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Diagnostic Performance of Plasma DNA Methylation Profiles in Lung Cancer, Pulmonary Fibrosis and COPD.

Wielscher M, Vierlinger K, Kegler U, Ziesche R, Gsur A, Weinhäusel A - EBioMedicine (2015)

Bottom Line: Disease-specific alterations of the cell-free DNA methylation status are frequently found in serum samples and are currently considered to be suitable biomarkers.The results were confirmed using an independent sample set (n = 46) by use of the four top markers discovered in the study (HOXD10, PAX9, PTPRN2, and STAG3) yielding an AUC of 0.85 (95%CI: 0.72-0.95).This technique was capable of distinguishing interrelated complex pulmonary diseases suggesting that multiplexed MSRE enrichment might be useful for simple and reliable diagnosis of diverse multifactorial disease states.

View Article: PubMed Central - PubMed

Affiliation: AIT - Austrian Institute of Technology, Health & Environment Department, Molecular Diagnostics Unit, Muthgasse 11/2, 1190 Vienna, Austria.

ABSTRACT
Disease-specific alterations of the cell-free DNA methylation status are frequently found in serum samples and are currently considered to be suitable biomarkers. Candidate markers were identified by bisulfite conversion-based genome-wide methylation screening of lung tissue from lung cancer, fibrotic ILD, and COPD. cfDNA from 400 μl serum (n = 204) served to test the diagnostic performance of these markers. Following methylation-sensitive restriction enzyme digestion and enrichment of methylated DNA via targeted amplification (multiplexed MSRE enrichment), a total of 96 markers were addressed by highly parallel qPCR. Lung cancer was efficiently separated from non-cancer and controls with a sensitivity of 87.8%, (95%CI: 0.67-0.97) and specificity 90.2%, (95%CI: 0.65-0.98). Cancer was distinguished from ILD with a specificity of 88%, (95%CI: 0.57-1), and COPD from cancer with a specificity of 88% (95%CI: 0.64-0.97). Separation of ILD from COPD and controls was possible with a sensitivity of 63.1% (95%CI: 0.4-0.78) and a specificity of 70% (95%CI: 0.54-0.81). The results were confirmed using an independent sample set (n = 46) by use of the four top markers discovered in the study (HOXD10, PAX9, PTPRN2, and STAG3) yielding an AUC of 0.85 (95%CI: 0.72-0.95). This technique was capable of distinguishing interrelated complex pulmonary diseases suggesting that multiplexed MSRE enrichment might be useful for simple and reliable diagnosis of diverse multifactorial disease states.

No MeSH data available.


Related in: MedlinePlus

Overview of cfDNA analysis. (A) Log2-transformed amount of cfDNA per ml serum/plasma is shown. Error bars indicate standard deviation of the mean. (B) The colored strings represent the cfDNAs. Those with CH3 groups represent methylated DNA, the purple strings demonstrate cfDNA from healthy tissue (purple) and lung cancer (red), respectively.cfDNA processing workflow: Each reaction was based on one serum sample (400 μl). During enzymatic digestion, methylation protected the methylated cfDNA strings which then served as templates for targeted amplification (Pre-amp). One multiplexed preamplification was performed per sample using 96 primer pairs as indicated by different colors. Amplification results are shown in black color. Specific methylation markers were detected by individual qPCR reactions. The lower panel shows the prediction and resampling approach (see Method section). (C) Fisher discriminant analysis was performed using the top 30 markers subsequently, the data were projected to 2 most informative projection directions (discriminant scores). The plot shows separation of patient samples based on the transformed data, which may be interpreted similar to a Principal Component Analysis. (D) ROC-curve analysis shows quality of separation of each analyzed disease versus healthy controls.
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f0010: Overview of cfDNA analysis. (A) Log2-transformed amount of cfDNA per ml serum/plasma is shown. Error bars indicate standard deviation of the mean. (B) The colored strings represent the cfDNAs. Those with CH3 groups represent methylated DNA, the purple strings demonstrate cfDNA from healthy tissue (purple) and lung cancer (red), respectively.cfDNA processing workflow: Each reaction was based on one serum sample (400 μl). During enzymatic digestion, methylation protected the methylated cfDNA strings which then served as templates for targeted amplification (Pre-amp). One multiplexed preamplification was performed per sample using 96 primer pairs as indicated by different colors. Amplification results are shown in black color. Specific methylation markers were detected by individual qPCR reactions. The lower panel shows the prediction and resampling approach (see Method section). (C) Fisher discriminant analysis was performed using the top 30 markers subsequently, the data were projected to 2 most informative projection directions (discriminant scores). The plot shows separation of patient samples based on the transformed data, which may be interpreted similar to a Principal Component Analysis. (D) ROC-curve analysis shows quality of separation of each analyzed disease versus healthy controls.

Mentions: All samples representing cancer, idiopathic pulmonary fibrosis (IPF; limited and advanced UIP), fibrotic non-specific interstitial pneumonia (NSIP), and COPD (GOLD grade 3) showed a significant difference regarding cfDNA concentrations compared to healthy controls (Fig. 2A and Supplemental Table S4). No difference was detected between serum and plasma samples (Supplemental Fig. S5). As previously shown, the highest amount of cfDNA was observed in lung cancer patients. cfDNA amounts in cancer increased by factor 2.8 to 35.6 ng/ml (95%CI: 29.05–43.23) for TNM stages I and II and 47.4 ng/ml (95%CI: 30.79–63.28), respectively, for TNM stages III and IV when compared to normal.


Diagnostic Performance of Plasma DNA Methylation Profiles in Lung Cancer, Pulmonary Fibrosis and COPD.

Wielscher M, Vierlinger K, Kegler U, Ziesche R, Gsur A, Weinhäusel A - EBioMedicine (2015)

Overview of cfDNA analysis. (A) Log2-transformed amount of cfDNA per ml serum/plasma is shown. Error bars indicate standard deviation of the mean. (B) The colored strings represent the cfDNAs. Those with CH3 groups represent methylated DNA, the purple strings demonstrate cfDNA from healthy tissue (purple) and lung cancer (red), respectively.cfDNA processing workflow: Each reaction was based on one serum sample (400 μl). During enzymatic digestion, methylation protected the methylated cfDNA strings which then served as templates for targeted amplification (Pre-amp). One multiplexed preamplification was performed per sample using 96 primer pairs as indicated by different colors. Amplification results are shown in black color. Specific methylation markers were detected by individual qPCR reactions. The lower panel shows the prediction and resampling approach (see Method section). (C) Fisher discriminant analysis was performed using the top 30 markers subsequently, the data were projected to 2 most informative projection directions (discriminant scores). The plot shows separation of patient samples based on the transformed data, which may be interpreted similar to a Principal Component Analysis. (D) ROC-curve analysis shows quality of separation of each analyzed disease versus healthy controls.
© Copyright Policy - CC BY-NC-ND
Related In: Results  -  Collection

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getmorefigures.php?uid=PMC4563135&req=5

f0010: Overview of cfDNA analysis. (A) Log2-transformed amount of cfDNA per ml serum/plasma is shown. Error bars indicate standard deviation of the mean. (B) The colored strings represent the cfDNAs. Those with CH3 groups represent methylated DNA, the purple strings demonstrate cfDNA from healthy tissue (purple) and lung cancer (red), respectively.cfDNA processing workflow: Each reaction was based on one serum sample (400 μl). During enzymatic digestion, methylation protected the methylated cfDNA strings which then served as templates for targeted amplification (Pre-amp). One multiplexed preamplification was performed per sample using 96 primer pairs as indicated by different colors. Amplification results are shown in black color. Specific methylation markers were detected by individual qPCR reactions. The lower panel shows the prediction and resampling approach (see Method section). (C) Fisher discriminant analysis was performed using the top 30 markers subsequently, the data were projected to 2 most informative projection directions (discriminant scores). The plot shows separation of patient samples based on the transformed data, which may be interpreted similar to a Principal Component Analysis. (D) ROC-curve analysis shows quality of separation of each analyzed disease versus healthy controls.
Mentions: All samples representing cancer, idiopathic pulmonary fibrosis (IPF; limited and advanced UIP), fibrotic non-specific interstitial pneumonia (NSIP), and COPD (GOLD grade 3) showed a significant difference regarding cfDNA concentrations compared to healthy controls (Fig. 2A and Supplemental Table S4). No difference was detected between serum and plasma samples (Supplemental Fig. S5). As previously shown, the highest amount of cfDNA was observed in lung cancer patients. cfDNA amounts in cancer increased by factor 2.8 to 35.6 ng/ml (95%CI: 29.05–43.23) for TNM stages I and II and 47.4 ng/ml (95%CI: 30.79–63.28), respectively, for TNM stages III and IV when compared to normal.

Bottom Line: Disease-specific alterations of the cell-free DNA methylation status are frequently found in serum samples and are currently considered to be suitable biomarkers.The results were confirmed using an independent sample set (n = 46) by use of the four top markers discovered in the study (HOXD10, PAX9, PTPRN2, and STAG3) yielding an AUC of 0.85 (95%CI: 0.72-0.95).This technique was capable of distinguishing interrelated complex pulmonary diseases suggesting that multiplexed MSRE enrichment might be useful for simple and reliable diagnosis of diverse multifactorial disease states.

View Article: PubMed Central - PubMed

Affiliation: AIT - Austrian Institute of Technology, Health & Environment Department, Molecular Diagnostics Unit, Muthgasse 11/2, 1190 Vienna, Austria.

ABSTRACT
Disease-specific alterations of the cell-free DNA methylation status are frequently found in serum samples and are currently considered to be suitable biomarkers. Candidate markers were identified by bisulfite conversion-based genome-wide methylation screening of lung tissue from lung cancer, fibrotic ILD, and COPD. cfDNA from 400 μl serum (n = 204) served to test the diagnostic performance of these markers. Following methylation-sensitive restriction enzyme digestion and enrichment of methylated DNA via targeted amplification (multiplexed MSRE enrichment), a total of 96 markers were addressed by highly parallel qPCR. Lung cancer was efficiently separated from non-cancer and controls with a sensitivity of 87.8%, (95%CI: 0.67-0.97) and specificity 90.2%, (95%CI: 0.65-0.98). Cancer was distinguished from ILD with a specificity of 88%, (95%CI: 0.57-1), and COPD from cancer with a specificity of 88% (95%CI: 0.64-0.97). Separation of ILD from COPD and controls was possible with a sensitivity of 63.1% (95%CI: 0.4-0.78) and a specificity of 70% (95%CI: 0.54-0.81). The results were confirmed using an independent sample set (n = 46) by use of the four top markers discovered in the study (HOXD10, PAX9, PTPRN2, and STAG3) yielding an AUC of 0.85 (95%CI: 0.72-0.95). This technique was capable of distinguishing interrelated complex pulmonary diseases suggesting that multiplexed MSRE enrichment might be useful for simple and reliable diagnosis of diverse multifactorial disease states.

No MeSH data available.


Related in: MedlinePlus