Q-omics provides the consensus-scored EIF2B5 profile across patient tissues and cancer cell-line models. EIF2B5 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in COAD. Among the 18 cancer types available for tumor–normal comparison, EIF2B5 is differentially expressed in 15, with the highest sampling consensus in COAD. Additionally, EIF2B5 RNA expression shows 19,227 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight COAD, and ACC as cancer lineages where EIF2B5 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 EIF2B5 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes EIF2B5 survival associations across molecular data types. EIF2B5 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (4) 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 EIF2B5 RNA expression–survival associations across cancer types. High EIF2B5 expression shows unfavorable associations in COAD, LIHC, ACC, KICH and MESO, but favorable associations in UVM. The COAD 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 COAD as the clearest survival context for EIF2B5 RNA expression.
This table summarizes EIF2B5 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 6. The strongest signals are observed in COAD for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for EIF2B5. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. EIF2B5 shows higher tumor expression in COAD, LIHC, BLCA, HNSC, LUSC and LUAD. The COAD box plot shows higher EIF2B5 RNA expression in tumor versus normal tissue (log2 FC = +0.595, t-test p < 0.001).
This table shows molecular features associated with EIF2B5 in patient tissues and cancer cell lines. In patient samples, EIF2B5 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, EIF2B5 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OVARY, while CRISPR and shRNA rows add functional-dependency signals in OESOPHAGUS and BLOOD_Lymphoma.
