Q-omics provides the consensus-scored EEF1E1-BLOC1S5 profile across patient tissues and cancer cell-line models. EEF1E1-BLOC1S5 expression is associated with patient survival in 8 of 34 cancer types, with the highest sampling consensus in ESCA. Among the 18 cancer types available for tumor–normal comparison, EEF1E1-BLOC1S5 is differentially expressed in 3, with the highest sampling consensus in KIRC. Additionally, EEF1E1-BLOC1S5 RNA expression shows 6,980 significant gene co-expression associations, with the highest sampling consensus in KIRP. Together, these results highlight ESCA, KIRC, and KIRP as cancer lineages where EEF1E1-BLOC1S5 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-BLOC1S5 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes EEF1E1-BLOC1S5 survival associations across molecular data types. EEF1E1-BLOC1S5 RNA expression shows survival associations in the most cancer types (8). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible EEF1E1-BLOC1S5 RNA expression–survival associations across cancer types. High EEF1E1-BLOC1S5 expression shows unfavorable associations in ESCA, ACC, LUAD, KIRP and KICH, but favorable associations in HNSC. The ESCA Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .001). Together, the overview and detailed table identify ESCA as the clearest survival context for EEF1E1-BLOC1S5 RNA expression.
This table summarizes EEF1E1-BLOC1S5 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 3. The strongest signals are observed in KIRC for RNA.
This table ranks reproducible tumor–normal expression differences for EEF1E1-BLOC1S5. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. EEF1E1-BLOC1S5 shows lower tumor expression in BRCA and higher tumor expression in KIRC and KIRP. The KIRC box plot shows higher EEF1E1-BLOC1S5 RNA expression in tumor versus normal tissue (log2 FC = +0.050, t-test p = .001).
This table shows molecular features associated with EEF1E1-BLOC1S5 in patient tissues and cancer cell lines. In patient samples, EEF1E1-BLOC1S5 shows the broadest associations at the RNA and protein expression levels, with KIRP recurring as the lineage with the largest associated feature set. In cancer cell lines, EEF1E1-BLOC1S5 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 LARGE_INTESTINE.
