Q-omics provides the consensus-scored DDOST profile across patient tissues and cancer cell-line models. DDOST expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in KICH. Among the 18 cancer types available for tumor–normal comparison, DDOST is differentially expressed in 17, with the highest sampling consensus in HNSC. Additionally, DDOST protein abundance shows 24,962 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight KICH, HNSC, and GBM as cancer lineages where DDOST 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 DDOST — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes DDOST survival associations across molecular data types. DDOST RNA expression shows survival associations in the most cancer types (25), followed by mutation status (3) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible DDOST RNA expression–survival associations across cancer types. High DDOST expression shows unfavorable associations in KICH, KIRP, ACC, LIHC, HNSC and LGG. 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 DDOST RNA expression.
This table summarizes DDOST 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 7. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for DDOST. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. DDOST shows higher tumor expression in HNSC, KIRC, BLCA, COAD, LIHC and KIRP. The HNSC box plot shows higher DDOST RNA expression in tumor versus normal tissue (log2 FC = +1.218, t-test p < 0.001).
This table shows molecular features associated with DDOST in patient tissues and cancer cell lines. In patient samples, DDOST shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, DDOST 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.
