Q-omics provides the consensus-scored DOK1 profile across patient tissues and cancer cell-line models. DOK1 expression is associated with patient survival in 28 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, DOK1 is differentially expressed in 16, with the highest sampling consensus in KIRC. Additionally, DOK1 protein abundance shows 31,819 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight KIRC, and LSCC as cancer lineages where DOK1 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 DOK1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes DOK1 survival associations across molecular data types. DOK1 RNA expression shows survival associations in the most cancer types (28), followed by mutation status (4) and mass-spec protein abundance (10). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible DOK1 RNA expression–survival associations across cancer types. High DOK1 expression shows unfavorable associations in KIRC, UVM and UCS, but favorable associations in SKCM, HNSC and SCLC. The KIRC Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .001). Together, the overview and detailed table identify KIRC as the clearest survival context for DOK1 RNA expression.
This table summarizes DOK1 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 7. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for DOK1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. DOK1 shows lower tumor expression in LUSC and LUAD and higher tumor expression in KIRC, KIRP, COAD and HNSC. The KIRC box plot shows higher DOK1 RNA expression in tumor versus normal tissue (log2 FC = +1.420, t-test p < 0.001).
This table shows molecular features associated with DOK1 in patient tissues and cancer cell lines. In patient samples, DOK1 shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set. In cancer cell lines, DOK1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SOFT_TISSUE, while CRISPR and shRNA rows add functional-dependency signals in OVARY and BLOOD_Lymphoma.
