scholarly journals Autoantibody Signatures Discovered by HuProt Protein Microarray to Enhance the Diagnosis of Lung Cancer

2021 ◽  
Author(s):  
Yulin Wang ◽  
Jiaqi Li ◽  
Xue Zhang ◽  
Man Liu ◽  
Longtao Ji ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Validation Cohort ◽  
Mediastinal Lymph Node ◽  
Protein Microarray ◽  
Characteristic Curve ◽  
Pulmonary Nodules ◽  
Diagnostic Value ◽  
Enzyme Linked Immunosorbent Assay ◽  
Significant Difference ◽  
Diagnosis Of Lung Cancer

Abstract Background: This study aims to comprehensively discover novel autoantibodies (TAAbs) against tumor-associated antigens (TAAs) and establish diagnostic models for assisting in the diagnosis of lung cancer (LC) and discrimination of pulmonary nodules (PN).Methods: HuProt human microarray was used to discover the candidate TAAs and Enzyme-linked immunosorbent assay (ELISA) was performed to detect the level of TAAbs in 634 participants of two independent validation cohorts. Logistic regression analysis was used to construct models. Receiver operating characteristic curve (ROC) analysis was utilized to assess the diagnostic value of models.Results: Eleven TAAs were discovered by means of protein microarray and data analysis. The level of ten TAAbs (anti-SARS, anti-ZPR1, anti-FAM131A, anti-GGA3, anti-PRKCZ, anti-HDAC1, anti-GOLPH3, anti-NSG1, anti-CD84 and anti-EEA1) was higher in LC patients than that in NC of validation cohort 1 (P<0.05). The model 1 comprising 4 TAAbs (anti-ZPR1, anti-PRKCZ, anti-NSG1 and anti-CD84) and CEA reached an AUC of 0.813 (95%CI: 0.762-0.864) for diagnosing LC from normal individuals. 5 of 10 TAAbs (anti-SARS, anti-GOLPH3, anti-NSG1, anti-CD84 and anti-EEA1) existed a significant difference between malignant pulmonary nodules (MPN) and benign pulmonary nodules (BPN) patients in validation cohort 2 (P<0.05). Model 2 consisting of anti-EEA1, traditional biomarkers (CEA, CYFRA211 and CA125) and 3 CT characteristics (vascular notch sign, lobulation sign, mediastinal lymph node enlargement) could distinguish MPN from BPN patients with an AUC of 0.845 (sensitivity: 58.3%, specificity: 96.6%).Conclusions: High-throughput protein microarray is an efficient approach to discovering novel TAAbs which could increase the accuracy of lung cancer diagnosis in the clinic.

scholarly journals Diagnostic value of HSP90α and Related Markers in Lung Cancer

2019 ◽  
Author(s):  
Zhimin Yuan ◽  
Songlin Hong ◽  
Lin Li ◽  
Lin He ◽  
Peng Xiao ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Age Groups ◽  
Diagnostic Value ◽  
Enzyme Linked Immunosorbent Assay ◽  
Cancer Type ◽  
Clinical Value ◽  
Early Screening ◽  
Significant Difference ◽  
Positive Rate ◽  
Diagnosis Of Lung Cancer

Abstract Aims To prove the expression of heat shock protein 90α (HSP90α) in the lung cancer and the clinical value of HSP90α and related markers in the diagnosis of lung cancer. Methods The concentrations of HSP90α and related markers were detected in the blood of 560 lung cancer patients by enzyme-linked immunosorbent assay for analyzing the statistical differences of HSP90α between the patients group and the healthy group in patients' age, gender, different pathological types, lung cancer staging, and metastasis status, as well as the differences and evaluate the value of HSP90α and related markers in lung cancer diagnosis. Results The results showed no statistical difference in HSP90α among different age groups. And the HSP90α level cannot be distinguished by genders significantly (P>0.05); In the group by lung cancer type, statistical differences were found in the HSP90α level between the small cell lung cancer group and the squamous cell carcinoma group (P<0.05); In the group by stage, the HSP90α level of high staging was significantly higher than that low staging (P<0.05), and the significant difference among the groups; the HSP90α level at I/II/III/IV shows statistical differences among the groups (P<0.05); And the test result of HSP90α was higher in the metastatic group than in the non-metastatic group significantly, and the significant difference between the two groups (P<0.05). The r value of the HSP90α and related markers in the diagnosis of lung cancer: NSE>CEA>ProGRP>CF211 (P<0.05). While HSP90α and related markers didn’t fit the satisfactory conformance, in terms of the positive rate of diagnosis, there were statistically differences in the diagnostic positive rate between HSP90α and each maker (P<0.01). Reducing HSP90α clinical references in lung cancer combined diagnosis can effectively improve the positive rate of the combined diagnosis. Conclusion HSP90α has significant value on early screening and diagnosis of lung cancer. The combined application of HSP90α and related markers can improve the positive rate of early diagnosis of lung cancer effectively.

scholarly journals A Prediction Model Based on DNA Methylation Biomarkers and Radiological Characteristics for Identifying Malignant From Benign Pulmonary Nodules

2020 ◽  
Author(s):  
Wenqun Xing ◽  
Haibo Sun ◽  
Chi Yan ◽  
Chengzhi Zhao ◽  
Dongqing Wang ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Dna Methylation ◽  
Prediction Model ◽  
Characteristic Curve ◽  
Multivariate Logistic Regression Analysis ◽  
Pulmonary Nodules ◽  
Diagnostic Value ◽  
Receiver Operator Characteristic Curve ◽  
Model Based ◽  
Diagnosis Of Lung Cancer

Abstract BackgroundLung cancer remains the leading cause of cancer deaths across the world. Early detection of lung cancer by low-dose computed tomography (LDCT) can reduce the mortality rate. However, making a definitive preoperative diagnosis of malignant pulmonary nodules (PNs) found by LDCT is a clinical challenge. This study aimed to develop a prediction model based on DNA methylation biomarkers and radiological characteristics for identifying malignant pulmonary nodules from benign PNs. MethodsWe assessed three DNA methylation biomarkers (PTGER4, RASSF1A, and SHOX2) in a training cohort of 110 individuals with PNs. Using univariate and multivariate logistic regression analysis, we developed a prediction model based on the three DNA methylation biomarkers and one radiological characteristic for identifying malignant from benign PNs. The performance of the prediction model with that of the methylation biomarkers and the Mayo Clinic model were compared using the non-parametric approach of DeLong et al. with the area under a receiver operator characteristic curve (AUC) analysis. ResultsThe developed prediction model achieved a sensitivity of 87.3% and a specificity of 95.7% with an AUC value of 0.951 in malignant PNs diagnosis, being significantly higher than the three DNA methylation biomarkers (84.1% sensitivity and 89.4% specificity, p=0.013) or clinical/radiological characteristics (76.2% sensitivity and 87.2% specificity, p=0.001) alone. Validation of the prediction model in the testing cohort of 100 subjects with PNs confirmed the diagnostic value.ConclusionWe have shown that integrating DNA methylation biomarkers and radiological characteristics could more accurately identify lung cancer in subjects with CT-found PNs. The prediction model developed in our study may provide clinical utility in combination with LDCT to improve the over-all diagnosis of lung cancer.

scholarly journals Diagnostic value of HSP90α and Related Markers in Lung Cancer

2019 ◽  
Author(s):  
Zhimin Yuan ◽  
Songlin Hong ◽  
Lin Li ◽  
Lin He ◽  
Peng Xiao ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Squamous Carcinoma ◽  
Diagnostic Value ◽  
Enzyme Linked Immunosorbent Assay ◽  
Cancer Type ◽  
Clinical Value ◽  
Early Screening ◽  
Significant Difference ◽  
Positive Rate ◽  
Diagnosis Of Lung Cancer

Abstract Aim: To prove the expression of heat shock protein 90α (HSP90α) in lung cancer and the clinical value of HSP90α and related markers in the diagnosis of lung cancer. Methods: The concentrations of HSP90α and related markers were detected in the blood of 560 lung cancer patients by enzyme-linked immunosorbent assay for analyzing the statistical differences of HSP90α in patients' age, gender, pathological types, tumour staging and metastasis status, as well as the differences and evaluate the value of HSP90α and related markers in lung cancer diagnosis. Results: The results showed no statistical difference in HSP90α among age and gender groups (P>0.05); In the group by lung cancer type, statistical differences were found in the HSP90α level between the small cell lung cancer (SCLC) group and the squamous carcinoma (SLC) group (P<0.05); In the group by staging, the HSP90α level of high staging was significantly higher than that low staging, and the HSP90α level at Ⅰ/Ⅱ/Ⅲ/Ⅳ shows statistical differences among the groups (P<0.05); The test result of HSP90α was higher in the metastatic group than in the non-metastatic group significantly, and the significant difference between the two groups (P<0.05). The r value of the HSP90α and related markers in the diagnosis of lung cancer: NSE>CEA>ProGRP>CF211 (P<0.05). Although HSP90α and related markers didn’t fit the satisfactory conformance, in terms of the positive rate of diagnosis, it were statistically differences in the diagnostic positive rate between HSP90α and each marker (P<0.01). Reducing HSP90α clinical references in lung cancer combined diagnosis can effectively improve the positive rate of the combined diagnosis. Conclusion: HSP90α has significant value on early screening and diagnosis of lung cancer. The combined application of HSP90α and related markers can improve the positive rate of early diagnosis of lung cancer effectively.

scholarly journals Diagnostic value of HSP90α and Related Markers in Lung Cancer

2019 ◽  
Author(s):  
Zhimin Yuan ◽  
Songlin Hong ◽  
Lin Li ◽  
Lin He ◽  
Peng Xiao ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Squamous Carcinoma ◽  
Diagnostic Value ◽  
Enzyme Linked Immunosorbent Assay ◽  
Cancer Type ◽  
Clinical Value ◽  
Early Screening ◽  
Significant Difference ◽  
Positive Rate ◽  
Diagnosis Of Lung Cancer

Abstract Aim: To prove the expression of heat shock protein 90α (HSP90α) in lung cancer and the clinical value of HSP90α and related markers in the diagnosis of lung cancer. Methods: The concentrations of HSP90α and related markers were detected in the blood of 560 lung cancer patients by enzyme-linked immunosorbent assay for analyzing the statistical differences of HSP90α in patients' age, gender, pathological types, tumour staging and metastasis status, as well as the differences and evaluate the value of HSP90α and related markers in lung cancer diagnosis. Results: The results showed no statistical difference in HSP90α among age and gender groups (P>0.05); In the group by lung cancer type, statistical differences were found in the HSP90α level between the small cell lung cancer (SCLC) group and the squamous carcinoma (SLC) group (P<0.05); In the group by staging, the HSP90α level of high staging was significantly higher than that low staging, and the HSP90α level at Ⅰ/Ⅱ/Ⅲ/Ⅳ shows statistical differences among the groups (P<0.05); The test result of HSP90α was higher in the metastatic group than in the non-metastatic group significantly, and the significant difference between the two groups (P<0.05). The r value of the HSP90α and related markers in the diagnosis of lung cancer: NSE>CEA>ProGRP>CF211 (P<0.05). Although HSP90α and related markers didn’t fit the satisfactory conformance, in terms of the positive rate of diagnosis, it were statistically differences in the diagnostic positive rate between HSP90α and each marker (P<0.01). Reducing HSP90α clinical references in lung cancer combined diagnosis can effectively improve the positive rate of the combined diagnosis. Conclusion: HSP90α has significant value on early screening and diagnosis of lung cancer. The combined application of HSP90α and related markers can improve the positive rate of early diagnosis of lung cancer effectively.

scholarly journals Diagnostic value of HSP90α and Related Markers in Lung Cancer

2019 ◽  
Author(s):  
Zhimin Yuan ◽  
Songlin Hong ◽  
Lin Li ◽  
Lin He ◽  
Peng Xiao ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Squamous Carcinoma ◽  
Diagnostic Value ◽  
Enzyme Linked Immunosorbent Assay ◽  
Cancer Type ◽  
Clinical Value ◽  
Early Screening ◽  
Significant Difference ◽  
Positive Rate ◽  
Diagnosis Of Lung Cancer

Abstract Aim: To prove the expression of heat shock protein 90α (HSP90α) in lung cancer and the clinical value of HSP90α and related markers in the diagnosis of lung cancer. Methods: The concentrations of HSP90α and related markers were detected in the blood of 560 lung cancer patients by enzyme-linked immunosorbent assay for analyzing the statistical differences of HSP90α in patients' age, gender, pathological types, tumour staging and metastasis status, as well as the differences and evaluate the value of HSP90α and related markers in lung cancer diagnosis. Results: The results showed no statistical difference in HSP90α among age and gender groups (P>0.05); In the group by lung cancer type, statistical differences were found in the HSP90α level between the small cell lung cancer (SCLC) group and the squamous carcinoma (SLC) group (P<0.05); In the group by staging, the HSP90α level of high staging was significantly higher than that low staging, and the HSP90α level at Ⅰ/Ⅱ/Ⅲ/Ⅳ shows statistical differences among the groups (P<0.05); The test result of HSP90α was higher in the metastatic group than in the non-metastatic group significantly, and the significant difference between the two groups (P<0.05). The r value of the HSP90α and related markers in the diagnosis of lung cancer: NSE>CEA>ProGRP>CF211 (P<0.05). Although HSP90α and related markers didn’t fit the satisfactory conformance, in terms of the positive rate of diagnosis, it were statistically differences in the diagnostic positive rate between HSP90α and each marker (P<0.01). Reducing HSP90α clinical references in lung cancer combined diagnosis can effectively improve the positive rate of the combined diagnosis. Conclusion: HSP90α has significant value on early screening and diagnosis of lung cancer. The combined application of HSP90α and related markers can improve the positive rate of early diagnosis of lung cancer effectively.

scholarly journals Diagnostic Value of HSP90α and Related Markers in Lung Cancer

2021 ◽  
Author(s):  
zhimin yuan ◽  
longhao wang ◽  
songlin hong ◽  
lin li ◽  
ting tang ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Squamous Carcinoma ◽  
Diagnostic Value ◽  
Enzyme Linked Immunosorbent Assay ◽  
Cancer Type ◽  
Clinical Value ◽  
Early Screening ◽  
Combined Application ◽  
Positive Rate ◽  
Diagnosis Of Lung Cancer

Abstract PurposeTo investigate the expression of heat shock protein 90α (HSP90α) in patients with lung cancer and the clinical value of HSP90α and other related markers in the diagnosis of lung cancer.MethodsThe plasma levels of HSP90α and related markers (CEA, NSE, CF211 and ProGRP) were detected in the blood of 560 patients with lung cancer by ELISA (enzyme-linked immunosorbent assay). Groups were divided according to the gender (male/female), age (age≤40, 41<age≤50, 51<age≤60, 61<age≤70 and age>70), types of lung cancer (small-cell, squamous carcinoma, adenocarcinoma, hybrid and other type), staging (Ⅰ, Ⅱ, Ⅲ and Ⅳ) and metastasis (metastasis and non-metastasis) separately. Wilcoxon Mann-Whitney test and Kruskal-Wallis test were used to compare statistical differences between two groups/among the multiple groups for each factor of HSP90α.ResultsNo statistical difference was found in plasma level of HSP90α among different age and gender groups (P> 0.05). In the group divided by lung cancer type, staging and metastasis status, there were statistical differences among different groups in HSP90α level (P< 0.05). R values of HSP90α correlated with other related markers in the diagnosis of lung cancer (P< 0.05). Although HSP90α and other related markers didn’t fit the satisfactory conformance, in terms of the positive rate of diagnosis, it was statistically differences in the diagnostic positive rate between HSP90α and each marker (P< 0.01). Reduced cut-off value of HSP90α in lung cancer can effectively improve the positive rate of diagnosis when combined with other tumor biomarkers.ConclusionsHSP90α has significant clinical value on early screening and diagnosis of lung cancer. The combined application of HSP90α and related markers can improve the positive rate of early diagnosis of lung cancer effectively.

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

2017 ◽  
Vol 313 (4) ◽  
pp. L664-L676 ◽  
Author(s):  
Laura M. López-Sánchez ◽  
Bernabé Jurado-Gámez ◽  
Nuria Feu-Collado ◽  
Araceli Valverde ◽  
Amanda Cañas ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Proteomic Analysis ◽  
Exhaled Breath Condensate ◽  
Characteristic Curve ◽  
Area Under The Curve ◽  
Diagnostic Value ◽  
Chronic Obstructive ◽  
Exhaled Breath ◽  
Diagnosis Of Lung Cancer ◽  
Breath Condensate

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

scholarly journals Evaluation Of The Diagnostic Value Of Electromagnetic Navigational Guided Targeted-Bronchoalveolar Lavage In The Diagnosis Of Lung Cancer

2020 ◽  
Vol 6 (4) ◽  
pp. 1-6
Author(s):  
Ismael Matus ◽  
Keyword(s):  
Lung Cancer ◽  
Diagnostic Yield ◽  
Pulmonary Nodules ◽  
Diagnostic Value ◽  
Electromagnetic Navigation ◽  
Diagnostic Bronchoscopy ◽  
Tissue Acquisition ◽  
Diagnosis Of Lung Cancer ◽  
The Ideal

Electromagnetic Navigation Bronchoscopy (ENB) is recommended for the evaluation of Peripheral Pulmonary Nodules (PPNs). Current diagnostic bronchoscopy and pulmonary nodule evaluation guidelines do not establish recommendations regarding the role of individual tissue acquisition techniques, the ideal combination or sequence of executing them to optimize diagnostic yield.

Urine β-2-glycoprotein 1 as a biomarker for diagnosis of systemic lupus erythematosus

Lupus ◽  
2021 ◽  
pp. 096120332110142
Author(s):  
Jung Sun Lee ◽  
Eun-Ju Lee ◽  
Jeonghun Yeom ◽  
Ji Seon Oh ◽  
Seokchan Hong ◽  
...  
Keyword(s):  
Systemic Lupus Erythematosus ◽  
Lupus Erythematosus ◽  
Medical Center ◽  
Characteristic Curve ◽  
Area Under The Curve ◽  
Diagnostic Value ◽  
Urine Samples ◽  
Enzyme Linked Immunosorbent Assay ◽  
Systemic Lupus ◽  
Asan Medical

Objective The need for a biomarker with robust sensitivity and specificity in diagnosing systemic lupus erythematosus (SLE) remains unmet. Compared with blood samples, urine samples are more easily collected; thus, we aimed to identify such a biomarker based on urinary proteomics which could distinguish patients with SLE from healthy controls (HCs). Methods Urine samples were collected from 76 SLE patients who visited rheumatology clinic in 2019 at Asan medical center and from 25 HCs. Urine proteins were analyzed using sequential windowed acquisition of all theoretical fragment ion spectra-mass spectrometry, and the candidate marker was confirmed by enzyme-linked immunosorbent assay (ELISA). Receiver operating characteristic curve analysis was used to determine the diagnostic value of the candidate biomarker. Results Of 1157 proteins quantified, 153 were differentially expressed in urine samples from HCs. Among them were previously known markers including α-1-acid glycoprotein 1, α-2-HS-glycoprotein, ceruloplasmin, and prostaglandin-H2 D-isomerase. Moreover, the amount of β-2 glycoprotein (APOH) was increased in the urine of patients with SLE. The ELISA results also showed the level of urine APOH was higher in patients with SLE than in HCs and patients with rheumatoid arthritis. Moreover, the level was not different between SLE patients with and without nephritis. The urine APOH had an area under the curve value of 0.946 at a cut-off value of 228.53 ng/mg (sensitivity 91.5%, specificity 92.0%) for the diagnosis of SLE. Conclusion The results indicate that the urine APOH level can be an appropriate screening tool in a clinical setting when SLE is suspected.

scholarly journals Radiomics is feasible for prediction of spread through air spaces in patients with nonsmall cell lung cancer

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yuki Onozato ◽  
Takahiro Nakajima ◽  
Hajime Yokota ◽  
Jyunichi Morimoto ◽  
Akira Nishiyama ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Predictive Model ◽  
Cell Lung Cancer ◽  
Early Stage ◽  
Characteristic Curve ◽  
Sublobar Resection ◽  
Tumor Spread ◽  
Early Stage Disease ◽  
Significant Difference ◽  
Spread Through Air Spaces

AbstractTumor spread through air spaces (STAS) in non-small-cell lung cancer (NSCLC) is known to influence a poor patient outcome, even in patients presenting with early-stage disease. However, the pre-operative diagnosis of STAS remains challenging. With the progress of radiomics-based analyses several attempts have been made to predict STAS based on radiological findings. In the present study, patients with NSCLC which is located peripherally and tumors ≤ 2 cm in size on computed tomography (CT) that were potential candidates for sublobar resection were enrolled in this study. The radiologic features of the targeted tumors on thin-section CT were extracted using the PyRadiomics v3.0 software package, and a predictive model for STAS was built using the t-test and XGBoost. Thirty-five out of 226 patients had a STAS histology. The predictive model of STAS indicated an area under the receiver-operator characteristic curve (AUC) of 0.77. There was no significant difference in the overall survival (OS) for lobectomy between the predicted-STAS (+) and (−) groups (p = 0.19), but an unfavorable OS for sublobar resection was indicated in the predicted-STAS (+) group (p < 0.01). These results suggest that radiomics with machine-learning helped to develop a favorable model of STAS (+) NSCLC, which might be useful for the proper selection of candidates who should undergo sublobar resection.

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