Dataset Information

Detection of the DNA methylation of seven genes contribute to the early diagnosis of lung cancer.

ABSTRACT:

Background

Low-dose Computed Tomography (CT) is used for the detection of pulmonary nodules, but the ambiguous risk evaluation causes overdiagnosis. Here, we explored the significance of the DNA methylation of 7 genes including TAC1, CDO1, HOXA9, ZFP42, SOX17, RASSF1A and SHOX2 in the blood cfDNA samples in distinguishing lung cancer from benign nodules and healthy individuals.

Method

A total of 149 lung cancer patients [72 mass and 77 ground-glass nodules (GGNs)], 5 benign and 48 healthy individuals were tested and analyzed in this study. The lasso-logistic regression model was built for distinguishing cancer and control/healthy individuals or IA lung cancer and non-IA lung cancer cases.

Results

The positive rates of methylation of 7 genes were higher in the cancer group as compared with the healthy group. We constructed a model using age, sex and the ΔCt value of 7 gene methylation to distinguish lung cancer from benign and healthy individuals. The sensitivity, specificity and AUC (area under the curve) were 86.7%, 81.4% and 0.891, respectively. Also, we assessed the significance of 7 gene methylation together with patients' age and sex in distinguishing of GGNs type from the mass type. The sensitivity, specificity and AUC were 77.1%, 65.8% and 0.753, respectively. Furthermore, the methylation positive rates of CDO1 and SHOX2 were different between I-IV stages of lung cancer. Specifically, the positive rate of CDO1 methylation was higher in the non-IA group as compared with the IA group.

Conclusion

Collectively, this study reveals that the methylation of 7 genes has a big significance in the diagnosis of lung cancer with high sensitivity and specificity. Also, the 7 genes present with certain significance in distinguishing the GGN type lung cancer, as well as different stages.

SUBMITTER: Du C

PROVIDER: S-EPMC10844440 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Detection of the DNA methylation of seven genes contribute to the early diagnosis of lung cancer.

Du Chaoxiang C Tan Lijie L Xiao Xiao X Xin Beibei B Xiong Hui H Zhang Yuying Y Ke Zhonghe Z Yin Jun J

Journal of cancer research and clinical oncology 20240205 2

<h4>Background</h4>Low-dose Computed Tomography (CT) is used for the detection of pulmonary nodules, but the ambiguous risk evaluation causes overdiagnosis. Here, we explored the significance of the DNA methylation of 7 genes including TAC1, CDO1, HOXA9, ZFP42, SOX17, RASSF1A and SHOX2 in the blood cfDNA samples in distinguishing lung cancer from benign nodules and healthy individuals.<h4>Method</h4>A total of 149 lung cancer patients [72 mass and 77 ground-glass nodules (GGNs)], 5 benign and 48 ...[more]

PMID: 38315228

Similar Datasets

Project description:ObjectiveSputum is a source of exfoliated respiratory epithelial cells transformed early in lung carcinogenesis. Malignant cells are hypomethylated and contain less genomic 5-methylcytosine (5mC). Validating a test that recognizes and quantifies aberrantly hypomethylated cells in sputum, we assessed its potential as a screening tool for detecting early-stage non-small cell lung cancer.MethodsCells extracted from sputum were immunofluorescence labeled with an anti-5-methylcytosine antibody and counterstained with 4',6-diamidino-2-phenylindole (DAPI) delineating global nuclear DNA (gDNA). Via confocal scanning and 3-dimensional image analysis, fluorescence 5mC and DAPI signals were measured in segmented cell nuclei, and a 5mC/DAPI co-distribution map was generated for each imaged cell. Cells were classified as hypomethylated based on 5mC load and 5mC/DAPI co-distribution. The proportion of hypomethylated epithelial cells in the sputum determines whether a patient has lung cancer.ResultsA total of 88 subjects were enrolled: 12 healthy subjects; 34 high-risk subjects with benign chronic lung disorders (10 with chronic obstructive pulmonary disease, 24 with idiopathic pulmonary fibrosis), and 43 subjects with non-small cell lung cancer (27 with stage I-II and 16 with stage III-IV). The test identified early-stage non-small cell lung cancer and distinguished it from the high-risk group with 95.8% (95% confidence interval, 78.9-99.9) sensitivity and 41.2% (95% confidence interval, 24.6-59.3) specificity applying only 5mC, 95.8% (95% confidence interval, 78.9-99.9) sensitivity and 26.5% (95% confidence interval, 12.9-44.4) specificity using solely 5mC/DAPI index, and 100% (95% confidence interval, 98.7-100) sensitivity and 26.1% (95% confidence interval, 26.2-27.8) specificity with the combined parameters.ConclusionsWe tested and validated a novel, noninvasive, highly sensitive screening test for non-small cell lung cancer. With the use of sputum, our test may impact lung cancer screening, evaluation of pulmonary nodules, and cancer surveillance algorithms.

Project description:BackgroundLung cancer remains the leading cause of cancer mortality worldwide. Early detection of lung cancer helps improve treatment and survival. Numerous aberrant DNA methylations have been reported in early-stage lung cancer. Here, we sought to identify novel DNA methylation biomarkers that could potentially be used for noninvasive early diagnosis of lung cancers.MethodsThis prospective-specimen collection and retrospective-blinded-evaluation trial enrolled a total of 317 participants (198 tissues and 119 plasmas) comprising healthy controls, patients with lung cancer and benign disease between January 2020 and December 2021. Tissue and plasma samples were subjected to targeted bisulfite sequencing with a lung cancer specific panel targeting 9,307 differential methylation regions (DMRs). DMRs associated with lung cancer were identified by comparing the methylation profiles of tissue samples from patients with lung cancer and benign disease. Markers were selected with minimum redundancy and maximum relevance algorithm. A prediction model for lung cancer diagnosis was built through logistic regression algorithm and validated independently in tissue samples. Furthermore, the performance of this developed model was evaluated in a set of plasma cell-free DNA (cfDNA) samples.ResultsWe identified 7 DMRs corresponding to 7 differentially methylated genes (DMGs) including HOXB4, HOXA7, HOXD8, ITGA4, ZNF808, PTGER4, and B3GNTL1 that were highly associated with lung cancer by comparing the methylation profiles of lung cancer and benign nodule tissue. Based on the 7-DMR biomarker panel, we developed a new diagnostic model in tissue samples, termed "7-DMR model", to distinguish lung cancers from benign diseases, achieving AUCs of 0.97 (95%CI: 0.93-1.00)/0.96 (0.92-1.00), sensitivities of 0.89 (0.82-0.95)/0.92 (0.86-0.98), specificities of 0.94 (0.89-0.99)/1.00 (1.00-1.00), and accuracies of 0.90 (0.84-0.96)/0.94 (0.89-0.99) in the discovery cohort (n = 96) and the independent validation cohort (n = 81), respectively. Furthermore, the 7-DMR model was applied to noninvasive discrimination of lung cancers and non-lung cancers including benign lung diseases and healthy controls in an independent validation cohort of plasma samples (n = 106), yielding an AUC of 0.94 (0.86-1.00), sensitivity of 0.81 (0.73-0.88), specificity of 0.98 (0.95-1.00), and accuracy of 0.93 (0.89-0.98).ConclusionThe 7 novel DMRs could be promising methylation biomarkers that merits further development as a noninvasive test for early detection of lung cancer.

Dataset Information

Detection of the DNA methylation of seven genes contribute to the early diagnosis of lung cancer.

Background

Method

Results

Conclusion

Publications

Detection of the DNA methylation of seven genes contribute to the early diagnosis of lung cancer.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets