Q-omics provides the consensus-scored DDX11 profile across patient tissues and cancer cell-line models. DDX11 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, DDX11 is differentially expressed in 14, with the highest sampling consensus in HNSC. Additionally, DDX11 RNA expression shows 17,716 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight ACC, and HNSC as cancer lineages where DDX11 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 DDX11 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes DDX11 survival associations across molecular data types. DDX11 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (7) 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 DDX11 RNA expression–survival associations across cancer types. High DDX11 expression shows unfavorable associations in ACC, KIRC, LIHC, MESO and COAD, but favorable associations in HNSC. 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 DDX11 RNA expression.
This table summarizes DDX11 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 DDX11. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. DDX11 shows higher tumor expression in HNSC, COAD, KIRC, KIRP, BLCA and LUAD. The HNSC box plot shows higher DDX11 RNA expression in tumor versus normal tissue (log2 FC = +1.336, t-test p < 0.001).
This table shows molecular features associated with DDX11 in patient tissues and cancer cell lines. In patient samples, DDX11 shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, DDX11 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 STOMACH and BLOOD_Leukemia.
