Q-omics provides the consensus-scored EEF1A1P33 profile across patient tissues and cancer cell-line models. EEF1A1P33 expression is associated with patient survival in 18 of 34 cancer types, with the highest sampling consensus in SKCM. Among the 18 cancer types available for tumor–normal comparison, EEF1A1P33 is differentially expressed in 9, with the highest sampling consensus in HNSC. Additionally, EEF1A1P33 RNA expression shows 15,575 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight SKCM, HNSC, and UVM as cancer lineages where EEF1A1P33 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 EEF1A1P33 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes EEF1A1P33 survival associations across molecular data types. EEF1A1P33 RNA expression shows survival associations in the most cancer types (18). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible EEF1A1P33 RNA expression–survival associations across cancer types. High EEF1A1P33 expression shows unfavorable associations in KICH and STAD, but favorable associations in SKCM, LUSC, UCS and READ. The SKCM 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 SKCM as the clearest survival context for EEF1A1P33 RNA expression.
This table summarizes EEF1A1P33 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 9. The strongest signals are observed in HNSC for RNA.
This table ranks reproducible tumor–normal expression differences for EEF1A1P33. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. EEF1A1P33 shows lower tumor expression in BRCA and UCEC and higher tumor expression in HNSC, COAD, LIHC and READ. The HNSC box plot shows higher EEF1A1P33 RNA expression in tumor versus normal tissue (log2 FC = +0.163, t-test p < 0.001).
This table shows molecular features associated with EEF1A1P33 in patient tissues and cancer cell lines. In patient samples, EEF1A1P33 shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set.
