Q-omics provides the consensus-scored EIF1AXP2 profile across patient tissues and cancer cell-line models. EIF1AXP2 expression is associated with patient survival in 11 of 34 cancer types, with the highest sampling consensus in OV. Among the 18 cancer types available for tumor–normal comparison, EIF1AXP2 is differentially expressed in 3, with the highest sampling consensus in STAD. Additionally, EIF1AXP2 RNA expression shows 7,948 significant protein co-abundance associations, with the highest sampling consensus in HNSC. Together, these results highlight OV, STAD, and HNSC as cancer lineages where EIF1AXP2 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 EIF1AXP2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes EIF1AXP2 survival associations across molecular data types. EIF1AXP2 RNA expression shows survival associations in the most cancer types (11). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible EIF1AXP2 RNA expression–survival associations across cancer types. High EIF1AXP2 expression shows unfavorable associations in ESCA and BLCA, but favorable associations in OV, COAD, LAML and STAD. The OV Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p = .015). Together, the overview and detailed table identify OV as the clearest survival context for EIF1AXP2 RNA expression.
This table summarizes EIF1AXP2 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 STAD for RNA.
This table ranks reproducible tumor–normal expression differences for EIF1AXP2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. EIF1AXP2 shows lower tumor expression in THCA and higher tumor expression in STAD and BRCA. The STAD box plot shows higher EIF1AXP2 RNA expression in tumor versus normal tissue (log2 FC = +0.168, t-test p = .019).
This table shows molecular features associated with EIF1AXP2 in patient tissues and cancer cell lines. In patient samples, EIF1AXP2 shows the broadest associations at the RNA and protein expression levels, with HNSC recurring as the lineage with the largest associated feature set.
