Q-omics provides the consensus-scored DDX43 profile across patient tissues and cancer cell-line models. DDX43 expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, DDX43 is differentially expressed in 10, with the highest sampling consensus in THCA. Additionally, DDX43 protein abundance shows 14,675 significant protein co-abundance associations, with the highest sampling consensus in LUAD. Together, these results highlight HNSC, THCA, and LUAD as cancer lineages where DDX43 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 DDX43 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes DDX43 survival associations across molecular data types. DDX43 RNA expression shows survival associations in the most cancer types (26), followed by mutation status (5) 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 DDX43 RNA expression–survival associations across cancer types. High DDX43 expression shows unfavorable associations in ACC and UCEC, but favorable associations in HNSC, SKCM, SCLC and UCS. The HNSC 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 HNSC as the clearest survival context for DDX43 RNA expression.
This table summarizes DDX43 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10, while mass-spec protein shows differences in 6. The strongest signals are observed in THCA for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for DDX43. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. DDX43 shows lower tumor expression in THCA, KICH, LUSC, BRCA, BLCA and LUAD. The THCA box plot shows higher DDX43 RNA expression in normal versus tumor tissue (log2 FC = −1.470, t-test p < 0.001).
This table shows molecular features associated with DDX43 in patient tissues and cancer cell lines. In patient samples, DDX43 shows the broadest associations at the RNA and protein expression levels, with LUAD recurring as the lineage with the largest associated feature set. In cancer cell lines, DDX43 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 SKIN and LARGE_INTESTINE.
