Q-omics provides the consensus-scored DYNLL1P4 profile across patient tissues and cancer cell-line models. DYNLL1P4 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, DYNLL1P4 is differentially expressed in 11, with the highest sampling consensus in HNSC. Additionally, DYNLL1P4 RNA expression shows 9,752 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight KIRC, HNSC, and UVM as cancer lineages where DYNLL1P4 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 DYNLL1P4 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes DYNLL1P4 survival associations across molecular data types. DYNLL1P4 RNA expression shows survival associations in the most cancer types (15). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible DYNLL1P4 RNA expression–survival associations across cancer types. High DYNLL1P4 expression shows unfavorable associations in KIRC, ACC, PRAD and MESO, but favorable associations in UCS and SKCM. 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 DYNLL1P4 RNA expression.
This table summarizes DYNLL1P4 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11. The strongest signals are observed in HNSC for RNA.
This table ranks reproducible tumor–normal expression differences for DYNLL1P4. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. DYNLL1P4 shows lower tumor expression in BRCA, UCEC and BLCA and higher tumor expression in HNSC, KIRC and ESCA. The HNSC box plot shows higher DYNLL1P4 RNA expression in tumor versus normal tissue (log2 FC = +0.380, t-test p < 0.001).
This table shows molecular features associated with DYNLL1P4 in patient tissues and cancer cell lines. In patient samples, DYNLL1P4 shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set.
