Q-omics provides the consensus-scored DYRK1A profile across patient tissues and cancer cell-line models. DYRK1A expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, DYRK1A is differentially expressed in 7, with the highest sampling consensus in THCA. Additionally, DYRK1A RNA expression shows 21,193 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight KIRC, THCA, and ACC as cancer lineages where DYRK1A 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 DYRK1A — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes DYRK1A survival associations across molecular data types. DYRK1A RNA expression shows survival associations in the most cancer types (27), followed by mutation status (7) and mass-spec protein abundance (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible DYRK1A RNA expression–survival associations across cancer types. High DYRK1A expression shows unfavorable associations in UVM and ACC, but favorable associations in KIRC, SKCM, UCS and GBM. The KIRC Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p = .001). Together, the overview and detailed table identify KIRC as the clearest survival context for DYRK1A RNA expression.
This table summarizes DYRK1A tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 7, while mass-spec protein shows differences in 5. The strongest signals are observed in THCA for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for DYRK1A. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. DYRK1A shows lower tumor expression in THCA, KICH, UCEC and KIRP and higher tumor expression in LIHC and CHOL. The THCA box plot shows higher DYRK1A RNA expression in normal versus tumor tissue (log2 FC = −0.544, t-test p < 0.001).
This table shows molecular features associated with DYRK1A in patient tissues and cancer cell lines. In patient samples, DYRK1A 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, DYRK1A RNA and mutation anchors are most strongly linked to RNA-expression features, especially in PANCREAS, while CRISPR and shRNA rows add functional-dependency signals in OESOPHAGUS and BLOOD_Leukemia.
