Q-omics provides the consensus-scored EIF1AX profile across patient tissues and cancer cell-line models. EIF1AX expression is associated with patient survival in 28 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, EIF1AX is differentially expressed in 12, with the highest sampling consensus in THCA. Additionally, EIF1AX RNA expression shows 19,319 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight HNSC, THCA, and ACC as cancer lineages where EIF1AX 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 EIF1AX — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes EIF1AX survival associations across molecular data types. EIF1AX RNA expression shows survival associations in the most cancer types (28), followed by mutation status (6) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible EIF1AX RNA expression–survival associations across cancer types. High EIF1AX expression shows unfavorable associations in HNSC, KIRP, LIHC, UVM and ACC, but favorable associations in OV. The HNSC 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 HNSC as the clearest survival context for EIF1AX RNA expression.
This table summarizes EIF1AX 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 6. The strongest signals are observed in THCA for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for EIF1AX. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. EIF1AX shows lower tumor expression in THCA and KICH and higher tumor expression in LIHC, HNSC, STAD and CHOL. The THCA box plot shows higher EIF1AX RNA expression in normal versus tumor tissue (log2 FC = −0.500, t-test p < 0.001).
This table shows molecular features associated with EIF1AX in patient tissues and cancer cell lines. In patient samples, EIF1AX 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, EIF1AX RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LARGE_INTESTINE, while CRISPR and shRNA rows add functional-dependency signals in CNS and BLOOD_Lymphoma.
