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fully methylated human genomic dna  (Zymo Research)


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    Zymo Research fully methylated human genomic dna
    Schematic and performance of the tMCTA-seq method (A) The tMCTA-seq begins with bisulfite treatment, converting unmethylated CpG tandems in CGIs to UpG tandems, leaving <t>methylated</t> CGIs unaffected. In the first step, primer A, which comprises a semi-random sequence with a CpG site at the 3′-end, a unique molecular identifier (UMI) sequence in the middle, and an anchor sequence at the 5′-end, anneals semi-randomly to converted <t>DNA</t> and extends. This step preferentially amplifies methylated CGIs due to their higher density of methylated CpG sites. Next, a set of locus-specific primers is used for targeted amplification in combination with primer TA (sharing partial sequence homology with primer A). Primer B, containing the “CGCGCGG” sequence, serves as a universal inner nested primer to selectively amplify methylated CpG tandem sites. Finally, indexed primers C and D were employed for PCR amplification to generate the sequencing library. (B) The input and captured molecules of 110 mCGCGCGG-CpG (upper: enlarged view of the dashed areas). The FMG was diluted from 150 pg (equivalent to 110 × 150 ÷ 3.3 = 5,000 molecules for the total 110 sites) down to 2.3 pg (equivalent to 110 × 2.3 ÷ 3.3 = 77 molecules for the total 110 sites) and spiked into 6 ng of WBC <t>gDNA.</t> (C) The captured molecules, and (D) sequencing depth of 110 mCGCGCGG-CpGs in MCTA-seq and tMCTA-seq, with 150 pg of FMGs spiked into 6 ng of WBC gDNA. Data are represented as the mean ± SD. ∗ p < 0.05, ∗∗ p < 0.01, two-tailed Mann–Whitney-Wilcoxon test.
    Fully Methylated Human Genomic Dna, supplied by Zymo Research, used in various techniques. Bioz Stars score: 95/100, based on 394 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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    Images

    1) Product Images from "A targeted DNA methylation method for detecting gastrointestinal cancer in circulating cell-free DNA"

    Article Title: A targeted DNA methylation method for detecting gastrointestinal cancer in circulating cell-free DNA

    Journal: iScience

    doi: 10.1016/j.isci.2025.114342

    Schematic and performance of the tMCTA-seq method (A) The tMCTA-seq begins with bisulfite treatment, converting unmethylated CpG tandems in CGIs to UpG tandems, leaving methylated CGIs unaffected. In the first step, primer A, which comprises a semi-random sequence with a CpG site at the 3′-end, a unique molecular identifier (UMI) sequence in the middle, and an anchor sequence at the 5′-end, anneals semi-randomly to converted DNA and extends. This step preferentially amplifies methylated CGIs due to their higher density of methylated CpG sites. Next, a set of locus-specific primers is used for targeted amplification in combination with primer TA (sharing partial sequence homology with primer A). Primer B, containing the “CGCGCGG” sequence, serves as a universal inner nested primer to selectively amplify methylated CpG tandem sites. Finally, indexed primers C and D were employed for PCR amplification to generate the sequencing library. (B) The input and captured molecules of 110 mCGCGCGG-CpG (upper: enlarged view of the dashed areas). The FMG was diluted from 150 pg (equivalent to 110 × 150 ÷ 3.3 = 5,000 molecules for the total 110 sites) down to 2.3 pg (equivalent to 110 × 2.3 ÷ 3.3 = 77 molecules for the total 110 sites) and spiked into 6 ng of WBC gDNA. (C) The captured molecules, and (D) sequencing depth of 110 mCGCGCGG-CpGs in MCTA-seq and tMCTA-seq, with 150 pg of FMGs spiked into 6 ng of WBC gDNA. Data are represented as the mean ± SD. ∗ p < 0.05, ∗∗ p < 0.01, two-tailed Mann–Whitney-Wilcoxon test.
    Figure Legend Snippet: Schematic and performance of the tMCTA-seq method (A) The tMCTA-seq begins with bisulfite treatment, converting unmethylated CpG tandems in CGIs to UpG tandems, leaving methylated CGIs unaffected. In the first step, primer A, which comprises a semi-random sequence with a CpG site at the 3′-end, a unique molecular identifier (UMI) sequence in the middle, and an anchor sequence at the 5′-end, anneals semi-randomly to converted DNA and extends. This step preferentially amplifies methylated CGIs due to their higher density of methylated CpG sites. Next, a set of locus-specific primers is used for targeted amplification in combination with primer TA (sharing partial sequence homology with primer A). Primer B, containing the “CGCGCGG” sequence, serves as a universal inner nested primer to selectively amplify methylated CpG tandem sites. Finally, indexed primers C and D were employed for PCR amplification to generate the sequencing library. (B) The input and captured molecules of 110 mCGCGCGG-CpG (upper: enlarged view of the dashed areas). The FMG was diluted from 150 pg (equivalent to 110 × 150 ÷ 3.3 = 5,000 molecules for the total 110 sites) down to 2.3 pg (equivalent to 110 × 2.3 ÷ 3.3 = 77 molecules for the total 110 sites) and spiked into 6 ng of WBC gDNA. (C) The captured molecules, and (D) sequencing depth of 110 mCGCGCGG-CpGs in MCTA-seq and tMCTA-seq, with 150 pg of FMGs spiked into 6 ng of WBC gDNA. Data are represented as the mean ± SD. ∗ p < 0.05, ∗∗ p < 0.01, two-tailed Mann–Whitney-Wilcoxon test.

    Techniques Used: Methylation, Sequencing, Amplification, Two Tailed Test, MANN-WHITNEY



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    Schematic and performance of the tMCTA-seq method (A) The tMCTA-seq begins with bisulfite treatment, converting unmethylated CpG tandems in CGIs to UpG tandems, leaving <t>methylated</t> CGIs unaffected. In the first step, primer A, which comprises a semi-random sequence with a CpG site at the 3′-end, a unique molecular identifier (UMI) sequence in the middle, and an anchor sequence at the 5′-end, anneals semi-randomly to converted <t>DNA</t> and extends. This step preferentially amplifies methylated CGIs due to their higher density of methylated CpG sites. Next, a set of locus-specific primers is used for targeted amplification in combination with primer TA (sharing partial sequence homology with primer A). Primer B, containing the “CGCGCGG” sequence, serves as a universal inner nested primer to selectively amplify methylated CpG tandem sites. Finally, indexed primers C and D were employed for PCR amplification to generate the sequencing library. (B) The input and captured molecules of 110 mCGCGCGG-CpG (upper: enlarged view of the dashed areas). The FMG was diluted from 150 pg (equivalent to 110 × 150 ÷ 3.3 = 5,000 molecules for the total 110 sites) down to 2.3 pg (equivalent to 110 × 2.3 ÷ 3.3 = 77 molecules for the total 110 sites) and spiked into 6 ng of WBC <t>gDNA.</t> (C) The captured molecules, and (D) sequencing depth of 110 mCGCGCGG-CpGs in MCTA-seq and tMCTA-seq, with 150 pg of FMGs spiked into 6 ng of WBC gDNA. Data are represented as the mean ± SD. ∗ p < 0.05, ∗∗ p < 0.01, two-tailed Mann–Whitney-Wilcoxon test.
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    Image Search Results


    Schematic and performance of the tMCTA-seq method (A) The tMCTA-seq begins with bisulfite treatment, converting unmethylated CpG tandems in CGIs to UpG tandems, leaving methylated CGIs unaffected. In the first step, primer A, which comprises a semi-random sequence with a CpG site at the 3′-end, a unique molecular identifier (UMI) sequence in the middle, and an anchor sequence at the 5′-end, anneals semi-randomly to converted DNA and extends. This step preferentially amplifies methylated CGIs due to their higher density of methylated CpG sites. Next, a set of locus-specific primers is used for targeted amplification in combination with primer TA (sharing partial sequence homology with primer A). Primer B, containing the “CGCGCGG” sequence, serves as a universal inner nested primer to selectively amplify methylated CpG tandem sites. Finally, indexed primers C and D were employed for PCR amplification to generate the sequencing library. (B) The input and captured molecules of 110 mCGCGCGG-CpG (upper: enlarged view of the dashed areas). The FMG was diluted from 150 pg (equivalent to 110 × 150 ÷ 3.3 = 5,000 molecules for the total 110 sites) down to 2.3 pg (equivalent to 110 × 2.3 ÷ 3.3 = 77 molecules for the total 110 sites) and spiked into 6 ng of WBC gDNA. (C) The captured molecules, and (D) sequencing depth of 110 mCGCGCGG-CpGs in MCTA-seq and tMCTA-seq, with 150 pg of FMGs spiked into 6 ng of WBC gDNA. Data are represented as the mean ± SD. ∗ p < 0.05, ∗∗ p < 0.01, two-tailed Mann–Whitney-Wilcoxon test.

    Journal: iScience

    Article Title: A targeted DNA methylation method for detecting gastrointestinal cancer in circulating cell-free DNA

    doi: 10.1016/j.isci.2025.114342

    Figure Lengend Snippet: Schematic and performance of the tMCTA-seq method (A) The tMCTA-seq begins with bisulfite treatment, converting unmethylated CpG tandems in CGIs to UpG tandems, leaving methylated CGIs unaffected. In the first step, primer A, which comprises a semi-random sequence with a CpG site at the 3′-end, a unique molecular identifier (UMI) sequence in the middle, and an anchor sequence at the 5′-end, anneals semi-randomly to converted DNA and extends. This step preferentially amplifies methylated CGIs due to their higher density of methylated CpG sites. Next, a set of locus-specific primers is used for targeted amplification in combination with primer TA (sharing partial sequence homology with primer A). Primer B, containing the “CGCGCGG” sequence, serves as a universal inner nested primer to selectively amplify methylated CpG tandem sites. Finally, indexed primers C and D were employed for PCR amplification to generate the sequencing library. (B) The input and captured molecules of 110 mCGCGCGG-CpG (upper: enlarged view of the dashed areas). The FMG was diluted from 150 pg (equivalent to 110 × 150 ÷ 3.3 = 5,000 molecules for the total 110 sites) down to 2.3 pg (equivalent to 110 × 2.3 ÷ 3.3 = 77 molecules for the total 110 sites) and spiked into 6 ng of WBC gDNA. (C) The captured molecules, and (D) sequencing depth of 110 mCGCGCGG-CpGs in MCTA-seq and tMCTA-seq, with 150 pg of FMGs spiked into 6 ng of WBC gDNA. Data are represented as the mean ± SD. ∗ p < 0.05, ∗∗ p < 0.01, two-tailed Mann–Whitney-Wilcoxon test.

    Article Snippet: Fully methylated human genomic DNA (FMG) , Zymo Research , D5014.

    Techniques: Methylation, Sequencing, Amplification, Two Tailed Test, MANN-WHITNEY

    MeD-seq wet laboratory and bioinformatics platform. ( A ) Genomic DNA is digested with LpnPI, followed by DNA repair, adaptor ligation to 32-bp fragments, size fractionation, amplification, and sequencing. ( B ) Sequencing reads are trimmed, filtered based on the CpG sequence, and aligned to the genome. ( C ) Nucleotide frequency plotted against the position in the sequencing reads, showing enrichment of CG nucleotides around 16–17 bp from the start. ( D ) Alignment of LpnPI, MspJI, and FspEI CpG-filtered MeD-seq reads obtained using fibroblast DNA. ( E ) Sequencing read profiles of the HOXA and KCNQ1 loci obtained with fibroblast DNA using LpnPI, MspJI, and FspEI. ( F ) Pearson correlation analysis of MeD-seq read counts of TSSs for LpnPI-MspJI ( left ), LpnPI-FspEI ( middle ), and FspEI-MspJI ( right ) comparisons. ( G ) Pearson correlation analysis of read counts of TSSs for technical replicates digested with LpnPI ( left ) and MspJI ( right ).

    Journal: Genome Research

    Article Title: Genome-wide DNA methylation profiling using the methylation-dependent restriction enzyme LpnPI

    doi: 10.1101/gr.222885.117

    Figure Lengend Snippet: MeD-seq wet laboratory and bioinformatics platform. ( A ) Genomic DNA is digested with LpnPI, followed by DNA repair, adaptor ligation to 32-bp fragments, size fractionation, amplification, and sequencing. ( B ) Sequencing reads are trimmed, filtered based on the CpG sequence, and aligned to the genome. ( C ) Nucleotide frequency plotted against the position in the sequencing reads, showing enrichment of CG nucleotides around 16–17 bp from the start. ( D ) Alignment of LpnPI, MspJI, and FspEI CpG-filtered MeD-seq reads obtained using fibroblast DNA. ( E ) Sequencing read profiles of the HOXA and KCNQ1 loci obtained with fibroblast DNA using LpnPI, MspJI, and FspEI. ( F ) Pearson correlation analysis of MeD-seq read counts of TSSs for LpnPI-MspJI ( left ), LpnPI-FspEI ( middle ), and FspEI-MspJI ( right ) comparisons. ( G ) Pearson correlation analysis of read counts of TSSs for technical replicates digested with LpnPI ( left ) and MspJI ( right ).

    Article Snippet: Fully methylated human genomic DNA was ordered from EpigenDX (Human High Methylated DNA control, 80-8061-HGHM5, HS091514) and HUES8 were acquired via NIH.

    Techniques: Ligation, Fractionation, Amplification, Sequencing

    Detection of DNA methylation genome wide. ( A ) Histogram showing sequencing read size of all reads (dark blue) and reads that passed the LpnPI filter (light blue) obtained with MeD-seq applied on human fibroblast DNA. ( B ) Sequencing reads larger ( top ) or shorter ( bottom ) than 32–33 bp shown in F display two LpnPI recognition sequences 16–17 bp from the end. ( C ) Alignment of LpnPI-filtered MeD-seq reads obtained using fibroblast DNA ( left ) and 100% methylated DNA ( right ). ( D ) Pearson correlation analysis of MeD-seq read counts of CpG islands for technical ( left ) and biological ( right ) replicates. ( E ) MeD-seq DNA methylation profiles of the HOXA cluster obtained with fibroblast DNA ( top two panels) and 100% methylated control DNA ( bottom two panels). ( F ) Ratio of digested LpnPI sites in CpG islands and TSSs for 100% methylated control DNA ( top ) and fibroblast DNA ( bottom ). ( G ) Overview and characteristics of LpnPI sites in CpG islands, TSSs (2 kb), gene bodies, and repetitive elements genome wide. Detection percentages are based on 100% methylated DNA. ( H ) Gene density plots showing distribution of LpnPI sites and CpG dinucleotides shown in 100 bins before the TSS, in the gene body, and behind the transcription stop.

    Journal: Genome Research

    Article Title: Genome-wide DNA methylation profiling using the methylation-dependent restriction enzyme LpnPI

    doi: 10.1101/gr.222885.117

    Figure Lengend Snippet: Detection of DNA methylation genome wide. ( A ) Histogram showing sequencing read size of all reads (dark blue) and reads that passed the LpnPI filter (light blue) obtained with MeD-seq applied on human fibroblast DNA. ( B ) Sequencing reads larger ( top ) or shorter ( bottom ) than 32–33 bp shown in F display two LpnPI recognition sequences 16–17 bp from the end. ( C ) Alignment of LpnPI-filtered MeD-seq reads obtained using fibroblast DNA ( left ) and 100% methylated DNA ( right ). ( D ) Pearson correlation analysis of MeD-seq read counts of CpG islands for technical ( left ) and biological ( right ) replicates. ( E ) MeD-seq DNA methylation profiles of the HOXA cluster obtained with fibroblast DNA ( top two panels) and 100% methylated control DNA ( bottom two panels). ( F ) Ratio of digested LpnPI sites in CpG islands and TSSs for 100% methylated control DNA ( top ) and fibroblast DNA ( bottom ). ( G ) Overview and characteristics of LpnPI sites in CpG islands, TSSs (2 kb), gene bodies, and repetitive elements genome wide. Detection percentages are based on 100% methylated DNA. ( H ) Gene density plots showing distribution of LpnPI sites and CpG dinucleotides shown in 100 bins before the TSS, in the gene body, and behind the transcription stop.

    Article Snippet: Fully methylated human genomic DNA was ordered from EpigenDX (Human High Methylated DNA control, 80-8061-HGHM5, HS091514) and HUES8 were acquired via NIH.

    Techniques: DNA Methylation Assay, Genome Wide, Sequencing, Methylation, Control

    MeD-seq versus WGBS, MeDIP, and the Infinium 450K technology. ( A ) MeD-seq, WGBS, and MeDIP DNA methylation profiles and Infinium 450K scores for a representative locus on Chromosome 19, obtained with human ES cell DNA. MeD-seq and MeDIP read count or relative DNA methylation level (0–1) is shown for all CpG sites. Infinium 450K scores: (dark blue) high CpG methylation; (light blue) intermediate DNA methylation; (green) low DNA methylation (based on B -value scores). ( B ) Correlation plots for MeD-seq:WGBS ( left ) and MeD-seq:MeDIP ( right ) comparison of CpG islands. ( C ) As in B , but now for TSS. ( D ) Overview of Pearson (P) and Spearman (S) correlation scores for different comparisons. ( E ) MeD-seq reads in a 100-bp window plotted against Infinium 450K scores binned in 10 different groups with increasing methylation scores for ES cell DNA. ( F ) As in B , but now with MeD-seq reads obtained from 100% methylated control DNA using 450K bins obtained with ES cell DNA.

    Journal: Genome Research

    Article Title: Genome-wide DNA methylation profiling using the methylation-dependent restriction enzyme LpnPI

    doi: 10.1101/gr.222885.117

    Figure Lengend Snippet: MeD-seq versus WGBS, MeDIP, and the Infinium 450K technology. ( A ) MeD-seq, WGBS, and MeDIP DNA methylation profiles and Infinium 450K scores for a representative locus on Chromosome 19, obtained with human ES cell DNA. MeD-seq and MeDIP read count or relative DNA methylation level (0–1) is shown for all CpG sites. Infinium 450K scores: (dark blue) high CpG methylation; (light blue) intermediate DNA methylation; (green) low DNA methylation (based on B -value scores). ( B ) Correlation plots for MeD-seq:WGBS ( left ) and MeD-seq:MeDIP ( right ) comparison of CpG islands. ( C ) As in B , but now for TSS. ( D ) Overview of Pearson (P) and Spearman (S) correlation scores for different comparisons. ( E ) MeD-seq reads in a 100-bp window plotted against Infinium 450K scores binned in 10 different groups with increasing methylation scores for ES cell DNA. ( F ) As in B , but now with MeD-seq reads obtained from 100% methylated control DNA using 450K bins obtained with ES cell DNA.

    Article Snippet: Fully methylated human genomic DNA was ordered from EpigenDX (Human High Methylated DNA control, 80-8061-HGHM5, HS091514) and HUES8 were acquired via NIH.

    Techniques: Methylated DNA Immunoprecipitation, DNA Methylation Assay, CpG Methylation Assay, Comparison, Methylation, Control

    Tissue-specific DMRs. ( A ) DMR counts for TSSs and CpG islands and Pearson correlation analysis of TSSs upon in silico dilution starting with 150 million reads. ( B ) DNA was collected of available organs (green) from 10 different female patients. ( C ) Correlation analysis of TSS read counts between blood samples of different patients. ( D ) Correlation analysis of TSS read counts between different organs of the same patients. ( E ) MeD-seq tracks of ribosomal RNA cluster in DNA of blood and thyroid from patients 8, 3, and 4. ( F ) Unsupervised hierarchical clustering of tissues based on differentially methylated CpG islands. Statistical significance was called by χ 2 testing and Bonferroni correction, the Z-scores of the read count are shown in the heatmap. ( G ) MeD-seq tracks of the HOXB and HOXD loci displaying differential methylation in TSS and CpG islands in different tissues.

    Journal: Genome Research

    Article Title: Genome-wide DNA methylation profiling using the methylation-dependent restriction enzyme LpnPI

    doi: 10.1101/gr.222885.117

    Figure Lengend Snippet: Tissue-specific DMRs. ( A ) DMR counts for TSSs and CpG islands and Pearson correlation analysis of TSSs upon in silico dilution starting with 150 million reads. ( B ) DNA was collected of available organs (green) from 10 different female patients. ( C ) Correlation analysis of TSS read counts between blood samples of different patients. ( D ) Correlation analysis of TSS read counts between different organs of the same patients. ( E ) MeD-seq tracks of ribosomal RNA cluster in DNA of blood and thyroid from patients 8, 3, and 4. ( F ) Unsupervised hierarchical clustering of tissues based on differentially methylated CpG islands. Statistical significance was called by χ 2 testing and Bonferroni correction, the Z-scores of the read count are shown in the heatmap. ( G ) MeD-seq tracks of the HOXB and HOXD loci displaying differential methylation in TSS and CpG islands in different tissues.

    Article Snippet: Fully methylated human genomic DNA was ordered from EpigenDX (Human High Methylated DNA control, 80-8061-HGHM5, HS091514) and HUES8 were acquired via NIH.

    Techniques: In Silico, Methylation

    Measured  methylated  BCAT1 and IKZF1 positivity rates by clinical findings.

    Journal: PLoS ONE

    Article Title: A Two-Gene Blood Test for Methylated DNA Sensitive for Colorectal Cancer

    doi: 10.1371/journal.pone.0125041

    Figure Lengend Snippet: Measured methylated BCAT1 and IKZF1 positivity rates by clinical findings.

    Article Snippet: Pooled plasma from gender- and age-matched donors under 30 years of age was commercially sourced (Bioreclamation, NY, USA) and used neat as a negative control or spiked with sonicated fully methylated human genomic DNA (Millipore, MA, US), 1250pg/mL, as a positive control.

    Techniques: Methylation, Marker

    BCAT1 (top panel, black triangles) and IKZF1 (bottom panel, white triangles) methylation specific assays were used to assess the appearance of circulating methylated BCAT1 and IKZF1 DNA in 218 plasma specimens including 144 healthy controls and 74 cancers. Mann-Whitney t-tests were performed on calculated positivity rates for each phenotypic class to derive the P-values. The calculated 95% confidence intervals (95% CI) are indicated.

    Journal: PLoS ONE

    Article Title: A Two-Gene Blood Test for Methylated DNA Sensitive for Colorectal Cancer

    doi: 10.1371/journal.pone.0125041

    Figure Lengend Snippet: BCAT1 (top panel, black triangles) and IKZF1 (bottom panel, white triangles) methylation specific assays were used to assess the appearance of circulating methylated BCAT1 and IKZF1 DNA in 218 plasma specimens including 144 healthy controls and 74 cancers. Mann-Whitney t-tests were performed on calculated positivity rates for each phenotypic class to derive the P-values. The calculated 95% confidence intervals (95% CI) are indicated.

    Article Snippet: Pooled plasma from gender- and age-matched donors under 30 years of age was commercially sourced (Bioreclamation, NY, USA) and used neat as a negative control or spiked with sonicated fully methylated human genomic DNA (Millipore, MA, US), 1250pg/mL, as a positive control.

    Techniques: Methylation, Clinical Proteomics, MANN-WHITNEY

    (A) Correlation plot of average Ct values (log(Ct)) measured by the BCAT1 or IKZF1 assays from 144 healthy controls (black circles) and 74 CRC (white circles). PCR replicates with no signal were assigned an arbitrary Ct value of 50 for depiction purposes. Square quadrants (a) to (d) represent: (a) 15 BCAT1 negative but IKZF1 positive cases; (b) 42 BCAT1 and IKZF1 positive cases including 41 cancer and 1 control; (c) 11 BCAT1 positive but IKZF1 negative cases; (d) 150 BCAT1 and IKZF1 negative cases. A linear regression analysis was performed on 38 of the 41 BCAT1 and IKZF1 positive CRC cases (quadrant b), omitting three CRC outliers. Broken diagonal lines indicate the 95% CI range. The calculated R square value is shown. The mass (ng) of methylated BCAT1 (B) and IKZF1 (C) DNA was calculated and plotted as mass of methylation per mL plasma drawn from 144 control cases, 4 Stage I, 28 Stage II, 23 Stage III, 8 Stage IV (the 8 CRC cases with unknown staging omitted). Average and median mass levels in the five phenotypic classes are indicated below the graphs. Mann-Whitney t-test performed on median values, ***: p value < 0.05, ns: non-significant, as compared with the 144 healthy control cases.

    Journal: PLoS ONE

    Article Title: A Two-Gene Blood Test for Methylated DNA Sensitive for Colorectal Cancer

    doi: 10.1371/journal.pone.0125041

    Figure Lengend Snippet: (A) Correlation plot of average Ct values (log(Ct)) measured by the BCAT1 or IKZF1 assays from 144 healthy controls (black circles) and 74 CRC (white circles). PCR replicates with no signal were assigned an arbitrary Ct value of 50 for depiction purposes. Square quadrants (a) to (d) represent: (a) 15 BCAT1 negative but IKZF1 positive cases; (b) 42 BCAT1 and IKZF1 positive cases including 41 cancer and 1 control; (c) 11 BCAT1 positive but IKZF1 negative cases; (d) 150 BCAT1 and IKZF1 negative cases. A linear regression analysis was performed on 38 of the 41 BCAT1 and IKZF1 positive CRC cases (quadrant b), omitting three CRC outliers. Broken diagonal lines indicate the 95% CI range. The calculated R square value is shown. The mass (ng) of methylated BCAT1 (B) and IKZF1 (C) DNA was calculated and plotted as mass of methylation per mL plasma drawn from 144 control cases, 4 Stage I, 28 Stage II, 23 Stage III, 8 Stage IV (the 8 CRC cases with unknown staging omitted). Average and median mass levels in the five phenotypic classes are indicated below the graphs. Mann-Whitney t-test performed on median values, ***: p value < 0.05, ns: non-significant, as compared with the 144 healthy control cases.

    Article Snippet: Pooled plasma from gender- and age-matched donors under 30 years of age was commercially sourced (Bioreclamation, NY, USA) and used neat as a negative control or spiked with sonicated fully methylated human genomic DNA (Millipore, MA, US), 1250pg/mL, as a positive control.

    Techniques: Control, Methylation, Clinical Proteomics, MANN-WHITNEY

    The estimated average mass of (A) BCAT1 and (B) IKZF1 DNA in each of the triplicate assays containing DNA isolated from the equivalent of 0.5mL plasma from healthy controls (black lines, BCAT1 : n = 5, IKZF1 : n = 2*), early stage cancer (blue lines, Stage I+II, BCAT1 : n = 19, IKZF1 : n = 17) and late stage cancer (red lines, Stage III+IV, BCAT1 : n = 22, IKZF1 : n = 26) were used to calculate the empirical probability density plots, omitting ‘no signal’ results (broken lines). Solid lines: Population means (μ) and standard deviations (σ) were calculated assuming a normal distribution for each of the three phenotypic classifications. *Five of the seven positive IKZF1 control cases had Ct signals within the last 5 cycles of PCR, therefore no mass estimation. (C) Cumulative probability of a plasma sample with BCAT1 or IKZF1 DNA methylation levels equal to or greater than 20-, 50- or 100pg methylated DNA coming from a patient with the indicated phenotypic classification; the mass thresholds were determined as the area under the curve (solid lines in panels A and B) for ln(pg) values greater than 3, 3.9 and 4.6, respectively (see dotted vertical lines and arrows) in Panels A and B. Likelihood ratios relative to healthy controls are shown in brackets.

    Journal: PLoS ONE

    Article Title: A Two-Gene Blood Test for Methylated DNA Sensitive for Colorectal Cancer

    doi: 10.1371/journal.pone.0125041

    Figure Lengend Snippet: The estimated average mass of (A) BCAT1 and (B) IKZF1 DNA in each of the triplicate assays containing DNA isolated from the equivalent of 0.5mL plasma from healthy controls (black lines, BCAT1 : n = 5, IKZF1 : n = 2*), early stage cancer (blue lines, Stage I+II, BCAT1 : n = 19, IKZF1 : n = 17) and late stage cancer (red lines, Stage III+IV, BCAT1 : n = 22, IKZF1 : n = 26) were used to calculate the empirical probability density plots, omitting ‘no signal’ results (broken lines). Solid lines: Population means (μ) and standard deviations (σ) were calculated assuming a normal distribution for each of the three phenotypic classifications. *Five of the seven positive IKZF1 control cases had Ct signals within the last 5 cycles of PCR, therefore no mass estimation. (C) Cumulative probability of a plasma sample with BCAT1 or IKZF1 DNA methylation levels equal to or greater than 20-, 50- or 100pg methylated DNA coming from a patient with the indicated phenotypic classification; the mass thresholds were determined as the area under the curve (solid lines in panels A and B) for ln(pg) values greater than 3, 3.9 and 4.6, respectively (see dotted vertical lines and arrows) in Panels A and B. Likelihood ratios relative to healthy controls are shown in brackets.

    Article Snippet: Pooled plasma from gender- and age-matched donors under 30 years of age was commercially sourced (Bioreclamation, NY, USA) and used neat as a negative control or spiked with sonicated fully methylated human genomic DNA (Millipore, MA, US), 1250pg/mL, as a positive control.

    Techniques: Isolation, Clinical Proteomics, Control, DNA Methylation Assay, Methylation