Q-omics provides the consensus-scored DDX49 profile across patient tissues and cancer cell-line models. DDX49 expression is associated with patient survival in 29 of 34 cancer types, with the highest sampling consensus in KICH. Among the 18 cancer types available for tumor–normal comparison, DDX49 is differentially expressed in 17, with the highest sampling consensus in KIRC. Additionally, DDX49 protein abundance shows 30,058 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight KICH, KIRC, and LSCC as cancer lineages where DDX49 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 DDX49 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes DDX49 survival associations across molecular data types. DDX49 RNA expression shows survival associations in the most cancer types (29), followed by mutation status (6) and mass-spec protein abundance (10). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible DDX49 RNA expression–survival associations across cancer types. High DDX49 expression shows unfavorable associations in KICH, ACC and LIHC, but favorable associations in CESC, SCLC and STAD. The KICH Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .001). Together, the overview and detailed table identify KICH as the clearest survival context for DDX49 RNA expression.
This table summarizes DDX49 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 17, while mass-spec protein shows differences in 8. The strongest signals are observed in KIRC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for DDX49. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. DDX49 shows higher tumor expression in KIRC, BLCA, COAD, LIHC, KIRP and LUSC. The KIRC box plot shows higher DDX49 RNA expression in tumor versus normal tissue (log2 FC = +1.049, t-test p < 0.001).
This table shows molecular features associated with DDX49 in patient tissues and cancer cell lines. In patient samples, DDX49 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, DDX49 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in CNS, while CRISPR and shRNA rows add functional-dependency signals in OESOPHAGUS and UPPER_AERODIGESTIVE_TRACT.
