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Pyrosequencing Inc mgmt pyrosequencing score
Analysis of differentially dissected tumor samples
Mgmt Pyrosequencing Score, supplied by Pyrosequencing Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/mgmt+pyrosequencing/mgmt+pyrosequencing/pmc10623846-159-0-3
Average 90 stars, based on 1 article reviews
mgmt pyrosequencing score - by Bioz Stars, 2026-11
90/100 stars

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1) Product Images from "Variant allelic frequencies of driver mutations can identify gliomas with potentially false-negative MGMT promoter methylation results"

Article Title: Variant allelic frequencies of driver mutations can identify gliomas with potentially false-negative MGMT promoter methylation results

Journal: Acta Neuropathologica Communications

doi: 10.1186/s40478-023-01680-0

Analysis of differentially dissected tumor samples
Figure Legend Snippet: Analysis of differentially dissected tumor samples

Techniques Used: Mutagenesis

MGMT promoter methylation trends in pyrosequencing samples . ( A ) Frequency of positive results for all glioma samples above and below the cutoff value of VAF = 0.325. ( B ) Cumulative mean frequency of positive test results as a function of VAF. ( C ) Trends in cumulative mean MGMT promoter pyrosequencing score with increasing VAF. ( D ) Mean MGMT promoter pyrosequencing scores above and below VAF = 0.325. Similar results are shown for each tumor subtype, including IDH-wildtype glioblastoma ( E - H ), IDH-mutant astrocytoma ( I - L ) and IDH-mutant and 1p/19q co-deleted oligodendroglioma ( M - P ). (Horizontal dashed black lines: mean values for cohort; Horizontal solid red lines: MGMT positivity cutoff of 10.0%; Vertical dashed black lines: cutoff values identified by Cutoff Finder; Vertical dashed red lines: cutoff values identified by multi-part linear regression; Panels A, E, I, M: Fisher’s exact test; Panels D, H, L, P: unpaired Student’s T-test; pyroseq: pyrosequencing; *p < 0.05; ****p < 0.0001)
Figure Legend Snippet: MGMT promoter methylation trends in pyrosequencing samples . ( A ) Frequency of positive results for all glioma samples above and below the cutoff value of VAF = 0.325. ( B ) Cumulative mean frequency of positive test results as a function of VAF. ( C ) Trends in cumulative mean MGMT promoter pyrosequencing score with increasing VAF. ( D ) Mean MGMT promoter pyrosequencing scores above and below VAF = 0.325. Similar results are shown for each tumor subtype, including IDH-wildtype glioblastoma ( E - H ), IDH-mutant astrocytoma ( I - L ) and IDH-mutant and 1p/19q co-deleted oligodendroglioma ( M - P ). (Horizontal dashed black lines: mean values for cohort; Horizontal solid red lines: MGMT positivity cutoff of 10.0%; Vertical dashed black lines: cutoff values identified by Cutoff Finder; Vertical dashed red lines: cutoff values identified by multi-part linear regression; Panels A, E, I, M: Fisher’s exact test; Panels D, H, L, P: unpaired Student’s T-test; pyroseq: pyrosequencing; *p < 0.05; ****p < 0.0001)

Techniques Used: Methylation, Mutagenesis

MGMT promoter methylation trends in DNA methylation array samples . ( A ) Frequency of positive results for all glioma array samples above and below the cutoff of VAF = 0.245. ( B ) Cumulative mean frequency of positive results for all glioma array samples as a function of VAF. ( C ) Frequency of positive results for GBM array samples above and below the cutoff of TERT VAF = 0.325. ( D ) Cumulative mean frequency of positive results in GBM array samples as a function of TERT VAF. ( E ) Frequency of positive results in GBM pyrosequencing samples using MGMT cutoff of 10.0% versus GBM array samples. ( F ) Frequency of positive results in GBM pyrosequencing samples using MGMT cutoff of 7.28% versus GBM array samples. ( G ) Frequency of positive results in GBM pyrosequencing samples with TERT VAF < 0.115, using MGMT cutoff of 7.28%, versus GBM array samples with TERT VAF < 0.325. ( H ) Frequency of positive results in GBM pyrosequencing samples with TERT VAF ≥ 0.115, using MGMT cutoff of 7.28%, versus GBM array samples with TERT VAF ≥ 0.325. ( I ) Frequency of positive results for IDHmut astrocytoma above and below the cutoff of IDH VAF = 0.325 (left), by methylation class match (center), and above and below the cutoff of classifier score = 0.955 (right). ( J ) Cumulative mean frequency of positive results in IDHmut astrocytoma array samples as a function of IDH VAF (Fisher’s exact test for panels A, C, E, F, G, H, I; GBM: IDH-wildtype glioblastoma, IDHmut astrocytoma: IDH-mutant astrocytoma)
Figure Legend Snippet: MGMT promoter methylation trends in DNA methylation array samples . ( A ) Frequency of positive results for all glioma array samples above and below the cutoff of VAF = 0.245. ( B ) Cumulative mean frequency of positive results for all glioma array samples as a function of VAF. ( C ) Frequency of positive results for GBM array samples above and below the cutoff of TERT VAF = 0.325. ( D ) Cumulative mean frequency of positive results in GBM array samples as a function of TERT VAF. ( E ) Frequency of positive results in GBM pyrosequencing samples using MGMT cutoff of 10.0% versus GBM array samples. ( F ) Frequency of positive results in GBM pyrosequencing samples using MGMT cutoff of 7.28% versus GBM array samples. ( G ) Frequency of positive results in GBM pyrosequencing samples with TERT VAF < 0.115, using MGMT cutoff of 7.28%, versus GBM array samples with TERT VAF < 0.325. ( H ) Frequency of positive results in GBM pyrosequencing samples with TERT VAF ≥ 0.115, using MGMT cutoff of 7.28%, versus GBM array samples with TERT VAF ≥ 0.325. ( I ) Frequency of positive results for IDHmut astrocytoma above and below the cutoff of IDH VAF = 0.325 (left), by methylation class match (center), and above and below the cutoff of classifier score = 0.955 (right). ( J ) Cumulative mean frequency of positive results in IDHmut astrocytoma array samples as a function of IDH VAF (Fisher’s exact test for panels A, C, E, F, G, H, I; GBM: IDH-wildtype glioblastoma, IDHmut astrocytoma: IDH-mutant astrocytoma)

Techniques Used: Methylation, DNA Methylation Assay, Mutagenesis

Driver mutation VAF , MGMT promoter methylation scores, and tumor cellularity . ( A ) Linear regression of MGMT promoter pyrosequencing score versus driver mutation VAF for all glioma samples. ( B ) Linear regression of MGMT promoter pyrosequencing score versus TERT promoter mutation VAF for GBM. ( C ) Linear regression of MGMT promoter pyrosequencing score versus IDH mutation VAF for IDHmut astrocytoma. ( D ) Linear regression of MGMT promoter pyrosequencing score versus IDH mutation VAF for IDHmut oligodendroglioma. ( E ) Linear regression of microscopically estimated cellularity versus cellularity calculated from driver mutation VAF (2×VAF×100%) for all glioma samples. ( F ) Differences between microscopically estimated cellularity and cellularity calculated from VAF (Y-axis) plotted as a function of VAF (X-axis), for all glioma samples. ( G ) TERT promoter mutation VAF by ddPCR in high versus low cellularity areas of GBM tissue samples. ( H ) MGMT promoter methylation score by ddPCR in high versus low cellularity areas of GBM tissue samples (GBM: IDH-wildtype glioblastoma, IDHmut astrocytoma: IDH-mutant astrocytoma, IDHmut oligodendroglioma: IDH-mutant and 1p/19q co-deleted oligodendroglioma, pyroseq: pyrosequencing, ddPCR: droplet digital PCR)
Figure Legend Snippet: Driver mutation VAF , MGMT promoter methylation scores, and tumor cellularity . ( A ) Linear regression of MGMT promoter pyrosequencing score versus driver mutation VAF for all glioma samples. ( B ) Linear regression of MGMT promoter pyrosequencing score versus TERT promoter mutation VAF for GBM. ( C ) Linear regression of MGMT promoter pyrosequencing score versus IDH mutation VAF for IDHmut astrocytoma. ( D ) Linear regression of MGMT promoter pyrosequencing score versus IDH mutation VAF for IDHmut oligodendroglioma. ( E ) Linear regression of microscopically estimated cellularity versus cellularity calculated from driver mutation VAF (2×VAF×100%) for all glioma samples. ( F ) Differences between microscopically estimated cellularity and cellularity calculated from VAF (Y-axis) plotted as a function of VAF (X-axis), for all glioma samples. ( G ) TERT promoter mutation VAF by ddPCR in high versus low cellularity areas of GBM tissue samples. ( H ) MGMT promoter methylation score by ddPCR in high versus low cellularity areas of GBM tissue samples (GBM: IDH-wildtype glioblastoma, IDHmut astrocytoma: IDH-mutant astrocytoma, IDHmut oligodendroglioma: IDH-mutant and 1p/19q co-deleted oligodendroglioma, pyroseq: pyrosequencing, ddPCR: droplet digital PCR)

Techniques Used: Mutagenesis, Methylation, Digital PCR

Re-testing pyrosequencing samples with DNA methylation array and droplet digital PCR
Figure Legend Snippet: Re-testing pyrosequencing samples with DNA methylation array and droplet digital PCR

Techniques Used: DNA Methylation Assay

False negative results in IDH-wildtype glioblastoma with low TERT VAF . ( A ) MGMT promoter methylation results for 12 GBM samples (6 with TERT VAF ≤ 0.10, 6 with TERT VAF ≥ 0.25) comparing initial pyrosequencing methylation scores (left Y-axis, cutoff for positive = 10.0%, horizontal solid red line) to results on re-testing with DNA methylation array (right Y-axis). ( B ) MGMT promoter methylation results for the same 12 GBM samples comparing initial pyrosequencing methylation levels to results on re-testing with ddPCR. (GBM: IDH-wildtype glioblastoma, pos: positive, equiv: equivocal, neg: negative, QNS: quality/quantity of DNA not sufficient for reliable test result, ddPCR: droplet digital PCR)
Figure Legend Snippet: False negative results in IDH-wildtype glioblastoma with low TERT VAF . ( A ) MGMT promoter methylation results for 12 GBM samples (6 with TERT VAF ≤ 0.10, 6 with TERT VAF ≥ 0.25) comparing initial pyrosequencing methylation scores (left Y-axis, cutoff for positive = 10.0%, horizontal solid red line) to results on re-testing with DNA methylation array (right Y-axis). ( B ) MGMT promoter methylation results for the same 12 GBM samples comparing initial pyrosequencing methylation levels to results on re-testing with ddPCR. (GBM: IDH-wildtype glioblastoma, pos: positive, equiv: equivocal, neg: negative, QNS: quality/quantity of DNA not sufficient for reliable test result, ddPCR: droplet digital PCR)

Techniques Used: Methylation, DNA Methylation Assay, Digital PCR

Central hypothesis . MGMT promoter methylation is pathologic, and occurs only in tumor cells. Cellular glioma samples are rich in DNA from tumor cells, whereas paucicellular glioma samples contain a large fraction of DNA from non-tumor cells, which can “dilute” positive methylation signals from tumor cell DNA, leading to false-negative results
Figure Legend Snippet: Central hypothesis . MGMT promoter methylation is pathologic, and occurs only in tumor cells. Cellular glioma samples are rich in DNA from tumor cells, whereas paucicellular glioma samples contain a large fraction of DNA from non-tumor cells, which can “dilute” positive methylation signals from tumor cell DNA, leading to false-negative results

Techniques Used: Methylation

Patient cohort characteristics
Figure Legend Snippet: Patient cohort characteristics

Techniques Used: Pyrosequencing Assay, Methylation, Mutagenesis

Related Articles

other:

Article Title: Defining the recommended gray zone in O6-methylguanine-DNA methyltransferase promoter methylation pyrosequencing reporting: A robust, translatable method to implement new EANO guidelines
Article Snippet: To the best of our knowledge, this is the first study that provides a method to derive the gray zone from MGMT pyrosequencing data.

Article Title: Molecularly matched targeted therapies plus radiotherapy in glioblastoma: the phase 1/2a N 2 M 2 umbrella trial
Article Snippet: MGMT pyrosequencing was the primary assay for MGMT testing and a cutoff ≤8% was used to verify MGMT promoter nonhypermethylated tumors.

Article Title: BRAF/MEK inhibition induces cell state transitions boosting immune checkpoint sensitivity in BRAF V600E -mutant glioma
Article Snippet: H&E-stained slides were scanned with a 20× objective on Aperio AT2 slide scanner (Leica Biosystems).

Article Title: Molecularly matched targeted therapies plus radiotherapy in glioblastoma: the phase 1/2a N 2 M 2 umbrella trial.
Article Snippet: MGMT pyrosequencing was the primary assay for MGMT testing and a cutoff ≤8% was used to verify MGMT promoter nonhypermethylated tumors.

Methylation:

Article Title: Variant allelic frequencies of driver mutations can identify gliomas with potentially false-negative MGMT promoter methylation results.
Article Snippet: .. Based on the fraction of IDHwt GBM samples in our cohort falling below the VAF/cellularity cutoffs identified by Cutoff Finder and regression (4.3% and 12.6%, respectively) and the known frequency of MGMT promoter methylation in IDH-wildtype GBM of ~ 35% [55], we estimate that 1.5-4.4% of IDHwt GBM MGMT pyrosequencing samples may have false-negative results, potentially impacting TMZ treatment decisions. ..

Article Title: Randomized phase III trial of metabolic imaging-guided dose escalation of radio-chemotherapy in patients with newly diagnosed glioblastoma (SPECTRO GLIO trial).
Article Snippet: Background.. Glioblastoma (GBM) systematically recurs after a standard 60 Gy radio-chemotherapy regimen.. Since magnetic resonance spectroscopic imaging (MRSI) has been shown to predict the site of relapse, we analyzed the effect of MRSI-guided dose escalation on overall survival (OS) of patients with newly diagnosed GBM.

Article Title: Variant allelic frequencies of driver mutations can identify gliomas with potentially false-negative MGMT promoter methylation results.
Article Snippet: .. Gurrieri L, De Carlo E, Gerratana L, De Maglio G, Macerelli M, Pisa FE, Masiero E, Aprile G, Follador A, Puglisi F al (2018) MGMT pyrosequencing-based cut-off methylation level and clinical outcome in patients with Glioblastoma Multiforme. ..

Immunohistochemistry:

Article Title: BRAF/MEK inhibition induces cell state transitions boosting immune checkpoint sensitivity in BRAF V600E -mutant glioma.
Article Snippet: .. MGMTp pyrosequencing and IHC for PD-L1 (SP142 clone) were performed on all samples. ..



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Image Search Results


Analysis of differentially dissected tumor samples

Journal: Acta Neuropathologica Communications

Article Title: Variant allelic frequencies of driver mutations can identify gliomas with potentially false-negative MGMT promoter methylation results

doi: 10.1186/s40478-023-01680-0

Figure Lengend Snippet: Analysis of differentially dissected tumor samples

Article Snippet: Cumulative mean MGMT pyrosequencing score trends are shown for IDHwt GBM (Fig. G), IDHmut astrocytoma (Fig. K), and IDHmut oligodendroglioma (Fig. O).

Techniques: Mutagenesis

MGMT promoter methylation trends in pyrosequencing samples . ( A ) Frequency of positive results for all glioma samples above and below the cutoff value of VAF = 0.325. ( B ) Cumulative mean frequency of positive test results as a function of VAF. ( C ) Trends in cumulative mean MGMT promoter pyrosequencing score with increasing VAF. ( D ) Mean MGMT promoter pyrosequencing scores above and below VAF = 0.325. Similar results are shown for each tumor subtype, including IDH-wildtype glioblastoma ( E - H ), IDH-mutant astrocytoma ( I - L ) and IDH-mutant and 1p/19q co-deleted oligodendroglioma ( M - P ). (Horizontal dashed black lines: mean values for cohort; Horizontal solid red lines: MGMT positivity cutoff of 10.0%; Vertical dashed black lines: cutoff values identified by Cutoff Finder; Vertical dashed red lines: cutoff values identified by multi-part linear regression; Panels A, E, I, M: Fisher’s exact test; Panels D, H, L, P: unpaired Student’s T-test; pyroseq: pyrosequencing; *p < 0.05; ****p < 0.0001)

Journal: Acta Neuropathologica Communications

Article Title: Variant allelic frequencies of driver mutations can identify gliomas with potentially false-negative MGMT promoter methylation results

doi: 10.1186/s40478-023-01680-0

Figure Lengend Snippet: MGMT promoter methylation trends in pyrosequencing samples . ( A ) Frequency of positive results for all glioma samples above and below the cutoff value of VAF = 0.325. ( B ) Cumulative mean frequency of positive test results as a function of VAF. ( C ) Trends in cumulative mean MGMT promoter pyrosequencing score with increasing VAF. ( D ) Mean MGMT promoter pyrosequencing scores above and below VAF = 0.325. Similar results are shown for each tumor subtype, including IDH-wildtype glioblastoma ( E - H ), IDH-mutant astrocytoma ( I - L ) and IDH-mutant and 1p/19q co-deleted oligodendroglioma ( M - P ). (Horizontal dashed black lines: mean values for cohort; Horizontal solid red lines: MGMT positivity cutoff of 10.0%; Vertical dashed black lines: cutoff values identified by Cutoff Finder; Vertical dashed red lines: cutoff values identified by multi-part linear regression; Panels A, E, I, M: Fisher’s exact test; Panels D, H, L, P: unpaired Student’s T-test; pyroseq: pyrosequencing; *p < 0.05; ****p < 0.0001)

Article Snippet: Cumulative mean MGMT pyrosequencing score trends are shown for IDHwt GBM (Fig. G), IDHmut astrocytoma (Fig. K), and IDHmut oligodendroglioma (Fig. O).

Techniques: Methylation, Mutagenesis

MGMT promoter methylation trends in DNA methylation array samples . ( A ) Frequency of positive results for all glioma array samples above and below the cutoff of VAF = 0.245. ( B ) Cumulative mean frequency of positive results for all glioma array samples as a function of VAF. ( C ) Frequency of positive results for GBM array samples above and below the cutoff of TERT VAF = 0.325. ( D ) Cumulative mean frequency of positive results in GBM array samples as a function of TERT VAF. ( E ) Frequency of positive results in GBM pyrosequencing samples using MGMT cutoff of 10.0% versus GBM array samples. ( F ) Frequency of positive results in GBM pyrosequencing samples using MGMT cutoff of 7.28% versus GBM array samples. ( G ) Frequency of positive results in GBM pyrosequencing samples with TERT VAF < 0.115, using MGMT cutoff of 7.28%, versus GBM array samples with TERT VAF < 0.325. ( H ) Frequency of positive results in GBM pyrosequencing samples with TERT VAF ≥ 0.115, using MGMT cutoff of 7.28%, versus GBM array samples with TERT VAF ≥ 0.325. ( I ) Frequency of positive results for IDHmut astrocytoma above and below the cutoff of IDH VAF = 0.325 (left), by methylation class match (center), and above and below the cutoff of classifier score = 0.955 (right). ( J ) Cumulative mean frequency of positive results in IDHmut astrocytoma array samples as a function of IDH VAF (Fisher’s exact test for panels A, C, E, F, G, H, I; GBM: IDH-wildtype glioblastoma, IDHmut astrocytoma: IDH-mutant astrocytoma)

Journal: Acta Neuropathologica Communications

Article Title: Variant allelic frequencies of driver mutations can identify gliomas with potentially false-negative MGMT promoter methylation results

doi: 10.1186/s40478-023-01680-0

Figure Lengend Snippet: MGMT promoter methylation trends in DNA methylation array samples . ( A ) Frequency of positive results for all glioma array samples above and below the cutoff of VAF = 0.245. ( B ) Cumulative mean frequency of positive results for all glioma array samples as a function of VAF. ( C ) Frequency of positive results for GBM array samples above and below the cutoff of TERT VAF = 0.325. ( D ) Cumulative mean frequency of positive results in GBM array samples as a function of TERT VAF. ( E ) Frequency of positive results in GBM pyrosequencing samples using MGMT cutoff of 10.0% versus GBM array samples. ( F ) Frequency of positive results in GBM pyrosequencing samples using MGMT cutoff of 7.28% versus GBM array samples. ( G ) Frequency of positive results in GBM pyrosequencing samples with TERT VAF < 0.115, using MGMT cutoff of 7.28%, versus GBM array samples with TERT VAF < 0.325. ( H ) Frequency of positive results in GBM pyrosequencing samples with TERT VAF ≥ 0.115, using MGMT cutoff of 7.28%, versus GBM array samples with TERT VAF ≥ 0.325. ( I ) Frequency of positive results for IDHmut astrocytoma above and below the cutoff of IDH VAF = 0.325 (left), by methylation class match (center), and above and below the cutoff of classifier score = 0.955 (right). ( J ) Cumulative mean frequency of positive results in IDHmut astrocytoma array samples as a function of IDH VAF (Fisher’s exact test for panels A, C, E, F, G, H, I; GBM: IDH-wildtype glioblastoma, IDHmut astrocytoma: IDH-mutant astrocytoma)

Article Snippet: Cumulative mean MGMT pyrosequencing score trends are shown for IDHwt GBM (Fig. G), IDHmut astrocytoma (Fig. K), and IDHmut oligodendroglioma (Fig. O).

Techniques: Methylation, DNA Methylation Assay, Mutagenesis

Driver mutation VAF , MGMT promoter methylation scores, and tumor cellularity . ( A ) Linear regression of MGMT promoter pyrosequencing score versus driver mutation VAF for all glioma samples. ( B ) Linear regression of MGMT promoter pyrosequencing score versus TERT promoter mutation VAF for GBM. ( C ) Linear regression of MGMT promoter pyrosequencing score versus IDH mutation VAF for IDHmut astrocytoma. ( D ) Linear regression of MGMT promoter pyrosequencing score versus IDH mutation VAF for IDHmut oligodendroglioma. ( E ) Linear regression of microscopically estimated cellularity versus cellularity calculated from driver mutation VAF (2×VAF×100%) for all glioma samples. ( F ) Differences between microscopically estimated cellularity and cellularity calculated from VAF (Y-axis) plotted as a function of VAF (X-axis), for all glioma samples. ( G ) TERT promoter mutation VAF by ddPCR in high versus low cellularity areas of GBM tissue samples. ( H ) MGMT promoter methylation score by ddPCR in high versus low cellularity areas of GBM tissue samples (GBM: IDH-wildtype glioblastoma, IDHmut astrocytoma: IDH-mutant astrocytoma, IDHmut oligodendroglioma: IDH-mutant and 1p/19q co-deleted oligodendroglioma, pyroseq: pyrosequencing, ddPCR: droplet digital PCR)

Journal: Acta Neuropathologica Communications

Article Title: Variant allelic frequencies of driver mutations can identify gliomas with potentially false-negative MGMT promoter methylation results

doi: 10.1186/s40478-023-01680-0

Figure Lengend Snippet: Driver mutation VAF , MGMT promoter methylation scores, and tumor cellularity . ( A ) Linear regression of MGMT promoter pyrosequencing score versus driver mutation VAF for all glioma samples. ( B ) Linear regression of MGMT promoter pyrosequencing score versus TERT promoter mutation VAF for GBM. ( C ) Linear regression of MGMT promoter pyrosequencing score versus IDH mutation VAF for IDHmut astrocytoma. ( D ) Linear regression of MGMT promoter pyrosequencing score versus IDH mutation VAF for IDHmut oligodendroglioma. ( E ) Linear regression of microscopically estimated cellularity versus cellularity calculated from driver mutation VAF (2×VAF×100%) for all glioma samples. ( F ) Differences between microscopically estimated cellularity and cellularity calculated from VAF (Y-axis) plotted as a function of VAF (X-axis), for all glioma samples. ( G ) TERT promoter mutation VAF by ddPCR in high versus low cellularity areas of GBM tissue samples. ( H ) MGMT promoter methylation score by ddPCR in high versus low cellularity areas of GBM tissue samples (GBM: IDH-wildtype glioblastoma, IDHmut astrocytoma: IDH-mutant astrocytoma, IDHmut oligodendroglioma: IDH-mutant and 1p/19q co-deleted oligodendroglioma, pyroseq: pyrosequencing, ddPCR: droplet digital PCR)

Article Snippet: Cumulative mean MGMT pyrosequencing score trends are shown for IDHwt GBM (Fig. G), IDHmut astrocytoma (Fig. K), and IDHmut oligodendroglioma (Fig. O).

Techniques: Mutagenesis, Methylation, Digital PCR

Re-testing pyrosequencing samples with DNA methylation array and droplet digital PCR

Journal: Acta Neuropathologica Communications

Article Title: Variant allelic frequencies of driver mutations can identify gliomas with potentially false-negative MGMT promoter methylation results

doi: 10.1186/s40478-023-01680-0

Figure Lengend Snippet: Re-testing pyrosequencing samples with DNA methylation array and droplet digital PCR

Article Snippet: Cumulative mean MGMT pyrosequencing score trends are shown for IDHwt GBM (Fig. G), IDHmut astrocytoma (Fig. K), and IDHmut oligodendroglioma (Fig. O).

Techniques: DNA Methylation Assay

False negative results in IDH-wildtype glioblastoma with low TERT VAF . ( A ) MGMT promoter methylation results for 12 GBM samples (6 with TERT VAF ≤ 0.10, 6 with TERT VAF ≥ 0.25) comparing initial pyrosequencing methylation scores (left Y-axis, cutoff for positive = 10.0%, horizontal solid red line) to results on re-testing with DNA methylation array (right Y-axis). ( B ) MGMT promoter methylation results for the same 12 GBM samples comparing initial pyrosequencing methylation levels to results on re-testing with ddPCR. (GBM: IDH-wildtype glioblastoma, pos: positive, equiv: equivocal, neg: negative, QNS: quality/quantity of DNA not sufficient for reliable test result, ddPCR: droplet digital PCR)

Journal: Acta Neuropathologica Communications

Article Title: Variant allelic frequencies of driver mutations can identify gliomas with potentially false-negative MGMT promoter methylation results

doi: 10.1186/s40478-023-01680-0

Figure Lengend Snippet: False negative results in IDH-wildtype glioblastoma with low TERT VAF . ( A ) MGMT promoter methylation results for 12 GBM samples (6 with TERT VAF ≤ 0.10, 6 with TERT VAF ≥ 0.25) comparing initial pyrosequencing methylation scores (left Y-axis, cutoff for positive = 10.0%, horizontal solid red line) to results on re-testing with DNA methylation array (right Y-axis). ( B ) MGMT promoter methylation results for the same 12 GBM samples comparing initial pyrosequencing methylation levels to results on re-testing with ddPCR. (GBM: IDH-wildtype glioblastoma, pos: positive, equiv: equivocal, neg: negative, QNS: quality/quantity of DNA not sufficient for reliable test result, ddPCR: droplet digital PCR)

Article Snippet: Cumulative mean MGMT pyrosequencing score trends are shown for IDHwt GBM (Fig. G), IDHmut astrocytoma (Fig. K), and IDHmut oligodendroglioma (Fig. O).

Techniques: Methylation, DNA Methylation Assay, Digital PCR

Central hypothesis . MGMT promoter methylation is pathologic, and occurs only in tumor cells. Cellular glioma samples are rich in DNA from tumor cells, whereas paucicellular glioma samples contain a large fraction of DNA from non-tumor cells, which can “dilute” positive methylation signals from tumor cell DNA, leading to false-negative results

Journal: Acta Neuropathologica Communications

Article Title: Variant allelic frequencies of driver mutations can identify gliomas with potentially false-negative MGMT promoter methylation results

doi: 10.1186/s40478-023-01680-0

Figure Lengend Snippet: Central hypothesis . MGMT promoter methylation is pathologic, and occurs only in tumor cells. Cellular glioma samples are rich in DNA from tumor cells, whereas paucicellular glioma samples contain a large fraction of DNA from non-tumor cells, which can “dilute” positive methylation signals from tumor cell DNA, leading to false-negative results

Article Snippet: Cumulative mean MGMT pyrosequencing score trends are shown for IDHwt GBM (Fig. G), IDHmut astrocytoma (Fig. K), and IDHmut oligodendroglioma (Fig. O).

Techniques: Methylation

Patient cohort characteristics

Journal: Acta Neuropathologica Communications

Article Title: Variant allelic frequencies of driver mutations can identify gliomas with potentially false-negative MGMT promoter methylation results

doi: 10.1186/s40478-023-01680-0

Figure Lengend Snippet: Patient cohort characteristics

Article Snippet: Cumulative mean MGMT pyrosequencing score trends are shown for IDHwt GBM (Fig. G), IDHmut astrocytoma (Fig. K), and IDHmut oligodendroglioma (Fig. O).

Techniques: Pyrosequencing Assay, Methylation, Mutagenesis