cyclin G associated kinaseGenealiases: DNAJ26 · DNAJC26
Q-omics provides the consensus-scored GAK profile across patient tissues and cancer cell-line models. GAK expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in LGG. Among the 18 cancer types available for tumor–normal comparison, GAK is differentially expressed in 11, with the highest sampling consensus in LIHC. Additionally, GAK RNA expression shows 19,898 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight LGG, LIHC, and ACC as cancer lineages where GAK 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 GAK — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes GAK survival associations across molecular data types. GAK RNA expression shows survival associations in the most cancer types (24), followed by mutation status (4) 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 GAK RNA expression–survival associations across cancer types. High GAK expression shows unfavorable associations in LGG and MESO, but favorable associations in UCS, HNSC, SCLC and UCEC. The LGG 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 LGG as the clearest survival context for GAK RNA expression.
This table summarizes GAK tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11, while mass-spec protein shows differences in 5. The strongest signals are observed in LIHC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for GAK. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. GAK shows lower tumor expression in COAD and higher tumor expression in LIHC, BRCA, STAD, KICH and CHOL. The LIHC box plot shows higher GAK RNA expression in tumor versus normal tissue (log2 FC = +1.121, t-test p < 0.001).
This table shows molecular features associated with GAK in patient tissues and cancer cell lines. In patient samples, GAK 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, GAK 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 KIDNEY and SOFT_TISSUE.
