Q-omics provides the consensus-scored DDX10 profile across patient tissues and cancer cell-line models. DDX10 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, DDX10 is differentially expressed in 14, with the highest sampling consensus in HNSC. Additionally, DDX10 protein abundance shows 26,065 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight HNSC, and LSCC as cancer lineages where DDX10 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 DDX10 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes DDX10 survival associations across molecular data types. DDX10 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (3) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible DDX10 RNA expression–survival associations across cancer types. High DDX10 expression shows unfavorable associations in HNSC, ACC, PAAD, LIHC and BLCA, but favorable associations in KIRC. The HNSC 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 HNSC as the clearest survival context for DDX10 RNA expression.
This table summarizes DDX10 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 5. The strongest signals are observed in HNSC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for DDX10. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. DDX10 shows higher tumor expression in HNSC, LUSC, COAD, LIHC, STAD and LUAD. The HNSC box plot shows higher DDX10 RNA expression in tumor versus normal tissue (log2 FC = +0.973, t-test p < 0.001).
This table shows molecular features associated with DDX10 in patient tissues and cancer cell lines. In patient samples, DDX10 shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set. In cancer cell lines, DDX10 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in PANCREAS, while CRISPR and shRNA rows add functional-dependency signals in CNS and BLOOD_Lymphoma.
