Q-omics provides the consensus-scored EEF2K profile across patient tissues and cancer cell-line models. EEF2K expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, EEF2K is differentially expressed in 12, with the highest sampling consensus in KIRP. Additionally, EEF2K RNA expression shows 19,820 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight HNSC, KIRP, and UVM as cancer lineages where EEF2K 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 EEF2K — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes EEF2K survival associations across molecular data types. EEF2K RNA expression shows survival associations in the most cancer types (24), followed by mutation status (7) 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 EEF2K RNA expression–survival associations across cancer types. High EEF2K expression shows unfavorable associations in LGG, but favorable associations in HNSC, KIRC, BRCA, SCLC and UCS. The HNSC Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p < 0.001). Together, the overview and detailed table identify HNSC as the clearest survival context for EEF2K RNA expression.
This table summarizes EEF2K tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 5. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for EEF2K. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. EEF2K shows lower tumor expression in BLCA and BRCA and higher tumor expression in KIRP, KIRC, LIHC and HNSC. The KIRP box plot shows higher EEF2K RNA expression in tumor versus normal tissue (log2 FC = +1.156, t-test p < 0.001).
This table shows molecular features associated with EEF2K in patient tissues and cancer cell lines. In patient samples, EEF2K shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set. In cancer cell lines, EEF2K RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OVARY, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Lymphoma and UPPER_AERODIGESTIVE_TRACT.
