Q-omics provides the consensus-scored DOLK profile across patient tissues and cancer cell-line models. DOLK expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in BLCA. Among the 18 cancer types available for tumor–normal comparison, DOLK is differentially expressed in 16, with the highest sampling consensus in HNSC. Additionally, DOLK RNA expression shows 18,655 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight BLCA, HNSC, and ACC as cancer lineages where DOLK 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 DOLK — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes DOLK survival associations across molecular data types. DOLK RNA expression shows survival associations in the most cancer types (24), followed by mutation status (4) and mass-spec protein abundance (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible DOLK RNA expression–survival associations across cancer types. High DOLK expression shows unfavorable associations in BLCA, UVM, ACC, LIHC and HNSC, but favorable associations in KIRC. The BLCA 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 BLCA as the clearest survival context for DOLK RNA expression.
This table summarizes DOLK tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 16, while mass-spec protein shows differences in 2. The strongest signals are observed in HNSC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for DOLK. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. DOLK shows lower tumor expression in KICH and higher tumor expression in HNSC, COAD, LIHC, STAD and BRCA. The HNSC box plot shows higher DOLK RNA expression in tumor versus normal tissue (log2 FC = +1.017, t-test p < 0.001).
This table shows molecular features associated with DOLK in patient tissues and cancer cell lines. In patient samples, DOLK shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, DOLK RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Leukemia, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Lymphoma and SOFT_TISSUE.
