scholarly journals A panel of DNA methylation biomarkers for detection and improving diagnostic efficiency of lung cancer

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Bing Wei ◽  
Fengxin Wu ◽  
Wenqun Xing ◽  
Haibo Sun ◽  
Chi Yan ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Dna Methylation ◽  
Imaging Techniques ◽  
High Sensitivity ◽  
Clinical Problem ◽  
Diagnostic Value ◽  
Prostaglandin E ◽  
High Risk Population ◽  
Diagnostic Efficiency ◽  
Diagnosis Of Lung Cancer

AbstractLung cancer remains the leading cause of cancer deaths worldwide. Although low-dose spiral computed tomography (LDCT) screening is used for the detection of lung cancer in a high-risk population, false-positive results of LDCT remain a clinical problem. Here, we developed a blood test of a novel panel of three established lung cancer methylation biomarkers for lung cancer detection. Short stature homeobox 2 gene (SHOX2), ras association domain family 1A gene (RASSF1A), and prostaglandin E receptor 4 gene (PTGER4) methylation was analyzed in a training cohort of 351 individuals (197 controls, 154 cases) and validated from an independent cohort of 149 subjects (89 controls, 60 cases). The novel panel biomarkers distinguished between malignant and benign lung disease at high sensitivity and specificity: 87.0% sensitivity [95% CI 80.2–91.5%], 98.0% specificity [95% CI 94.9–99.4%]. Sensitivity in adenocarcinoma, squamous cell carcinoma, small cell lung cancer, and other lung cancer was 89.0%, 87.5%, 85.7%, and 77.8%, respectively. Notably, cancer patients in stage I and II showed high diagnostic sensitivity at 82.5% and 90.5%, respectively. Moreover, the diagnostic efficiency did not show bias toward age, gender, smoking, and the presence of other (nonlung) cancers. The performance of the panel in the validation cohort confirmed the diagnostic value. These findings clearly showed that this panel of DNA methylation biomarkers was effective in detecting lung cancer noninvasively and may provide clinical utility in stand-alone or in combination with current imaging techniques to improve the diagnosis of lung cancer.

scholarly journals A Panel of DNA Methylation Biomarkers for Detection and Improving Diagnostic Efficiency of Lung Cancer

2021 ◽  
Author(s):  
Bing Wei ◽  
Fengxin Wu ◽  
Wenqun Xing ◽  
Haibo Sun ◽  
Chi Yan ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Dna Methylation ◽  
Imaging Techniques ◽  
High Sensitivity ◽  
Clinical Problem ◽  
Prostaglandin E ◽  
High Risk Population ◽  
Diagnostic Efficiency ◽  
Gene Methylation ◽  
Diagnosis Of Lung Cancer

Abstract Lung cancer remains the leading cause of cancer deaths worldwide. Although low-dose spiral computed tomography (LDCT) screening is used for the detection of lung cancer in a high-risk population, false-positive results of LDCT remain a clinical problem. Here, we developed a blood test of a novel three gene methylation panel and validated the diagnostic efficiency from a total of 351 subjects (197 controls, 154 cases). DNA methylation of short stature homeobox 2 gene (SHOX2), ras association domain family 1A gene (RASSF1A), and prostaglandin E receptor 4 gene (PTGER4) could be used as a panel of biomarkers to distinguish between malignant and benign lung disease at high sensitivity and specificity: 87.0% sensitivity [95% CI 80.2-91.5%], 98.0% specificity [95% CI 94.9-99.4%]. Sensitivity in adenocarcinoma, squamous cell carcinoma, small cell lung cancer, and other lung cancer was 89.0%, 87.5%, 85.7%, and 77.8%, respectively. Notably, cancer patients in stage I and II showed high diagnostic sensitivity at 82.5% and 90.5%, respectively. Moreover, the diagnostic efficiency did not show bias toward age, gender, smoking, and the presence of other (nonlung) cancers. These findings clearly showed that this panel of DNA methylation biomarkers was effective in detecting lung cancer noninvasively and may provide clinical utility in stand-alone or in combination with current imaging techniques to improve the diagnosis of lung cancer.

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 Translational value of IDH1 and DNA methylation biomarkers in diagnosing lung cancers: a novel diagnostic panel of stage and histology-specificity

2019 ◽  
Vol 17 (1) ◽  
Author(s):  
Ruochuan Zang ◽  
Xinfeng Wang ◽  
Runsen Jin ◽  
Yuanyuan Lei ◽  
Jianbing Huang ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Dna Methylation ◽  
Subgroup Analysis ◽  
Diagnostic Value ◽  
Histological Type ◽  
Blood Levels ◽  
Prostaglandin E ◽  
Diagnostic Model ◽  
Lung Cancers ◽  
Diagnostic Panel

Abstract Background Lung cancer is the leading cause of cancer-related death worldwide, and the timely and serial assessment of low-dose computed tomography (LDCT) in high-risk populations remains a challenge. Furthermore, testing a single biomarker for the diagnosis of lung cancers is of relatively low effectiveness. Thus, a stronger diagnostic combination of blood biomarkers is needed to improve the diagnosis of non-small cell lung cancer (NSCLC). Methods The blood levels of individual biomarkers [IDH1, DNA methylation of short stature homeobox 2 gene (SHOX2), and prostaglandin E receptor 4 gene (PTGER4)] were measured and statistically analyzed in samples from healthy controls and patients with lung cancer. In total, 221 candidates were enrolled and randomly assigned into two groups for the training and validation of a diagnostic panel. Additionally, a subgroup analysis was performed in the whole cohort. Results A newly combined 3-marker diagnostic model for lung cancers was established and validated with area under the receiver operating characteristic (ROC) curve (AUC) values ranging from 0.835 to 0.905 in independent groups showing significantly stronger diagnostic value compared with a single tested biomarker. The sensitivity of the diagnostic model was as high as 86.1% and 80.0% in the training and validation sets, respectively. Although no apparent differences were found between the 3-marker and 2-marker models, the high clinical T-stage and histological type specificity of IDH1 and two other methylated DNA biomarkers were demonstrated in the subgroup analysis. Conclusions The combination of single biomarkers with high stage-specificity and histological type specificity (SHOX2 and PTGER4 DNA methylation and IDH1) showed better diagnostic performance in the detection of lung cancers compared with single marker assessment. A greater clinical utility of the panel may be developed by adding demographic/epidemiologic characteristics.

scholarly journals MicroRNA Biomarker hsa-miR-195-5p for Detecting the Risk of Lung Cancer

2020 ◽  
Vol 2020 ◽  
pp. 1-9 ◽  
Author(s):  
Lei Li ◽  
Tienan Feng ◽  
Weituo Zhang ◽  
Sumeng Gao ◽  
Ruoyang Wang ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Diagnostic Value ◽  
High Risk Population ◽  
Roc Curve Analysis ◽  
Lung Cancer Patients ◽  
Diagnose Lung Cancer ◽  
Copd Patients ◽  
Diagnosis Of Lung Cancer ◽  
Normal Controls ◽  
Lower Expression

Background. Lung cancer is one of the leading diagnosed cancers worldwide, and microRNAs could be used as biomarkers to diagnose lung cancer. hsa-miR-195 has been demonstrated to affect the prognosis of NSCLC (non-small-cell lung cancer) in a previous study. However, the diagnostic value of hsa-miR-195-5p in lung cancer has not been investigated. Methods. To evaluate the ability of hsa-miR-195-5p to diagnose lung cancer, we compared the expression of hsa-miR-195-5p in lung cancer patients, COPD patients, and normal controls. Receiver operating characteristic (ROC) curve analysis was performed to investigate the sensitivity and specificity of hsa-miR-195-5p. Coexpression network and pathway analysis were carried out to explore the mechanism. Results. We found that hsa-miR-195-5p had lower expression in lung cancer and COPD patients than in normal controls, and the AUC was 0.92 for diagnosing lung cancer. hsa-miR-143 correlated with hsa-miR-195-5p, and by combining these two microRNAs, the AUC was 0.97 for diagnosing lung cancer. Conclusions. hsa-miR-195-5p may act as a biomarker that contributes to the diagnosis of lung cancer and the detection of its high-risk population.

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.

The utility of six serum tumor markers in early detection of lung cancer

2019 ◽  
Author(s):  
Qingwen Jiang ◽  
Xu Zheng ◽  
Yiting Li ◽  
Weina Huang ◽  
Xinjian Li ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Sensitivity And Specificity ◽  
Operating Characteristic ◽  
Early Stage ◽  
High Sensitivity ◽  
Roc Curves ◽  
Serum Levels ◽  
Benign Diseases ◽  
Significant Difference ◽  
Diagnosis Of Lung Cancer

Abstract Background: Lung cancer has become the leading cause of cancer-related death in China. However, most of patients were diagnosed at advanced stage. Thus, novel lung cancer diagnostic tests, which can be used to screen individuals in early stage, are required.Methods: A total of 208 patients involving 161 cases of lung cancer and 47 cases of benign diseases were enrolled. Serum concentration of GTM, CETM, PTM, CTM, ETM and HTM were analyzed by kits according to the manufacturer’s guidelines.Results: The results showed significant difference in serum concentrations of GTM, CETM, PTM, CTM, ETM, and HTM between patients with lung cancer and benign diseases. In addition, when compared with benign diseases, higher levels of those six markers were also observed in patient with SCC and SCLC, but not for ADC. Receiver operating characteristic (ROC) curves were further suggested a high sensitivity and specificity of six markers to identify lung cancer.Conclusion: The serum levels of GTM, CETM, PTM, CTM, ETM and HTM in lung cancer were significantly higher than those of benign diseases. Moreover, these six biomarkers showed a high sensitivity and specificity to identify a patient with malignant. These findings suggested that detection of those six biomarkers in serum might be helpful for differential diagnosis of lung cancer.

scholarly journals Diagnostic value of SHOX2 DNA methylation in lung cancer: a meta-analysis

2015 ◽  
pp. 3433 ◽  
Author(s):  
Guo-Chen Duan ◽  
Qing-tao Zhao ◽  
Tao Guo ◽  
Hui-En Wang ◽  
Xiao-Peng Zhang ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Dna Methylation ◽  
Meta Analysis ◽  
Diagnostic Value

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.

A REVIEW ON COMPUTER AIDED DETECTION AND DIAGNOSIS OF LUNG CANCER NODULES

2012 ◽  
Vol 3 (3) ◽  
pp. 393-400 ◽  
Author(s):  
S.Shaik Parveen ◽  
Dr. C Kavitha
Keyword(s):  
Lung Cancer ◽  
Medical Information ◽  
Imaging Techniques ◽  
Computer Aided Detection ◽  
Ultrasound Diagnostics ◽  
Computer Aided ◽  
Detection And Diagnosis ◽  
Diagnosis Of Lung Cancer ◽  
Short Time ◽  
Early Detection And Diagnosis

In this paper, a attempt has been made to summarize some of the information about CAD and CADx for the purpose of early detection and diagnosis of lung cancer. Computer Aided Detection (CADe) and Computer Aided Diagnosis (CADx), are procedures in medical information that assist doctors in the interpretation of medical images. Imaging techniques in X-ray, MRI, and Ultrasound diagnostics yield a great deal of information, which the radiologist has to analyze and evaluate comprehensively in a short time. Thus, the use of digital computers to assist practitioners and physicians in diagnosing diseases and to offer a rapid access to medical information gained importance. CAD systems help scan digital images, e.g. from Computed Tomography (CT), for typical appearances and to highlight conspicuous sections, such as focal areas of lung nodules.

Sign in / Sign up

Export Citation Format

Share Document