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94
Miltenyi Biotec isolation buffer provided in the mitochondria isolation kit miltenyi biotec 130 096 946
Isolation Buffer Provided In The Mitochondria Isolation Kit Miltenyi Biotec 130 096 946, supplied by Miltenyi Biotec, used in various techniques. Bioz Stars score: 94/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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isolation buffer provided in the mitochondria isolation kit miltenyi biotec 130 096 946 - by Bioz Stars, 2026-08
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Vazyme Biotech Co fastpure cell tissue total rna isolation kit v2
Fastpure Cell Tissue Total Rna Isolation Kit V2, supplied by Vazyme Biotech Co, used in various techniques. Bioz Stars score: 99/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Human Protein Atlas casp8
Biological functions associated with the recurrent scores. (A-B) The recurrent score related biological process revealed by Gene ontology analysis in the CGGA 693 and CGGA 325 database . (C-D) The heatmap showed the recurrent score and the enrichment scores of apoptosis-related functions of each patient in the CGGA 693 and CGGA 325 database. The samples were arranged in ascending order of the recurrent score. The column graph and line graph on the right showed the R -value and P -value of the correlation analysis. (E) Flow chart for recurrent score correlation analysis. (F-G) Using Pearson correlation analysis, the top 18 apoptosis-related genes mostly correlated with recurrent score were selected in CGGA 693 and CGGA 325 database. (H-I) The relationship between recurrent score and 6 apoptosis-related genes in glioma. The correlation coefficients were demonstrated as the proportion of the pie charts. The bottom right showed the correlation coefficient. The red parts represented a positive correlation. The correlation was tested by Pearson correlation analysis. (J) Correlation between the expression of the 6 genes in CGGA 693 and CGGA 325 database. ( K ) Expression levels of the 6 genes in primary glioma and recurrent glioma in CGGA 325 database and CGGA 693 database. (L) Survival analyses of the 6 genes by Kaplan-Meier curves and log-rank tests based on CCGA 693 database and CGGA 325 database. ( M ) Protein levels of SH3GLB1, NEK6, <t>CASP8</t> and ITGB1 in normal tissues and GBM from The Human Protein Atlas database
Casp8, supplied by Human Protein Atlas, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/tissues/pmc12465967-156-63-71?v=Human+Protein+Atlas
Average 86 stars, based on 1 article reviews
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96
Favorgen Biotech favorprep tissue genomic dna extraction mini kit
Biological functions associated with the recurrent scores. (A-B) The recurrent score related biological process revealed by Gene ontology analysis in the CGGA 693 and CGGA 325 database . (C-D) The heatmap showed the recurrent score and the enrichment scores of apoptosis-related functions of each patient in the CGGA 693 and CGGA 325 database. The samples were arranged in ascending order of the recurrent score. The column graph and line graph on the right showed the R -value and P -value of the correlation analysis. (E) Flow chart for recurrent score correlation analysis. (F-G) Using Pearson correlation analysis, the top 18 apoptosis-related genes mostly correlated with recurrent score were selected in CGGA 693 and CGGA 325 database. (H-I) The relationship between recurrent score and 6 apoptosis-related genes in glioma. The correlation coefficients were demonstrated as the proportion of the pie charts. The bottom right showed the correlation coefficient. The red parts represented a positive correlation. The correlation was tested by Pearson correlation analysis. (J) Correlation between the expression of the 6 genes in CGGA 693 and CGGA 325 database. ( K ) Expression levels of the 6 genes in primary glioma and recurrent glioma in CGGA 325 database and CGGA 693 database. (L) Survival analyses of the 6 genes by Kaplan-Meier curves and log-rank tests based on CCGA 693 database and CGGA 325 database. ( M ) Protein levels of SH3GLB1, NEK6, <t>CASP8</t> and ITGB1 in normal tissues and GBM from The Human Protein Atlas database
Favorprep Tissue Genomic Dna Extraction Mini Kit, supplied by Favorgen Biotech, used in various techniques. Bioz Stars score: 96/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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favorprep tissue genomic dna extraction mini kit - by Bioz Stars, 2026-08
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96
Favorgen Biotech fatrk001
Biological functions associated with the recurrent scores. (A-B) The recurrent score related biological process revealed by Gene ontology analysis in the CGGA 693 and CGGA 325 database . (C-D) The heatmap showed the recurrent score and the enrichment scores of apoptosis-related functions of each patient in the CGGA 693 and CGGA 325 database. The samples were arranged in ascending order of the recurrent score. The column graph and line graph on the right showed the R -value and P -value of the correlation analysis. (E) Flow chart for recurrent score correlation analysis. (F-G) Using Pearson correlation analysis, the top 18 apoptosis-related genes mostly correlated with recurrent score were selected in CGGA 693 and CGGA 325 database. (H-I) The relationship between recurrent score and 6 apoptosis-related genes in glioma. The correlation coefficients were demonstrated as the proportion of the pie charts. The bottom right showed the correlation coefficient. The red parts represented a positive correlation. The correlation was tested by Pearson correlation analysis. (J) Correlation between the expression of the 6 genes in CGGA 693 and CGGA 325 database. ( K ) Expression levels of the 6 genes in primary glioma and recurrent glioma in CGGA 325 database and CGGA 693 database. (L) Survival analyses of the 6 genes by Kaplan-Meier curves and log-rank tests based on CCGA 693 database and CGGA 325 database. ( M ) Protein levels of SH3GLB1, NEK6, <t>CASP8</t> and ITGB1 in normal tissues and GBM from The Human Protein Atlas database
Fatrk001, supplied by Favorgen Biotech, used in various techniques. Bioz Stars score: 96/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Average 96 stars, based on 1 article reviews
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97
Vazyme Biotech Co fastpure cell tissue dna isolation kit
Biological functions associated with the recurrent scores. (A-B) The recurrent score related biological process revealed by Gene ontology analysis in the CGGA 693 and CGGA 325 database . (C-D) The heatmap showed the recurrent score and the enrichment scores of apoptosis-related functions of each patient in the CGGA 693 and CGGA 325 database. The samples were arranged in ascending order of the recurrent score. The column graph and line graph on the right showed the R -value and P -value of the correlation analysis. (E) Flow chart for recurrent score correlation analysis. (F-G) Using Pearson correlation analysis, the top 18 apoptosis-related genes mostly correlated with recurrent score were selected in CGGA 693 and CGGA 325 database. (H-I) The relationship between recurrent score and 6 apoptosis-related genes in glioma. The correlation coefficients were demonstrated as the proportion of the pie charts. The bottom right showed the correlation coefficient. The red parts represented a positive correlation. The correlation was tested by Pearson correlation analysis. (J) Correlation between the expression of the 6 genes in CGGA 693 and CGGA 325 database. ( K ) Expression levels of the 6 genes in primary glioma and recurrent glioma in CGGA 325 database and CGGA 693 database. (L) Survival analyses of the 6 genes by Kaplan-Meier curves and log-rank tests based on CCGA 693 database and CGGA 325 database. ( M ) Protein levels of SH3GLB1, NEK6, <t>CASP8</t> and ITGB1 in normal tissues and GBM from The Human Protein Atlas database
Fastpure Cell Tissue Dna Isolation Kit, supplied by Vazyme Biotech Co, used in various techniques. Bioz Stars score: 97/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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fastpure cell tissue dna isolation kit - by Bioz Stars, 2026-08
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97
Miltenyi Biotec neural tissue dissociation kit
Biological functions associated with the recurrent scores. (A-B) The recurrent score related biological process revealed by Gene ontology analysis in the CGGA 693 and CGGA 325 database . (C-D) The heatmap showed the recurrent score and the enrichment scores of apoptosis-related functions of each patient in the CGGA 693 and CGGA 325 database. The samples were arranged in ascending order of the recurrent score. The column graph and line graph on the right showed the R -value and P -value of the correlation analysis. (E) Flow chart for recurrent score correlation analysis. (F-G) Using Pearson correlation analysis, the top 18 apoptosis-related genes mostly correlated with recurrent score were selected in CGGA 693 and CGGA 325 database. (H-I) The relationship between recurrent score and 6 apoptosis-related genes in glioma. The correlation coefficients were demonstrated as the proportion of the pie charts. The bottom right showed the correlation coefficient. The red parts represented a positive correlation. The correlation was tested by Pearson correlation analysis. (J) Correlation between the expression of the 6 genes in CGGA 693 and CGGA 325 database. ( K ) Expression levels of the 6 genes in primary glioma and recurrent glioma in CGGA 325 database and CGGA 693 database. (L) Survival analyses of the 6 genes by Kaplan-Meier curves and log-rank tests based on CCGA 693 database and CGGA 325 database. ( M ) Protein levels of SH3GLB1, NEK6, <t>CASP8</t> and ITGB1 in normal tissues and GBM from The Human Protein Atlas database
Neural Tissue Dissociation Kit, supplied by Miltenyi Biotec, used in various techniques. Bioz Stars score: 97/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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neural tissue dissociation kit - by Bioz Stars, 2026-08
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96
Miltenyi Biotec multi tissue dissociation kit
Biological functions associated with the recurrent scores. (A-B) The recurrent score related biological process revealed by Gene ontology analysis in the CGGA 693 and CGGA 325 database . (C-D) The heatmap showed the recurrent score and the enrichment scores of apoptosis-related functions of each patient in the CGGA 693 and CGGA 325 database. The samples were arranged in ascending order of the recurrent score. The column graph and line graph on the right showed the R -value and P -value of the correlation analysis. (E) Flow chart for recurrent score correlation analysis. (F-G) Using Pearson correlation analysis, the top 18 apoptosis-related genes mostly correlated with recurrent score were selected in CGGA 693 and CGGA 325 database. (H-I) The relationship between recurrent score and 6 apoptosis-related genes in glioma. The correlation coefficients were demonstrated as the proportion of the pie charts. The bottom right showed the correlation coefficient. The red parts represented a positive correlation. The correlation was tested by Pearson correlation analysis. (J) Correlation between the expression of the 6 genes in CGGA 693 and CGGA 325 database. ( K ) Expression levels of the 6 genes in primary glioma and recurrent glioma in CGGA 325 database and CGGA 693 database. (L) Survival analyses of the 6 genes by Kaplan-Meier curves and log-rank tests based on CCGA 693 database and CGGA 325 database. ( M ) Protein levels of SH3GLB1, NEK6, <t>CASP8</t> and ITGB1 in normal tissues and GBM from The Human Protein Atlas database
Multi Tissue Dissociation Kit, supplied by Miltenyi Biotec, used in various techniques. Bioz Stars score: 96/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Average 96 stars, based on 1 article reviews
multi tissue dissociation kit - by Bioz Stars, 2026-08
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Miltenyi Biotec ffpe tissue dissociation kit miltenyi biotec
Biological functions associated with the recurrent scores. (A-B) The recurrent score related biological process revealed by Gene ontology analysis in the CGGA 693 and CGGA 325 database . (C-D) The heatmap showed the recurrent score and the enrichment scores of apoptosis-related functions of each patient in the CGGA 693 and CGGA 325 database. The samples were arranged in ascending order of the recurrent score. The column graph and line graph on the right showed the R -value and P -value of the correlation analysis. (E) Flow chart for recurrent score correlation analysis. (F-G) Using Pearson correlation analysis, the top 18 apoptosis-related genes mostly correlated with recurrent score were selected in CGGA 693 and CGGA 325 database. (H-I) The relationship between recurrent score and 6 apoptosis-related genes in glioma. The correlation coefficients were demonstrated as the proportion of the pie charts. The bottom right showed the correlation coefficient. The red parts represented a positive correlation. The correlation was tested by Pearson correlation analysis. (J) Correlation between the expression of the 6 genes in CGGA 693 and CGGA 325 database. ( K ) Expression levels of the 6 genes in primary glioma and recurrent glioma in CGGA 325 database and CGGA 693 database. (L) Survival analyses of the 6 genes by Kaplan-Meier curves and log-rank tests based on CCGA 693 database and CGGA 325 database. ( M ) Protein levels of SH3GLB1, NEK6, <t>CASP8</t> and ITGB1 in normal tissues and GBM from The Human Protein Atlas database
Ffpe Tissue Dissociation Kit Miltenyi Biotec, supplied by Miltenyi Biotec, used in various techniques. Bioz Stars score: 96/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/tissues/pm41175874-232-234-238?v=Miltenyi+Biotec
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ffpe tissue dissociation kit miltenyi biotec - by Bioz Stars, 2026-08
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96
Miltenyi Biotec multi tissue dissociation kit 3
Biological functions associated with the recurrent scores. (A-B) The recurrent score related biological process revealed by Gene ontology analysis in the CGGA 693 and CGGA 325 database . (C-D) The heatmap showed the recurrent score and the enrichment scores of apoptosis-related functions of each patient in the CGGA 693 and CGGA 325 database. The samples were arranged in ascending order of the recurrent score. The column graph and line graph on the right showed the R -value and P -value of the correlation analysis. (E) Flow chart for recurrent score correlation analysis. (F-G) Using Pearson correlation analysis, the top 18 apoptosis-related genes mostly correlated with recurrent score were selected in CGGA 693 and CGGA 325 database. (H-I) The relationship between recurrent score and 6 apoptosis-related genes in glioma. The correlation coefficients were demonstrated as the proportion of the pie charts. The bottom right showed the correlation coefficient. The red parts represented a positive correlation. The correlation was tested by Pearson correlation analysis. (J) Correlation between the expression of the 6 genes in CGGA 693 and CGGA 325 database. ( K ) Expression levels of the 6 genes in primary glioma and recurrent glioma in CGGA 325 database and CGGA 693 database. (L) Survival analyses of the 6 genes by Kaplan-Meier curves and log-rank tests based on CCGA 693 database and CGGA 325 database. ( M ) Protein levels of SH3GLB1, NEK6, <t>CASP8</t> and ITGB1 in normal tissues and GBM from The Human Protein Atlas database
Multi Tissue Dissociation Kit 3, supplied by Miltenyi Biotec, used in various techniques. Bioz Stars score: 96/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/tissues/pm38951692-398-6-11?v=Miltenyi+Biotec
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multi tissue dissociation kit 3 - by Bioz Stars, 2026-08
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93
Elabscience Biotechnology timp 2
Biological functions associated with the recurrent scores. (A-B) The recurrent score related biological process revealed by Gene ontology analysis in the CGGA 693 and CGGA 325 database . (C-D) The heatmap showed the recurrent score and the enrichment scores of apoptosis-related functions of each patient in the CGGA 693 and CGGA 325 database. The samples were arranged in ascending order of the recurrent score. The column graph and line graph on the right showed the R -value and P -value of the correlation analysis. (E) Flow chart for recurrent score correlation analysis. (F-G) Using Pearson correlation analysis, the top 18 apoptosis-related genes mostly correlated with recurrent score were selected in CGGA 693 and CGGA 325 database. (H-I) The relationship between recurrent score and 6 apoptosis-related genes in glioma. The correlation coefficients were demonstrated as the proportion of the pie charts. The bottom right showed the correlation coefficient. The red parts represented a positive correlation. The correlation was tested by Pearson correlation analysis. (J) Correlation between the expression of the 6 genes in CGGA 693 and CGGA 325 database. ( K ) Expression levels of the 6 genes in primary glioma and recurrent glioma in CGGA 325 database and CGGA 693 database. (L) Survival analyses of the 6 genes by Kaplan-Meier curves and log-rank tests based on CCGA 693 database and CGGA 325 database. ( M ) Protein levels of SH3GLB1, NEK6, <t>CASP8</t> and ITGB1 in normal tissues and GBM from The Human Protein Atlas database
Timp 2, supplied by Elabscience Biotechnology, used in various techniques. Bioz Stars score: 93/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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timp 2 - by Bioz Stars, 2026-08
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94
R&D Systems erythropoietin
Biological functions associated with the recurrent scores. (A-B) The recurrent score related biological process revealed by Gene ontology analysis in the CGGA 693 and CGGA 325 database . (C-D) The heatmap showed the recurrent score and the enrichment scores of apoptosis-related functions of each patient in the CGGA 693 and CGGA 325 database. The samples were arranged in ascending order of the recurrent score. The column graph and line graph on the right showed the R -value and P -value of the correlation analysis. (E) Flow chart for recurrent score correlation analysis. (F-G) Using Pearson correlation analysis, the top 18 apoptosis-related genes mostly correlated with recurrent score were selected in CGGA 693 and CGGA 325 database. (H-I) The relationship between recurrent score and 6 apoptosis-related genes in glioma. The correlation coefficients were demonstrated as the proportion of the pie charts. The bottom right showed the correlation coefficient. The red parts represented a positive correlation. The correlation was tested by Pearson correlation analysis. (J) Correlation between the expression of the 6 genes in CGGA 693 and CGGA 325 database. ( K ) Expression levels of the 6 genes in primary glioma and recurrent glioma in CGGA 325 database and CGGA 693 database. (L) Survival analyses of the 6 genes by Kaplan-Meier curves and log-rank tests based on CCGA 693 database and CGGA 325 database. ( M ) Protein levels of SH3GLB1, NEK6, <t>CASP8</t> and ITGB1 in normal tissues and GBM from The Human Protein Atlas database
Erythropoietin, supplied by R&D Systems, used in various techniques. Bioz Stars score: 94/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Image Search Results


Biological functions associated with the recurrent scores. (A-B) The recurrent score related biological process revealed by Gene ontology analysis in the CGGA 693 and CGGA 325 database . (C-D) The heatmap showed the recurrent score and the enrichment scores of apoptosis-related functions of each patient in the CGGA 693 and CGGA 325 database. The samples were arranged in ascending order of the recurrent score. The column graph and line graph on the right showed the R -value and P -value of the correlation analysis. (E) Flow chart for recurrent score correlation analysis. (F-G) Using Pearson correlation analysis, the top 18 apoptosis-related genes mostly correlated with recurrent score were selected in CGGA 693 and CGGA 325 database. (H-I) The relationship between recurrent score and 6 apoptosis-related genes in glioma. The correlation coefficients were demonstrated as the proportion of the pie charts. The bottom right showed the correlation coefficient. The red parts represented a positive correlation. The correlation was tested by Pearson correlation analysis. (J) Correlation between the expression of the 6 genes in CGGA 693 and CGGA 325 database. ( K ) Expression levels of the 6 genes in primary glioma and recurrent glioma in CGGA 325 database and CGGA 693 database. (L) Survival analyses of the 6 genes by Kaplan-Meier curves and log-rank tests based on CCGA 693 database and CGGA 325 database. ( M ) Protein levels of SH3GLB1, NEK6, CASP8 and ITGB1 in normal tissues and GBM from The Human Protein Atlas database

Journal: BMC Immunology

Article Title: Establishment and validation of a recurrent prediction model for glioma: extrinsic apoptotic molecules FADD and CASP8 are closely associated with glioma recurrence

doi: 10.1186/s12865-025-00746-z

Figure Lengend Snippet: Biological functions associated with the recurrent scores. (A-B) The recurrent score related biological process revealed by Gene ontology analysis in the CGGA 693 and CGGA 325 database . (C-D) The heatmap showed the recurrent score and the enrichment scores of apoptosis-related functions of each patient in the CGGA 693 and CGGA 325 database. The samples were arranged in ascending order of the recurrent score. The column graph and line graph on the right showed the R -value and P -value of the correlation analysis. (E) Flow chart for recurrent score correlation analysis. (F-G) Using Pearson correlation analysis, the top 18 apoptosis-related genes mostly correlated with recurrent score were selected in CGGA 693 and CGGA 325 database. (H-I) The relationship between recurrent score and 6 apoptosis-related genes in glioma. The correlation coefficients were demonstrated as the proportion of the pie charts. The bottom right showed the correlation coefficient. The red parts represented a positive correlation. The correlation was tested by Pearson correlation analysis. (J) Correlation between the expression of the 6 genes in CGGA 693 and CGGA 325 database. ( K ) Expression levels of the 6 genes in primary glioma and recurrent glioma in CGGA 325 database and CGGA 693 database. (L) Survival analyses of the 6 genes by Kaplan-Meier curves and log-rank tests based on CCGA 693 database and CGGA 325 database. ( M ) Protein levels of SH3GLB1, NEK6, CASP8 and ITGB1 in normal tissues and GBM from The Human Protein Atlas database

Article Snippet: Characterizing the differential expression patterns of CASP8 and FADD in gliomas and normal tissues will play a crucial role in the further development of targeted therapeutic strategies for gliomas Fig. 9 RNA and protein levels of CASP8 and FADD in normal tissues and tumors. (A-B) RNA expression of CASP8 and FADD in normal tissues from the NCBI database (https://www.ncbi.nlm.nih.gov/). (C-D) RNA expression of CASP8 and FADD in normal tissues from the Human Protein Atlas database (https://www.proteinatlas.org/). (E) Protein levels of CASP8 and FADD in normal brain tissues from The Human Protein Atlas database. (F) Protein levels of CASP8 and FADD in normal tissues from The Human Protein Atlas database. (G) Protein levels of CASP8 and FADD in tumors from The Human Protein Atlas database

Techniques: Expressing

The association between recurrent score and classical apoptotic genes. (A) The relationship between the 6 genes and recurrent score in CGGA and TCGA database . (B) PPI network of CASP3, CASP9, FADD, CASP7, CASP8, BCL2,and the 9-gene signature from the STRING. (C-D) The expression levels of the 6 apoptotic genes in low- and high-risk levels . (E-J) Correlation between recurrent score and expression levels of apoptotic genes. *P<0.05; ***P<0.001; ns, not significant

Journal: BMC Immunology

Article Title: Establishment and validation of a recurrent prediction model for glioma: extrinsic apoptotic molecules FADD and CASP8 are closely associated with glioma recurrence

doi: 10.1186/s12865-025-00746-z

Figure Lengend Snippet: The association between recurrent score and classical apoptotic genes. (A) The relationship between the 6 genes and recurrent score in CGGA and TCGA database . (B) PPI network of CASP3, CASP9, FADD, CASP7, CASP8, BCL2,and the 9-gene signature from the STRING. (C-D) The expression levels of the 6 apoptotic genes in low- and high-risk levels . (E-J) Correlation between recurrent score and expression levels of apoptotic genes. *P<0.05; ***P<0.001; ns, not significant

Article Snippet: Characterizing the differential expression patterns of CASP8 and FADD in gliomas and normal tissues will play a crucial role in the further development of targeted therapeutic strategies for gliomas Fig. 9 RNA and protein levels of CASP8 and FADD in normal tissues and tumors. (A-B) RNA expression of CASP8 and FADD in normal tissues from the NCBI database (https://www.ncbi.nlm.nih.gov/). (C-D) RNA expression of CASP8 and FADD in normal tissues from the Human Protein Atlas database (https://www.proteinatlas.org/). (E) Protein levels of CASP8 and FADD in normal brain tissues from The Human Protein Atlas database. (F) Protein levels of CASP8 and FADD in normal tissues from The Human Protein Atlas database. (G) Protein levels of CASP8 and FADD in tumors from The Human Protein Atlas database

Techniques: Expressing

RNA and protein levels of CASP8 and FADD in normal tissues and tumors. (A-B) RNA expression of CASP8 and FADD in normal tissues from the NCBI database (https://www.ncbi.nlm.nih.gov/). (C-D) RNA expression of CASP8 and FADD in normal tissues from the Human Protein Atlas database (https://www.proteinatlas.org/). (E) Protein levels of CASP8 and FADD in normal brain tissues from The Human Protein Atlas database. (F) Protein levels of CASP8 and FADD in normal tissues from The Human Protein Atlas database. (G) Protein levels of CASP8 and FADD in tumors from The Human Protein Atlas database

Journal: BMC Immunology

Article Title: Establishment and validation of a recurrent prediction model for glioma: extrinsic apoptotic molecules FADD and CASP8 are closely associated with glioma recurrence

doi: 10.1186/s12865-025-00746-z

Figure Lengend Snippet: RNA and protein levels of CASP8 and FADD in normal tissues and tumors. (A-B) RNA expression of CASP8 and FADD in normal tissues from the NCBI database (https://www.ncbi.nlm.nih.gov/). (C-D) RNA expression of CASP8 and FADD in normal tissues from the Human Protein Atlas database (https://www.proteinatlas.org/). (E) Protein levels of CASP8 and FADD in normal brain tissues from The Human Protein Atlas database. (F) Protein levels of CASP8 and FADD in normal tissues from The Human Protein Atlas database. (G) Protein levels of CASP8 and FADD in tumors from The Human Protein Atlas database

Article Snippet: Characterizing the differential expression patterns of CASP8 and FADD in gliomas and normal tissues will play a crucial role in the further development of targeted therapeutic strategies for gliomas Fig. 9 RNA and protein levels of CASP8 and FADD in normal tissues and tumors. (A-B) RNA expression of CASP8 and FADD in normal tissues from the NCBI database (https://www.ncbi.nlm.nih.gov/). (C-D) RNA expression of CASP8 and FADD in normal tissues from the Human Protein Atlas database (https://www.proteinatlas.org/). (E) Protein levels of CASP8 and FADD in normal brain tissues from The Human Protein Atlas database. (F) Protein levels of CASP8 and FADD in normal tissues from The Human Protein Atlas database. (G) Protein levels of CASP8 and FADD in tumors from The Human Protein Atlas database

Techniques: RNA Expression