Q-omics provides the consensus-scored GMFB profile across patient tissues and cancer cell-line models. GMFB expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, GMFB is differentially expressed in 16, with the highest sampling consensus in HNSC. Additionally, GMFB protein abundance shows 24,607 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight ACC, HNSC, and PDAC as cancer lineages where GMFB 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 GMFB — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes GMFB survival associations across molecular data types. GMFB RNA expression shows survival associations in the most cancer types (21), followed by mutation status (2) and mass-spec protein abundance (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible GMFB RNA expression–survival associations across cancer types. High GMFB expression shows unfavorable associations in ACC, LIHC, HNSC, BLCA and UVM, but favorable associations in KIRC. The ACC 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 ACC as the clearest survival context for GMFB RNA expression.
This table summarizes GMFB tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 16, while mass-spec protein shows differences in 5. The strongest signals are observed in HNSC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for GMFB. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. GMFB shows lower tumor expression in KIRC, KICH and LUAD and higher tumor expression in HNSC, LIHC and STAD. The HNSC box plot shows higher GMFB RNA expression in tumor versus normal tissue (log2 FC = +1.463, t-test p < 0.001).
This table shows molecular features associated with GMFB in patient tissues and cancer cell lines. In patient samples, GMFB shows the broadest associations at the RNA and protein expression levels, with PDAC recurring as the lineage with the largest associated feature set. In cancer cell lines, GMFB RNA and mutation anchors are most strongly linked to RNA-expression features, especially in KIDNEY, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and CNS.
