Q-omics provides the consensus-scored DOHH profile across patient tissues and cancer cell-line models. DOHH expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in UCEC. Among the 18 cancer types available for tumor–normal comparison, DOHH is differentially expressed in 12, with the highest sampling consensus in COAD. Additionally, DOHH protein abundance shows 19,861 significant protein co-abundance associations, with the highest sampling consensus in LUAD. Together, these results highlight UCEC, COAD, and LUAD as cancer lineages where DOHH 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 DOHH — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes DOHH survival associations across molecular data types. DOHH RNA expression shows survival associations in the most cancer types (26), followed by mutation status (3) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible DOHH RNA expression–survival associations across cancer types. High DOHH expression shows unfavorable associations in ACC, UCS, PRAD and LGG, but favorable associations in UCEC and SCLC. The UCEC 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 UCEC as the clearest survival context for DOHH RNA expression.
This table summarizes DOHH tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 3. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for DOHH. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. DOHH shows higher tumor expression in COAD, KIRC, STAD, LIHC, HNSC and KIRP. The COAD box plot shows higher DOHH RNA expression in tumor versus normal tissue (log2 FC = +0.949, t-test p < 0.001).
This table shows molecular features associated with DOHH in patient tissues and cancer cell lines. In patient samples, DOHH 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, DOHH RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BONE, while CRISPR and shRNA rows add functional-dependency signals in BREAST and SOFT_TISSUE.
