Q-omics provides the consensus-scored DTX3 profile across patient tissues and cancer cell-line models. DTX3 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, DTX3 is differentially expressed in 12, with the highest sampling consensus in KIRC. Additionally, DTX3 protein abundance shows 21,655 significant protein co-abundance associations, with the highest sampling consensus in UCEC. Together, these results highlight ACC, KIRC, and UCEC as cancer lineages where DTX3 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 DTX3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes DTX3 survival associations across molecular data types. DTX3 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (4) and mass-spec protein abundance (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible DTX3 RNA expression–survival associations across cancer types. High DTX3 expression shows unfavorable associations in ACC, KIRC and DLBC, but favorable associations in PAAD, KIRP and BRCA. The ACC Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p < 0.001). Together, the overview and detailed table identify ACC as the clearest survival context for DTX3 RNA expression.
This table summarizes DTX3 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 4. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for DTX3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. DTX3 shows lower tumor expression in KIRC, THCA, UCEC and KICH and higher tumor expression in HNSC and LIHC. The KIRC box plot shows higher DTX3 RNA expression in normal versus tumor tissue (log2 FC = −1.286, t-test p < 0.001).
This table shows molecular features associated with DTX3 in patient tissues and cancer cell lines. In patient samples, DTX3 shows the broadest associations at the RNA and protein expression levels, with UCEC recurring as the lineage with the largest associated feature set. In cancer cell lines, DTX3 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUAD, while CRISPR and shRNA rows add functional-dependency signals in URINARY_TRACT and LUNG_SCLC.
