Q-omics provides the consensus-scored EIF2AK3 profile across patient tissues and cancer cell-line models. EIF2AK3 expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in SKCM. Among the 18 cancer types available for tumor–normal comparison, EIF2AK3 is differentially expressed in 12, with the highest sampling consensus in THCA. Additionally, EIF2AK3 RNA expression shows 20,626 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight SKCM, THCA, and ACC as cancer lineages where EIF2AK3 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 EIF2AK3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes EIF2AK3 survival associations across molecular data types. EIF2AK3 RNA expression shows survival associations in the most cancer types (22), followed by mutation status (5) 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 EIF2AK3 RNA expression–survival associations across cancer types. High EIF2AK3 expression shows unfavorable associations in KIRP, LGG and UVM, but favorable associations in SKCM, KIRC and LUAD. 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 EIF2AK3 RNA expression.
This table summarizes EIF2AK3 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 5. The strongest signals are observed in THCA for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for EIF2AK3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. EIF2AK3 shows lower tumor expression in THCA and COAD and higher tumor expression in KIRC, BRCA, LUAD and CHOL. The THCA box plot shows higher EIF2AK3 RNA expression in normal versus tumor tissue (log2 FC = −1.311, t-test p < 0.001).
This table shows molecular features associated with EIF2AK3 in patient tissues and cancer cell lines. In patient samples, EIF2AK3 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, EIF2AK3 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUAD, while CRISPR and shRNA rows add functional-dependency signals in LARGE_INTESTINE and BLOOD_Leukemia.
