Q-omics provides the consensus-scored DYNLL1P2 profile across patient tissues and cancer cell-line models. DYNLL1P2 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in STAD. Among the 18 cancer types available for tumor–normal comparison, DYNLL1P2 is differentially expressed in 3, with the highest sampling consensus in KICH. Additionally, DYNLL1P2 RNA expression shows 10,752 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight STAD, KICH, and GBM as cancer lineages where DYNLL1P2 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 DYNLL1P2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes DYNLL1P2 survival associations across molecular data types. DYNLL1P2 RNA expression shows survival associations in the most cancer types (23). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible DYNLL1P2 RNA expression–survival associations across cancer types. High DYNLL1P2 expression shows unfavorable associations in STAD, LIHC, KICH, MESO, LUAD and LGG. The STAD 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 STAD as the clearest survival context for DYNLL1P2 RNA expression.
This table summarizes DYNLL1P2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 3. The strongest signals are observed in KICH for RNA.
This table ranks reproducible tumor–normal expression differences for DYNLL1P2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. DYNLL1P2 shows lower tumor expression in KICH and higher tumor expression in BRCA and LUAD. The KICH box plot shows higher DYNLL1P2 RNA expression in normal versus tumor tissue (log2 FC = −0.415, t-test p = .001).
This table shows molecular features associated with DYNLL1P2 in patient tissues and cancer cell lines. In patient samples, DYNLL1P2 shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set.
