Q-omics provides the consensus-scored EEF2 profile across patient tissues and cancer cell-line models. EEF2 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, EEF2 is differentially expressed in 12, with the highest sampling consensus in KIRC. Additionally, EEF2 protein abundance shows 35,119 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight KIRC, and GBM as cancer lineages where EEF2 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 EEF2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes EEF2 survival associations across molecular data types. EEF2 RNA expression shows survival associations in the most cancer types (27), 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 EEF2 RNA expression–survival associations across cancer types. High EEF2 expression shows unfavorable associations in ACC, but favorable associations in KIRC, UCEC, SCLC, LGG and UCS. The KIRC 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 KIRC as the clearest survival context for EEF2 RNA expression.
This table summarizes EEF2 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 7. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for EEF2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. EEF2 shows lower tumor expression in BRCA and higher tumor expression in KIRC, COAD, LIHC, KIRP and READ. The KIRC box plot shows higher EEF2 RNA expression in tumor versus normal tissue (log2 FC = +0.658, t-test p < 0.001).
This table shows molecular features associated with EEF2 in patient tissues and cancer cell lines. In patient samples, EEF2 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, EEF2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in UPPER_AERODIGESTIVE_TRACT, while CRISPR and shRNA rows add functional-dependency signals in KIDNEY and BLOOD_Leukemia.
