eukaryotic translation initiation factor 4E family member 3Genealiases: eIF-4E3 · eIF4E-3
Q-omics provides the consensus-scored EIF4E3 profile across patient tissues and cancer cell-line models. EIF4E3 expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, EIF4E3 is differentially expressed in 14, with the highest sampling consensus in COAD. Additionally, EIF4E3 protein abundance shows 21,849 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight KIRC, COAD, and LSCC as cancer lineages where EIF4E3 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 EIF4E3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes EIF4E3 survival associations across molecular data types. EIF4E3 RNA expression shows survival associations in the most cancer types (26), followed by mutation status (1) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible EIF4E3 RNA expression–survival associations across cancer types. High EIF4E3 expression shows favorable associations in KIRC, SKCM, BRCA, OV, COAD and CHOL. 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 EIF4E3 RNA expression.
This table summarizes EIF4E3 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, while mass-spec protein shows differences in 6. The strongest signals are observed in HNSC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for EIF4E3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. EIF4E3 shows lower tumor expression in COAD, HNSC, KICH, LUSC, LUAD and BLCA. The COAD box plot shows higher EIF4E3 RNA expression in normal versus tumor tissue (log2 FC = −1.765, t-test p < 0.001).
This table shows molecular features associated with EIF4E3 in patient tissues and cancer cell lines. In patient samples, EIF4E3 shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set. In cancer cell lines, EIF4E3 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LIVER, while CRISPR and shRNA rows add functional-dependency signals in SKIN and BLOOD_Lymphoma.
