Q-omics provides the consensus-scored DYTN profile across patient tissues and cancer cell-line models. DYTN expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in CHOL. Among the 18 cancer types available for tumor–normal comparison, DYTN is differentially expressed in 5, with the highest sampling consensus in HNSC. Additionally, DYTN RNA expression shows 6,849 significant pathway-activity associations, with the highest sampling consensus in STAD. Together, these results highlight CHOL, HNSC, and STAD as cancer lineages where DYTN 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 DYTN — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes DYTN survival associations across molecular data types. DYTN RNA expression shows survival associations in the most cancer types (22), followed by mutation status (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible DYTN RNA expression–survival associations across cancer types. High DYTN expression shows unfavorable associations in CHOL, SCLC, CESC, UCEC, UVM and LUSC. The CHOL 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 CHOL as the clearest survival context for DYTN RNA expression.
This table summarizes DYTN 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 DYTN. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. DYTN shows lower tumor expression in COAD and LUAD and higher tumor expression in HNSC, BLCA and PRAD. The HNSC box plot shows higher DYTN RNA expression in tumor versus normal tissue (log2 FC = +0.014, t-test p = .002).
This table shows molecular features associated with DYTN in patient tissues and cancer cell lines. In patient samples, DYTN 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, DYTN 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 BONE and LARGE_INTESTINE.
