Q-omics provides the consensus-scored DDX25 profile across patient tissues and cancer cell-line models. DDX25 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in LGG. Among the 18 cancer types available for tumor–normal comparison, DDX25 is differentially expressed in 13, with the highest sampling consensus in KIRC. Additionally, DDX25 protein abundance shows 23,532 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight LGG, KIRC, and LSCC as cancer lineages where DDX25 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 DDX25 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes DDX25 survival associations across molecular data types. DDX25 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (3) and mass-spec protein abundance (8). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible DDX25 RNA expression–survival associations across cancer types. High DDX25 expression shows unfavorable associations in LUAD, but favorable associations in LGG, UCS, PAAD, LUSC and MESO. 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 DDX25 RNA expression.
This table summarizes DDX25 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 8. The strongest signals are observed in KIRC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for DDX25. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. DDX25 shows lower tumor expression in KIRC, THCA, KICH, KIRP, COAD and HNSC. The KIRC box plot shows higher DDX25 RNA expression in normal versus tumor tissue (log2 FC = −0.736, t-test p < 0.001).
This table shows molecular features associated with DDX25 in patient tissues and cancer cell lines. In patient samples, DDX25 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, DDX25 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BREAST, while CRISPR and shRNA rows add functional-dependency signals in BONE and BLOOD_Leukemia.
