Q-omics provides the consensus-scored GFUS profile across patient tissues and cancer cell-line models. GFUS expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, GFUS is differentially expressed in 17, with the highest sampling consensus in COAD. Additionally, GFUS protein abundance shows 19,606 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight UVM, COAD, and PDAC as cancer lineages where GFUS 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 GFUS — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes GFUS survival associations across molecular data types. GFUS RNA expression shows survival associations in the most cancer types (26), followed by mutation status (3) and mass-spec protein abundance (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible GFUS RNA expression–survival associations across cancer types. High GFUS expression shows unfavorable associations in UVM, KIRC, ACC, LUSC, BRCA and HNSC. The UVM 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 UVM as the clearest survival context for GFUS RNA expression.
This table summarizes GFUS tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 17, while mass-spec protein shows differences in 4. The strongest signals are observed in COAD for RNA and PDAC for protein.
This table ranks reproducible tumor–normal expression differences for GFUS. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. GFUS shows higher tumor expression in COAD, BLCA, THCA, LUAD, LIHC and LUSC. The COAD box plot shows higher GFUS RNA expression in tumor versus normal tissue (log2 FC = +2.384, t-test p < 0.001).
This table shows molecular features associated with GFUS in patient tissues and cancer cell lines. In patient samples, GFUS 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, GFUS RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LIVER, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Myeloma and BLOOD_Lymphoma.
