Q-omics provides the consensus-scored FUT2 profile across patient tissues and cancer cell-line models. FUT2 expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, FUT2 is differentially expressed in 14, with the highest sampling consensus in KIRC. Additionally, FUT2 RNA expression shows 19,008 significant gene co-expression associations, with the highest sampling consensus in TGCT. Together, these results highlight ACC, KIRC, and TGCT as cancer lineages where FUT2 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 FUT2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes FUT2 survival associations across molecular data types. FUT2 RNA expression shows survival associations in the most cancer types (22), followed by mutation status (4) 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 FUT2 RNA expression–survival associations across cancer types. High FUT2 expression shows unfavorable associations in ACC, SKCM and ESCA, but favorable associations in HNSC, STAD and LUSC. 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 FUT2 RNA expression.
This table summarizes FUT2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, while mass-spec protein shows differences in 3. The strongest signals are observed in KIRC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for FUT2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. FUT2 shows lower tumor expression in KIRC and HNSC and higher tumor expression in LUAD, THCA, LUSC and LIHC. The KIRC box plot shows higher FUT2 RNA expression in normal versus tumor tissue (log2 FC = −1.180, t-test p < 0.001).
This table shows molecular features associated with FUT2 in patient tissues and cancer cell lines. In patient samples, FUT2 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, FUT2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_SCLC, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and LUNG_NSCLC_LUAD.
