Q-omics provides the consensus-scored FUT9 profile across patient tissues and cancer cell-line models. FUT9 expression is associated with patient survival in 16 of 34 cancer types, with the highest sampling consensus in LGG. Among the 18 cancer types available for tumor–normal comparison, FUT9 is differentially expressed in 10, with the highest sampling consensus in BLCA. Additionally, FUT9 RNA expression shows 15,260 significant gene co-expression associations, with the highest sampling consensus in TGCT. Together, these results highlight LGG, BLCA, and TGCT as cancer lineages where FUT9 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 FUT9 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes FUT9 survival associations across molecular data types. FUT9 RNA expression shows survival associations in the most cancer types (16), followed by mutation status (10). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible FUT9 RNA expression–survival associations across cancer types. High FUT9 expression shows unfavorable associations in LUAD, UVM and THCA, but favorable associations in LGG, KIRP and SARC. The LGG Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p < 0.001). Together, the overview and detailed table identify LGG as the clearest survival context for FUT9 RNA expression.
This table summarizes FUT9 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10. The strongest signals are observed in BLCA for RNA.
This table ranks reproducible tumor–normal expression differences for FUT9. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. FUT9 shows lower tumor expression in COAD and READ and higher tumor expression in BLCA, THCA, LUAD and LUSC. The BLCA box plot shows higher FUT9 RNA expression in tumor versus normal tissue (log2 FC = +1.778, t-test p = .002).
This table shows molecular features associated with FUT9 in patient tissues and cancer cell lines. In patient samples, FUT9 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, FUT9 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 LUNG_SCLC and BREAST.
