Q-omics provides the consensus-scored DYNAP profile across patient tissues and cancer cell-line models. DYNAP expression is associated with patient survival in 15 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, DYNAP is differentially expressed in 5, with the highest sampling consensus in HNSC. Additionally, DYNAP RNA expression shows 8,937 significant gene co-expression associations, with the highest sampling consensus in TGCT. Together, these results highlight KIRC, HNSC, and TGCT as cancer lineages where DYNAP 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 DYNAP — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes DYNAP survival associations across molecular data types. DYNAP RNA expression shows survival associations in the most cancer types (15), followed by mutation status (2). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible DYNAP RNA expression–survival associations across cancer types. High DYNAP expression shows unfavorable associations in KIRC, UCEC, KICH and KIRP, but favorable associations in SCLC and HNSC. The KIRC 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 KIRC as the clearest survival context for DYNAP RNA expression.
This table summarizes DYNAP 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 DYNAP. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. DYNAP shows lower tumor expression in HNSC and higher tumor expression in LUSC, UCEC, BRCA and LUAD. The HNSC box plot shows higher DYNAP RNA expression in normal versus tumor tissue (log2 FC = −3.712, t-test p < 0.001).
This table shows molecular features associated with DYNAP in patient tissues and cancer cell lines. In patient samples, DYNAP shows the broadest associations at the RNA and protein expression levels, with TGCT recurring as the lineage with the largest associated feature set. In cancer cell lines, DYNAP 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 LUNG_NSCLC_LUAD and LARGE_INTESTINE.
