Q-omics provides the consensus-scored ODF4 profile across patient tissues and cancer cell-line models. ODF4 expression is associated with patient survival in 20 of 34 cancer types, with the highest sampling consensus in READ. Among the 18 cancer types available for tumor–normal comparison, ODF4 is differentially expressed in 5, with the highest sampling consensus in HNSC. Additionally, ODF4 RNA expression shows 6,836 significant pathway-activity associations, with the highest sampling consensus in STAD. Together, these results highlight READ, HNSC, and STAD as cancer lineages where ODF4 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 ODF4 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ODF4 survival associations across molecular data types. ODF4 RNA expression shows survival associations in the most cancer types (20), followed by mutation status (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ODF4 RNA expression–survival associations across cancer types. High ODF4 expression shows unfavorable associations in READ, KIRC and SCLC, but favorable associations in LAML, HNSC and CESC. The READ Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .016). Together, the overview and detailed table identify READ as the clearest survival context for ODF4 RNA expression.
This table summarizes ODF4 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 5. The strongest signals are observed in HNSC for RNA.
This table ranks reproducible tumor–normal expression differences for ODF4. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ODF4 shows lower tumor expression in HNSC, STAD and LUAD and higher tumor expression in BLCA and THCA. The HNSC box plot shows higher ODF4 RNA expression in normal versus tumor tissue (log2 FC = −0.467, t-test p < 0.001).
This table shows molecular features associated with ODF4 in patient tissues and cancer cell lines. In patient samples, ODF4 shows the broadest associations at the RNA and protein expression levels, with STAD recurring as the lineage with the largest associated feature set. In cancer cell lines, ODF4 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SKIN, while CRISPR and shRNA rows add functional-dependency signals in LUNG_SCLC and BREAST.
