Q-omics provides the consensus-scored DYNC1LI2 profile across patient tissues and cancer cell-line models. DYNC1LI2 expression is associated with patient survival in 20 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, DYNC1LI2 is differentially expressed in 13, with the highest sampling consensus in THCA. Additionally, DYNC1LI2 RNA expression shows 20,674 significant gene co-expression associations, with the highest sampling consensus in THYM. Together, these results highlight KIRC, THCA, and THYM as cancer lineages where DYNC1LI2 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 DYNC1LI2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes DYNC1LI2 survival associations across molecular data types. DYNC1LI2 RNA expression shows survival associations in the most cancer types (20), followed by mutation status (2) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible DYNC1LI2 RNA expression–survival associations across cancer types. High DYNC1LI2 expression shows unfavorable associations in LUSC, BLCA, MESO and THCA, but favorable associations in KIRC and SCLC. The KIRC Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p < 0.001). Together, the overview and detailed table identify KIRC as the clearest survival context for DYNC1LI2 RNA expression.
This table summarizes DYNC1LI2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 5. The strongest signals are observed in THCA for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for DYNC1LI2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. DYNC1LI2 shows lower tumor expression in THCA, KICH, BRCA and LUSC and higher tumor expression in HNSC and CHOL. The THCA box plot shows higher DYNC1LI2 RNA expression in normal versus tumor tissue (log2 FC = −1.080, t-test p < 0.001).
This table shows molecular features associated with DYNC1LI2 in patient tissues and cancer cell lines. In patient samples, DYNC1LI2 shows the broadest associations at the RNA and protein expression levels, with THYM recurring as the lineage with the largest associated feature set. In cancer cell lines, DYNC1LI2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in KIDNEY, while CRISPR and shRNA rows add functional-dependency signals in BONE and LARGE_INTESTINE.
