Q-omics provides the consensus-scored CDK2AP1 profile across patient tissues and cancer cell-line models. CDK2AP1 expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, CDK2AP1 is differentially expressed in 16, with the highest sampling consensus in HNSC. Additionally, CDK2AP1 protein abundance shows 27,506 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight KIRP, HNSC, and GBM as cancer lineages where CDK2AP1 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 CDK2AP1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CDK2AP1 survival associations across molecular data types. CDK2AP1 RNA expression shows survival associations in the most cancer types (26), followed by mutation status (1) 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 CDK2AP1 RNA expression–survival associations across cancer types. High CDK2AP1 expression shows unfavorable associations in KIRP, UVM, KICH and HNSC, but favorable associations in SCLC and UCS. The KIRP 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 KIRP as the clearest survival context for CDK2AP1 RNA expression.
This table summarizes CDK2AP1 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 8. The strongest signals are observed in HNSC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for CDK2AP1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CDK2AP1 shows higher tumor expression in HNSC, LUSC, COAD, LIHC, BLCA and KIRC. The HNSC box plot shows higher CDK2AP1 RNA expression in tumor versus normal tissue (log2 FC = +0.769, t-test p < 0.001).
This table shows molecular features associated with CDK2AP1 in patient tissues and cancer cell lines. In patient samples, CDK2AP1 shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, CDK2AP1 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 BLOOD_Leukemia and UPPER_AERODIGESTIVE_TRACT.
