Q-omics provides the consensus-scored EEF1A1 profile across patient tissues and cancer cell-line models. EEF1A1 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, EEF1A1 is differentially expressed in 11, with the highest sampling consensus in BLCA. Additionally, EEF1A1 protein abundance shows 24,334 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight KIRC, BLCA, and PDAC as cancer lineages where EEF1A1 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 EEF1A1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes EEF1A1 survival associations across molecular data types. EEF1A1 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (10) and mass-spec protein abundance (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible EEF1A1 RNA expression–survival associations across cancer types. High EEF1A1 expression shows unfavorable associations in CESC and ACC, but favorable associations in KIRC, LGG, UCS and SKCM. 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 EEF1A1 RNA expression.
This table summarizes EEF1A1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11, while mass-spec protein shows differences in 6. The strongest signals are observed in BLCA for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for EEF1A1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. EEF1A1 shows lower tumor expression in BLCA, KICH, UCEC, BRCA and LUSC and higher tumor expression in LIHC. The BLCA box plot shows higher EEF1A1 RNA expression in normal versus tumor tissue (log2 FC = −0.648, t-test p < 0.001).
This table shows molecular features associated with EEF1A1 in patient tissues and cancer cell lines. In patient samples, EEF1A1 shows the broadest associations at the RNA and protein expression levels, with PDAC recurring as the lineage with the largest associated feature set. In cancer cell lines, EEF1A1 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 UPPER_AERODIGESTIVE_TRACT and CNS.
