mgmt methylation test psq  (Pyrosequencing Inc)

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: 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: Figure 7 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.

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: Figure 7 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.

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: Figure 7 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.

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: Figure 7 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.

Techniques: Histopathology, Mutagenesis, Methylation