Q-omics provides the consensus-scored EEF1E1 profile across patient tissues and cancer cell-line models. EEF1E1 expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in LIHC. Among the 18 cancer types available for tumor–normal comparison, EEF1E1 is differentially expressed in 15, with the highest sampling consensus in BLCA. Additionally, EEF1E1 RNA expression shows 18,913 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight LIHC, BLCA, and ACC as cancer lineages where EEF1E1 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 EEF1E1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes EEF1E1 survival associations across molecular data types. EEF1E1 RNA expression shows survival associations in the most cancer types (26), followed by mutation status (1) 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 EEF1E1 RNA expression–survival associations across cancer types. High EEF1E1 expression shows unfavorable associations in LIHC, ACC, LUAD, SCLC, SARC and ESCA. The LIHC 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 LIHC as the clearest survival context for EEF1E1 RNA expression.
This table summarizes EEF1E1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 15, while mass-spec protein shows differences in 5. The strongest signals are observed in BLCA for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for EEF1E1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. EEF1E1 shows lower tumor expression in KICH and higher tumor expression in BLCA, LIHC, COAD, LUAD and HNSC. The BLCA box plot shows higher EEF1E1 RNA expression in tumor versus normal tissue (log2 FC = +1.249, t-test p < 0.001).
This table shows molecular features associated with EEF1E1 in patient tissues and cancer cell lines. In patient samples, EEF1E1 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, EEF1E1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BREAST, while CRISPR and shRNA rows add functional-dependency signals in CNS and LARGE_INTESTINE.
