Q-omics provides the consensus-scored MAGEB17 profile across patient tissues and cancer cell-line models. MAGEB17 expression is associated with patient survival in 18 of 34 cancer types, with the highest sampling consensus in LGG. Among the 18 cancer types available for tumor–normal comparison, MAGEB17 is differentially expressed in 12, with the highest sampling consensus in LIHC. Additionally, MAGEB17 RNA expression shows 11,357 significant gene co-expression associations, with the highest sampling consensus in TGCT. Together, these results highlight LGG, LIHC, and TGCT as cancer lineages where MAGEB17 shows reproducible signals across survival, tumor–normal expression, and patient cross-omics analyses.
Every result is evaluated using two consensus scores. Sampling consensus measures how consistently a finding is reproduced within a cancer lineage across different conditions. Lineage consensus measures how broadly the result is shared across cancer types, distinguishing pan-cancer signals from lineage-specific patterns.
Premium analyses for MAGEB17 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes MAGEB17 survival associations across molecular data types. MAGEB17 RNA expression shows survival associations in the most cancer types (18). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible MAGEB17 RNA expression–survival associations across cancer types. High MAGEB17 expression shows unfavorable associations in LGG and LUAD, but favorable associations in BRCA, SKCM, ACC and SARC. The LGG Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p < 0.001). Together, the overview and detailed table identify LGG as the clearest survival context for MAGEB17 RNA expression.
This table summarizes MAGEB17 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12. The strongest signals are observed in LIHC for RNA.
This table ranks reproducible tumor–normal expression differences for MAGEB17. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. MAGEB17 shows higher tumor expression in LIHC, COAD, UCEC, BRCA, KICH and HNSC. The LIHC box plot shows higher MAGEB17 RNA expression in tumor versus normal tissue (log2 FC = +1.100, t-test p < 0.001).
This table shows molecular features associated with MAGEB17 in patient tissues and cancer cell lines. In patient samples, MAGEB17 shows the broadest associations at the RNA and protein expression levels, with TGCT recurring as the lineage with the largest associated feature set. In cancer cell lines, MAGEB17 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in PANCREAS, while CRISPR and shRNA rows add functional-dependency signals in SKIN and BREAST.
