quantitative mgmt promoter methylation analysis  (Pyrosequencing Inc)

Journal: Cancer Imaging

Article Title: Assessment of MGMT promoter methylation status in glioblastoma using deep learning features from multi-sequence MRI of intratumoral and peritumoral regions

doi: 10.1186/s40644-024-00817-1

Figure Lengend Snippet: Segmentation illustration of tumor T1WI and CE-T1WI sequence imaging. Patient a is a 66-year-old male with unmethylated MGMT status, and patient b is a 68-year-old female with methylated MGMT status. The red region represents the NCR, the yellow region represents the ET, and the green region represents the PED

Article Snippet: The inclusion criteria included: (1) comprehensive imaging, pathological, and clinical data; (2) pathological confirmation of glioblastoma (WHO CNS 2021) with a definitive diagnosis of MGMT promoter methylation status (in house method developed by UCSF clinical labs, https://genomics.ucsf.edu/content/mgmt-promoter-methylation-assay ); (3) surgical intervention within one week following MRI examination; and (4) absence of any prior surgical, radiotherapy, or chemotherapy treatments before the MRI examination.

Techniques: Sequencing, Imaging, Methylation

Journal: Cancer Imaging

Article Title: Assessment of MGMT promoter methylation status in glioblastoma using deep learning features from multi-sequence MRI of intratumoral and peritumoral regions

doi: 10.1186/s40644-024-00817-1

Figure Lengend Snippet: Prediction results of MGMT promoter methylation status using different models

Article Snippet: The inclusion criteria included: (1) comprehensive imaging, pathological, and clinical data; (2) pathological confirmation of glioblastoma (WHO CNS 2021) with a definitive diagnosis of MGMT promoter methylation status (in house method developed by UCSF clinical labs, https://genomics.ucsf.edu/content/mgmt-promoter-methylation-assay ); (3) surgical intervention within one week following MRI examination; and (4) absence of any prior surgical, radiotherapy, or chemotherapy treatments before the MRI examination.

Techniques: Methylation

Journal: Scientific Reports

Article Title: Functional prediction of response to therapy prior to therapeutic intervention is associated with improved survival in patients with high-grade glioma

doi: 10.1038/s41598-024-68801-0

Figure Lengend Snippet: 3D Predict Glioma identified those patients with an unmethylated MGMT promoter that still did well with temozolomide treatment. ( a ) Individual patient information and drug response. ( b,c ) Kaplan–Meier survival curves stratified by MGMT promoter methylation in the HGG ( b ) and GBM ( c ) populations. ( d ) Table summarizing the PFS and OS and corresponding statistics for GBM patients with an unmethylated MGMT promoter (GBM, MGMT U ). ( e,f ) Kaplan–Meier survival curves for GBM, MGMT U patients for PFS ( e ) and OS ( f ) separated by test-predicted responders (green) and test-predicted non-responders (red). The dashed black line is the patient population unseparated by test prediction.

Article Snippet: When enough cells were available, MGMT promoter methylation was assayed using Kiyatec’s in-house, validated MGMT promoter methylation test to compare with and standardize the MGMT promoter methylation categorization coming from individual clinical sites.

Techniques: Methylation

Journal: Scientific Reports

Article Title: Functional prediction of response to therapy prior to therapeutic intervention is associated with improved survival in patients with high-grade glioma

doi: 10.1038/s41598-024-68801-0

Figure Lengend Snippet: 3D Predict Glioma stratified patient response regardless of the MGMT promoter methylation test used. ( a ) bar graph indicating the different tests used to clinically determine MGMT promoter methylation, including the number of methylated (light purple), unmethylated (dark purple) and inconclusive (gray) patients identified with each test type. ( b ) Table summarizing the OS for each test and categorization of patients along with the associated statistics. ( c,e ) Kaplan–Meier survival curves of the populations stratified by methylation state for the msPCR ( c ) and pyrosequencing ( e ) tested populations. ( d,f ) Kaplan–Meier survival curves of the populations stratified by 3D Predict Glioma test prediction for the msPCR ( d ) and pyrosequencing ( f ) tested populations.

Article Snippet: When enough cells were available, MGMT promoter methylation was assayed using Kiyatec’s in-house, validated MGMT promoter methylation test to compare with and standardize the MGMT promoter methylation categorization coming from individual clinical sites.

Techniques: Methylation

Journal: Scientific Reports

Article Title: Functional prediction of response to therapy prior to therapeutic intervention is associated with improved survival in patients with high-grade glioma

doi: 10.1038/s41598-024-68801-0

Figure Lengend Snippet: Standardization of MGMT promoter methylation testing affects MGMT promoter methylation categorization. ( a,b ) Kaplan–Meier survival curves stratified by MGMT promoter methylation in the GBM population as a conglomerate of multiple test types ( a ) and tested with Kiyatec’s MGMT methylation test ( b ). ( c ) Bar graph indicating the different tests used to clinically determine MGMT promoter methylation, including the number of methylated (light purple), unmethylated (dark purple) and inconclusive (gray) patients identified with each test type. ( d ) Table summarizing the OS for each test and categorization of patients along with the associated statistics. ( e,g ) Kaplan–Meier survival curves of the populations stratified by methylation state for the msPCR ( e ) and pyrosequencing ( g ) tested populations. ( f,h ) Kaplan–Meier survival curves of the populations stratified by 3D Predict Glioma test prediction for the msPCR ( f ) and pyrosequencing ( h ) tested populations.

Article Snippet: When enough cells were available, MGMT promoter methylation was assayed using Kiyatec’s in-house, validated MGMT promoter methylation test to compare with and standardize the MGMT promoter methylation categorization coming from individual clinical sites.

Techniques: Methylation

Journal: Scientific Reports

Article Title: Functional prediction of response to therapy prior to therapeutic intervention is associated with improved survival in patients with high-grade glioma

doi: 10.1038/s41598-024-68801-0

Figure Lengend Snippet: Demographics of patients at clinical correlation, Irrespective of study predicted treatment response.

Article Snippet: When enough cells were available, MGMT promoter methylation was assayed using Kiyatec’s in-house, validated MGMT promoter methylation test to compare with and standardize the MGMT promoter methylation categorization coming from individual clinical sites.

Techniques: Histopathology, Mutagenesis, Methylation

Journal: bioRxiv

Article Title: Mitochondrial sites of contact with the nucleus aid in chemotherapy evasion of glioblastoma cells

doi: 10.1101/2024.08.27.608373

Figure Lengend Snippet: (A) Cell viability was evaluated via crystal violet in U87MG cells treated with Etifoxine (30μM) and in combination with TMZ (100μM) for 48 and 72 hours. (B) Representative images of U87MG spheroids stained with Dapi, PI and antibody for TSPO at resting conditions, following TMZ alone and combined with Etifoxine (TMZ+Etifoxine). Histograms reporting quantification of spheroids diameter in the conditions of analysis ( C ) and relative changes in fluorescent intensity ( D ). (E) Percentage of MGMT promoter methylation (MGMTp meth%) in t98G and ADF cell lines. (F) Immunoblotting of MGMT and TSPO in ADF total lysates treated with TMZ (100μM) alone or combined with Lovastatin (10μM) and Etifoxine (30μM) for 24 hours. The graph in panel ( G ) shows the relative densitometry of MGMT and TSPO normalized to GAPDH. All data are represented as mean±sem. *p≤0.05; **p≤0.01; ***p≤0.001

Article Snippet: We used the MGMT Promoter Methylation Detection Kit (EntroGen, CA, USA) following the manufacturer’s instructions.

Techniques: Staining, Methylation, Western Blot

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: Fig. 2 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.

Techniques: Methylation, Mutagenesis

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: Fig. 2 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.

Techniques: Methylation, DNA Methylation Assay, Mutagenesis

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: Fig. 2 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.

Techniques: Mutagenesis, Methylation, 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: Fig. 2 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.

Techniques: DNA Methylation Assay

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: Fig. 2 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.

Techniques: Methylation, DNA Methylation Assay, 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: 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: Fig. 2 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.

Techniques: Methylation

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: Fig. 2 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.

Techniques: Pyrosequencing Assay, Methylation, Mutagenesis

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: Fig. 5 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: Methylation, Mutagenesis

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: Fig. 5 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: Methylation, DNA Methylation Assay, Mutagenesis

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: Fig. 5 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: Mutagenesis, Methylation, 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: Fig. 5 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: Methylation, DNA Methylation Assay, 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: 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: Fig. 5 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: Methylation

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: Fig. 5 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: Pyrosequencing Assay, Methylation, Mutagenesis