage lung cancer.

Lung cancer is the most common cause of death from cancer worldwide, largely due to late diagnosis. Thus, there is an urgent need to develop new approaches to improve the detection of early-stage lung cancer, which would greatly improve patient survival. The quantitative protein expression profiles of microvesicles isolated from the sera from 46 lung cancer patients and 41 high-risk non-cancer subjects were obtained using a mass spectrometry method based on a peptide library matching approach. We identified 33 differentially expressed proteins that allow discriminating the two groups. We also built a machine learning model based on serum protein expression profiles that can correctly classify the majority of lung cancer cases and that highlighted a decrease in the levels of Arysulfatase A (ARSA) as the most discriminating factor found in tumors. Our study identified a preliminary, non-invasive protein signature able to discriminate with high specificity and selectivity early-stage lung cancer patients from high-risk healthy subjects. These results provide the basis for future validation studies for the development of a non-invasive diagnostic tool for lung cancer.

MicroRNAs in exhaled breath condensate: A pilot study of biomarker detection for lung cancer

IntroductionQuantitation of microRNAs secreted by lung cells can provide valuable information regarding lung health. Exhaled breath condensate (EBC) offers a non-invasive way to sample the secreted microRNAs, and could be used as diagnostic tools for lung cancer. Materials & MethodsEBC samples from twenty treatment-naïve patients with pathologically confirmed lung cancer and twenty healthy subjects were profiled for miRNAs expression. Selected microRNAs were further validated, using quantitative-PCR, in an independent set of 10 subjects from both groups. ResultsA total of 78 miRNAs were found to be significantly upregulated in the EBC of lung cancer patients compared to the control group. Six of these 78 miRNAs were shortlisted for validation. Of these, miR-31–3p, let7i, and miR-449c were significantly upregulated, exhibited good discriminatory power. DiscussionDifferential expression of miRNAs secreted by lung cells could be quantitated in EBC samples, and could be used as a potential non-invasive tool for early diagnosis of lung cancer.

Bronchoscopy findings in 1074 lung cancer patients in a tertiary care center in Nepal

Background: Fiberoptic bronchoscopy is the most important diagnostic tool for lung cancer. Early tissue diagnosis and proper staging remains the key to the management of the lung cancer patient. Endobronchial forceps biopsy has high diagnostic yield from the visible lesions. The aim of the study was to evaluate diagnostic yield of endobronchial biopsy. Methods: A retrospective cross-sectional study was conducted at B.P. Koirala Memorial Cancer Hospital, Bharatpur, Nepal. Bronchoscopy reports of 1074 patients from January 2000 to December 2009 were included. Endobronchial biopsy was the main procedure performed. Results: A total of 1074 patients underwent bronchoscopy for suspected lung cancer. Majority of the patients (N=340) had lesion in lobar bronchus. Squamous cell carcinoma was the most common histological diagnosis. The diagnostic yield of endobronchial biopsy was 75%. The diagnostic yield for central tumor was 82.3% which was statistically significant (p<0.001) compared to peripheral tumor and extrinsic compression. Conclusion: Endobronchial biopsy provides good diagnostic yield especially in central tumors. Fiberoptic bronchoscopy is a safe procedure.

Changes in Metabolism as a Diagnostic Tool for Lung Cancer: Systematic Review.

Lung cancer is the leading cause of cancer-related mortality worldwide, with five-year survival rates varying from 3–62%. Screening aims at early detection, but half of the patients are diagnosed in advanced stages, limiting therapeutic possibilities. Positron emission tomography-computed tomography (PET-CT) is an essential technique in lung cancer detection and staging, with a sensitivity reaching 96%. However, since elevated 18F-fluorodeoxyglucose (18F-FDG) uptake is not cancer-specific, PET-CT often fails to discriminate between malignant and non-malignant PET-positive hypermetabolic lesions, with a specificity of only 23%. Furthermore, discrimination between lung cancer types is still impossible without invasive procedures. High mortality and morbidity, low survival rates, and difficulties in early detection, staging, and typing of lung cancer motivate the search for biomarkers to improve the diagnostic process and life expectancy. Metabolomics has emerged as a valuable technique for these pitfalls. Over 150 metabolites have been associated with lung cancer, and several are consistent in their findings of alterations in specific metabolite concentrations. However, there is still more variability than consistency due to the lack of standardized patient cohorts and measurement protocols. This review summarizes the identified metabolic biomarkers for early diagnosis, staging, and typing and reinforces the need for biomarkers to predict disease progression and survival and to support treatment follow-up.

Current Biosensors Used for Early Detection of Lung Cancer Biomarkers

Cancer, the abnormal and uncontrolled cell growth due to an accumulation of specific genetic and epigenetic defects, has posed a particular threat to human health which makes it to be ranked third in Kenya as a cause of death after infectious and cardiovascular diseases. The unregulated cell growth leads to the formation of a tumor, which after some period of time spreads beyond the site of origin and metastasizes to other body organs and systems, making it incurable. Early detection of cancer (long before the tumor is perceived) greatly increases the chance of curability, and is the point of focus for many cancer researchers. Lung cancer is the primary cancer threatening human life worldwide and its mortality rate has not decreased for a number of years. The mortality rate can be reduced by early diagnosis and subsequent treatment, for example if the serum proteins, microRNA, tumor-associated antigens, are detected in elevated amounts in the blood of potential lung cancer patients using a highly sensitive biosensor. Throughout the years, researchers worldwide have extensively investigated many screening modalities for lung cancer detection, including chest radiograph (CRG), computed tomography (CT), low-dose CT (LDCT), magnetic resonance imaging (MRI), and positron emission tomography (PET) and biopsy. However, these techniques are not suitable for patients with other pathologies. Developing a rapid and sensitive technique for early diagnosis of lung cancer plays an important role in early diagnosis and subsequent treatment. The typical methodologies limit the applications due to the low selectivity, low sensitivity, high cost, low stability and invasive procedure. Tumor markers as biochemical parameters can reveal cancer occurrence and progression, which show selectivity, stability sensitivity, convenience, and low cost in developing biosensors, and act as good prospect for fabricating biosensors of detecting lung cancer. This review portrays several biosensors (2010-2019) for detection of lung cancer biomarkers. To start with, cancer in general and Lung cancer has been briefly described focusing on the screening methods that have been used for lung cancer. The currently used diagnostic tools for lung cancer with their advantages and disadvantages is also portrayed. overview of the application of transducers used, including optical, mass-based, electrochemical and calorimetric biosensors, in lung cancer detection, together with the advantages and disadvantages of the development of new biosensors. Finally, the recent challenges and further opportunities for developing effective biosensors for early diagnosis of lung cancer are discussed.

Biomarkers and diagnostic tools for lung cancer

Lung cancer is the leading cause of cancer-related deaths in developing to advanced countries worldwide. The incidence rate of lung cancer in Korea has been increasing steadily since 1997. Statistics show that in 2017 alone, the incidence and mortality rates for lung cancer were 52.7 and 34.8 per 100,000 people, respectively, accounting for the highest cause of cancer death in Korea. The process of accurately diagnosing lung cancer consists of several steps, starting with the discovery of pulmonary nodule(s) via a cancer screening test or various other methods followed by the collection of cells or tissues and the identification of target molecules. Thereafter, staging and the development of a therapeutic plan lead to improved clinical outcomes. After the completion of a pilot study, a nationwide lung cancer screening program was introduced in Korea; since 2019, this program has targeted population at high risk for lung cancer: men and women aged 54 to 74 years who had a smoking history of 30 pack-years or more. The frequency of detection of pulmonary nodules is increasing in proportion to the public interest in health and economic growth. In this review, we present diagnostic techniques and biomarkers that are widely used in the medical field in the hope that such information would benefit clinical practice.

Ekstra-torasik maligniteli hastalarda EBUS-TBİA tanı değeri ve PET-BT ile ilişkisi

Endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) is a well-established diagnostic tool for lung cancer, sarcoidosis, and suspected metastatic extra-thoracic malignancy (ETM). Patients with primary ETM often have hypermetabolic mediastinal/hilar lymph node enlargement in the PET-scan done for initial staging or post treatment followup. We aimed to determine the diagnostic performance of EBUS-TBNA and the relationship between PET-SUV values and diagnosis of malignancy metastasis in patients with ETM.Results of EBUS-TBNA in ETM patients with suspected MLN metastasis were retrospectively analysed (May 2016 to July 2019). Non-malign results were confirmed for surgery or clinical/radiological followup. Lymph nodes with a high FDG-uptake (SUV > 2.5, MLN) were reported as suspicious for metastasis.Of the 588 EBUS procedures, 109 were included in the analysis. Patient' mean age was 62.5 ± 10.1 years; there were 35 men and 74 women. Primary malignancies were breast cancer in 33, gastrointestinal in 23, female genital tract in 17, head and neck in 14, genitourinary cancer in 13, malignant melanoma in 6, sarcoma in 2 and kaposi sarcoma in 1. According to EBUS-TBNA smear and cell block histopathologic evaluations, 16 patients' results (14.7%) were malignant compatible with metastasis of ETM. Among the 93 patients with non-malignant diagnosis, EBUS-TBNA revealed a granulomatous lympadenitis compatible with sarcoid reaction in 7 and tuberculosis in 2. A total of 9 patients underwent surgical procedures after EBUSTBNA, with a definitive histological diagnosis of granulomatous lymphadenitis in 2, malignancy in 5 and, reactive lymph node in 2. Overall sensitivity, specificity, positive predictive value, negative predictive value and diagnostic accuracy of EBUS-TBNA were 76.19% (95% CI 52.83-91.78), 100% (95% CI 95.89-100.00), 100%, 94.62% (95% CI 89.12-97.12) and 95.4%, respectively.EBUS-TBNA sampling has high diagnostic performance. Histopathological confirmation requirement for MLN should be kept in mind in patients with ETM, even they have negative EBUS results.

Identification of a Blood-Based Protein Biomarker Panel for Lung Cancer Detection.

Lung cancer is the deadliest cancer worldwide, mainly due to its advanced stage at the time of diagnosis. A non-invasive method for its early detection remains mandatory to improve patients’ survival. Plasma levels of 351 proteins were quantified by Liquid Chromatography-Parallel Reaction Monitoring (LC-PRM)-based mass spectrometry in 128 lung cancer patients and 93 healthy donors. Bootstrap sampling and least absolute shrinkage and selection operator (LASSO) penalization were used to find the best protein combination for outcome prediction. The PanelomiX platform was used to select the optimal biomarker thresholds. The panel was validated in 48 patients and 49 healthy volunteers. A 6-protein panel clearly distinguished lung cancer from healthy individuals. The panel displayed excellent performance: area under the receiver operating characteristic curve (AUC) = 0.999, positive predictive value (PPV) = 0.992, negative predictive value (NPV) = 0.989, specificity = 0.989 and sensitivity = 0.992. The panel detected lung cancer independently of the disease stage. The 6-protein panel and other sub-combinations displayed excellent results in the validation dataset. In conclusion, we identified a blood-based 6-protein panel as a diagnostic tool in lung cancer. Used as a routine test for high- and average-risk individuals, it may complement currently adopted techniques in lung cancer screening.

Validation of tumor DNA in bronchial lavage as a diagnostic tool in lung cancer.

9020 Background: Diagnosing lung cancer requires invasive procedures with risk of complications for the patient. The HOXA9 gene is highly methylated in lung cancer, and methylated tumor DNA (meth-tDNA) in bronchial lavage has previously shown potential as a diagnostic biomarker. The aim of the present study was to validate these preliminary results. Methods: Patients were referred by the general practitioner on suspicion of lung cancer. The Danish diagnostic package includes chest and abdominal CT scan, bronchoscopy, blood tests, and histopathological or cytological verification. Twelve ml lavage fluid was collected at bronchoscopy for analysis of meth-tDNA based on droplet digital PCR according to our published method. A positive test was defined as ≥ 4 droplets containing meth-tDNA and a ratio between HOXA9 and Albumin of > 0.15%. The analysis was performed blinded to clinical data and meth-tDNA status was compared with the final diagnosis. Results: The study population was 204 consecutively enrolled patients. The material consisted of a discovery cohort (n = 105, presented at ASCO 2019) used for establishing the cut-points, and a validation cohort (n = 99). Six were excluded from analysis due to malignancy other than lung cancer and one due to failed analysis. In the discovery cohort, the sensitivity was 68.7% (95% CI 56.2-79.4%), specificity 88.2% (95% CI 72.6-96.7%), and positive predictive value (PPV) 92.0% (95% CI 80.8-97.8%). In the validation cohort, the same values were 76.9% (95% CI 63.2-87.5%), 77.3% (95% CI 62.2-88.5%), and 80.0% (95% CI 66.3-90.0%), respectively. Analyzing the entire patient material (n = 197) the sensitivity, specificity, and PPV were 72.3% (95% CI 63.3-80.1%), 82.1% (95% CI 71.7-89.8%), and 86.0% (95% CI 77.6-92.1%), respectively. The false positive samples were equally distributed among patients with cryptogenic organizing pneumonia, granulomatous inflammation, and acute inflammatory disease. The false negative samples were mainly from patients with peripheral tumor, no radiologically detectable tumor, and mesothelioma. Conclusions: Meth-tDNA in bronchial lavage holds potential as a supplementary tool in the diagnosis of lung cancer with a clinically relevant sensitivity and specificity. Routine clinical application awaits further validation in a clinical trial. [Table: see text]

A novel Approach for Non-Invasive Lung Imaging and Targeting Lung Immune Cells.

Despite developments in pulmonary radiotherapy, radiation-induced lung toxicity remains a problem. More sensitive lung imaging able to increase the accuracy of diagnosis and radiotherapy may help reduce this problem. Super-paramagnetic iron oxide nanoparticles are used in imaging, but without further modification can cause unwanted toxicity and inflammation. Complex carbohydrate and polymer-based coatings have been used, but simpler compounds may provide additional benefits. Herein, we designed and generated super-paramagnetic iron oxide nanoparticles coated with the neutral natural dietary amino acid glycine (GSPIONs), to support non-invasive lung imaging and determined particle biodistribution, as well as understanding the impact of the interaction of these nanoparticles with lung immune cells. These GSPIONs were characterized to be crystalline, colloidally stable, with a size of 12 ± 5 nm and a hydrodynamic diameter of 84.19 ± 18 nm. Carbon, Hydrogen, Nitrogen (CHN) elemental analysis estimated approximately 20.2 × 103 glycine molecules present per nanoparticle. We demonstrated that it is possible to determine the biodistribution of the GSPIONs in the lung using three-dimensional (3D) ultra-short echo time magnetic resonance imaging. The GSPIONs were found to be taken up selectively by alveolar macrophages and neutrophils in the lung. In addition, the GSPIONs did not cause changes to airway resistance or induce inflammatory cytokines. Alveolar macrophages and neutrophils are critical regulators of pulmonary inflammatory diseases, including allergies, infections, asthma and chronic obstructive pulmonary disease (COPD). Therefore, pulmonary Magnetic Resonance (MR) imaging and preferential targeting of these lung resident cells by our nanoparticles offer precise imaging tools, which can be utilized to develop precision targeted radiotherapy as well as diagnostic tools for lung cancer, thereby having the potential to reduce the pulmonary complications of radiation.

Aspartyl (asparaginyl) β-hydroxylase (AABH), a serum biomarker for lung cancer.

45 Background: There are no serum biomarkers currently approved for the detection of lung cancer, a leading cause of cancer associated mortality world wide. More than 180,000 cases of lung cancer will be diagnosed in the United States in 2020 by other means such as by X-ray and CT scanning methods, which have inherently lower sensitivity and higher cost when compared generally to serological methods. While the five year survival for lung cancer is 15%, a survival rate of 50% can be achieved when detection is made early in individuals with localized cancer. Current detection methods, however, enable such detection in only about 18% of cases overall. Methods: A prospective serum biomarker Aspartyl (Asparaginyl) ß Hydroxylase (AABH), has been previously found to be elevated by immunohistochemical staining (IHC) in a broad range of cancers, including lung cancer. AABH was detected in > 99% of tumor specimens tested (n > 1000) but absent in adjacent tissue. The present study introduces a double monoclonal sandwich ELISA which provides detection and comparative quantification of AABH in serum of lung cancer patients vs. normal, and high-risk controls such as cigarette smokers without cancer. This is relevant since 87% of lung cancers are attributable to cigarette smoking, and associative parallels can be seen with recent reductions in rates of smoking. Results: Increased levels of serum AABH were found in 99% of patients with lung cancer (n = 192). Serum AABH was found to be undetectable in individuals not known to have cancer (n = 129, specificity = 93%). In patients with lung cancer, AABH was detectable at all stages. In a population of 50 smokers not known to have cancer, the mean serum AABH level was 0 ng/ml with 90% specificity. Conclusions: The AABH serum ELISA therefore has great promise as an additional diagnostic tool for lung cancer having the practicality and cost effectiveness of conventional serological screening. Elevated serum AABH in conjunction with CT scanning may greatly facilitate earlier diagnosis of lung cancer at a stage in which cure rates are significantly higher and thus may contribute to increased patient survival.

Could microRNA be used as a diagnostic tool for lung cancer?

Current methods for diagnosing lung cancer (LC) have varying degrees of risks and complications. MicroRNA (miRNA) is a small molecule noncoding RNA with gene regulation functions. Many studies have shown that miRNA can be used for the diagnosis of LC, but there are differences in diagnostic accuracy. Therefore, we aim to systematically review and meta-analyze published articles to comprehensively evaluate the diagnostic value of miRNA for LC. We searched the PubMed, Embase, and Cochrane databases, and calculated the area under the curve (AUC) by plotting the summary receiver operator characteristic curve using the sensitivity and specificity of each included study. The AUC was calculated and the likelihood ratio was plotted to assess the diagnostic accuracy of miRNA. We used QUADAS-2 in Review Manager 5.3 to evaluate the quality of all the articles. The other analyses were performed using the STATA 12.0 software. We included a total of 29 articles, 98 studies, and the qualities of all the articles were satisfactory. The overall pooled parameters calculated from all studies were as follows: sensitivity = 0.77, specificity = 0.83, positive likelihood ratio (PLR) = 4.6, negative likelihood ratio (NLR) = 0.28, and AUC = 0.87 for miRNA diagnosis. It had significant advantages over other biomarkers. Subgroup analysis showed that when combined four or more miRNA for the diagnosis of LC, the parameters were as follows: sensitivity = 0.90, specificity = 0.93, PLR = 13.2, NLR = 0.11, and AUC = 0.97. Four or more miRNA combination could be used for the diagnosis of LC. Besides this, we also found that miRNA showed a greater advantage in distinguishing LC from benign lung diseases than distinguishing between LC and normal people. Our findings provided a new way of thinking about the clinical diagnosis of LC from a nonmorphological aspect.

Automatic Detection and Staging of Lung Tumors using Locational Features and Double-Staged Classifications

Lung cancer is a life-threatening disease with the highest morbidity and mortality rates of any cancer worldwide. Clinical staging of lung cancer can significantly reduce the mortality rate, because effective treatment options strongly depend on the specific stage of cancer. Unfortunately, manual staging remains a challenge due to the intensive effort required. This paper presents a computer-aided diagnosis (CAD) method for detecting and staging lung cancer from computed tomography (CT) images. This CAD works in three fundamental phases: segmentation, detection, and staging. In the first phase, lung anatomical structures from the input tomography scans are segmented using gray-level thresholding. In the second, the tumor nodules inside the lungs are detected using some extracted features from the segmented tumor candidates. In the last phase, the clinical stages of the detected tumors are defined by extracting locational features. For accurate and robust predictions, our CAD applies a double-staged classification: the first is for the detection of tumors and the second is for staging. In both classification stages, five alternative classifiers, namely the Decision Tree (DT), K-nearest neighbor (KNN), Support Vector Machine (SVM), Ensemble Tree (ET), and Back Propagation Neural Network (BPNN), are applied and compared to ensure high classification performance. The average accuracy levels of 92.8% for detection and 90.6% for staging are achieved using BPNN. Experimental findings reveal that the proposed CAD method provides preferable results compared to previous methods; thus, it is applicable as a clinical diagnostic tool for lung cancer.