A Novel Diagnosis Method Based on Methylation Analysis of SHOX2 and Serum Biomarker for Early Stage Lung Cancer
Objectives: Lung cancer (LC) is often accompanied by significant methylation abnormalities. This study aimed to develop a decision tree (DT) accompanied the stature homeobox 2 gene (SHOX2) / prostaglandin E receptor 4 (PTGER4) gene DNA methylation with traditional tumor marker in the differential di...
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Published in | Cancer control Vol. 27; no. 1; p. 1073274820969703 |
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Main Authors | , , , , , , |
Format | Journal Article |
Language | English |
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SAGE Publications
01.10.2020
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Abstract | Objectives:
Lung cancer (LC) is often accompanied by significant methylation abnormalities. This study aimed to develop a decision tree (DT) accompanied the stature homeobox 2 gene (SHOX2) / prostaglandin E receptor 4 (PTGER4) gene DNA methylation with traditional tumor marker in the differential diagnosis of benign and malignant lung nodule.
Methods:
We performed a study with 104 patients enrolled in the LC group and 36 patients in the benign lung diseases group. All the clinical data of these patients were collected through electronic medical record. Total Methylation (TM) status of both SHOX2 and PTGER4 was defined as methylation levels of SHOX2 plus methylation levels of PTGER4. One-way analysis was used to compare the concentrations of serum samples and t-test was used to compare pairwise mean values between groups. Receiver operating curve (ROC) was used to evaluate the diagnostic value. Furthermore, the strategy was validated in 19 LC patients and 11 patients with benign lung diseases.
Results:
There were significant differences between the concentration of neuron-specific enolase (NSE), carcinoembryonic antigen (CEA), cytokeratin 19 fragments (CYFRA21 -1) and the methylation levels of SHOX2, PTGER4 and TM in lung benign diseases and cancer group. The AUCs of NSE, CEA, CYFRA21 -1, Methylation SHOX2, Methylation PTGER4 and TM were 0.721 (95% CI: 0.627–0.816), 0.753 (95% CI: 0.673–0.833) and 0.778(95% CI: 0.700–0.856), 0.851(0.786-0.916), 0.847(0.780-0.913) and 0.861(0.800-0.922) respectively. We developed a DT model with TM and CYFRA21 -1 used in this study, and the area under the curve (AUC) of DT was 0.921 and the sensitivity up to 0.856. In the validation cohort, the AUC of SHOX2, PTGER4 and TM was also much higher than traditional serum markers.
Conclusions:
Our results indicated that the DT model calculated from the TM and CYFRA21 -1 can accurately classify LC and benign diseases, which showed better diagnostic performance than traditional serum parameter. |
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AbstractList | Objectives:
Lung cancer (LC) is often accompanied by significant methylation abnormalities. This study aimed to develop a decision tree (DT) accompanied the stature homeobox 2 gene (SHOX2) / prostaglandin E receptor 4 (PTGER4) gene DNA methylation with traditional tumor marker in the differential diagnosis of benign and malignant lung nodule.
Methods:
We performed a study with 104 patients enrolled in the LC group and 36 patients in the benign lung diseases group. All the clinical data of these patients were collected through electronic medical record. Total Methylation (TM) status of both SHOX2 and PTGER4 was defined as methylation levels of SHOX2 plus methylation levels of PTGER4. One-way analysis was used to compare the concentrations of serum samples and t-test was used to compare pairwise mean values between groups. Receiver operating curve (ROC) was used to evaluate the diagnostic value. Furthermore, the strategy was validated in 19 LC patients and 11 patients with benign lung diseases.
Results:
There were significant differences between the concentration of neuron-specific enolase (NSE), carcinoembryonic antigen (CEA), cytokeratin 19 fragments (CYFRA21 -1) and the methylation levels of SHOX2, PTGER4 and TM in lung benign diseases and cancer group. The AUCs of NSE, CEA, CYFRA21 -1, Methylation SHOX2, Methylation PTGER4 and TM were 0.721 (95% CI: 0.627–0.816), 0.753 (95% CI: 0.673–0.833) and 0.778(95% CI: 0.700–0.856), 0.851(0.786-0.916), 0.847(0.780-0.913) and 0.861(0.800-0.922) respectively. We developed a DT model with TM and CYFRA21 -1 used in this study, and the area under the curve (AUC) of DT was 0.921 and the sensitivity up to 0.856. In the validation cohort, the AUC of SHOX2, PTGER4 and TM was also much higher than traditional serum markers.
Conclusions:
Our results indicated that the DT model calculated from the TM and CYFRA21 -1 can accurately classify LC and benign diseases, which showed better diagnostic performance than traditional serum parameter. Lung cancer (LC) is often accompanied by significant methylation abnormalities. This study aimed to develop a decision tree (DT) accompanied the stature homeobox 2 gene (SHOX2) / prostaglandin E receptor 4 (PTGER4) gene DNA methylation with traditional tumor marker in the differential diagnosis of benign and malignant lung nodule. We performed a study with 104 patients enrolled in the LC group and 36 patients in the benign lung diseases group. All the clinical data of these patients were collected through electronic medical record. Total Methylation (TM) status of both SHOX2 and PTGER4 was defined as methylation levels of SHOX2 plus methylation levels of PTGER4. One-way analysis was used to compare the concentrations of serum samples and t-test was used to compare pairwise mean values between groups. Receiver operating curve (ROC) was used to evaluate the diagnostic value. Furthermore, the strategy was validated in 19 LC patients and 11 patients with benign lung diseases. There were significant differences between the concentration of neuron-specific enolase (NSE), carcinoembryonic antigen (CEA), cytokeratin 19 fragments (CYFRA21 -1) and the methylation levels of SHOX2, PTGER4 and TM in lung benign diseases and cancer group. The AUCs of NSE, CEA, CYFRA21 -1, Methylation SHOX2, Methylation PTGER4 and TM were 0.721 (95% CI: 0.627-0.816), 0.753 (95% CI: 0.673-0.833) and 0.778(95% CI: 0.700-0.856), 0.851(0.786-0.916), 0.847(0.780-0.913) and 0.861(0.800-0.922) respectively. We developed a DT model with TM and CYFRA21 -1 used in this study, and the area under the curve (AUC) of DT was 0.921 and the sensitivity up to 0.856. In the validation cohort, the AUC of SHOX2, PTGER4 and TM was also much higher than traditional serum markers. Our results indicated that the DT model calculated from the TM and CYFRA21 -1 can accurately classify LC and benign diseases, which showed better diagnostic performance than traditional serum parameter. Objectives: Lung cancer (LC) is often accompanied by significant methylation abnormalities. This study aimed to develop a decision tree (DT) accompanied the stature homeobox 2 gene (SHOX2) / prostaglandin E receptor 4 (PTGER4) gene DNA methylation with traditional tumor marker in the differential diagnosis of benign and malignant lung nodule. Methods: We performed a study with 104 patients enrolled in the LC group and 36 patients in the benign lung diseases group. All the clinical data of these patients were collected through electronic medical record. Total Methylation (TM) status of both SHOX2 and PTGER4 was defined as methylation levels of SHOX2 plus methylation levels of PTGER4. One-way analysis was used to compare the concentrations of serum samples and t-test was used to compare pairwise mean values between groups. Receiver operating curve (ROC) was used to evaluate the diagnostic value. Furthermore, the strategy was validated in 19 LC patients and 11 patients with benign lung diseases. Results: There were significant differences between the concentration of neuron-specific enolase (NSE), carcinoembryonic antigen (CEA), cytokeratin 19 fragments (CYFRA21 -1) and the methylation levels of SHOX2, PTGER4 and TM in lung benign diseases and cancer group. The AUCs of NSE, CEA, CYFRA21 -1, Methylation SHOX2, Methylation PTGER4 and TM were 0.721 (95% CI: 0.627–0.816), 0.753 (95% CI: 0.673–0.833) and 0.778(95% CI: 0.700–0.856), 0.851(0.786-0.916), 0.847(0.780-0.913) and 0.861(0.800-0.922) respectively. We developed a DT model with TM and CYFRA21 -1 used in this study, and the area under the curve (AUC) of DT was 0.921 and the sensitivity up to 0.856. In the validation cohort, the AUC of SHOX2, PTGER4 and TM was also much higher than traditional serum markers. Conclusions: Our results indicated that the DT model calculated from the TM and CYFRA21 -1 can accurately classify LC and benign diseases, which showed better diagnostic performance than traditional serum parameter. Lung cancer (LC) is often accompanied by significant methylation abnormalities. This study aimed to develop a decision tree (DT) accompanied the stature homeobox 2 gene (SHOX2) / prostaglandin E receptor 4 (PTGER4) gene DNA methylation with traditional tumor marker in the differential diagnosis of benign and malignant lung nodule.OBJECTIVESLung cancer (LC) is often accompanied by significant methylation abnormalities. This study aimed to develop a decision tree (DT) accompanied the stature homeobox 2 gene (SHOX2) / prostaglandin E receptor 4 (PTGER4) gene DNA methylation with traditional tumor marker in the differential diagnosis of benign and malignant lung nodule.We performed a study with 104 patients enrolled in the LC group and 36 patients in the benign lung diseases group. All the clinical data of these patients were collected through electronic medical record. Total Methylation (TM) status of both SHOX2 and PTGER4 was defined as methylation levels of SHOX2 plus methylation levels of PTGER4. One-way analysis was used to compare the concentrations of serum samples and t-test was used to compare pairwise mean values between groups. Receiver operating curve (ROC) was used to evaluate the diagnostic value. Furthermore, the strategy was validated in 19 LC patients and 11 patients with benign lung diseases.METHODSWe performed a study with 104 patients enrolled in the LC group and 36 patients in the benign lung diseases group. All the clinical data of these patients were collected through electronic medical record. Total Methylation (TM) status of both SHOX2 and PTGER4 was defined as methylation levels of SHOX2 plus methylation levels of PTGER4. One-way analysis was used to compare the concentrations of serum samples and t-test was used to compare pairwise mean values between groups. Receiver operating curve (ROC) was used to evaluate the diagnostic value. Furthermore, the strategy was validated in 19 LC patients and 11 patients with benign lung diseases.There were significant differences between the concentration of neuron-specific enolase (NSE), carcinoembryonic antigen (CEA), cytokeratin 19 fragments (CYFRA21 -1) and the methylation levels of SHOX2, PTGER4 and TM in lung benign diseases and cancer group. The AUCs of NSE, CEA, CYFRA21 -1, Methylation SHOX2, Methylation PTGER4 and TM were 0.721 (95% CI: 0.627-0.816), 0.753 (95% CI: 0.673-0.833) and 0.778(95% CI: 0.700-0.856), 0.851(0.786-0.916), 0.847(0.780-0.913) and 0.861(0.800-0.922) respectively. We developed a DT model with TM and CYFRA21 -1 used in this study, and the area under the curve (AUC) of DT was 0.921 and the sensitivity up to 0.856. In the validation cohort, the AUC of SHOX2, PTGER4 and TM was also much higher than traditional serum markers.RESULTSThere were significant differences between the concentration of neuron-specific enolase (NSE), carcinoembryonic antigen (CEA), cytokeratin 19 fragments (CYFRA21 -1) and the methylation levels of SHOX2, PTGER4 and TM in lung benign diseases and cancer group. The AUCs of NSE, CEA, CYFRA21 -1, Methylation SHOX2, Methylation PTGER4 and TM were 0.721 (95% CI: 0.627-0.816), 0.753 (95% CI: 0.673-0.833) and 0.778(95% CI: 0.700-0.856), 0.851(0.786-0.916), 0.847(0.780-0.913) and 0.861(0.800-0.922) respectively. We developed a DT model with TM and CYFRA21 -1 used in this study, and the area under the curve (AUC) of DT was 0.921 and the sensitivity up to 0.856. In the validation cohort, the AUC of SHOX2, PTGER4 and TM was also much higher than traditional serum markers.Our results indicated that the DT model calculated from the TM and CYFRA21 -1 can accurately classify LC and benign diseases, which showed better diagnostic performance than traditional serum parameter.CONCLUSIONSOur results indicated that the DT model calculated from the TM and CYFRA21 -1 can accurately classify LC and benign diseases, which showed better diagnostic performance than traditional serum parameter. |
Author | Zhang, Shuishen Wang, Xueping Chen, Peisong Huang, Hao Ouyang, Juan Lin, Zhichao Huang, Wenhai |
AuthorAffiliation | 2 Department of Laboratory Medicine, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China 1 Department of Thoracic Surgery, Jiangmen Centre Hospital, Jiangmen, Guangdong, China 3 Department of Thoracic Surgery, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China 4 Department of Laboratory Medicine, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, China |
AuthorAffiliation_xml | – name: 3 Department of Thoracic Surgery, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China – name: 4 Department of Laboratory Medicine, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, China – name: 1 Department of Thoracic Surgery, Jiangmen Centre Hospital, Jiangmen, Guangdong, China – name: 2 Department of Laboratory Medicine, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China |
Author_xml | – sequence: 1 givenname: Wenhai surname: Huang fullname: Huang, Wenhai – sequence: 2 givenname: Hao surname: Huang fullname: Huang, Hao – sequence: 3 givenname: Shuishen surname: Zhang fullname: Zhang, Shuishen – sequence: 4 givenname: Xueping surname: Wang fullname: Wang, Xueping – sequence: 5 givenname: Juan surname: Ouyang fullname: Ouyang, Juan – sequence: 6 givenname: Zhichao surname: Lin fullname: Lin, Zhichao – sequence: 7 givenname: Peisong orcidid: 0000-0003-0640-3663 surname: Chen fullname: Chen, Peisong |
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Keywords | lung cancer diagnosis decision tree total methylation stature homeobox 2 |
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Lung cancer (LC) is often accompanied by significant methylation abnormalities. This study aimed to develop a decision tree (DT) accompanied the... Lung cancer (LC) is often accompanied by significant methylation abnormalities. This study aimed to develop a decision tree (DT) accompanied the stature... Objectives: Lung cancer (LC) is often accompanied by significant methylation abnormalities. This study aimed to develop a decision tree (DT) accompanied the... |
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SubjectTerms | Adult Aged Aged, 80 and over Benign Biomarkers, Tumor - blood Biomarkers, Tumor - genetics Carcinoembryonic antigen Cytokeratin Diagnosis, Differential Differential diagnosis DNA Methylation Early Detection of Cancer - methods Electronic medical records Epigenesis, Genetic Female Gene Expression Regulation, Neoplastic Homeobox Homeodomain Proteins - genetics Humans Lung - pathology Lung cancer Lung diseases Lung Neoplasms - blood Lung Neoplasms - diagnosis Lung Neoplasms - genetics Male Middle Aged Neoplasm Staging Original Research Paper Patients Phosphopyruvate hydratase Predictive Value of Tests Prospective Studies Prostaglandin E Receptors, Prostaglandin E, EP4 Subtype - genetics ROC Curve Tumor markers Young Adult |
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Title | A Novel Diagnosis Method Based on Methylation Analysis of SHOX2 and Serum Biomarker for Early Stage Lung Cancer |
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